Informe sobre Desarrollo Humano 2011 en el mundo

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Human Development Report 2011
Sustainability and Equity: A Better Future for All
GREATEST
Human capabilities supported equitably and sustainably
S U U S ST A
Y
II N
IT
A A
U
B
Q
IL
E
T IT Y
LEAST
Sustainable but not equitable
Equitable Equitable, but not sustainable
LEAST
Unsustainable and inequitable
This Report explores the integral links between environmental sustainability and equity and shows that these are critical to expanding human freedoms for people today and in generations to come. The point of departure is that the remarkable progress in human development over recent decades that the Human Development Report has documented cannot continue without bold global steps to reduce environmental risks and inequality. We identify pathways for people, communities, countries and the international community to promote environmental sustainability and equity in mutually reinforcing ways. The cover diagram symbolizes how different policies can have different implications for sustainability and equity. Whenever available, we should prefer solutions that are good for the environment while also promoting equity and human development. Pursuing sustainability and equity jointly does not require that they be mutually reinforcing. In many instances they will not be. Sometimes the most feasible alternative involves trade-offs between sustainability and equity and requires explicit and careful consideration. No trade-off is isolated from a society’s structural and institutional conditions, and so we must address the underlying constraints and identify positive synergies between sustainability and equity. This Report is aimed not only at finding positive synergies but also at identifying ways to build them.
Human Development Report 2011 Sustainability and Equity: A Better Future for All
Published for the United Nations Development Programme (UNDP)
Copyright © 2011 by the United Nations Development Programme 1 UN Plaza, New York, NY 10017, USA All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise without prior permission. ISBN: 9780230363311 Palgrave Macmillan Houndmills, Basingstoke, Hampshire RG21 6XS and 175 Fifth Avenue, New York, NY 10010 Companies and representatives throughout the world Palgrave Macmillan in the UK is an imprint of Macmillan Publishers Limited, registered in England, company number 785998, of Houndmills, Basingstoke, Hampshire RG21 6XS. Palgrave Macmillan in the US is a division of St Martin’s Press LLC, 175 Fifth Avenue, New York, NY 10010. Palgrave Macmillan is the global academic imprint of the above companies and has companies and representatives throughout the world. Palgrave® and Macmillan® are registered trademarks in the United States, the United Kingdom, Europe and other countries. A catalogue record for this book is available from the British Library and the Library of Congress. Printed in the United States by Consolidated Graphics. Cover is printed on Tembec’s 12 pt Kallima coated‑one‑side paper. Text pages are printed on Cascades Mills’ 60# Rolland Opaque Smooth text that is 50% de‑inked post‑ consumer recycled fibre. Both sheets are Forest Stewardship Council Certified, elemental chlorine‑free papers and printed with vegetable‑based inks and produced by means of environmentally compatible technology.
Editing and production: Communications Development Incorporated, Washington DC Design: Gerry Quinn For a list of any errors or omissions found subsequent to printing please visit our website at http://hdr.undp.org
Human Development Report 2011 team
The UNDP Human Development Report Office
The Human Development Report is the product of a collective effort under the guidance of the Director, with research, statistics, communications and publishing staff, and a team supporting National Human Development Reports. Operations and administration colleagues facilitate the work of the office.
Director and lead author
Jeni Klugman
Research
Francisco Rodríguez (Head), Shital Beejadhur, Subhra Bhattacharjee, Monalisa Chatterjee, Hyung-Jin Choi, Alan Fuchs, Mamaye Gebretsadik, Zachary Gidwitz, Martin Philipp Heger, Vera Kehayova, José Pineda, Emma Samman and Sarah Twigg
Statistics
Milorad Kovacevic (Head), Astra Bonini, Amie Gaye, Clara Garcia Aguña and Shreyasi Jha
Communications and publishing
William Orme (Head), Botagoz Abdreyeva, Carlotta Aiello, Wynne Boelt and Jean-Yves Hamel
National Human Development Reports
Eva Jespersen (Deputy Director), Mary Ann Mwangi, Paola Pagliani and Tim Scott
Operations and administration
Sarantuya Mend (Operations Manager), Diane Bouopda and Fe Juarez-Shanahan
Foreword
In June 2012 world leaders will gather in Rio de Janeiro to seek a new consensus on global actions to safeguard the future of the planet and the right of future generations everywhere to live healthy and fulfilling lives. This is the great development challenge of the 21st century. The 2011 Human Development Report offers important new contributions to the global dialogue on this challenge, showing how sustainability is inextricably linked to basic questions of equity—that is, of fairness and social justice and of greater access to a better quality of life. Sustainability is not exclusively or even primarily an environmental issue, as this Report so persuasively argues. It is fundamentally about how we choose to live our lives, with an awareness that everything we do has consequences for the 7 billion of us here today, as well as for the billions more who will follow, for centuries to come. Understanding the links between environmental sustainability and equity is critical if we are to expand human freedoms for current and future generations. The remarkable progress in human development over recent decades, which the global Human Development Reports have documented, cannot continue without bold global steps to reduce both environmental risks and inequality. This Report identifies pathways for people, local communities, countries and the international community to promote environmental sustainability and equity in mutually reinforcing ways. In the 176 countries and territories where the United Nations Development Programme is working every day, many disadvantaged people carry a double burden of deprivation. They are more vulnerable to the wider effects of environmental degradation, because of more severe stresses and fewer coping tools. They must also deal with threats to their immediate environment from indoor air pollution, dirty water and unimproved sanitation. Forecasts suggest that continuing failure to reduce the grave environmental risks and deepening social inequalities threatens to slow decades of sustained progress by the world’s poor majority—and even to reverse the global convergence in human development. Major disparities in power shape these patterns. New analysis shows how power imbalances and gender inequalities at the national level are linked to reduced access to clean water and improved sanitation, land degradation and deaths due to indoor and outdoor air pollution, amplifying the effects associated with income disparities. Gender inequalities also interact with environmental outcomes and make them worse. At the global level governance arrangements often weaken the voices of developing countries and exclude marginalized groups. Yet there are alternatives to inequality and unsustainability. Growth driven by fossil fuel consumption is not a prerequisite for a better life in broader human development terms. Investments that improve equity—in access, for example, to renewable energy, water and sanitation, and reproductive healthcare—could advance both sustainability and human development. Stronger accountability and democratic processes, in part through support for an active civil society and media, can also improve outcomes. Successful approaches rely on community management, inclusive institutions that pay particular attention to disadvantaged groups, and cross-cutting approaches that coordinate budgets and mechanisms across government agencies and development partners. Beyond the Millennium Development Goals, the world needs a post-2015 development framework that reflects equity and sustainability; Rio+20 stands out as a key opportunity to
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reach a shared understanding of how to move forward. This Report shows that approaches that integrate equity into policies and programmes and that empower people to bring about change in the legal and political arenas hold enormous promise. Growing country experiences around the world have demonstrated the potential of these approaches to generate and capture positive synergies. The financing needed for development—including for environmental and social protection —will have to be many times greater than current official development assistance. Today’s spending on low-carbon energy sources, for example, is only 1.6 percent of even the lowest estimate of need, while spending on climate change adaptation and mitigation is around 11 percent of estimated need. Hope rests on new climate finance. While market mechanisms and private funding will be vital, they must be supported and leveraged by proactive public investment. Closing the financing gap requires innovative thinking, which this Report provides. Beyond raising new sources of funds to address pressing environmental threats equitably, the Report advocates reforms that promote equity and voice. Financing flows need to be channelled towards the critical challenges of unsustainability and inequity—and not exacerbate existing disparities. Providing opportunities and choices for all is the central goal of human development. We have a collective responsibility towards the least privileged among us today and in the future around the world—and a moral imperative to ensure that the present is not the enemy of the future. This Report can help us see the way forward.
Helen Clark Administrator United Nations Development Programme
The analysis and policy recommendations of this Report do not necessarily reflect the views of the United Nations Development Programme or its Executive Board. The Report is an independent publication commissioned by UNDP. The research and writing of the Report was a collaborative effort by the Human Development Report team and a group of eminent advisors led by Jeni Klugman, Director of the Human Development Report Office.
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Acknowledgements
This is my third and final year of directing the global Human Development Report, which, as ever, has been an enormous collaborative effort. The hard work and dedication of the Human Development Report Office team anchor the work, supported by a much broader family of researchers, advocates and officials whose commitment and vision are equally critical to our success. An academic advisory panel provided valuable guidance, for which we thank Bina Agarwal, Sabina Alkire, Anthony Atkinson, Tariq Banuri, François Bourguignon, William Easterly, Daniel Esty, Sakiko Fukuda-Parr, Enrico Giovannini, Stephany Griffith-Jones, Brian Hammond, Geoffrey Heal, Cesar Hidalgo, Richard Jolly, Gareth Jones, Martin Khor, Mwangi S. Kimenyi, Adil Najam, Eric Neumayer, Michael Noble, José Antonio Ocampo, Marcio Pochmann, Henry Richardson, Ingrid Robeyns, José Salazar-Xirinachs, Frances Stewart, Pavan Sukhdev, Miguel Székely, Dennis Trewin, Leonardo Villar and Tarik Yousef. A reconstituted statistical advisory panel, comprising official statisticians and academic experts, provided excellent advice on the methodology and data sources related to the family of human development indices: Anthony Atkinson, Grace Bediako, Haishan Fu, Enrico Giovannini, Peter Harper, Gareth Jones, Irena Krizman, Charles Leyeka Lufumpa, Michael Noble, Eduardo Nunes, Marcio Pochmann, Eric Swanson, Miguel Székely and Dato’ Hajan Wan Ramlah Wan Abd. Raof. More generally, the United Nations Statistical Commission provided useful feedback from member states. An extensive series of consultations involved some 500 researchers, civil society advocates, development practitioners and policy-makers from around the globe. Twenty-six events were held between February 2010 and September 2011—in Amman, Bamako, Bangkok, Beijing, Berkeley, Bonn, Copenhagen, Dubai, Geneva, Kigali, Ljubljana, London, Nairobi, New Delhi, New York, Paris, Quito, San José—with the support of the United Nations Development Programme (UNDP) country and regional offices. Support from partnering institutions, listed at http://hdr. undp.org/en/reports/global/hdr2011/consultations, is also gratefully acknowledged. Background research, commissioned on a range of thematic issues, is available online in our Human Development Research Papers series and listed in References. Special thanks to Sabina Alkire and the Oxford Human Development and Poverty Initiative for their continued collaboration and efforts to improve our measure of multidimensional poverty. The statistics used in this Report rely on various databases. We are particularly grateful to the Carbon Dioxide Information Analysis Center of the US Department of Energy, Yale Center for Environmental Law and Policy, Robert Barro and Jong-Wha Lee, Food and Agricultural Organization, Gallup World Poll, Global Footprint Network, ICF Macro, International Monetary Fund, International Energy Agency, International Labour Organization, International Union for Conservation of Nature, Inter-Parliamentary Union, Luxembourg Income Study, United Nations Department of Economic and Social Affairs, United Nations Educational, Scientific and Cultural Organization Institute for Statistics, United Nations Children’s Fund, World Bank and World Health Organization. Claudio Montenegro conducted the analysis on the World Bank’s International Income Distribution Database, Suman Seth on the European Union Statistics on Income and Living Conditions and Kenneth Harttgen on the ICF Macro Demographic and Health Surveys.
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A UNDP Readers Group, representing all the regional and policy bureaus, and other colleagues, too numerous to list, provided valuable advice throughout the preparation of the Report. Particular thanks are due to Jennifer Laughlin, Charles MacPherson and colleagues at the Bureau of Development Policy. The HD Network, which comprises some 1,500 UNDP staff, academics and nongovernmental organizations, generated a range of useful ideas and feedback through online discussions. Martha Mai of the UN Office for Project Services provided administrative support. Several hard working interns made important contributions over the course of the year: Raphaelle Aubert, Uttara Balakrishnan, Luis Fernando Cervantes, Nicole Glanemann, Faith Kim, Meng Lu, Francesca Rappocciolo, Andrés Méndez Ruiz, Fredrik M. Sjoberg and Seol Yoo. A team at Communications Development Incorporated, led by Bruce Ross-Larson, with Meta de Coquereaumont, Rob Elson, Jack Harlow, Christopher Trott and Elaine Wilson, edited, proofread and laid out the Report. Gerry Quinn designed the Report and created the figures. We thank all of those involved directly or indirectly in contributing to our efforts, while acknowledging sole responsibility for errors of commission and omission. Directing the global Human Development Report has been a great experience for me, both personally and professionally over the past three years. The human development approach continues to demonstrate its value as a lens for critical and constructive thinking about some of the most fundamental challenges facing us today, and I am confident that the independent global reports, commissioned by UNDP, will remain as central as ever in key global debates. I wish my successor, Khalid Malik, the best of luck in taking this endeavour forward into the next decade.
Jeni Klugman Director and lead author Human Development Report 2011
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Contents
Foreword Acknowledgements
iv vi
Other adverse repercussions Disequalizing effects of extreme events Disempowerment and environmental degradation Gender equality Power inequalities
57 59 61 61 64
Overview ChApter 1
Why sustainability and equity? Are there limits to human development? Competing paradigms The critical role of uncertainty Sustainability, equity and human development What we mean by sustainability What we mean by equity Why centre on equitable sustainability? Our focus of inquiry
1
13 14 15 16 17 17 18 19 20
ChApter 4
Positive synergies—winning strategies for the environment, equity and human development Scaling up to address environmental deprivations and build resilience Energy Water access, water security and sanitation Averting degradation Expanding reproductive choice Supporting community management of natural resources Conserving biodiversity while promoting equity Addressing climate change—risks and realities Equitable and adaptive disaster responses Innovative social protection 67
67 67 71 73 73 75 76 77 77 78
ChApter 2
Patterns and trends in human development, equity and environmental indicators Progress and prospects Progress in human development Equity trends Prospects—and environmental threats Threats to sustaining progress Climate change Chronic environmental threats Success in promoting sustainable and equitable human development 23 23 23 28 30 31 32 37 41
ChApter 5
Rising to the policy challenges Business-as-usual is neither equitable nor sustainable Rethinking our development model—levers for change Integrating equity concerns into green economy policies Empowering people to bring about change Financing investment and the reform agenda Where does the world stand? What development assistance can do Innovations at the global level Innovative new sources to meet the financing gap Ensuring equity and voice in governing and in access to finance Enabling universal access to energy 81 81 83 83 86 90 90 90 94 94 96 98
ChApter 3
Tracing the effects—understanding the relations A poverty lens Deprivations facing the poor Understanding the relations Environmental threats to people’s well-being Harming health Impeding education Endangering livelihoods 45 45 46 47 50 51 54 54
Notes References
99 105
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StAtiStiCAl Annex
Readers guide Key to HDI countries and ranks, 2011 Statistical tables 1 2 3 4 5 6 7 8 9 10 Human Development Index and its components Human Development Index trends, 1980–2011 Inequality‑adjusted Human Development Index Gender Inequality Index and related indicators Multidimensional Poverty Index Environmental sustainability Human development effects of environmental threats Perceptions about well‑being and the environment Education and health Population and economy 127 131 135 139 143 146 150 154 158 162 123 126
3.3 3.4 4.1 4.2 5.1 5.2 5.3
Indigenous peoples, land rights and livelihoods Women’s participation in community forest management From subsidy to self‑respect—the revolution of Community‑led Total Sanitation Culture, norms and environmental protection Distributional impacts of policies to cut pollution Innovative financing schemes for water and sanitation The currency transaction tax: newfound feasibility
55 65 73 76 84 93 95
FigureS
1.1 2.1 An illustration of policy synergies and trade‑offs between equity and sustainability 20 The association with carbon dioxide emissions per capita is positive and strong for income, positive for the HDI and nonexistent for health and education
26 26 27 29 31
2.2 Countries with higher growth also experience faster increase in carbon dioxide emissions per capita 2.3 Patterns of risk change: environmental transitions and human development 2.4 High HIV/AIDS prevalence rates in Southern Africa stall improvements in health inequality
Technical notes Regions Statistical references
167 174 175
BOxeS
1.1 1.2 2.1 Environmental risk management—gambling with the planet Measures of sustainability—a conceptual overview Overcoming the democratic deficit—empowerment and the Arab Spring 16 18 24 25 27 30 33 36 38 39 41 42 50 52
2.5 Scenarios projecting impacts of environmental risks on human development through 2050 2.6 Scenarios projecting slowdown and reversals of convergence in human development due to environmental risks through 2050 2.7 2.9 3.1 3.2 3.3 3.4 Average world temperatures have risen since 1900 Rising temperatures and reduced rainfall 2.8 Sources of greenhouse gas growth 2.10 Some regions deforest, others reforest and afforest Environmental deprivations in the MPI Environmental deprivations are greatest for access to modern cooking fuel The share of the population with environmental deprivations
31 32 34 35 38 46 47
2.2 What can we learn from trends in aggregate measures of sustainability? 2.3 Consumption and human development 2.4 Sustainability, crises and inequality 2.5 Are people aware of climate change and its causes? 2.6 Impacts of climate change on small island developing states 2.7 2.9 3.1 3.2
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Multidimensional Poverty Index—a focus on the most deprived 46
Biodiversity—the accelerating loss of our ecosystems Hazardous waste and the Basel Convention Trends in multidimensional poverty Air pollution and its health consequences in China
2.8 Land grabbing—a growing phenomenon? 2.10 Positive synergies in Sweden and Costa Rica
rises with the MPI but with much variation around the trend 48 3.5 Deaths attributable to environmental risks are associated with high MPI levels 3.6 51
Gender equality and contraceptive prevalence are closely linked 62
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3.7 4.1 5.1 5.2 5.3
Unmet contraceptive need is higher among the multidimensionally poor Large regional differences in the share of multidimensionally poor people lacking electricity Integrating equity into policy design Official development assistance falls far short of needs Key elements in transforming climate financing efforts
63 68 84 91 97
2.3 Disaster‑related casualties and costs, median annual values by HDI group, 1971–1990 and 1991–2010 2.4 3.1 Good performers on the environment, equity and human development, most recent year available Ten countries with the lowest share of environmental deprivations among the multidimensionally poor, most recent year available for 2000–2010 Average time per week spent fetching wood and water, rural areas of selected Sub‑Saharan African countries 3.3 Attitudes towards the environment, by gender, low and very high HDI countries, 2010
37 42
48 58 64 70 78
3.2
MAp
2.1 Temperature changes are greatest in polar regions and higher latitudes 34
4.1 4.2
Key equity aspects of a menu of instruments to reduce carbon dioxide emissions Social protection for adaptation and disaster risk reduction: benefits and challenges
tABleS
2.1 Growth in carbon dioxide emissions and its drivers, 1970–2007 32 36 2.2 Projected impacts of a half‑metre rise in sea level by 2050
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Overview
This year’s Report focuses on the challenge of sustainable and equitable progress. A joint lens shows how environmental degradation intensifies inequality through adverse impacts on already disadvantaged people and how inequalities in human development amplify environmental degradation. Human development, which is about expanding people’s choices, builds on shared natural resources. Promoting human development requires addressing sustainability— locally, nationally and globally—and this can and should be done in ways that are equitable and empowering. We seek to ensure that poor people’s aspirations for better lives are fully taken into account in moving towards greater environmental sustainability. And we point to pathways that enable people, communities, countries and the international community to promote sustainability and equity so that they are mutually reinforcing.
why sustainability and equity?
The human development approach has enduring relevance in making sense of our world and addressing challenges now and in the future. Last year’s 20th anniversary Human Development Report (HDR) celebrated the concept of human development, emphasizing how equity, empowerment and sustainability expand people’s choices. At the same time it highlighted inherent challenges, showing that these key aspects of human development do not always come together.
The case for considering sustainability and equity together
concern for distributive justice. We value sustainability because future generations should have at least the same possibilities as people today. Similarly, all inequitable processes are unjust: people’s chances at better lives should not be constrained by factors outside their control. Inequalities are especially unjust when particular groups, whether because of gender, race or birthplace, are systematically disadvantaged. More than a decade ago Sudhir Anand and Amartya Sen made the case for jointly considering sustainability and equity. “It would be a gross violation of the universalist principle,” they argued, “if we were to be obsessed about intergenerational equity without at the same time seizing the problem of intragenerational equity” (emphasis in original). Similar themes emerged from the Brundtland Commission’s 1987 report and a series of international declarations from Stockholm in 1972 through Johannesburg in 2002. Yet today many debates about sustainability neglect equality, treating it as a separate and unrelated concern. This perspective is incomplete and counterproductive.
Some key definitions
This year we explore the intersections between environmental sustainability and equity, which are fundamentally similar in their
Human development is the expansion of people’s freedoms and capabilities to lead lives that they value and have reason to value. It is about expanding choices. Freedoms and capabilities are a more expansive notion than basic needs. Many ends are necessary for a “good life,” ends that can be intrinsically as well as instrumentally valuable—we may value biodiversity, for example, or natural beauty, independently of its contribution to our living standards. Disadvantaged people are a central focus of human development. This includes people in the future who will suffer the most severe consequences of the risks arising from our activities today. We are concerned not only with
Overview
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Sustainable human development is the expansion of the substantive freedoms of people today while making reasonable efforts to avoid seriously compromising those of future generations
what happens on average or in the most probable scenario but also with what happens in the less likely but still possible scenarios, particularly when the events are catastrophic for poor and vulnerable people. Debates over what environmental sustainability means often focus on whether human-made capital can substitute for natural resources—whether human ingenuity will relax natural resource constraints, as in the past. Whether this will be possible in the future is unknown and, coupled with the risk of catastrophe, favours the position of preserving basic natural assets and the associated flow of ecological services. This perspective also aligns with human rights–based approaches to development. Sustainable human development is the expansion of the substantive freedoms of people today while making reasonable efforts to avoid seriously compromising those of future generations. Reasoned public deliberation, vital to defining the risks a society is willing to accept, is crucial to this idea. The joint pursuit of environmental sustainability and equity does not require that the two always be mutually reinforcing. In many instances there will be trade-offs. Measures to improve the environment can have adverse effects on equity—for example, if they constrain economic growth in developing countries. This Report illustrates the types of joint impacts that policies could have, while acknowledging that they do not hold universally and underlining that context is critical. The framework encourages special attention to identifying positive synergies and to considering trade-offs. We investigate how societies can implement win-win-win solutions that favour sustainability, equity and human development.
patterns and trends, progress and prospects
Increasing evidence points to widespread environmental degradation around the world and potential future deterioration. Because the extent of future changes is uncertain, we explore a range of predictions and consider the insights for human development.
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Our starting point, and a key theme of the 2010 HDR, is the enormous progress in human development over the past several decades—with three caveats: • Income growth has been associated with deterioration in such key environmental indicators as carbon dioxide emissions, soil and water quality and forest cover. • The distribution of income has worsened at the country level in much of the world, even with the narrowing of gaps in health and education achievement. • While empowerment on average tends to accompany a rising Human Development Index (HDI), there is considerable variation around the relationship. Simulations for this Report suggest that by 2050 the global HDI would be 8 percent lower than in the baseline in an “environmental challenge” scenario that captures the adverse effects of global warming on agricultural production, on access to clean water and improved sanitation and on pollution (and 12 percent lower in South Asia and Sub-Saharan Africa). Under an even more adverse “environmental disaster” scenario, which envisions vast deforestation and land degradation, dramatic declines in biodiversity and accelerated extreme weather events, the global HDI would be some 15 percent below the projected baseline. If we do nothing to halt or reverse current trends, the environmental disaster scenario leads to a turning point before 2050 in developing countries—their convergence with rich countries in HDI achievements begins to reverse. These projections suggest that in many cases the most disadvantaged people bear and will continue to bear the repercussions of environmental deterioration, even if they contribute little to the problem. For example, low HDI countries have contributed the least to global climate change, but they have experienced the greatest loss in rainfall and the greatest increase in its variability, with implications for agricultural production and livelihoods. Emissions per capita are much greater in very high HDI countries than in low, medium and high HDI countries combined because of more energy-intensive activities—driving cars,
cooling and heating homes and businesses, consuming processed and packaged food. The average person in a very high HDI country accounts for more than four times the carbon dioxide emissions and about twice the methane and nitrous oxide emissions of a person in a low, medium or high HDI country—and about 30 times the carbon dioxide emissions of a person in a low HDI country. The average UK citizen accounts for as much greenhouse gas emissions in two months as a person in a low HDI country generates in a year. And the average Qatari—living in the country with the highest per capita emissions—does so in only 10 days, although that value reflects consumption as well as production that is consumed elsewhere. While three-quarters of the growth in emissions since 1970 comes from low, medium and high HDI countries, overall levels of greenhouse gases remain much greater in very high HDI countries. And this stands without accounting for the relocation of carbon-intensive production to poorer countries, whose output is largely exported to rich countries. Around the world rising HDI has been associated with environmental degradation —though the damage can be traced largely to economic growth. Countries with higher incomes generally have higher carbon dioxide emissions per capita. But our analysis finds no association between emissions and the health and education components of the HDI. This result is intuitive: activities that emit carbon dioxide into the atmosphere are those linked to the production of goods, not to the provision of health and education. These results also show the nonlinear nature of the relationship between carbon dioxide emissions per capita and HDI components: little or no relationship at low HDI, but as the HDI rises a “tipping point” is reached, beyond which appears a strong positive correlation between carbon dioxide emissions and income. Countries with faster improvements in the HDI have also experienced faster increases in carbon dioxide emissions per capita. These changes over time—rather than the snapshot relationship—highlight what to expect
tomorrow as a result of development today. Again, income changes drive the trend. But these relationships do not hold for all environmental indicators. Our analysis finds only a weak positive correlation between the HDI and deforestation, for example. Why do carbon dioxide emissions differ from other environmental threats? We suggest that where the link between the environment and quality of life is direct, as with pollution, environmental achievements are often greater in developed countries; where the links are more diffuse, performance is much weaker. Looking at the relationship between environmental risks and the HDI, we observe three general findings: • Household environmental deprivations— indoor air pollution, inadequate access to clean water and improved sanitation—are more severe at low HDI levels and decline as the HDI rises. • Environmental risks with community effects—such as urban air pollution— seem to rise and then fall with development; some suggest that an inverted U-shaped curve describes the relationship. • Environmental risks with global effects —namely greenhouse gas emissions— typically rise with the HDI. The HDI itself is not the true driver of these transitions. Incomes and economic growth have an important explanatory role for emissions—but the relationship is not deterministic either. And complex interactions of broader forces change the risk patterns. For example, international trade allows countries to outsource the production of goods that degrade the environment; large-scale commercial use of natural resources has different impacts than subsistence exploitation; and urban and rural environmental profiles differ. And as we will see, policies and the political context matter greatly. It follows that the patterns are not inevitable. Several countries have achieved significant progress both in the HDI and in equity and environmental sustainability. In line with our focus on positive synergies, we propose a multidimensional strategy to identify countries that have done better than regional peers in promoting equity, raising the HDI,
where the link between the environment and quality of life is direct, as with pollution, environmental achievements are often greater in developed countries; where the links are more diffuse, performance is much weaker
Overview
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Environmental trends over recent decades show deterioration on several fronts, with adverse repercussions for human development, especially for the millions of people who depend directly on natural resources for their livelihoods
reducing household indoor air pollution and increasing access to clean water and that are top regional and global performers in environmental sustainability. Environmental sustainability is judged on greenhouse gas emissions, water use and deforestation. The results are illustrative rather than indicative because of patchy data and other comparability issues. Just one country, Costa Rica, outperforms its regional median on all the criteria, while the three other top performers display unevenness across dimensions. Sweden is notable for its high reforestation rate compared with regional and global averages. Our list shows that across regions, development stages and structural characteristics countries can enact policies conducive to environmental sustainability, equity and the key facets of human development captured in the HDI. We review the types of policies and programmes associated with success while underlining the importance of local conditions and context. More generally, however, environmental trends over recent decades show deterioration on several fronts, with adverse repercussions for human development, especially for the millions of people who depend directly on natural resources for their livelihoods. • Globally, nearly 40 percent of land is degraded due to soil erosion, reduced fertility and overgrazing. Land productivity is declining, with estimated yield loss as high as 50 percent in the most adverse scenarios. • Agriculture accounts for 70–85 percent of water use, and an estimated 20 percent of global grain production uses water unsustainably, imperilling future agricultural growth. • Deforestation is a major challenge. Between 1990 and 2010 Latin America and the Caribbean and Sub-Saharan Africa experienced the greatest forest losses, followed by the Arab States. The other regions have seen minor gains in forest cover. • Desertification threatens the drylands that are home to about a third of the world’s people. Some areas are particularly vulnerable—notably Sub-Saharan Africa,
where the drylands are highly sensitive and adaptive capacity is low. Adverse environmental factors are expected to boost world food prices 30–50 percent in real terms in the coming decades and to increase price volatility, with harsh repercussions for poor households. The largest risks are faced by the 1.3 billion people involved in agriculture, fishing, forestry, hunting and gathering. The burden of environmental degradation and climate change is likely to be disequalizing across groups—for several reasons: • Many rural poor people depend overwhelmingly on natural resources for their income. Even people who do not normally engage in such activities may do so as a coping strategy during hardship. • How environmental degradation will affect people depends on whether they are net producers or net consumers of natural resources, whether they produce for subsistence or for the market and how readily they can shift between these activities and diversify their livelihoods with other occupations. • Today, around 350 million people, many of them poor, live in or near forests on which they rely for subsistence and incomes. Both deforestation and restrictions on access to natural resources can hurt the poor. Evidence from a range of countries suggests that women typically rely on forests more than men do because women tend to have fewer occupational options, be less mobile and bear most of the responsibility for collecting fuelwood. • Around 45 million people—at least 6 million of them women—fish for a living and are threatened by overfishing and climate change. The vulnerability is twofold: the countries most at risk also rely the most on fish for dietary protein, livelihoods and exports. Climate change is expected to lead to major declines in fish stocks in the Pacific Islands, while benefits are predicted at some northern latitudes, including around Alaska, Greenland, Norway and the Russian Federation. To the extent that women in poor countries are disproportionately involved in
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subsistence farming and water collection, they face greater adverse consequences of environmental degradation. Many indigenous peoples also rely heavily on natural resources and live in ecosystems especially vulnerable to the effects of climate change, such as small island developing states, arctic regions and high altitudes. Evidence suggests that traditional practices can protect natural resources, yet such knowledge is often overlooked or downplayed. The effects of climate change on farmers’ livelihoods depend on the crop, region and season, underlining the importance of in-depth, local analysis. Impacts will also differ depending on household production and consumption patterns, access to resources, poverty levels and ability to cope. Taken together, however, the net biophysical impacts of climate change on irrigated and rainfed crops by 2050 will likely be negative—and worst in low HDI countries.
understanding the links
Drawing on the important intersections between the environment and equity at the global level, we explore the links at the community and household levels. We also highlight countries and groups that have broken the pattern, emphasizing transformations in gender roles and in empowerment. A key theme: the most disadvantaged people carry a double burden of deprivation. More vulnerable to the wider effects of environmental degradation, they must also cope with threats to their immediate environment posed by indoor air pollution, dirty water and unimproved sanitation. Our Multidimensional Poverty Index (MPI), introduced in the 2010 HDR and estimated this year for 109 countries, provides a closer look at these deprivations to see where they are most acute. The MPI measures serious deficits in health, education and living standards, looking at both the number of deprived people and the intensity of their deprivations. This year we explore the pervasiveness of environmental deprivations among the multidimensionally poor and their overlaps at the household level, an innovation in the MPI.
The poverty-focused lens allows us to examine environmental deprivations in access to modern cooking fuel, clean water and basic sanitation. These absolute deprivations, important in themselves, are major violations of human rights. Ending these deprivations could increase higher order capabilities, expanding people’s choices and advancing human development. In developing countries at least 6 people in 10 experience one of these environmental deprivations, and 4 in 10 experience two or more. These deprivations are especially acute among multidimensionally poor people, more than 9 in 10 of whom experience at least one. Most suffer overlapping deprivations: 8 in 10 multidimensionally poor people have two or more, and nearly 1 in 3 (29 percent) is deprived in all three. These environmental deprivations disproportionately contribute to multidimensional poverty, accounting for 20 percent of the MPI—above their 17 percent weight in the index. Across most developing countries deprivations are highest in access to cooking fuel, though lack of water is paramount in several Arab States. To better understand environmental deprivations, we analysed the patterns for given poverty levels. Countries were ordered by the share of multidimensionally poor people facing one environmental deprivation and the share facing all three. The analysis shows that the shares of the population with environmental deprivations rise with the MPI, but with much variation around the trend. Countries with the lowest share of poor people facing at least one deprivation are mainly in the Arab States and Latin American and the Caribbean (7 of the top 10). Of the countries with the fewest multidimensionally poor people with all three environmental deprivations, better performers are concentrated in South Asia—5 of the top 10. Several South Asian countries have reduced some environmental deprivations, notably access to potable water, even as other deprivations have remained severe. And five countries are in both top 10 lists—not only is their environmental poverty relatively low, it is also less intense.
the most disadvantaged people carry a double burden of deprivation: more vulnerable to the wider effects of environmental degradation, they must also cope with threats to their immediate environment posed by indoor air pollution, dirty water and unimproved sanitation
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Environmental degradation stunts people’s capabilities in many ways, going beyond incomes and livelihoods to include impacts on health, education and other dimensions of well-being
Performance on these indicators does not necessarily identify environmental risks and degradation more broadly, for example, in terms of exposure to floods. At the same time the poor, more subject to direct environmental threats, are also more exposed to environmental degradation writ large. We investigate this pattern further by looking at the relationship between the MPI and stresses posed by climate change. For 130 nationally defined administrative regions in 15 countries, we compare area-specific MPIs with changes in precipitation and temperature. Overall, the poorest regions and locales in these countries seem to have gotten hotter but not much wetter or drier—change that is consistent with evidence exploring the effects of climate change on income poverty.
Environmental threats to selected aspects of human development
environmental factors, including that unclean water and inadequate sanitation and hygiene are among the 10 leading causes of disease worldwide. Each year environment-related diseases, including acute respiratory infections and diarrhoea, kill at least 3 million children under age 5—more than the entire under-five populations of Austria, Belgium, the Netherlands, Portugal and Switzerland combined. Environmental degradation and climate change affect physical and social environments, knowledge, assets and behaviours. Dimensions of disadvantage can interact, compounding adverse impacts—for example, the intensity of health risks is highest where water and sanitation are inadequate, deprivations that often coincide. Of the 10 countries with the highest rates of death from environmental disasters, 6 are also in the top 10 in the MPI, including Niger, Mali and Angola.
Impeding education advances for disadvantaged children, especially girls
Environmental degradation stunts people’s capabilities in many ways, going beyond incomes and livelihoods to include impacts on health, education and other dimensions of well-being.
Bad environments and health— overlapping deprivations
The disease burden arising from indoor and outdoor air pollution, dirty water and unimproved sanitation is greatest for people in poor countries, especially for deprived groups. Indoor air pollution kills 11 times more people living in low HDI countries than people elsewhere. Disadvantaged groups in low, medium and high HDI countries face greater risk from outdoor air pollution because of both higher exposure and greater vulnerability. In low HDI countries more than 6 people in 10 lack ready access to improved water, while nearly 4 in 10 lack sanitary toilets, contributing to both disease and malnourishment. Climate change threatens to worsen these disparities through the spread of tropical diseases such as malaria and dengue fever and through declining crop yields. The World Health Organization’s Global Burden of Disease database provides some striking findings on the repercussions of
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Despite near universal primary school enrolment in many parts of the world, gaps remain. Nearly 3 in 10 children of primary school age in low HDI countries are not even enrolled in primary school, and multiple constraints, some environmental, persist even for enrolled children. Lack of electricity, for example, has both direct and indirect effects. Electricity access can enable better lighting, allowing increased study time, as well as the use of modern stoves, reducing time spent collecting fuelwood and water, activities shown to slow education progress and lower school enrolment. Girls are more often adversely affected because they are more likely to combine resource collection and schooling. Access to clean water and improved sanitation is also especially important for girls’ education, affording them health gains, time savings and privacy.
Other repercussions
Household environmental deprivations can coincide with wider environmental stresses, constricting people’s choices in a wide range of contexts and making it harder to earn a living from natural resources: people have to work more to achieve the same returns or may
even have to migrate to escape environmental degradation. Resource-dependent livelihoods are time consuming, especially where households face a lack of modern cooking fuel and clean water. And time-use surveys offer a window into the associated gender-based inequalities. Women typically spend many more hours than men do fetching wood and water, and girls often spend more time than boys do. Women’s heavy involvement in these activities has also been shown to prevent them from engaging in higher return activities. As argued in the 2009 HDR, mobility— allowing people to choose where they live—is important for expanding people’s freedoms and achieving better outcomes. But legal constraints make migration risky. Estimating how many people move to escape environmental stresses is difficult because other factors are in play, notably poverty. Nevertheless, some estimates are very high. Environmental stress has also been linked to an increased likelihood of conflict. The link is not direct, however, and is influenced by the broader political economy and contextual factors that make individuals, communities and society vulnerable to the effects of environmental degradation.
Disequalizing effects of extreme weather events
Children disproportionately suffer from weather shocks because the lasting effects of malnourishment and missing school limit their prospects. Evidence from many developing countries shows how transitory income shocks can cause households to pull children out of school. More generally, several factors condition households’ exposure to adverse shocks and their capacity to cope, including the type of shock, socioeconomic status, social capital and informal support, and the equity and effectiveness of relief and reconstruction efforts.
Empowerment—reproductive choice and political imbalances
Transformations in gender roles and empowerment have enabled some countries and groups to improve environmental sustainability and equity, advancing human development.
Gender inequality
a 10 percent increase in the number of people affected by an extreme weather event reduces a country’s HDI almost 2 percent, with larger effects on incomes and in medium HDI countries
Alongside pernicious chronic threats, environmental degradation can amplify the likelihood of acute threats, with disequalizing impacts. Our analysis suggests that a 10 percent increase in the number of people affected by an extreme weather event reduces a country’s HDI almost 2 percent, with larger effects on incomes and in medium HDI countries. And the burden is not borne equally: the risk of injury and death from floods, high winds and landslides is higher among children, women and the elderly, especially for the poor. The striking gender inequality of natural disasters suggests that inequalities in exposure —as well as in access to resources, capabilities and opportunities—systematically disadvantage some women by making them more vulnerable.
Our Gender Inequality Index (GII), updated this year for 145 countries, shows how reproductive health constraints contribute to gender inequality. This is important because in countries where effective control of reproduction is universal, women have fewer children, with attendant gains for maternal and child health and reduced greenhouse gas emissions. For instance, in Cuba, Mauritius, Thailand and Tunisia, where reproductive healthcare and contraceptives are readily available, fertility rates are below two births per woman. But substantial unmet need persists worldwide, and evidence suggests that if all women could exercise reproductive choice, population growth would slow enough to bring greenhouse gas emissions below current levels. Meeting unmet need for family planning by 2050 would lower the world’s carbon emissions an estimated 17 percent below what they are today. The GII also focuses on women’s participation in political decision-making, highlighting that women lag behind men across the world, especially in Sub-Saharan Africa, South Asia and the Arab States. This has important implications for sustainability and equity. Because women often shoulder the heaviest burden of resource collection and are
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Meeting unmet need for family planning by 2050 would lower the world’s carbon emissions an estimated 17 percent below what they are today
the most exposed to indoor air pollution, they are often more affected than men by decisions related to natural resources. Recent studies reveal that not only is women’s participation important but also how they participate—and how much. And because women often show more concern for the environment, support proenvironmental policies and vote for proenvironmental leaders, their greater involvement in politics and in nongovernmental organizations could result in environmental gains, with multiplier effects across all the Millennium Development Goals. These arguments are not new, but they reaffirm the value of expanding women’s effective freedoms. Thus, women’s participation in decision-making has both intrinsic value and instrumental importance in addressing equity and environmental degradation.
Power disparities
air pollution and dirty water—suggesting an important scope for positive synergies.
positive synergies—winning strategies for the environment, equity and human development
In facing the challenges elaborated here, a range of governments, civil society, private sector actors and development partners have created approaches that integrate environmental sustainability and equity and promote human development—win-win-win strategies. Effective solutions must be context-specific. But it is important, nonetheless, to consider local and national experiences that show potential and to recognize principles that apply across contexts. At the local level we stress the need for inclusive institutions; and at the national level, the scope for the scaling up of successful innovations and policy reform. The policy agenda is vast. This Report cannot do it full justice—but the value added is in identifying win-win-win strategies that demonstrate success in addressing our social, economic and environmental challenges by managing, or even bypassing, trade-offs through approaches that are good not only for the environment but also for equity and human development more broadly. To inspire debate and action, we offer concrete examples showing how the strategy of overcoming potential trade-offs and identifying positive synergies has worked in practice. Here, we present the example of modern energy.
Access to modern energy
As argued in the 2010 HDR, empowerment has many aspects, including formal, procedural democracy at the national level and participatory processes at the local level. Political empowerment at the national and subnational levels has been shown to improve environmental sustainability. And while context is important, studies show that democracies are typically more accountable to voters and more likely to support civil liberties. A key challenge everywhere, however, is that even in democratic systems, the people most adversely affected by environmental degradation are often the worst off and least empowered, so policy priorities do not reflect their interests and needs. Evidence is accumulating that power inequalities, mediated through political institutions, affect environmental outcomes in a range of countries and contexts. This means that poor people and other disadvantaged groups disproportionately suffer the effects of environmental degradation. New analysis for this Report covering some 100 countries confirms that greater equity in power distribution, broadly defined, is positively associated with better environmental outcomes, including better access to water, less land degradation and fewer deaths due to indoor and outdoor
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Energy is central to human development, yet some 1.5 billion people worldwide—more than one in five—lack electricity. Among the multidimensionally poor the deprivations are much greater—one in three lacks access. Is there a trade-off between expanding energy provision and carbon emissions? Not necessarily. We argue that this relationship is wrongly characterized. There are many promising prospects for expanding access without a heavy environmental toll: • Off-grid decentralized options are technically feasible for delivering energy services
to poor households and can be financed and delivered with minimal impact on the climate. • Providing basic modern energy services for all would increase carbon dioxide emissions by only an estimated 0.8 percent— taking into account broad policy commitments already announced. Global energy supply reached a tipping point in 2010, with renewables accounting for 25 percent of global power capacity and delivering more than 18 percent of global electricity. The challenge is to expand access at a scale and speed that will improve the lives of poor women and men now and in the future.
Averting environmental degradation
Promising avenues are also emerging to reduce the adverse impacts of disasters through equitable and adaptive disaster responses and innovative social protection schemes. Disaster responses include community-based riskmapping and more progressive distribution of reconstructed assets. Experience has spurred a shift to decentralized models of risk reduction. Such efforts can empower local communities, particularly women, by emphasizing participation in design and decision-making. Communities can rebuild in ways that redress existing inequalities.
rethinking our development model—levers for change
The large disparities across people, groups and countries that add to the large and growing environmental threats pose massive policy challenges. But there is cause for optimism. In many respects the conditions today are more conducive to progress than ever—given innovative policies and initiatives in some parts of the world. Taking the debate further entails bold thinking, especially on the eve of the UN Conference on Sustainable Development (Rio+20) and the dawn of the post2015 era. This Report advances a new vision for promoting human development through the joint lens of sustainability and equity. At the local and national levels we stress the need to bring equity to the forefront of policy and programme design and to exploit the potential multiplier effects of greater empowerment in legal and political arenas. At the global level we highlight the need to devote more resources to pressing environmental threats and to boost the equity and representation of disadvantaged countries and groups in accessing finance.
Integrating equity concerns into green economy policies
there are many promising prospects for expanding energy provision without a heavy environmental toll
A broader menu of measures to avert environmental degradation ranges from expanding reproductive choice to promoting community forest management and adaptive disaster responses. Reproductive rights, including access to reproductive health services, are a precondition for women’s empowerment and could avert environmental degradation. Major improvements are feasible. Many examples attest to the opportunities for using the existing health infrastructure to deliver reproductive health services at little additional cost and to the importance of community involvement. Consider Bangladesh, where the fertility rate plunged from 6.6 births per woman in 1975 to 2.4 in 2009. The government used outreach and subsidies to make contraceptives more easily available and influenced social norms through discussions with opinion leaders of both sexes, including religious leaders, teachers and nongovernmental organizations. Community forest management could redress local environmental degradation and mitigate carbon emissions, but experience shows that it also risks excluding and disadvantaging already marginalized groups. To avoid these risks, we underline the importance of broad participation in designing and implementing forest management, especially for women, and of ensuring that poor groups and those who rely on forest resources are not made worse-off.
A key theme of this Report is the need to fully integrate equity concerns into policies that affect the environment. Traditional methods of assessing environmental policies fall short. They might expose the impacts on the path of future emissions, for example, but they are
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traditional methods of assessing environmental policies are often silent on distribution issues. while the importance of equity and inclusion is already explicit in the objectives of green economy policies, we propose taking the agenda further
often silent on distributive issues. Even when the effects on different groups are considered, attention is typically restricted to people’s incomes. The importance of equity and inclusion is already explicit in the objectives of green economy policies. We propose taking the agenda further. Several key principles could bring broader equity concerns into policy-making through stakeholder involvement in analysis that considers: • Nonincome dimensions of well-being, through such tools as the MPI. • Indirect and direct effects of policy. • Compensation mechanisms for adversely affected people. • Risk of extreme weather events that, however unlikely, could prove catastrophic. Early analysis of the distributional and environmental consequences of policies is critical.
A clean and safe environment— a right, not a privilege
Embedding environmental rights in national constitutions and legislation can be effective, not least by empowering citizens to protect such rights. At least 120 countries have constitutions that address environmental norms. And many countries without explicit environmental rights interpret general constitutional provisions for individual rights to include a fundamental right to a healthy environment. Constitutionally recognizing equal rights to a healthy environment promotes equity by no longer limiting access to those who can afford it. And embodying this right in the legal framework can affect government priorities and resource allocations. Alongside legal recognition of equal rights to a healthy, well functioning environment is the need for enabling institutions, including a fair and independent judiciary, and the right to information from governments and corporations. The international community, too, increasingly recognizes a right to environmental information.
Participation and accountability
have both intrinsic and instrumental value. Major disparities in power translate into large disparities in environmental outcomes. But the converse is that greater empowerment can bring about positive environmental outcomes equitably. Democracy is important, but beyond that, national institutions need to be accountable and inclusive—especially with respect to affected groups, including women —to enable civil society and foster popular access to information. A prerequisite for participation is open, transparent and inclusive deliberative processes —but in practice, barriers to effective participation persist. Despite positive change, further efforts are needed to strengthen the possibilities for some traditionally excluded groups, such as indigenous peoples, to play a more active role. And increasing evidence points to the importance of enabling women’s involvement, both in itself and because it has been linked to more sustainable outcomes. Where governments are responsive to popular concerns, change is more likely. An environment in which civil society thrives also engenders accountability at the local, national and global levels, while freedom of press is vital in raising awareness and facilitating public participation.
Financing investments: where do we stand?
Process freedoms are central to human development and, as discussed in last year’s HDR,
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Sustainability debates raise major questions of costs and financing, including who should finance what—and how. Equity principles argue for large transfers of resources to poor countries, both to achieve more equitable access to water and energy and to pay for adapting to climate change and mitigating its effects. Four important messages emerge from our financing analysis: • Investment needs are large, but they do not exceed current spending on other sectors such as the military. The estimated annual investment to achieve universal access to modern sources of energy is less than an eighth of annual subsidies for fossils fuels. • Public sector commitments are important (the generosity of some donors stands out), and the private sector is a major—and
critical—source of finance. Public efforts can catalyse private investment, emphasizing the importance of increasing public funds and supporting a positive investment climate and local capacity. • Data constraints make it hard to monitor private and domestic public sector spending on environmental sustainability. Available information allows only official development assistance flows to be examined. • Funding architecture is complex and fragmented, reducing its effectiveness and making spending hard to monitor. There is much to learn from earlier commitments to aid effectiveness made in Paris and Accra. Although the evidence on needs, commitments and disbursements is patchy and the magnitudes uncertain, the picture is clear. The gaps between official development assistance spending and the investments needed to address climate change, low-carbon energy, and water and sanitation are huge— even larger than the gap between commitments and investment needs. Spending on low-carbon energy sources is only 1.6 percent of the lower bound estimate of needs, while spending on climate change adaptation and mitigation is around 11 percent of the lower bound of estimated need. For water and sanitation the amounts are much smaller, and official development assistance commitments are closer to the estimated costs.
Closing the funding gap: currency transaction tax—from great idea to practical policy
implementing the tax is something new to highlight. It has high-level endorsement, including from the Leading Group on Innovative Financing, with some 63 countries, among them China, France, Germany, Japan and the United Kingdom. And the UN High-Level Advisory Group on Climate Change Financing recently proposed that 25–50 percent of the proceeds from such a tax be directed to climate change adaptation and mitigation in developing countries. Our updated analysis shows that at a very minimal rate (0.005 percent) and without any additional administrative costs, the currency transaction tax could yield additional annual revenues of about $40 billion. Not many other options at the required scale could satisfy the new and additional funding needs that have been stressed in international debates. A broader financial transaction tax also promises large revenue potential. Most G-20 countries have already implemented a financial transaction tax, and the International Monetary Fund (IMF) has confirmed the administrative feasibility of a broader tax. One version of the tax, a levy of 0.05 percent on domestic and international financial transactions, could raise an estimated $600–$700 billion. Monetizing part of the IMF’s surplus Special Drawing Rights has also attracted interest. This could raise up to $75 billion at little or no budgetary cost to contributing governments. The SDRs have the added appeal of acting as a monetary rebalancing instrument; demand is expected to come from emerging market economies looking to diversify their reserves.
Reforms for greater equity and voice
at a minimal rate and without additional administrative costs, a currency transaction tax could yield annual revenues of $40 billion. Not many other options could satisfy the new and additional funding needs stressed in international debates
The funding gap in resources available to address the deprivations and challenges documented in this Report could be substantially narrowed by taking advantage of new opportunities. The prime candidate is a currency transaction tax. Argued for by the 1994 HDR, the idea is increasingly being accepted as a practical policy option. The recent financial crisis has revived interest in the proposal, underscoring its relevance and timeliness. Today’s foreign exchange settlement infrastructure is more organized, centralized and standardized, so the feasibility of
Bridging the gap that separates policy-makers, negotiators and decision-makers from the citizens most vulnerable to environmental degradation requires closing the accountability gap in global environmental governance. Accountability alone cannot meet the challenge, but it is fundamental for building a socially and environmentally effective global governance system that delivers for people. We call for measures to improve equity and voice in access to financial flows directed
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any truly transformational effort to scale up efforts to slow or halt climate change will require blending domestic and international, private and public, and grant and loan resources
at supporting efforts to combat environmental degradation. Private resources are critical, but because most of the financial flows into the energy sector, for example, come from private hands, the greater risks and lower returns of some regions in the eyes of private investors affect the patterns of flows. Without reform, access to financing will remain unevenly distributed across countries and, indeed, exacerbate existing inequalities. This underlines the importance of ensuring that flows of public investments are equitable and help create conditions to attract future private flows. The implications are clear—principles of equity are needed to guide and encourage international financial flows. Support for institution building is needed so that developing countries can establish appropriate policies and incentives. The associated governance mechanisms for international public financing must allow for voice and social accountability. Any truly transformational effort to scale up efforts to slow or halt climate change will require blending domestic and international, private and public, and grant and loan resources. To facilitate both equitable access and efficient use of international financial flows, this Report advocates empowering national stakeholders to blend climate finance at the country level. National climate funds can facilitate the operational blending and monitoring of domestic and international, private and public, and grant and loan resources. This is essential to ensure domestic accountability and positive distributional effects.
The Report proposes an emphasis on four country-level sets of tools to take this agenda forward: • Low-emission, climate-resilient strategies —to align human development, equity and climate change goals. • Public-private partnerships—to catalyse capital from businesses and households. • Climate deal-flow facilities—to bring about equitable access to international public finance. • Coordinated implementation and monitoring, reporting and verification systems—to bring about long-term, efficient results and accountability to local populations as well as partners. Finally, we call for a high-profile, global Universal Energy Access Initiative with advocacy and awareness and dedicated support to developing clean energy at the country level. Such an initiative could kickstart efforts to shift from incremental to transformative change. * * * This Report casts light on the links between sustainability and equity and shows how human development can become more sustainable and more equitable. It reveals how environmental degradation hurts poor and vulnerable groups more than others. We propose a policy agenda that will redress these imbalances, framing a strategy for tackling current environmental problems in a way that promotes equity and human development. And we show practical ways to promote jointly these complementary goals, expanding people’s choices while protecting our environment.
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1
chap ter
why sustainability and equity?
The human development approach has enduring relevance for making sense of our world. Last year’s Human Development Report (HDR) reaffirmed the concept of human development— emphasizing empowerment, equity and sustainability in expanding people’s choices. It showed that these key aspects do not always coincide and highlighted challenges in addressing them. And it raised the need to promote empowerment, equity and sustainability so that they are mutually reinforcing. That report also documented substantial progress over the past four decades. The Human Development Index (HDI) has risen dramatically since 1970 — 41 percent overall and 61 percent in low HDI countries— reflecting strong advances in health, education and incomes. Significant gains have been made in girls’ primary and secondary education, for example. If these rates of progress are sustained, by 2050 more than three-quarters of the world’s people will live in countries with an HDI similar to that of very high HDI countries today. There has also been progress in other dimensions: the share of countries that are democracies has risen from less than a third to three-fifths. The 2011 Arab Spring marked another leap forward, appearing to end decades of autocratic rule for some 100 million people. But we cannot assume that average past rates of progress will continue: progress has been far from uniform across countries and over time. And in two key dimensions of human development, conditions have deteriorated. For environmental sustainability, evidence of devastating current and future impacts is mounting. And income inequality has worsened, while disparities in health and education remain significant. These are the themes of this Report: the adverse human repercussions of environmental
degradation, which causes disproportionate harm to poor and disadvantaged people, and the need to make greater equity part of the solution. Exploring patterns and implications, the Report sounds a bold call to action. In so doing, it identifies ways to break the pernicious link between environmental degradation and economic growth that has tainted much of the development experience of at least the past half-century and threatens future progress. This vision aligns with that of international declarations on sustainable development —including those in Stockholm (1972), Rio de Janeiro (1992) and Johannesburg (2002)— which advanced the notion of three pillars of sustainable development: environmental, economic and social.1 Intragenerational equity is part of the social pillar. Our call for prudence in managing the environment and basic natural resources springs from an emphasis on expanding opportunities for the most disadvantaged and from the need to consider the risks of catastrophic events. We do not deal at length with broader issues of economic, financial and political sustainability, though we draw on some important lessons from those spheres. We can add more value by concentrating on a well defined set of issues, rather than attempting to cover related fields. The choice of scope is also driven by the urgency of addressing today’s grave environmental threats. In sum, this Report highlights the links between two closely related challenges to show how human development can become both more environmentally sustainable and more equitable. * * * This chapter sets the stage by reviewing the notion of limits to human development and two alternate paradigms of sustainability that
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we care about environmental sustainability because of the fundamental injustice of one generation living at the expense of others. Poeple born today should not have a greater claim on Earth’s resources than those born a hundred or a thousand years from now
fundamentally affect how we assess some of humanity’s most pressing choices. We take a conservative stance because we cannot be certain of always finding technological fixes to the problems we create. Central to this approach is recognizing the inherent uncertainty associated with the future and the need to deal with risks responsibly to meet our obligations to current and future generations.
The 1994 HDR asserted “there is no tension between human development and sustainable development. Both are based in the universalism of life claims.”6 The 2010 HDR went further, emphasizing sustainability in reaffirming human development:7 Human development is the expansion of people’s freedoms to live long, healthy and creative lives; to advance other goals they have reason to value; and to engage actively in shaping development equitably and sustainably on a shared planet. People are both the beneficiaries and the drivers of human development, as individuals and in groups. Sustainable development gained prominence with the 1987 publication of Our Common Future, the report of the UN World Commission on Environment and Development, headed by former Norwegian Prime Minister Gro Harlem Brundtland. The report produced what became the standard definition of sustainable development: “development that meets the needs of the present without compromising the ability of future generations to meet their own needs.”8 But the commission’s work is relevant for much more. It differed from much subsequent work on sustainability in its emphasis on equity: Many problems of resource depletion and environmental stress arise from disparities in economic and political power. An industry may get away with unacceptable levels of water pollution because the people who bear the brunt of it are poor and unable to complain effectively. A forest may be destroyed by excessive felling because the people living there have no alternatives or because timber contractors generally have more influence than forest dwellers. Globally, wealthier nations are better placed financially and technologically to cope with the effects of climatic change. Hence, our inability to promote the common interest in sustainable development is often a product of the relative neglect of economic and social justice within and amongst nations.
Are there limits to human development?
Most people around the world have seen major improvements in their lives over the last 40 years. But there are major constraints in our capacity to sustain these trends. If we deal decisively with these challenges, we could be on the cusp of an era of historic opportunities for expanded choices and freedoms. But if we fail to act, future generations may remember the early 21st century as the time when the doors to a better future closed for most of the world’s people. We care about environmental sustainability because of the fundamental injustice of one generation living at the expense of others. Poeple born today should not have a greater claim on Earth’s resources than those born a hundred or a thousand years from now. We can do much to ensure that our use of the world’s resources does not damage future opportunities—and we should. Amartya Sen notes that “a fouled environment in which future generations are denied the presence of fresh air … will remain foul even if future generations are so very rich.” 2 The fundamental uncertainty about what people will value in the future means that we need to ensure equal freedom of choice, the lynchpin of the capability approach, in part by protecting the availability and diversity of natural resources.3 Such resources are critical in allowing us to lead lives that we value and have reason to value.4 The early HDRs recognized the centrality of the environment. The first report warned of the continuing increase in environmental hazards, including health risks, from Earth’s warming, damage to the ozone layer, industrial pollution and environmental disasters.5
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The commission also voiced concerns that the world was reaching its natural limits to growth in economic activity. In 1972 a group of scientists commissioned by the Club of Rome published The Limits to Growth, predicting that at current rates of consumption growth, many natural resources would run out in the next century. Economists criticized this thesis for its disregard of price adjustments and technological change that would moderate rising demand for resources.9 But the facts seemed to bear out some of their predictions —adjusted for inflation, oil prices rose fivefold between 1970 and 1985.10 Over the next two decades the perception of scarcity changed. Most commodity prices peaked in the mid-1980s, and by 1990 prices had fallen from their 1980s highs—57  percent for petroleum, 45 percent for coal and 19 percent for copper. Against this backdrop the belief that we were approaching a global resource constraint became less plausible—if resources were becoming scarce, prices should be rising not falling. By 1997 even the United Nations Economic and Social Council was referring to the Club of Rome report’s predictions as “dogmatic,” “unreliable” and “politically counterproductive.”11 Now, the pendulum has swung back again. Concerns differ in some respects from those four decades ago. Today, the problems are more evident in the preservation of renewable natural resources, ranging from forests and fisheries to the air we breathe. But the message is clear: our development model is bumping up against concrete limits.
Competing paradigms
The idea that resource scarcity limits the world’s development potential has a long history. In the late 18th century Malthus believed that limited land was an absolute constraint on food consumption and therefore on the population that could inhabit the Earth. Yet 200 years later, the world is home to seven times more people than when Malthus wrote. In practice, technological improvements and substitution of abundant for scarce resources have allowed living standards to continue to rise over the past two centuries. The
inflation-adjusted price of food is much lower today than it was 200 —or even 50 —years ago, and known reserves of many minerals are now substantially higher than in 1950.12 With improved farming techniques, world food production has outstripped population growth. The Green Revolution doubled rice and wheat yields in Asia between the 1960s and 1990s through the introduction of high-yield plant varieties, better irrigation and the use of fertilizers and pesticides.13 These increased yields were achieved, however, through means that were not always sustainable. Our concerns for more sustainable agricultural practices go hand in hand with our awareness of the roughly 1 billion people who are undernourished and face serious food insecurity.14 These observations have led some to posit that as the stock of nonrenewable resources is consumed, technological innovation and price signals will avert shortages that limit future development. As a resource becomes scarcer, rising relative prices mean higher potential profits for innovators and for the owners of assets that can be substituted for the diminished scarce resource. These forces can cut resource use substantially even as consumption grows. The Worldwatch Institute estimates that the production of one unit of output in the United States in 2000 required less than a fifth as much energy as it did in 1800.15 This leads to a thesis known as weak sustainability, which focuses on total capital stock rather than on natural resource depletion. Disputing this view, advocates of the strong sustainability thesis believe that some basic natural assets have no real substitutes and thus must be preserved.16 These assets are fundamental not only to our capacity to produce goods and services but also to human life. Societies should strive to sustain the flow of services from natural capital over time because the accumulation of physical or other kinds of capital cannot compensate for Earth’s warming, ozone layer depletion and major biodiversity losses. While advocates of strong sustainability do not disregard the growing efficiency of resource use, they argue that history is not necessarily a good guide to the future. In the past some
CHapteR 1
the thesis of weak sustainability focuses on total capital stock rather than on natural resource depletion; that of strong sustainability focuses on the belief that some basic natural assets have no real substitutes and thus must be preserved
why SuStAinABility And equity?
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constraints on natural capital may not have been binding, but today some types of natural capital are irreplaceable. No example illustrates this better than Earth’s warming. There is overwhelming evidence that we are reaching an upper limit to our capacity to emit greenhouse gases without dire consequences. As one advocate of strong sustainability argues, we are moving from an “empty world” economy, where human-made capital was limiting and natural capital superabundant, to a “full world” economy, where the opposite is true.17 Beyond these debates, more recent thinking has emphasized the potential congruence of growth and environmental sustainability within the broader paradigm of a green economy.18 This thinking diverges from the traditional discourse on sustainability by focusing on ways in which economic policies
BOX 1.1
can engender sustainable production and consumption patterns with inclusive, pro-poor solutions that integrate environmental considerations into everyday economic decisions.19 Our approach complements and enriches the green economy discourse, emphasizing people, the multiple dimensions of well-being and equity. Our concerns include—but go beyond —growth alone.
The critical role of uncertainty
Environmental risk management—gambling with the planet
We are gambling with our planet through “games” in which private individuals reap the benefits while society bears the costs. A system that allows such outcomes is doomed to mismanage risk. As Nobel Prize–winning economist Joseph Stiglitz recently noted, “the bankers that put our economy at risk and the owners of energy companies that put our planet at risk may walk off with a mint. But on average and almost certainly, we as a society, like gamblers, will lose.” Perverse incentives provide investment banks and energy companies with hidden subsidies, like low liability caps, the prospect of bailouts, and the knowledge that taxpayers will shoulder the costs. Because these companies do not have to bear the full cost of any resulting crises, they may take excessive risks. Consider the 2010 BP Deepwater Horizon oil spill in the United States, for example, where the costs well exceeded the $75 million liability limit. And even where liability is limitless, loopholes exist. In Japan, for instance, the Nuclear Compensation Act excludes cases in which “the damage is caused by a grave natural disaster of exceptional character.” Rare events with huge consequences are of course difficult to predict. But we can no longer afford to turn a blind eye, notwithstanding uncertainties. These events are occurring more frequently. And because most greenhouse gases will remain in the atmosphere for centuries, we cannot wait until all uncertainties are resolved. The sooner we act, the better. What level of risk will persuade people of the need to change their behaviour? Research in behavioural psychology and experimental economics yields sobering insights. In simulation exercises showing how groups of participants respond when asked to invest collectively in preventing climate change, too many players were free riding, that is, counting on the altruism of others. In scenarios where the probability of disastrous climate change was very low, almost no funds were pledged. But even when the probability was 90 percent, only about half of 30 study groups pledged sufficient funds. The projected costs of averting climate change pale beside those of allowing change to continue unbridled. But precisely because cooperation is not guaranteed, even under highprobability scenarios, strong political and advocacy efforts are needed to elicit commitments. As Joseph Stiglitz warns, the risks of inaction are too high: “If there were other planets to which we could move at low cost in the event of the almost certain outcome predicted by scientists, one could argue that this risk is worth taking. But there aren’t, so it isn’t.”
Source: Stiglitz 2011; Milinksi and others 2008; Speth 2008.
Differences between strong and weak sustainability approaches go beyond whether financial savings can substitute for natural resource depletion. A key difference lies in the role of uncertainty. How can we be sure of finding ways to offset the damage caused by current and future production and consumption? The answer is that we cannot be certain. Acknowledging this inherent uncertainty supports the strong sustainability thesis. Consider biodiversity. Its instrumental benefits for people are well known: greater biodiversity increases the chances of finding cures for illnesses, developing high-yield crops and maintaining ecosystem goods and services such as water quality. We know that ecosystems are resilient—up to a point. Yet defining the threshold at which ecosystems break down is hard. An ecosystem might sustain piecemeal destruction for some time until an unknown threshold is breached such that it unravels. 20 These risks and unknown thresholds have led to real concerns about gambling with the planet (box 1.1). Technological change is uncertain. Productivity growth accelerated after the Second World War, for example, then slowed between the 1970s and 1990s.21 We can understand retroactively what drove accelerations and slowdowns, but it is very difficult to predict the future. Even more uncertainty surrounds the types of innovations that will emerge. History is replete with unfulfilled predictions of specific innovations—from all-purpose personal robots to mass-market space travel—and with the failure to anticipate other innovations, such as personal computers, the Internet and mobile communications.22
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Climate change debates have brought into sharp relief the relevance of uncertainty and risk for understanding the future.23 Scientists have concluded that the probability of a disastrous systemwide collapse is not negligible. And since we cannot place a meaningful upper bound on the catastrophic losses from large temperature changes, we need to cut greenhouse gas emissions not only to mitigate the consequences known to result from their accumulation but also to protect ourselves against uncertain worst-case scenarios.24 It follows that weak and strong sustainability differ, more than anything, in their attitude towards risk. The question is not whether different types of natural and other forms of capital were substitutes in the past, but whether technological and institutional change will proceed at a pace and direction that ensure continuing improvements in human development. The position we take depends also on the value we put on the well-being of future generations relative to that of current generations —in other words, on how we discount the future. From the perspective of capabilities, there is no justification to assume that the future will provide greater opportunities than the present or to place a lower value on the well-being of the present generation over future ones.25 Given the principles underlying the human development approach, the inclination to give equal weight to the well-being of all generations and the centrality of risk and uncertainty, our position leans towards that of strong sustainability.
not any particular thing but rather to endow them with whatever it takes to achieve a standard of living at least as good as our own and to look after their next generation similarly.” Solow added, “We are not to consume humanity’s capital, in the broadest sense,” which is a succinct statement of the case for weak sustainability. Of course, just what “standard of living” refers to is an open question, 26 while what is “good” is also value dependent.
What we mean by sustainability
Sustainability, equity and human development
Since the Brundtland Report, scholars have offered further definitions of sustainable development. One point of contention was the commission’s reference to “needs,” often interpreted to mean basic needs, which some believe is too narrow. Economist Robert Solow offered an alternative definition in 1993, arguing that the duty of sustainability was “to bequeath to posterity
Most definitions of sustainable development capture the precept that the possibilities open to people tomorrow should not differ from those open today, but generally do not adequately capture sustainable human development. They do not refer to the expansion of choice, freedoms and capabilities intrinsic to human development. They do not recognize that some dimensions of well-being are incommensurable. And they do not consider risk. Human development is the expansion of the freedoms and capabilities people have to lead lives they value and have reason to value. Freedoms and capabilities that enable us to lead meaningful lives go beyond satisfaction of essential needs. In recognizing that many ends are necessary for a good life and that these ends can be intrinsically valuable, freedoms and capabilities are also very different from living standards and consumption.27 We can respect other species, independent of their contribution to our living standards, just as we can value natural beauty, regardless of its direct contribution to our material standard of living. The human development approach recognizes that people have rights that are not affected by the arbitrariness of when they were born. Further, the rights in question refer not only to the capacity to sustain the same living standards but also to access the same opportunities. This limits the substitution that can occur across dimensions of well-being. Today’s generation cannot ask future generations to breathe polluted air in exchange for a greater capacity to produce goods and services. That would restrict the freedom of future generations to choose clean air over more goods and services.
CHapteR 1
Since we cannot place a meaningful upper bound on the catastrophic losses from large temperature changes, we need to cut greenhouse gas emissions not only to mitigate the known consequences but also to protect against uncertain worst-case scenarios
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A central concern of the human development approach is protecting the most disadvantaged groups. The most disadvantaged are not just the generations that are worse off on average. They are also those who would suffer most from the realizations of the adverse risks they face as a result of our activity. Thus, we are concerned not only with what happens on average or in the most likely scenario but also with what happens in less likely but still possible scenarios, particularly those that entail catastrophic risks. Building on the work of Anand and Sen, 28 we define “sustainable human development” as “the expansion of the substantive freedoms of people today while making reasonable efforts to avoid seriously compromising those of future generations.” Like the 1994 HDR, this definition emphasizes that the objective of development is to sustain the freedoms and capabilities that allow people to lead meaningful lives. Our definition of sustainable human development is normative: we seek the sustainability not just of any state of events but of those that expand substantive freedoms.
BOX 1.2
Therefore, inequitable development can never be sustainable human development. This Report does not propose a unique measure of sustainable human development. Despite recent advances, measuring sustainability remains plagued by major data limitations (box 1.2). A perennial challenge is the disconnect among local, national and global measures—such as the distinction between whether a national economy is sustainable and its contribution to global sustainability. For example, attributing the damage from carbon dioxide to the economy that produces goods that have been exported for consumption ignores both who benefited from consuming the goods and services and the global nature of the damage. Focusing too much on measurement can obscure some key but unquantifiable issues. These include the risks faced by different people and groups and the role of public deliberation in making policy choices and enabling a society to decide how to avoid seriously compromising future well-being.
What we mean by equity
Measures of sustainability—a conceptual overview
The conceptual paradigm — weak sustainability or strong — has implications for how we measure and assess trends. Given the range of opinions on how to define sustainability, it is not surprising that a broadly acceptable quantitative measure is hard to pin down. Many measures have emerged in the literature. One recent study identified 37— some better known than others. Here we review those that are most in use. Green national accounting adjusts such measures as gross domestic product or savings for environmental quality and resource depletion. Adjusted net savings, a measure of weak sustainability, adds education spending and subtracts for the depletion of energy, minerals and forests and for damage from carbon dioxide emissions and pollution. It is an aggregate measure of all capital in an economy — financial, physical, human and environmental. It implies that the different kinds of capital are perfect substitutes, so that financial savings can replace a loss of natural resources, for example. Composite indices aggregate social, economic and environmental indicators into a single index. A great deal of innovative work has pursued this approach. Two examples capturing strong sustainability are the ecological footprint— a measure of the annual stress people put on the biosphere — and the environmental performance index. None of the aggregate measures is perfect. For instance, some scholars take issue with adjusted net savings’ valuing such nonmarket components as the damage from carbon dioxide emissions, while the ecological footprint has been criticized for neglecting biodiversity. Informed by ongoing debates about measurement, we refer to the main composite measures alongside a dashboard that presents specific indicators to capture different aspects of sustainability (see statistical tables 6 and 7). The single indicators underline the importance of strong sustainability by exposing poor performance and deterioration on any front.
Source: Jha and Pereira 2011; Dasgupta 2007; Neumayer 2010a, 2010b.
Early ideas of equity postulated that individuals should be rewarded according to their contribution to society. 29 Used interchangeably with fairness, equity has come to refer primarily to distributive justice—that is, unjust inequalities between people. Contemporary thinking on equity owes much to the work of US philosopher John Rawls, who argued that just outcomes are those that people would agree to under a “veil of ignorance”—that is, if they did not know what status they would occupy in society.30 Rawls’s idea of justice espoused basic liberties and procedural fairness and permitted inequalities only if they could reasonably be expected to be to everyone’s advantage (and if reducing them would make everyone worse off). The capability approach emerged from thinking about which inequalities are just or unjust. In a set of landmark lectures in 1979, Amartya Sen proposed that we think about equality in terms of capabilities. Equality is neither necessary nor sufficient for equity. Different individual abilities and preferences lead to
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different outcomes, even with identical opportunities and access to resources. Absolute levels of capabilities matter: inequality between millionaires and billionaires is less the focus than inequalities between the poor and the wealthy. And personal characteristics are also important: poor and disadvantaged groups, including people with mental or physical disabilities, need greater access to public goods and services to achieve equality of capabilities. Despite conceptual differences, inequity and inequality in outcomes are closely linked in practice—because inequalities in outcomes are largely the product of unequal access to capabilities. A Malian can expect to live 32 fewer years on average than a Norwegian because the possibilities for people in Mali are far narrower on average than those for people in Norway. In this case, clearly the inequalities between Mali and Norway are also inequitable. Moreover, we can measure inequality in key outcomes, whereas we cannot readily observe the distribution of capabilities. So, in this Report we use inequality as a proxy for inequity, pointing out the exceptions where the relationship is not straightforward. We also consider inequality in human development—extending beyond income inequality to inequalities in access to health, education and broader political freedoms.
Why centre on equitable sustainability?
This Report concentrates on the links between sustainability and equity. The main issues are the adverse repercussions for human development of the lack of environmental sustainability, especially for those currently disadvantaged, and more positively, the intersections between greater sustainability and equity, as well as the potential for progressive reforms that promote both goals. We will argue that promoting human development entails addressing local, national and global sustainability and that this can—and should—be equitable and empowering. We ensure that the aspirations of the world’s poor for better lives are fully taken into account in moving towards greater environmental sustainability.31 Expanding people’s
opportunities and choices is a major imperative of the human development approach. There may be trade-offs and difficult choices. But as we discuss below, the existence of these choices also implies a higher order moral imperative to consider how to build positive synergies that keep the present from being at odds with the future. Concerns with sustainability and equity are similar in one fundamental sense: both are about distributive justice. Inequitable processes are unjust, whether across groups or generations. Inequalities are especially unjust when they systematically disadvantage specific groups of people, whether because of gender, race or birthplace, or when the gap is so great that acute poverty is high. The current generation’s destroying the environment for future generations is no different from a present-day group’s suppressing the aspirations of other groups for equal opportunities to jobs, health or education. Anand and Sen made the case for jointly considering sustainability and equity more than a decade ago: “It would be a gross violation of the universalist principle,” they argued, “if we were to be obsessed about intergenerational equity without at the same seizing the problem of intragenerational equity.”32 Yet many theories on sustainability view equity and the plight of the poor as separate and unrelated. Such thinking is incomplete and counterproductive. Thinking about policies to restore sustainability independent of policies to address inequalities between and within countries is equivalent to framing policies to address inequalities between groups (such as rural and urban) while disregarding the interrelationships with equity between other groups (such as poor and rich). While we argue strongly for the need to consider sustainability and equity jointly, we do not claim that the two are the same. Sustainability is concerned with one type of equity—across people born in different times —as distinct from the distribution of outcomes, opportunities or capabilities today. If this were not the case, it would be meaningless to speak about the effect of equity on sustainability.
CHapteR 1
Promoting human development entails addressing local, national and global sustainability; this can—and should —be equitable and empowering
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The reasons to focus on the links between sustainability and equity are normative but also empirical. The empirics help us understand their links—how they reinforce each other in some cases—and the trade-offs that can arise, as we investigate in chapters 2 and 3.
Our focus of inquiry
This Report identifies ways to jointly advance sustainability and equity. Our line of inquiry supports the broader human development agenda, which seeks to understand the actions and strategies people can use to expand their freedoms and capabilities. While we recognize that many factors could impede or enhance the sustainability of human development, we limit our focus to environmental sustainability. We discuss what people, communities, societies and the world can do to ensure that processes respect distributive justice between and across generations while expanding capabilities wherever possible. Pursuing sustainability and equity jointly does not require that they be mutually reinforcing. In many instances they will not be. But it compels us to identify positive synergies between the two and to give special consideration to the trade-offs.
FIGURE 1.1
An illustration of policy synergies and trade-offs between equity and sustainability
This framework encourages special attention to identifying positive synergies between the two goals and to considering trade-offs.
Expand access to renewable energy 1 Subsidize coal Restrict access 2 in developing 4 to public countries forests 3 Subsidize gasoline consumption
GR EA TE ST GR TE EA ST
LEAST
Figure 1.1 illustrates this logic with examples of specific policies that typically improve or worsen sustainability and equity.33 While we have sought to highlight likely outcomes, the implications are often context-specific, so the figure is not intended to be deterministic. Some examples: • Expanded access to renewable energy and a global currency transaction tax to finance climate change mitigation and adaptation can advance both sustainability and equity (quadrant 1), as we will explore in chapters 4 and 5. • Subsidies on gasoline consumption, still common in many countries, may set us back in both dimensions (quadrant  3) by favouring those who can afford a car while generating an incentive for excessive resource depletion. Countless cases of regressive, inequitable subsidies in agriculture, energy and water are also often associated with environmental damage.34 • Some policies may advance one objective but set back the other. Subsidizing coal in developing countries may promote growth but also contribute to higher greenhouse gas emissions. Such a policy could have positive effects on global equity but negative effects on sustainability (quadrant 4). • The converse can also occur: policies can improve sustainability while worsening inequity (quadrant 2). For example, policies that limit access to common property resources such as forests may enhance sustainability by preserving the natural resource but can deprive poor groups of their primary source of livelihoods, though this is certainly not always the case. We do not assume a positive empirical association between sustainability and equity. This association may well exist, and it requires investigation. Schematically, it can arise whenever most of the feasible alternatives fall in either quadrant 1 or 3 of figure 1.1. But it is also possible that most feasible alternatives fall in quadrant 2 or 4, which present trade-offs between sustainability and equity. And the pathways may be nonlinear. Such possibilities require explicit and careful consideration.
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SU
ST A
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TY
EQ U IT Y
But we can go further. A trade-off between sustainability and equity is like a trade-off in the well-being of two disadvantaged groups. Because no trade-off is isolated from a society’s structural and institutional conditions, as in the case of trade-offs between the claims of different groups, we must address the underlying constraints. So, our policy focus is aimed not only at finding positive synergies but also at identifying ways to build synergies. Our objective is to find solutions that fall in quadrant 1—solutions that are win-win-win (good for the environment while promoting equity and human
development). We should prefer approaches in quadrant 1, whenever available, to those that fall in quadrant  2 or 3 but recognize that options in quadrant  1 may not always be available.35 * * * The next chapter reviews how resource constraints and environmental thresholds impede human development and equity. We review the cross-national evidence of links among sustainability, equity and human development —and identify the challenges to meeting these goals successfully.
CHapteR 1
why SuStAinABility And equity?
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2
patterns and trends in human development, equity and environmental indicators
This chapter reviews patterns and trends in human development, inequality and key environmental indicators. We present new evidence of the threats to progress posed by environmental degradation and inequalities within and across countries. The most disadvantaged bear and will continue to bear the consequences of environmental degradation, even if many contribute little to the underlying causes.
chap ter
progress and prospects
Progress in many aspects of human development has been substantial over the past 40 years, as the 2010 Human Development Report (HDR) showed. But income distribution has worsened, and environmental degradation threatens future prospects.
Progress in human development
Most people today live longer, are more educated and have more access to goods and services than ever before. Even in economically distressed countries, people’s health and education have improved greatly. And progress has extended to expansions in people’s power to select leaders, influence public decisions and share knowledge. Witness the gains in our summary measure of development, the Human Development Index (HDI), a simple composite measure that includes health, schooling and income. The world’s average HDI increased 18 percent between 1990 and 2010 (41 percent since 1970), reflecting large improvements in life expectancy, school enrolment, literacy and income.1 Almost all countries benefited. Of the 135 countries in our sample for 1970– 2010 (with 92 percent of the world’s people), only three had a lower HDI in 2010 than in 1970. Poor countries are catching up with rich
CHapteR 2
countries on the HDI, convergence that paints a far more optimistic picture than do trends in income, where divergence continues. But not all countries have seen rapid progress, and the variations are striking. People in Southern Africa and the former Soviet Union have endured times of regress, especially in health. And countries starting from the same position had markedly different experiences. China’s per capita income grew an astounding 1,200 percent over the 40 years, but the Democratic Republic of the Congo’s fell 80 percent. Advances in technical knowledge and globalization made progress more feasible for countries at all levels of development, but countries took advantage of the opportunities in different ways. The 2010 HDR reviewed trends in empowerment—people’s ability to exercise choices and to participate in, shape and benefit from household, community and national processes. For the Arab States the situation described last year—of few signs of in-depth democratization—has changed profoundly since late 2010 (box 2.1).
Has progress come at the cost of environmental degradation?
Not all sides of the story are positive. Income inequality has worsened, and production and consumption patterns, especially in rich countries, seem to be unsustainable. To explore environmental trends, we need to decide which measure of environmental degradation to use. The conceptual challenges were considered in chapter 1. There are also data challenges, and some measures are available only for recent years. Box 2.2 discusses the important insights offered by leading aggregate sustainability measures. But to understand patterns and trends, we prefer to use specific indicators. 2
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BOX 2.1
Overcoming the democratic deficit—empowerment and the Arab Spring
Last year’s Human Development Report (HDR) looked at the “democratic deficit” in the Arab States, seeking to understand why the region had demonstrated few signs of significant democratization. Drawing on the Arab Human Development Reports since 2002, the 2010 global HDR pointed to the stark contrasts between actual practice and formal adherence to democracy, human rights and the rule of law. It emphasized that many democratic reforms in the region had been offset by countermeasures limiting citizen rights in other respects — including nearly unchecked concentration of power in the executive branch. Civil society, in turn, was weak: “Popular demand for democratic transformation and citizens’ participation is a nascent and fragile development in the Arab countries,” noted the 2009 Arab Human Development Report (p. 73). Even so, in most of the Arab States long-term trends showed major progress in income, health and education, the Human Development Index (HDI) dimensions, since 1970. Five Arab States emerged among the top 10 performers — Oman, Saudi Arabia, Tunisia, Algeria and Morocco — while Libya was among the top 10 countries in nonincome HDI achievement. All these countries advanced due mainly to improvements in health and education. Particularly striking were the changes in these countries relative to others at a similar HDI 40 years earlier. For instance, in 1970 Tunisia had a lower life expectancy than the Democratic Republic of the Congo and fewer children in school than Malawi. Yet by 2010 Tunisia was in the high HDI category, with an average life expectancy of 74 years and most children enrolled through secondary school. The recent pro-democracy protests across the Arab States began in Tunisia and Egypt, driven in both cases by educated urban youth. Multiple and complex causes underlie any social phenomena, but the democratization movement can be considered a direct consequence of human development progress. Indeed, many analysts over the years — sociologists, political scientists and others both in and outside the region — have argued that popular demand for democracy and human rights is an integral part of broader modernization and development. As the first Arab Human Development Report affirmed in 2002 (p. 18): “Human development, by enhancing human capabilities, creates the ability to exercise freedom, and human rights, by providing the necessary framework, create the opportunity to exercise it. Freedom is both the guarantor and the goal of both human development and human rights.” In the long run people who have attained higher levels of education and who have experienced rising living standards are unwilling to tolerate continued autocratic rule. For example, health and education are often necessary for meaningful participation in public life. Progress in these areas often occurs through their extension to the disadvantaged and disenfranchised, and once extended, it is very hard for elites to exclude the broader population from civic and political rights. The transition in the former Soviet Union is an earlier example of this pattern. But this progress must be placed within a broader context. Development has led to other contradictions, with rising but unfulfilled expectations often generating deep social frustrations. Inequality has increased while cellphones and Twitter™ have permitted more rapid transmission of ideas. Many analysts have pointed to high unemployment and underemployment among educated youth as a key factor driving political dissent in the region. Half the population in the Arab States is under 25, and youth unemployment rates are nearly double the global average. In Egypt an estimated 25 percent of college graduates cannot find full-time professional work—in Tunisia that figure rises to 30 percent. Although the outcome of this year’s political upheavals will not be clear for some time, the region has already profoundly changed. What was striking until recently was the juxtaposition of authoritarian rule and rising development achievement. In 2011 this “Arab democracy paradox” seemed to be coming to a sudden end, opening the door to a much fuller realization of people’s freedoms and capabilities throughout the region.
Source: 2010 HDR (UNDP–HDRO 2010; see inside back cover for a list of HDRs); UNDP 2002, 2009; Kimenyi 2011.
We have drawn on a wealth of research and analysis to determine which indicators provide the best insights. We start by looking at patterns of carbon dioxide emissions over time, a good if imperfect proxy for the environmental impacts of a country’s economic activity on climate. Emissions per capita are much greater in very high HDI countries than in low, medium and high HDI countries combined, because of many more energy-intensive activities, such as driving cars, using air conditioning and relying on fossil fuel–based electricity.3 Today, the average person in a very high HDI country accounts for more than four times the carbon dioxide emissions and about twice the emissions of the other important greenhouse gases (methane, nitrous oxide) as a person in a low,
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medium or high HDI country.4 Compared with an average person living in a low HDI country, a person in a very high HDI country accounts for about 30 times the carbon dioxide emissions. For example, the average UK citizen accounts for as much greenhouse gas emissions in two months as a person in a low HDI country generates in a year. And the average Qatari —living in the country with the highest per capita greenhouse gas emissions—does so in only 10 days, although this figure reflects both consumption within the country and production that is consumed elsewhere, an issue we revisit below. Of course, development has many dimensions. The HDI recognizes this by aggregating measures of three key dimensions— income, health and education. How do these
BOX 2.2
What can we learn from trends in aggregate measures of sustainability?
Of the aggregate measures of sustainability surveyed in box 1.2 in chapter 1, only two are available for a large number of countries over a reasonably long period: the World Bank’s adjusted net savings and the Global Footprint Network’s ecological footprint. What do these measures tell us? Adjusted net savings is positive for all Human Development Index (HDI) groups, meaning that the world is (weakly) sustainable (see figure). The positive trend for low, medium and high HDI countries suggests that their sustainability has improved over time, while that of the very high HDI countries is declining over time. However, as reviewed in chapter 1, the concept of weak sustainability underlying adjusted net savings has been criticized for not acknowledging that sustainability requires maintaining some natural capital. Adjusted net savings also involves some other controversial methodological choices. For example, valuing natural resources at market prices can overestimate the sustainability of an economy that produces them as the resources become scarcer and thus more expensive. Further analysis — taking into account the uncertainty embodied in greenhouse gas emissions and their monetary valuation — shows that the number of countries considered unsustainable in 2005 would rise about two-thirds —from 15 to 25— if adjusted net savings used a more comprehensive measure of emissions that includes methane and nitrous oxide as well as carbon dioxide and acknowledged valuation uncertainties. In other words, adjusted net savings may be overestimated. The ecological footprint, by contrast, shows that the world is increasingly exceeding its global capacity to provide resources and absorb wastes. If everyone in the world had the same consumption as people in very high HDI countries and with current technologies, we would need more than three Earths to withstand the pressure on the environment. The big message from the ecological footprint is that patterns of consumption and production are unsustainable at the global level Adjusted net savings (percent of GNI) and imbalanced regionally. And Low, 20 medium the situation is worsening, espeand high cially in very high HDI countries. HDI 10 The ecological footprint esVery high HDI timates the amount of forest that 0 1980 1990 2005 would be required to absorb carbon dioxide emissions —though this is Ecological footprint (hectares per capita) not the only method for sequesterVery high 6 ing emissions. It neglects other key HDI aspects of the environment, includ4 Low, medium ing biodiversity, and such amenities 2 and high as water quality. And it focuses on HDI 0 1980 1990 2005 consumption, so that the consumer Source: HDRO calculations based on data from country rather than the producer World Bank (2011b) and www.footprintnetwork.org. country is responsible for the impact of imported natural resources. One further issue is that most changes over time (both global and national) are driven by carbon dioxide emissions, and there is a strong correlation between the volume of carbon emissions and the value of the ecological footprint. Another more recent measure is the environmental performance index, developed at Yale and Columbia Universities. This composite index uses 25 indicators to establish how close countries are to established environmental policy goals — a useful policy tool, built from a rich set of indicators and providing a broad definition of sustainability. But the measure’s data intensity (requiring 25 indicators for more than 160 countries) inhibits construction of a time series for the analysis of trends in this Report. Adjusted net savings and ecological footprint show different results for sustainability trends over time
Source: Garcia and Pineda 2011; Stiglitz, Sen and Fitoussi 2009.
dimensions interact with measures of environmental degradation? The dimensions interact very differently with carbon dioxide emissions per capita: the association is positive and strong for income, still positive but weaker for the HDI and nonexistent for health and education (figure 2.1). This result is of course intuitive: activities that emit carbon dioxide into the atmosphere are those linked to the production and distribution of goods. Carbon dioxide is emitted by factories and trucks, not by learning and vaccinations. These results also show the nonlinear relationship between carbon dioxide emissions per capita and HDI components: there is practically no relation at low levels of human development, but a “tipping point” appears to be reached beyond which a strong positive correlation between carbon dioxide emissions per capita and income is observed.
CHapteR 2
The correlation between some key measures of sustainability and national levels of development are well known. Less well known, and emerging from our analysis, is that growth in carbon dioxide emissions per capita is related to the speed of development. Countries with faster HDI improvements also experience a faster increase in carbon dioxide emissions per capita (figure 2.2).5 Changes over time—not the snapshot relationship, which reflects cumulative effects— are the best guide to what to expect as a result of development today. The bottom line: recent progress in the HDI has come at the cost of global warming. In countries advancing fastest in the HDI, carbon dioxide emissions per capita also grew faster. But these environmental costs come from economic growth, not broader gains in HDI, and the relationship is not fixed. Some
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FIGURE 2.1
the association with carbon dioxide emissions per capita is positive and strong for income, positive for the hdi and nonexistent for health and education
Carbon dioxide emissions per capita (tonnes)
35 30 25 20 15 10 5 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
–0.3
–0.2
–0.1
0
0.1
0.2
Income component of the HDI
Note: Data are for 2007. Source: HDRO calculations, based on data from the HDRO database.
HDI
Health and education (nonincome) components of the HDI
countries have advanced in both the HDI and environmental sustainability (those in the lower right quadrants of figure 2.2)—an important point investigated below. This relationship does not hold for all environmental indicators. Our analysis finds only a weak positive correlation between levels of the HDI and deforestation, for example. Why do carbon dioxide emissions per capita differ from other environmental threats?
FIGURE 2.2
Research shows that some environmental threats have increased with development and others have not. A seminal study points to an inverted-U relationship for air and water pollution, showing that environmental degradation worsens then improves as the level of development rises (a pattern known as the environmental Kuznets curve). 6 This can be explained in terms of the increasing responsiveness of governments to people’s desire for
Countries with higher growth also experience faster increase in carbon dioxide emissions per capita
Change in carbon dioxide emissions per capita (tonnes)
0.06 0.04 0.02 0 –0.02 –0.04 –0.06 –0.08 –0.01 0 0.01 –0.01 0 0.01 –0.01 0 0.01
Change in the income component of the HDI
Note: Data are for 2007. Source: HDRO calculations, based on data from the HDRO database.
Change in the HDI
Change in the health and education (nonincome) components of the HDI
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clean and healthy environments as countries become richer. But with carbon dioxide emissions, the damage is global and harms mostly future generations, so even very rich countries have little to gain from reining in greenhouse gas emissions unless others act too. These global patterns can be seen as a series of environmental transitions and related risks for people, set against overall HDI trends. In a twist on the traditional Kuznets story, the global evidence suggests that countries address direct household deprivations first (such as access to water and energy), then community deprivations (notably pollution) and finally deprivations with global effects and externalities (namely climate change).7 Where the link between the environment and quality of life is direct, as with pollution, environmental achievements are often greater in developed countries; where the links are more diffuse, performance is much weaker. Figure 2.3 depicts three generalized findings: • Environmental risk factors with an immediate impact on households—such as indoor air pollution, poor water and sanitation—are more severe at lower HDI levels and decline as the HDI rises. As we show in chapter 3, within countries these threats also tend to be concentrated among the multidimensionally poor. • Environmental risks with community effects—such as urban air pollution— seem to worsen as the HDI rises from low levels and then begin to improve beyond a certain point.8 This is the Kuznets part of the story. • Environmental risk factors with global effects—such as greenhouse gas emissions —tend to increase with the HDI, as shown empirically in figure 2.2. Of course, the HDI itself is not the true driver of these transitions. Public policies are important too. Incomes and economic growth have an important explanatory role for emissions—but the relationship is not deterministic. For example, Norway’s per capita carbon dioxide emissions (11  tonnes) are less than a third those of the United Arab Emirates (35 tonnes), although both have high incomes.9 Patterns of natural resource use also
CHapteR 2
FIGURE 2.3
patterns of risk change: environmental transitions and human development
Household Indoor air pollution Poor water and sanitation Global Greenhouse gas emissions
Community Urban air pollution
Severity of environmental impact
HDI
Source: Based on Hughes, Kuhn and others (2011).
BOX 2.3
Consumption and human development
Runaway growth in consumption among the best-off people in the world is putting unprecedented pressure on the environment. The inequalities remain stark. Today, there are more than 900 cars per 1,000 people of driving age in the United States and more than 600 in Western Europe, but fewer than 10 in India. US households average more than two television sets, whereas in Liberia and Uganda fewer than 1 household in 10 has a television set. Domestic per capita water consumption in the very high Human Development Index (HDI) countries, at 425 litres a day, is more than six times that in the low HDI countries, where it averages 67 litres a day. Consumption patterns are converging in some respects as people in many developing countries are consuming more luxury goods: China is poised to overtake the United States as the world’s largest luxury consumer market. But even among very high HDI countries, consumption patterns vary. Consumption accounts for 79 percent of GDP in the United Kingdom and 34 percent in Singapore despite the countries’ having nearly the same HDI. Among the explanations for these differences are demographic patterns and social and cultural norms, which affect savings practices, for example. At the same time, the links with human development are often broken, as explored in the 1998 Human Development Report: new products often target richer consumers, discounting the needs of the poor in developing countries. Education can be fundamentally important in tempering excessive consumption. Such efforts have been promoted by the UN General Assembly’s declaration of the UN Decade of Education for Sustainable Development (2005–2014) and United Nations Educational, Scientific and Cultural Organization activities geared at encouraging sustainable consumption.
Source: Data from Morgan Stanley, as cited in The Economist 2008a; data from Bain and Company 2011, as cited in Reuters 2011; Heston, Summers and Aten 2009 (Penn World Table 6.3).
vary: Indonesia deforested nearly 20 percent a year between 1990 and 2008; the Philippines, with similar per capita income, reforested 15 percent over the same period.10 And consumption patterns are also important (box 2.3). At the international level broader forces
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interact in a complex manner, changing patterns of risk—trade often allows countries to outsource the production of goods that degrade the environment, as we discuss below for deforestation. There are also outlier countries that have performed relatively well, as we show later using a broader framework of environmental risk. the findings of the quasi-experimental analysis lend empirical weight to our argument that inequality is bad not just intrinsically but also for the environment and that weak environmental performance can worsen disparities in the HDI
Are there causal relations at play?
• Higher levels of gender inequality (as measured by the Gender Inequality Index) led to lower levels of sustainability—a theme explored in chapter 3.13 These findings lend empirical weight to our argument that inequality is bad not just intrinsically but also for the environment. And weak environmental performance can worsen disparities in the HDI. We now examine these disparities in more detail.
Equity trends
Did changes in sustainability come before or after changes in human development? Is there a causal relation? Are increasing inequality and environmental unsustainability causally related? For example, if wealthier groups and corporations have disproportionate political and economic power and benefit from activities that degrade the environment, they may obstruct measures that protect the environment. A counter-example is how the empowerment of women often goes hand in hand with greater protection of the environment. Our analysis of sequencing finds that in the short run the effects go in both directions for the HDI, greenhouse gas emissions and pollution. In the long run, however, a rising HDI precedes a rise in greenhouse gas emissions, so while not conclusive, the evidence is consistent with a causal relationship where rising HDI—or at least the income component —implies higher greenhouse gas emissions in the future. What about inequality? Using quasiexperimental methods, we explored the causal relationship between inequality (measured in terms of HDI and gender disparities) and sustainability. Although country differences in environmental performance are driven by multiple contextual and other factors, it is possible to establish causality where sources of what economists call “exogenous variation” can be identified.11 We used climate-related shocks and changes in institutional arrangements, such as the year women received full electoral rights, as sources of exogenous variation. The results are striking. • Poor sustainability performance — as measured by net forest depletion and especially air pollution—raised inequality in the HDI.12
To explore what has happened to equity over time we use a multidimensional approach that goes beyond incomes. This analysis builds on the innovation in the 2010 HDR, the Inequality-adjusted HDI (IHDI), which discounts human development achievements by the inequality in each dimension, and so the IHDI falls farther below the HDI as inequality rises.14 The basic idea is intuitive. Schooling and longevity (like income) are necessary to lead fulfilling lives; therefore, we care about how they are distributed between those with more and those with less. Although incomplete, especially in the neglect of empowerment, the approach provides a fuller picture than a focus on income inequality alone. This Report takes an important step forward by presenting trends in the IHDI since 1990 for 66 countries (see statistical table 3 for the 2011 values; Technical note 2 explains the methodology).15 • Worsening income inequality has offset large improvements in health and education inequality, such that the aggregate loss in human development due to inequality sums to 24 percent.16 • The global trends conceal widening educational inequality in South Asia and deep health inequality in Africa. • Latin America remains the most unequal region in income, but not in health and education. • Sub-Saharan Africa has the greatest inequality in the HDI.
Narrowing health inequalities
Health affects people’s capability to function and flourish. The evidence shows a positive
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correlation between health and socioeconomic status. This has led researchers to focus on income and social inequalities as determinants of health, with recent investigations using new household data to examine trends.17 Our analysis suggests that the rising longevity around the world—investigated in the 2010 HDR—has been associated with greater equity: health inequality, measured by life expectancy, declined across the board.18 Very high HDI countries led the way, closely followed by improvements in East Asia and the Pacific and Latin America and the Caribbean, with the Arab States not far behind. Gains were most modest in Sub-Saharan Africa, from the lowest starting levels, due mainly to the HIV/AIDS pandemic, especially in Southern Africa, where adult HIV/AIDS prevalence rates still exceed 15 percent (figure 2.4).19
Improving equity in education
FIGURE 2.4
high hiv/AidS prevalence rates in Southern Africa stall improvements in health inequality
Loss in the health component of the HDI due to inequality, 1970–2010 Atkinson inequality index 0.5 Botswana Lesotho South Africa Zimbabwe
0.4
0.3
0.2
0.1 1970 1975 1980 1985 1990 1995 2000 2005 2010
Note: See Technical note 2 for definition of the Atkinson inequality index. Each observation represents a five-year average. Source: HDRO calculations based on life expectancy data from the United Nations Department of Economic and Social Affairs, Population Division, Population Estimates and Projections Section, and Fuchs and Jayadev (2011).
Progress in expanding education opportunities has been substantial and widespread, reflecting improvements in the quantity of schooling and greater gender equity and access. Not only are more children going to school, more finish.20 As with health, trends in the distribution of education opportunities show narrowing inequalities around the world as overall enrolments and attainment rise. For example, a study of 29 developing countries and 13 developed countries found that the power of parents’ education as a predictor of their children’s schooling fell substantially in most countries over the last 50 years, indicating reduced intergenerational inequality in education.21 Our analysis of national trends in education inequality (measured by average years of schooling) since 1970 shows improvements in most countries. In contrast with trends in income inequality, education inequality declined most in Europe and Central Asia (almost 76 percent), followed by East Asia and the Pacific (52 percent) and Latin America and the Caribbean (48 percent). Though rising average levels of education and health attainments have generally been accompanied by narrowing inequality, the effect is not automatic. Average attainments and inequality can move in different directions
CHapteR 2
and at different speeds.22 Education inequality worsened about 8 percent in South Asia, for instance, despite a massive average increase in education attainment of 180 percent.
Widening income disparities
Income inequality has deteriorated in most countries and regions—with some notable exceptions in Latin America and Sub-Saharan Africa. Some highlights: • Detailed studies show a striking increase in the income share of the wealthiest groups in much of Europe, North America, Australia and New Zealand. 23 From 1990 to 2005 within-country income inequality, measured by the Atkinson inequality index, increased 23.3 percent in very high HDI countries.24 The gap between the rich and the poor widened over the last two decades in more than three-quarters of Organisation for Economic Co-operation and Development countries and in many emerging market economies.25 • Income has also become more concentrated among top earners in China, India and South Africa. 26 In China, for example, the top quintile of income earners had 41  percent of total income in 2008, and the Gini coefficient for income inequality rose from 0.31 in 1981 to 0.42 in 2005.
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Using the same Atkinson inequality index applied to health and education and the overall IHDI, our own analysis confirms this picture and finds that average country-level income inequality increased around 20 percent over 1990–2005. The worst deterioration was in Europe and Central Asia (more than 100 percent). Over the last decade or so, much of Latin America and the Caribbean has bucked this trend: within-country inequality has been falling, especially in Argentina, Brazil, Honduras, Mexico and Peru, with some exceptions, including Jamaica.27 Some trace Latin America’s performance to the shrinking earnings gap between high- and low-skilled workers and to the increase in targeted social transfer payments. 28 The shrinking earnings gap follows expanding coverage in basic education in recent decades, but it may run into headwinds when the poor are turned away from university
BOX 2.4
education because of the low quality of their primary and secondary schooling. Why has declining inequality in health and education not been accompanied by improved income distribution? Increased access to education may be part of the story. The returns to basic education fall as more people gain access. Completion of primary school brought smaller income gains than before, while the relative value of education to those at the top of the distribution increased. This increase in the “skill premium” resulted from a combination of skill-biased technical change and changes in policy—though country institutions and policies strongly influenced country-level effects. 29 We might also expect financial crises to affect trends in inequality. To what extent do crises increase income inequality? Does income inequality make crises more likely? Can government policy make a difference? This Report focuses on the effects of environmental shocks, but recent research on the causes and effects of financial crises offers some parallels (box 2.4).
Prospects—and environmental threats
Sustainability, crises and inequality
Background research commissioned for this Report considered income inequality and two types of economic crisis — banking crises and collapses in consumption or gross domestic product— over the century to 2010. The analysis focused on 25 countries — some experiencing the crisis, others not—14 in North America and Europe and 11 elsewhere. Does inequality make crises more likely? There is some support for the hypothesis that a rise in inequality is associated with subsequent crises, but high inequality is not always linked to crisis. Rising inequality preceded crises in Sweden in 1991 and in Indonesia in 1997 but not in India in 1993. Where rising inequality did precede a crisis, it could be attributed to overconsumption among some groups or underconsumption among others and to the effects of such patterns on the broader economy. Who bears the brunt of a crisis? For 31 banking crises for which inequality data are available, there are a few cases of rising overall inequality followed by crises and then a fall in inequality, notably the 2007 Icelandic crisis — but such cases do not predominate. Inequality rose in about 40 percent of the cases, fell in just over a quarter and showed no change in the remainder. Overall, the analysis suggests no systematic relationship between crises and income inequality, even for countries simultaneously experiencing banking crisis and economic collapse. Inequality rose in the Republic of Korea, Malaysia and Singapore as a result of the 1997 Asian financial crises but remained steady in Indonesia. While data are not yet available to allow rigorous analysis of the effects of the 2008 financial crisis, some evidence affirms the lack of a clear pattern across countries — with inequality rising in some countries and falling in others. The effects of inequality and of crisis also reflect policy responses. For example, following crises, compensatory transfers or progressive taxation can mitigate inequality, while cutting transfers to reduce budget deficits can do the opposite. Crises have often prompted institutional change, for instance the introduction of social security in the United States in the 1930s. Following the Nordic crises of the 1990s, the welfare state and fiscal provisions seem to have been a powerful moderating force on any increase in inequality.
Source: Atkinson and Morelli 2011.
The global HDI has risen strongly in recent decades, but what does the future hold? How might HDI values change for developed and developing countries through 2050? And how severely might environmental and inequality constraints affect that advance? Given inherent uncertainties, we compare three scenarios through 2050, produced by the University of Denver’s Frederick S. Pardee Center for International Futures (figure 2.5).30 • A base case scenario, which assumes limited changes in inequality, environmental threats and risks, anticipates for 2050 a global HDI that is 19 percent higher than today’s (44 percent higher for Sub-Saharan Africa). The increase is less than a simple extrapolation of past trends would yield because progress in the HDI tends to slow at very high levels.31 • The environmental challenge scenario envisions intensified environmental risks at the household (indoor solid fuel use), local (water and sanitation), urban and regional (outdoor air pollution) and global levels
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(especially increasing impacts of climate change on agricultural production) and inequality and insecurity.32 The global HDI in 2050 is 8 percent lower than in the base case and 12 percent lower for South Asia and Sub-Saharan Africa. • Under an environmental disaster scenario most early 21st century gains have eroded by 2050 as biophysical and human systems are stressed by overuse of fossil fuels and falling water tables, glacial melting, progressive deforestation and land degradation, dramatic declines in biodiversity, greater frequency of extreme weather events, peaking production of oil and gas, increased civil conflict and other disruptions. The model does not exhaustively consider the potential for associated vicious feedback loops, which would exacerbate these trends. Under this scenario the global HDI in 2050 would be some 15 percent below the baseline scenario. Both the environmental challenge and environmental disaster scenarios would lead to breaks in the pattern of convergence in human development across countries observed over the past 40 years. And longer term projections suggest that divergence would widen further after 2050. This is illustrated by projections of crosscountry inequality in the HDI, using the Atkinson inequality index, which has fallen more than two-thirds over the past 40 years, reflecting the convergence trends. Under the base case, inequality among countries is projected to continue to fall over the next 40 years. But under the disaster scenario, future convergence, as measured by changes in the Atkinson inequality index, would be on the order of only 24 percent by 2050, compared with 57 percent under the baseline (figure 2.6).
FIGURE 2.5
Scenarios projecting impacts of environmental risks on human development through 2050
HDI
1.0
Very high HDI countries
0.9
Base case Environmental challenge Environmental disaster
0.8
0.7
Low, medium and high HDI countries
Base case Environmental challenge Environmental disaster
0.6
0.5
0.4
0.3
1980
1990
2000
2010
2020
2030
2040
2050
Note: See text for explanation of scenarios. Source: HDRO calculations based on data from the HDRO database and Hughes, Irfan and others (2011), who draw on forecasts from International Futures, Version 6.42.
FIGURE 2.6
Scenarios projecting slowdown and reversals of convergence in human development due to environmental risks through 2050
Atkinson inequality index
.07 (loss in the HDI due to inequality)
.06
.05
.04
.03
World median Environmental disaster
threats to sustaining progress
Past patterns suggest that, in the absence of reform, the links between economic growth and rising greenhouse gas emissions could jeopardize the extraordinary progress in the HDI in recent decades. But climate change —with effects on temperatures, precipitation,
CHapteR 2
.02
Environmental challenge Base case
.01
0 1980 1990 2000 2010 2020 2030 2040 2050
Note: See text for explanation of scenarios. Source: HDRO calculations based on data from the HDRO database and Hughes, Irfan and others (2011), who draw on forecasts from International Futures, Version 6.42.
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sea levels and natural disasters—is not the only environmental problem. Degraded land, forests and marine ecosystems pose chronic threats to well-being, while pollution has substantial costs that appear to rise and then fall with development levels. We discuss these threats in turn, then consider which countries have performed better than their regions and the world.
Climate change
Global temperatures now average 0.75°C higher than at the beginning of the 20th century, and the rate of change has accelerated (figure 2.7). The main cause is human activity, particularly burning fossil fuels, cutting forests
FIGURE 2.7
and manufacturing cement, which increase carbon dioxide emissions. Other greenhouse gases, such as those regulated by the Montreal Protocol, also pose serious threats. The 100-year global warming potential of nitrous oxide is nearly 300 times that of carbon dioxide and 25 times that of methane.33 That climate change is caused by human activities is scientifically accepted,34 though public awareness still lags, with less than two-thirds of the population worldwide aware of climate change and its causes (box 2.5).
Key drivers
Average world temperatures have risen since 1900
Variation from 1951–1980 mean (degrees Celsius) 1.0 0.8 0.6 0.4 0.2 0 –0.2 –0.4 1900 1920 1940 1960 1980 2000 2008
Note: Calculated using average temperatures in 173 countries, weighted by average population in 1950–2008. Source: HDRO calculations based on data from the University of Delaware.
Annual mean Five-year mean
TABlE 2.1
growth in carbon dioxide emissions and its drivers, 1970–2007 (percent)
Growth Per capita HDI group Very high High Medium Low World 7 3 276 49 17 42 73 609 304 112 81 94 32 72 79 233 116 82 21 91 –213 –111 –15 7 –70 Total Percentage share of total growtha Population GDP per capita Carbon intensity
a. Based on an accounting decomposition of the effects on carbon growth that simplifies the Kaya identity presented in Raupach and others (2007) from four drivers to three. Values may not sum to 100 percent because of rounding. Source: HDRO calculations based on data from World Bank (2011b).
Global carbon dioxide emissions have increased since 1970—248 percent in low, medium and high HDI countries and 42 percent in very high HDI countries. The global growth of 112 percent can be broken down into three drivers: population growth, rising consumption and carbon-intensive production.35 Rising consumption (as reflected by GDP growth) has been the main driver, accounting for 91 percent of the change in emissions, while population growth contributed 79 percent. The contribution of carbon intensity, in contrast, was –70 percent, reflecting technological advances (table 2.1). In other words, the principal driver of increases in emissions is that more people are consuming more goods—even if production itself has become more efficient, on average. Although the carbon efficiency of production (units of carbon to produce a unit of GDP) has improved 40 percent, total carbon dioxide emissions continue to rise. Average carbon dioxide emissions per capita have grown 17 percent over 1970–2007. Patterns of carbon dioxide emissions vary widely across regions and stages of development. Some highlights: • In very high HDI countries the carbon intensity of production has fallen 52 percent, but total emissions and emissions per capita have more than doubled and are 112 percent higher now than 40 years ago. Improvements in carbon efficiency have not kept up with economic growth. • Emissions are more than 10 times higher in East Asia and the Pacific than in SubSaharan Africa.
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• Emissions per capita vary from a low of 0.04 tonnes in Burundi to a high of 53 tonnes in Qatar. Trade enables countries to shift the carbon content of the goods they consume to the trading partners that produce them. The carbon dioxide emitted in the production of goods traded internationally increased by half from 1995 to 2005.36 Several countries that have committed to cutting their own emissions are net carbon importers, including Germany and Japan, as are countries that have not signed or ratified global treaties, such as the United States. While very high HDI countries account for the largest share of world carbon dioxide emissions, low, medium and high HDI countries account for more than three-fourths of the growth in carbon dioxide emissions since 1970. East Asia and the Pacific is the largest contributor by far to the increase in these emissions (45  percent), while Sub-Saharan Africa contributed only 3 percent, and Europe and Central Asia, 2 percent (figure 2.8). For methane and nitrous oxide, we have data for a shorter period, but here too, the contribution of the East Asia and the Pacific region is pronounced. The stock of carbon dioxide trapped in the atmosphere is a product of historical emissions— “carbon is forever.”37 Today’s concentrations are largely the accumulation of developed countries’ past emissions. With about a sixth of the world’s population, very high HDI countries emitted almost two-thirds (64 percent) of carbon dioxide emissions between 1850 and 2005.38 Since 1850 about 30 percent of total accumulated emissions have come from the United States. The next highest emitters are China (9  percent), the Russian Federation (8 percent) and Germany (7 percent). Very high HDI countries have generated cumulatively more than nine times more carbon dioxide per capita than low, medium and high HDI countries combined —hence the Kyoto Protocol’s “common but differentiated responsibilities” for addressing climate change, explored in detail below.
Repercussions for temperature, rainfall, sea level and disaster risk
BOX 2.5
Are people aware of climate change and its causes?
Despite overwhelming scientific evidence of the seriousness of the climate change threat and growing evidence around the world that we are already experiencing many of the effects, public awareness remains limited. The Gallup World Poll, a representative survey carried out regularly in nearly 150 countries since 2007, reveals some major gaps in public knowledge of the seriousness of the problem, its causes and even its existence (see table). Less than two-thirds of people in the world have heard of climate change. Awareness is associated with level of development. Some 92 percent of respondents in very high Human Development Index (HDI) countries reported at least some knowledge of climate change, compared with 52 percent in medium HDI countries and 40 percent in low HDI countries. Perceptions of other environmental issues also differ. Overall, 69 percent of people are satisfied with water quality while 29 percent are not, and 76 percent of people are satisfied with air quality while 22 percent are not. Not surprising, there is wide disparity across countries. For example, only 2.5 percent of people are dissatisfied with water quality in Denmark, compared with 78 percent in the Democratic Republic of the Congo. Public opinions on climate change (percent agreeing)
Country group Regions Arab States East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean South Asia Sub-Saharan Africa HDI groups Very high High Medium Low World 91.7 76.1 51.6 40.2 60.0 60.2 61.2 29.3 32.8 39.7 65.3 60.7 38.8 26.7 44.5 42.1 62.6 77.7 76.5 38.0 43.4 28.7 27.7 48.2 72.7 31.3 35.5 30.3 48.3 55.0 64.8 26.9 30.6 Aware of climate change (n = 147) Climate change is a Human activity causes serious threat climate change (n = 135) (n = 145)
Note: n refers to the number of countries surveyed. Data are population-weighted averages and refer to the most recent year available since 2007. For details on the Gallup sample and method, see https://worldview.gallup.com/content/methodology.aspx. Source: HDRO calculations based on Gallup World Poll data (www.gallup.com/se/126848/worldview.aspx).
Temperature and precipitation
Climate change affects not only temperature but also rainfall, sea level and natural disasters.
CHapteR 2
The past half century’s most dramatic changes in temperature have been in the polar regions and at higher latitudes (map 2.1).39 Does this mean that climate change harms high HDI countries more? Not necessarily. Countries with lower initial temperatures can better withstand temperature rises—whereas in climate-sensitive tropical areas a small rise in temperature can severely disrupt natural conditions, with adverse repercussions for water availability and crop productivity.40 In recent decades precipitation has fallen more than 2  millimetres (almost 3 percent)
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FIGURE 2.8
Sources of greenhouse gas growth
Share of the increase in total emissions (percent)
120 100 80 60 China and India 40 20 0 –20 –40 –60 –80
Source: HDRO calculations based on data from World Bank (2011b).
175
Carbon dioxide (1970–2007) Methane (1990–2005) Nitrous oxide (1990–2005)
China India
Europe and Central Asia Arab States East Asia and the Pacific Latin America and the Caribbean
Sub-Saharan Africa South Asia
Very high HDI High HDI Medium HDI Low HDI
MAP 2.1
temperature changes are greatest in polar regions and higher latitudes
Change from 1951–1980 average to 2000–2008 average More than –1°C –1°C to 0°C 0°C to 1°C 1°C to 2°C More than 2°C
Source: HDRO calculations based on data from the University of Delaware.
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from a 1951–1980 baseline. The largest decline has been in Sub-Saharan Africa (7  millimetres, or more than 7 percent) and in low HDI countries (4 millimetres, or more than 4  percent), followed by medium HDI countries (figure 2.9). 41 Low HDI countries have also experienced the sharpest increases in rainfall variability. What to expect going forward? There is no scientific consensus on the net effects of climate change on precipitation, given different patterns around the world. 42 However, some broad regional trends emerge from the climate models. Africa is expected to see higher than average warming—with less rain in North Africa and the southern and western parts of the continent but more rain in East Africa. Western Europe is expected to become warmer and wetter, while the Mediterranean will experience less rainfall. In Asia the number of hot days will increase, and the number of cold days will decrease. In Latin America and the Caribbean temperatures are likely to rise while precipitation falls. Small island developing states are expected to have lower than average temperature increases, but they will likely be hard hit by changes in the sea level, as we see further below.43
Sea level rise
FIGURE 2.9
rising temperatures and reduced rainfall
Levels and changes in climate variability by HDI group Levels Average value, 2000s 0.74 0.66 0.64
(degrees Celsius)
Temperature
0.84
(millimetres per month)
Precipitation
Average value, 1951–1980
Very high HDI Very high HDI High HDI Medium HDI Low HDI –1.49
High HDI –0.07
Medium HDI
Low HDI
–2.89 –4.16 Change in variability (percentage points) 1.38
(degrees Celsius)
Temperature
(millimetres per month)
Precipitation High HDI
Average value, 1951–1980
Very high High HDI HDI –0.17
Medium HDI –0.08
Low HDI –0.15
Very high HDI
Medium HDI Low HDI –0.65
Since 1870 the average sea level has risen 20 centimetres, and the rate of change has accelerated. If this accelerated rate holds, the sea level will be 31 centimetres higher in 2100 than in 1990, 44 with devastating impacts, especially for small island developing states, which are particularly exposed (box 2.6, table 2.2). Many face high mitigation costs relative to income, and their vulnerability risks discouraging private investors, affecting their ability to adapt. 45 These sea-related increases will affect all coastal regions. A half-metre sea level rise by 2050 would flood almost a million square kilometres—an area the size of France and Italy combined—and affect some 170 million people.46 The share of people likely to be affected is largest in very high HDI countries and small island developing states, but very high HDI
CHapteR 2
Average value, 2000s –1.35
population for 1950–2008. Source: HDRO calculations based on data from the University of Delaware.
–0.98 –1.38
Note: Change in variability is the difference in the coefficients of variation between 1951–1980 and the 2000s, weighted by average
countries have the resources and technology to reduce the risk of losses. The Netherlands, with large, densely populated areas of lowlying land, has abated the risk of flooding and reclaimed inundated land with innovative technology and infrastructure investments. 47 Among regions, the impact will be largest in East Asia and the Pacific, where more than 63 million people are likely to be affected (see table 2.2). The greatest economic impacts will be felt in East Asia and the Pacific and in medium HDI countries (both around
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BOX 2.6
Impacts of climate change on small island developing states
Small island and low-lying coastal countries share similar challenges, including small populations, lack of resources, remoteness, susceptibility to natural disasters, dependence on international trade and vulnerability to global developments. Their temperatures are predicted to increase 1˚–4˚C by 2100 (relative to 1960–1990), with adverse effects on people, including displacement and poorer health. Rising sea levels will displace people and inundate cultivable low-lying lands. Island countries with a low mean elevation — such as Tuvalu (1.83 metres), Kiribati (2.0 metres) and the Marshall Islands (2.13 metres) — are seriously threatened by the possibility of a 0.18–0.59 metre sea level rise by the end of 21st century. In low-elevation coastal zones the entire population of the Maldives and 85 percent of the population of the Bahamas are at risk. Health effects may be severe as well. Kiribati can expect a 10 percent drop in rainfall by 2050 — reducing fresh water 20 percent. Moreover, salt water intrusions are increasing due to sea level rise and frequent coastal flooding, further contaminating ground water wells, the primary fresh water source for its rapidly growing population. About 19 percent of potable water in Trinidad and Tobago following heavy rainfall tested positive for cryptosporidium, a diarrhoea-causing parasite. Similarly, dengue fever has a clear association with rainfall and temperature in the Caribbean. Small island developing states are vulnerable not only to climate change but also to natural disasters, including storm surges, floods, droughts, tsunamis and cyclones. Natural disasters are particularly frequent on small islands. Of the 10 countries suffering the greatest number of natural disasters per capita from 1970 to 2010, 6 were small island developing states. And a single disaster can cause huge economic losses. Hurricane Gilbert in 1988 cost Saint Lucia almost four times its GDP, while Hurricane Ivan in 2004 was responsible for losses in Grenada that were twice its GDP. The 2004 Indian Ocean tsunami that hit the Maldives killed more than 100 people and affected more than 27,000. By 2100, 90 percent of coral reefs that protect islands from ocean waves and storms could disappear, making natural disasters more likely still. Constraints extend to data and statistics. We have improved coverage of the HDI in these states, from 23 last year to 32 out of 49 this year. These states have an average HDI of 0.617, compared with the global average of 0.649.
Source: www.sidsnet.org/2.html; Elisara 2008; UNDESA 2010a; Kelman and West 2009; Mimura and others 2007; Elbi and others 2006; Amarakoon and others 2008; Noy 2009; Heger, Julca and Paddison 2009; www.climate.gov.ki/Climate_change_effects_in_Kiribati.html; www.emdat.be/result-country-profile; http://pdf.wri.org/reefs_at_risk_revisited.pdf.
TABlE 2.2
projected impacts of a half-metre rise in sea level by 2050
Number of countries 20 22 17 31 6 30 35 41 42 38 32 153 Population likely to be affected by sea level rise (millions) 8.9 63.1 4.4 7.0 38.9 10.2 1.7 41.0 15.0 84.6 30.8 171.4 Share of total population likely to be affected (percent) 2.6 3.3 1.2 1.3 2.4 1.9 3.4 16.0 4.5 0.4 9.4 2.7
Country group Regions Arab States East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean South Asia Sub-Saharan Africa Small island developing states HDI groups Very high High Medium Low World
Source: HDRO calculations based on data from Wheeler 2011.
2 percent of GDP). Low HDI countries, many landlocked, will lose proportionately less (0.5 percent).48
Natural disasters
Climate change is increasing the likelihood of extreme weather events, such as droughts, storms and floods. The average number of such
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natural disasters more than doubled from 132 a year over 1980–1985 to 357 over 2005– 2009.49 Although it is hard to link any single disaster directly to climate change—given the inherent randomness in what generates these events—science links global warming to their increased incidence.50 The frequency of high intensity tropical cyclones and associated precipitation is predicted to rise 20 percent by 2100.51 The growing incidence of reported natural disasters does not affect everyone equally— not only because the damage wrought by the average natural disaster may change but also because the capacity of societies to respond and protect themselves also varies.52 Most countries do not experience natural disasters, so patterns differ markedly by country and region. In recent years South Asia experienced the largest number, an average of almost six a year per country. Low HDI countries, while often vulnerable to drought, tend to have fewer disasters than medium HDI countries, partly because many are landlocked. Small island developing states are also highly exposed to natural disasters (see box 2.6). These numbers, which are affected by extreme cases and may differ from the
average, can reveal how societies are marked by most natural disasters and demonstrate their resilience. The good news is that the median costs of these events (whether number of deaths, people affected or economic losses) have fallen over the past four decades globally and for all HDI groups (table 2.3). Highlights include the significant drop in the median number of deaths due to natural disasters, with the steepest declines in low HDI countries (down almost 72 percent). Natural disasters afflict many more people and are much more costly in low and medium HDI countries than in high and very high HDI countries. Medium HDI countries are particularly affected: the typical natural disaster in a medium HDI country takes 11 percent more lives and affects nearly twice as many people as a typical natural disaster in a low HDI country. Economic losses have also declined over time as a share of income, though the estimates depend on underlying assumptions. * * * In sum, the poorest countries bear many of the costs of climate change, and the prospect of worsening global inequality is very real. Low HDI countries are experiencing the steepest declines in precipitation and the sharpest increases in its variability. Some of the largest temperature increases are in already-hot parts of developing countries. The frequency of natural disasters is highest in low and medium HDI countries, though the good news is that the human development cost of the typical natural disaster has declined. Sea level rise has the largest direct effects on coastal developed countries, which are often better prepared to deal with them, and on small island developing states, which are far more vulnerable.
Chronic environmental threats
opportunities and power, as chapter 3 shows, and carry further implications such as loss of biodiversity (box 2.7).
Soil erosion, desertification and water scarcity
Agricultural output has doubled over the past 50 years, with only a 10 percent increase in cultivated land. But degradation of soil and water resources is increasing: soil erosion, reduced fertility and overgrazing are affecting as much as 40 percent of croplands.53 At the extreme, overexploitation can turn arable land into desert—though the overall extent of degradation is hard to quantify.54 It affects an estimated 31 percent of total land area in low, medium and high HDI countries and about 51 percent in very high HDI countries. The lowest shares of severely and very severely degraded land in developing regions are in Latin America and the Caribbean and Europe and Central Asia, and the highest are in South Asia. Nonetheless the highest shares of people living on degraded land are in the Arab States (25 percent of the population) and Sub-Saharan Africa (22 percent) (see statistical table 7). Water is vital for natural systems and human development. Irrigated lands produce two to three times as much as rainfed agriculture. Agriculture accounts for 70–85 percent of water use—and an estimated 20 percent of global grain production uses water unsustainably. And demand for water for food production is projected to double by 2050.55
TABlE 2.3
Low HDI countries are experiencing the steepest declines in precipitation and the sharpest increases in its variability
disaster-related casualties and costs, median annual values by hdi group, 1971–1990 and 1991–2010
Deaths (per million people) Country group HDI group Very high High Medium Low World 0.9 2.1 2.7 6.9 2.1 0.5 1.1 2.1 1.9 1.3 196 1,437 11,700 12,385 3,232 145 1,157 7,813 4,102 1,822 1.0 1.3 3.3 7.6 1.7 0.7 0.7 2.1 2.8 1.0 1971–1990 1991–2010 Affected population (per million people) 1971–1990 1991–2010 Cost (percent of GNI) 1971–1990 1991–2010
Climate change is not the only environmental threat. Deforestation and overexploitation of soil and waterways can threaten long-term livelihoods, fresh water availability and essential renewable resources, such as fisheries. These problems sometimes reflect imbalances in
CHapteR 2
Note: Values are for median impacts of climatological, hydrological and meteorological natural disasters. Source: HDRO calculations based on Centre for Research on the Epidemiology of Disasters Emergency Events Database: International Disaster Database.
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BOX 2.7
Biodiversity—the accelerating loss of our ecosystems
Healthy and resilient ecosystems — and the life-supporting services that they provide — depend on the biodiversity they contain. But rapid loss of biodiversity is accelerating globally, with serious declines experienced in the last decade in fresh water wetlands, sea ice habitats, salt marshes and coral reefs. The Convention on Biological Diversity’s Global Biodiversity Outlook 3 points to “multiple indications of continuing decline in biodiversity in all three of its main components — genes, species and ecosystems.” According to the report, natural habitats in most parts of the world are shrinking, and nearly a quarter of plant species are estimated to be threatened with extinction. Environmental scientists believe that we are witnessing what may be the fastest mass extinction of species, with about half the Earth’s estimated 10 million species expected to disappear this century. The biggest cause of this loss is the conversion of natural areas to agriculture and urban development; other causes include the introduction of invasive alien species; overexploitation of natural resources; pollution; and, increasingly, the effects of climate change. Some 10–30 percent of mammal, bird and amphibian species are threatened by extinction, with more in poorer countries. This partly reflects the location of “biodiversity hotspots” (areas with the richest and most threatened resources of animal and plant life) in tropical areas. The impact of biodiversity loss on human development is severe in tropical developing countries, where poor communities rely heavily on natural resources. For example, wild foods are an important source of vitamins and minerals in the diets of many African communities. Use of wild foods can also reduce disease transmission in complex tropical ecosystems.
Source: Klein and others 2009; Myers and Knoll 2001; Rockström and others 2009; Roscher and others 2007; Secretariat of the Convention on Biological Diversity 2010.
Water withdrawals have tripled over the last 50 years.56 Pumping from aquifers exceeds natural replenishment, so water tables are falling. The main causes: destruction of wetlands, watersheds and natural water towers to make way for industrial and agricultural use. The 2006 HDR documented how power, poverty and inequality contribute to water scarcity.
Deforestation
FIGURE 2.10
Some regions deforest, others reforest and afforest
Forest cover shares and rates of change by region, 1990–2010 (millions of square kilometres) Forest area, 2010
Arab States East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean South Asia Sub-Saharan Africa Very high HDI High HDI Medium HDI Low HDI
6.72 6.58 –0.81 0.93 5.85 –0.70 0.88 4.70 9.00 9.47 –0.93 0.02
Change in forest area, 1990–2010
–0.07 0.10 0.06
10.10 16.80 –0.71
0.11
0.03
Source: HDRO calculations based on data from World Bank (2011b).
One way the demands of development appear at odds with environmental sustainability is in the loss of forest cover. This has been occurring for a long time: Earth’s forest cover today is only three-fifths of what it was in prehistoric times.57 While deforestation has often been linked to development, trends today are associated more with underdevelopment. The average forest share is similar in very high and low HDI countries (28–29 percent), and around 23 percent in medium HDI countries.58 And while very high HDI countries have increased total forest cover about 1 percent since 1990, low HDI countries have averaged 11 percent loss and high HDI countries 4 percent loss, while medium HDI countries have had almost no change. Latin America and the Caribbean and Sub-Saharan Africa had the greatest loss, followed by the Arab States; the other regions have seen minor gains (figure 2.10).59 Seven developing countries (Bhutan, China, Costa Rica, Chile, El Salvador, India, and Viet  Nam) have recently transitioned from deforesting to reforesting with support from domestic and international programmes. However, there are indications that some of these countries have, in effect, shifted deforestation to other developing countries, so that for every 100 hectares of reforestation they import the equivalent of 74 hectares in wood products. 60 Simulations suggest that the European Union transfers 75 of every 100 cubic metres of reduced timber harvest to developing countries, mainly to the tropics; Australia and New Zealand, 70 cubic metres; and the United States, 46 cubic metres. 61 Understanding trends in global forestation thus requires examining consumption and trade as well as production. 62 Switzerland,
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for example, consumes agricultural products equivalent to more than 150 percent of its cultivated land. 63 A related concern is the rise of international “land grabs,” as governments and corporations acquire large tracts in land-abundant and poorer countries (box 2.8).
Degradation of marine ecosystems
BOX 2.8
land grabbing—a growing phenomenon?
Private, government and public-private joint ventures, usually from capital-rich countries, are acquiring long-term leases or ownership rights to large portions of land (often more than 1,000 hectares) in developing countries. Economically powerful developing countries, such as China, India and Saudi Arabia, as well as developed countries, are joining the land grab. While sources differ, all suggest a recent acceleration, with estimates of more than 20–30 million hectares transacted between 2005 and mid-2009 and about 45 million hectares between 2008 and 2010. The rise in commodity prices appears to be motivating both government and private purchases. Some see this phenomenon as an opportunity for long-awaited investments in agricultural modernization that will provide access to better technology, create more jobs for farmers and reduce poverty in rural areas. But others consider it a threat to local populations. A recent World Bank study supports the latter view, finding that expected benefits were not achieved. Several studies have reported human rights violations, with local populations forcibly displaced and access to local natural resources restricted. Hurt most were smallholders, indigenous people and women, who often lack formal title to the lands on which they live and farm. Environmental organizations have criticized negative impacts, including deforestation, loss of biodiversity and threats to wildlife. Recent international initiatives seek to provide a regulatory framework to spread out the benefits and balance opportunities with risks. The challenge is to implement multilevel institutional arrangements, including effective local participation, to promote sustainability and equity in this major change in land use.
Source: Borras and Franco 2010; Deiniger and others 2011; IFAD 2011; Da Vià 2011.
Fish are an important source of protein for hundreds of millions of people: on average, people eat 24 kilograms of fish a year in North America, 18.5 in Asia and 9.2 in Latin America and the Caribbean. 64 But fishing that exceeds the natural rate of regeneration, coupled with dredging, dumping, discharge of pollutants, coastal infrastructure and coastal tourism undermines the conditions required for healthy marine ecosystems, thereby threatening their sustainability. The current annual fish catch of 145 million tonnes far exceeds the maximum annual sustainable yield of 80–100 million tonnes.65 In 2008 the Food and Agriculture Organization estimated that 53 percent of known fish stocks were fully exploited, 28 percent were overexploited, 3 percent were depleted and only 15 percent were moderately exploited.66 Although total output has not yet fallen, yields for some species, especially larger fish, have declined considerably since the 1980s.  Here again we see considerable disparity. Some 10 percent of fishing activities account for an estimated 90 percent of the total catch —mostly developed country fishers using capital-intensive methods such as technologically advanced fishing vessels with long-term storage facilities and mechanized trawls suitable for fishing in deep waters. Average annual production by fish farmers is 172 tonnes in Norway, 72 in Chile, 6 in China and 2 in India. Although 85 percent of people in the fish industry work in Asia, annual production in the region is 2.4 tonnes per ocean fisher, compared with amounts as high as 23.9 tonnes in developed regions such as Europe.67 Large commercial fishing companies not only catch more fish but also engage in damaging practices, using high bycatch methods and bottom trawling.
CHapteR 2
Catch rates are still rising, most rapidly in some developing regions, despite government initiatives to reduce overfishing. 68 Rates more than quadrupled in East Asia and the Pacific, for example, between 1980 and 2005. Once again, this increase partly reflects high production for export to developed countries, where consumption per capita is greater.
Pollution
Recent studies suggest that pollution transitions may be more complex than those described by the environmental Kuznets curve, which asserts that pollution first rises and then falls with economic development.69 For example, low-income cities have local, immediate and poverty-related environmental problems; middle-income cities have citywide problems related to rapid growth; and highincome cities experience the consequences of wealthy lifestyles.70 So, while affluence reduces the “brown” pollution problems of low-income cities, such as poor water supply, sanitation and solid waste management, it replaces them with “green” ecological issues such as waste reduction, high emissions and inefficient transport systems.
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Cities can foster sustainability, especially when urban planning integrates environmental considerations. High population density fosters economies of scale and skill and enterprise specialization, but the downside from waste generation and outdoor air pollution can be huge
Cities are at once sources of major pollution and opportunities for fostering sustainability. People in cities consume 60–80 percent of energy produced worldwide and account for roughly similar proportions of carbon emissions.71 Cities can foster sustainability, especially when urban planning integrates environmental considerations. High population density fosters economies of scale and skill and enterprise specialization. These features make most infrastructure and public goods, such as water, sanitation and drainage, and public transportation systems, more cost efficient and provide more options for material reuse and recycling. It has been estimated that when a city doubles in population, the associated increase in infrastructure requirements is only 85 percent.72 Per capita emissions in New York City are only 30 percent of the US average; the same holds for Rio de Janeiro and Brazil.73 The average Manhattan resident accounts for 14,127 fewer pounds of carbon emissions annually than a suburban New Yorker, in part due to lower vehicle use.74 The pattern appears in all US metropolitan areas. But the downside of cities from waste generation and outdoor air pollution can be huge. Air pollution, which tends to be worse in urban areas, is a major cause of respiratory and cardiovascular diseases globally, while limited access to safe drinking water and proper sanitation accounts for 1.6 million deaths a year.75 Urbanites also produce enormous quantities of waste, too often poorly managed. Areas near New Delhi and Kathmandu, for example, suffer from severe river pollution.76 Some richer countries are exporting their waste to poorer countries, with harmful effects, despite the 1992 Basel Convention restricting such trade (box 2.9). Outdoor air pollution is generally worse in cities, as are related health effects (chapter 3). The high density of pollutants also increases cloud concentration, affecting precipitation. High population density means that even small declines in per capita pollution emissions, water use or energy use can bring major absolute improvements. With around half the world’s population living in urban areas,
these potential improvements present an enormous opportunity. The relationship between equity and the density of cities is complex. But more compact neighbourhoods and affordable transport systems can enhance equity by increasing accessibility, and some evidence suggests that higher density is correlated with less social segregation. Natural disasters affecting cities can be especially devastating, as with Hurricane Katrina in New Orleans in the United States. Cities need investments in infrastructure and systems to manage these vulnerabilities. Rio de Janeiro uses sophisticated modelling techniques to predict natural disasters and take pre-emptive measures. Global trends tell a more optimistic story. Pollution measurement has been a subject of vigorous debate, but outdoor concentrations of particulate matter suggest declines around the world over the past two decades.77 SubSaharan Africa has seen more rapid decline, though from a higher level. In very high HDI countries pollution has fallen almost onethird. Even so, average concentrations of particulate matter in urban areas are 2.3 times higher in low, medium and high HDI countries than in very high HDI countries.78 Richer countries have tougher air quality regulations and measures targeting air pollution, such as control systems on power plants and industrial facilities, catalytic converters on vehicles and cleaner fuels.79 * * * This section on trends in key environmental indicators and their threats to human development has shown deterioration on several fronts, but not on all. Remarkable progress in curbing air pollution, for example, suggests that some dimensions of the environment can improve with development. Of greatest concern is that the poorest countries experience the most serious consequences of environmental degradation. The next chapter confirms that this pattern also holds within countries. We now explore how countries have broken these patterns to achieve sustainable and equitable progress in human development.
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BOX 2.9
Hazardous waste and the Basel Convention
As public concern about hazardous waste mounted in developed countries in the 1970s and 1980s, many governments passed restrictive legislation. An unexpected result was a massive increase in exports of hazardous waste — including asbestos, mercury, ash, heavy metals, clinical waste and pesticides — to developing countries. Economic inequalities made the prospect of accepting hazardous waste attractive to some countries. In the 1980s a coalition of European and US companies offered Guinea-Bissau $600 million — about five times its gross national product—to accept shipments of toxic waste, an offer it ultimately refused because of international pressure. The Basel Convention on the Control of Transboundary Movements of Hazardous Wastes and Their Disposal regulates such exports, requiring informed consent about the nature of the waste. Today, 175 countries are parties to the Basel Convention; the United States is among those that are not. A 1995 amendment prohibits all exports of hazardous waste, but it has not yet been ratified by the necessary three-quarters of participants. The convention recognizes the urgency of the problem, but an adequate international regulatory framework has not yet been established. Exposure to hazardous waste in developing countries remains serious. In 2006 a Dutch company dumped 500 tonnes of toxic waste in 16 sites in Abidjan, contaminating the city’s drinking water, soil and fisheries; killing at least 10 people; and affecting more than 100,000 people. Such cases reflect not only weaknesses in the Basel Convention but also the economic reality in many developing countries. The convention assumes that developing countries have the technical and administrative capacity to assess the risk of accepting waste shipments and the good governance necessary to resist monetary inducements, not always the case. Electronic waste (e-waste), the fastest growing sector of global waste, is hazardous to human health and the environment. E-waste from China, India, Thailand, the United States and the European Union over 2004–2008 totalled 17 million tonnes a year; the United Nations Environment Programme estimates global e-waste at 20–50 million tonnes a year. Only a small share of e-waste is recycled. For example, in 2007 the United States recycled less than 20 percent of e-waste from obsolete televisions, cell phones and computer products. The rest was disposed in landfills, mostly in developing countries such as China, India and Nigeria. Nevertheless, e-waste recycling has become a dynamic economic sector, particularly in China and India, where recovering, repairing, and trading materials from discarded electronic devices provide an important livelihood for poor people. But the lead, mercury and cadmium in these products are highly toxic. While precautions can be taken, many people are unaware of the risks.
Source: Andrews 2009; Sonak, Sonak, and Giriyan 2008; Widmer and others 2005; Robinson 2009; UNEP/GRID-Europe 2005; GreenPeace 2009; UNEP and UNU 2009; www.epa.gov/international/toxics/ ewaste.html; http://toxipedia.org/display/toxipedia/Electronic+Waste+%28E-Waste%29.
Success in promoting sustainable and equitable human development
How can we best interpret these contrasting patterns? Can we identify the better performing countries in human development, sustainability and equity? The task is difficult, not least because no single indicator captures sustainability well. But we illustrate a potentially useful approach to assessing joint progress towards these objectives and review a range of indicators that provide interesting insights into promising policy approaches. The findings synthesize much of the evidence we have accumulated so far and provide a bridge to the community and household analysis in the next chapter. We propose a method, identify some instances of positive synergies, where countries have promoted sustainable human development with equity, and discuss the main policy implications. How can we identify positive synergies? Our framework reflects both local and global dimensions of sustainability that we highlighted in figure 2.3. The local aspects, which we will explore in greater depth in the
CHapteR 2
next chapter, relate to the immediate human impacts of household-level deprivation in terms of access to water and indoor air pollution. These variables are gauged relative to regional medians of achievement. We need to account for regional differences—otherwise only very high HDI countries would be deemed successful, which would shed little light on the range of circumstances facing people around the world. The global environmental aspects of sustainability—those that pose wide-ranging threats—are measured by greenhouse gas emissions, deforestation and water use, in a normative manner, each relative to global norms reflecting good practice. Following the same logic, we identify countries with a better record on the HDI and inequality than the median of their region. Applying this multidimensional filter enables us to identify a shortlist of countries with relatively better performance in responding to both localized and global environmental threats, as well as with respect to the HDI and equity. The results are illustrative, owing to patchy data and other issues relating to comparability. Nonetheless, for the indicators that we are able to assemble,
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they suggest some promising approaches that have the potential to promote relatively equitable and environmentally sustainable policy as well as human development more broadly. Table 2.4 illustrates the application of the joint lens described above to identify countries that have performed better than the global
BOX 2.10
Positive synergies in Sweden and Costa Rica
The performance of countries identified as doing well on environmental, human development and equity fronts can offer insights and development lessons. Here we focus on environmental performance in Sweden and Costa Rica. Sweden is currently seventh in the Human Development Index (HDI), sixth best in human development loss due to inequality and first in the Gender Inequality Index. Its per capita emissions were the sixth lowest for very high HDI countries, and air pollution rates were the lowest for very high HDI countries and the fourth lowest globally. Sweden’s performance appears to be rooted in its strong environmental awareness and a tradition of egalitarian and democratic policy. For example, the Committee for Research into the Preservation and Utilization of Natural Resources, established in 1957, worked to raise public awareness of environmental issues and served as a powerful pressure group. Other early clues include a 1969 survey indicating majority support for both slower economic growth to prevent environmental deterioration and for higher local taxes to fight water pollution, reflecting a willingness to pay for better environment quality. The right to common access is rooted deeply in the Swedish social psyche and in centuries-old customs. Contemporary awareness is reflected in Gallup Poll results showing that 96 percent of Swedes are aware of climate change and almost half regard it as a serious threat. Sweden’s achievements in equity and education might translate into stronger political voice, partly explaining why popular environmental awareness and sensitivity are reflected in environmentally friendly policies. Successive governments in Costa Rica have implemented policies and built institutions with environmental objectives in mind. In 1955 Costa Rica established the Institute for Tourism to protect the country’s natural resources. But it was the forestry legislation of the late 1980s that really launched its environmental policy. The law defines the environmental services of forests as carbon sequestration, biodiversity protection, water flow regulation and scenery. It was also the foundation for introducing payments for environmental services as a financial mechanism to protect forests. By the mid-1990s environmental rights were enshrined in the Constitution, and Costa Rica had become a pioneer in selling carbon reduction credits (to Norway). Active participation by civil society, the population’s pride in the country’s beauty, biodiversity and natural resources, and investment opportunities related to sustainable practices in sectors such as tourism have also contributed.
Source: UNDP Costa Rica Country Office, Observatorio del Desarrollo and Universidad de Costa Rica 2011; Kristrom and Wibe 1997; Lundqvist 1972.
TABlE 2.4
threshold (for global threats) and better than the regional median (for local impacts, HDI and HDI losses due to inequality). 80 A few countries perform well on at least four of the five environmental fronts considered. Costa Rica stands out for good performance on all five criteria. Germany and Sweden, two very high HDI countries, perform well in deforestation, water use, water access and indoor air pollution but less well in greenhouse gas emissions. The Philippines is an interesting case particularly with respect to afforestation, because the increase in forest area has been supported by community-based social forestry programs. Also, indoor air pollution in the Philippines is only 48 percent of the regional median, and broad access to schooling and healthcare offsets traditionally high income inequality. Box 2.10 highlights the experiences of Costa Rica and Sweden. Of course, this picture is incomplete. Data limitations have already been hinted at. And, an obvious shortcoming, it does not include any indicators of political freedom and empowerment or performance on gender equality and women’s empowerment (as captured by the GII, for example, which is explored in the next chapter). All four countries are democracies and do well relative to their HDI group in terms of gender equality. Exploring trends over time also gives a more mixed picture. Of the four countries we identify here as relatively strong performers, only Germany and Sweden improved on all dimensions. Since the 1990s all countries on the list have reduced air pollution and maintained or improved the share of the population with access to water, and all but
good performers on the environment, equity and human development, most recent year available
Global threats Greenhouse gas emissions ✔ ✔ Local impacts Equity and human development HDI Overall loss (percent of regional (percent of regional median) median) 104 103 103 102 77 91 89 70
Country Costa Rica Germany Philippines Sweden
Deforestation ✔ ✔ ✔ ✔
Water use ✔ ✔ ✔
Water access ✔ ✔ ✔ ✔
Air pollution ✔ ✔ ✔ ✔
Note: These countries all pass the criteria of absolute thresholds for global threats as defined in note 80, perform better than the median of their respective regional peers both in the human development and inequality dimensions and perform better than the regional median for local impacts.
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the Philippines have reduced greenhouse gas emissions.81 Multidimensional inequality also fell in these top countries except in Costa Rica, which nevertheless still has lower inequality than its regional median.82 Many developing countries also demonstrate successful, scalable, sectoral models for transition to a green economy. Some examples:83 • The city of Curitiba in Brazil has successfully implemented innovative approaches to urban planning, city management and transport to address the challenge of rapid population growth. The city now has the highest rate of public transport use in Brazil (45 percent of all journeys) and one of the country’s lowest rates of air pollution. • Kenya’s Ministry of Energy adopted a feed-in tariff in 2008 to supply and diversify electricity generation sources, generate income and employment and reduce greenhouse gas emissions. The tariff covers biomass, geothermal, small hydroelectric, solar and wind power. In sum, it is possible to identify countries that have promoted sustainable and equitable human development through a higher HDI, lower inequality and performance on a set of environmental indicators that reflect global
sustainability and local threats. While data constraints preclude presenting a complete ranking of countries, we offer some illustrative results and suggest that the method offers a valuable means of demonstrating that countries in different regions, with very different structural characteristics and levels of development, can adopt policies consistent with more sustainable and equitable human development. * * * This chapter has considered key patterns and trends in human development and the environment and provided evidence of major cross-country disparities as well as new findings about positive synergies. In many cases the poorest countries bear the brunt of environmental deterioration, even though they contribute only a small share to the problem. But greater equality—both across and within countries—is consistent with better environmental performance. The analysis underlines the potential pay-offs from development models that both promote equity and less lopsidedly favour economic growth, themes that we explore in subsequent chapters.
CHapteR 2
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3
tracing the effects— understanding the relations
We have seen major intersections between equity and the environment. In this chapter we focus on how environmental unsustainability affects people and how inequality mediates this relationship. We also draw attention to countries and groups that have broken the pattern, emphasizing transformations in gender roles and empowerment. Poor and disadvantaged people suffer most from environmental degradation. That fact surprises no one. Almost every week the media report catastrophes that shatter lives in the poorest parts of the world—lives of people who already face major disadvantages. While extreme events are disequalizing, so too are activities that harm the environment. Studies for the United States, for example, show that toxic waste facilities are located disproportionately in working class and minority neighbourhoods, harming health and education as well as property values.1 Whether these outcomes arose because land and housing in those areas lost value after the facilities were built or because residents were less able to resist location decisions, it is clear that environmentally harmful practices accentuate racial and social inequalities. These location decisions do not happen only in market economies: in the former Soviet Union the Mayak nuclear facility was built in a region settled mostly by Muslim Tatar and Bashkir people and descendants of people repressed and exiled under Stalin. 2 This chapter aims to understand why and how these patterns come about today. Which factors condition the relationship between environmental degradation and human development? Both the absolute level and the distribution of individual, household and community capabilities matter. Absolute deprivations can hurt the environment, and bad environmental conditions erode people’s capabilities. Many examples illustrate these
chap ter
links—educated girls have lower fertility rates, and more empowered communities suffer less pollution. Through the lens of multidimensional poverty, this chapter first documents deprivations in the immediate environments of the poor and how such deprivations can intersect with adverse repercussions of climate change. Next the related environmental threats to people’s health, education and livelihoods are explored, followed by how chronic disadvantage interacts with acute risks to make extreme events more disequalizing. The chapter closes with a focus on gender and power inequalities and on how greater equality in these areas can have positive effects on the environment, laying the ground for the investigation of policy options in the chapters that follow.
A poverty lens
A key theme of this Report is that the world’s most disadvantaged people carry a “double burden.” More vulnerable to environmental degradation, they must also cope with immediate environmental threats from indoor air pollution, dirty water and unimproved sanitation.3 Our Multidimensional Poverty Index (MPI), introduced in the 2010 Human Development Report (HDR), gives us a closer look at these household-level deprivations (figure 3.1). The MPI measures deficits in health, education and living standards, combining both the number of deprived people and the intensity of their deprivations. This year we explore the pervasiveness of environmental deprivations among the multidimensionally poor—focusing on the lack of improved cooking fuel, drinking water and sanitation—and the extent of their overlap at the household level, an innovation of the MPI. These are absolute deprivations that both matter in themselves and are violations of basic
CHapteR 3 trACing the eFFeCtS—underStAnding the relAtiOnS
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FIGURE 3.1
Multidimensional poverty index— a focus on the most deprived
Multidimensional poverty Living standard MPI
human rights. Ensuring access—including to modern cooking fuel, safe water and basic sanitation—also creates the potential to expand higher order capabilities, thereby enlarging people’s choices and furthering human development. The lens of the MPI highlights joint deprivations in access.
Deprivations facing the poor
Health
Education
FIGURE 3.2
environmental deprivations in the Mpi
MPI
0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 10 20 30 40
• Arab States
East Asia and the Pacific
✖ Europe and Central Asia
Latin America and the Caribbean
• South Asia
✖ Sub-Saharan Africa
17
Environmental deprivation contribution to the MPI (percent)
MPI
0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 10 20 30 40 50 60 70 80
Share of multidimensionally poor with three environmental deprivations (percent)
Note: The dashed line in the top panel denotes what the average contribution of environmental deprivations would be if their contribution to total poverty were equal to their weight in the MPI. Countries to the right have disproportionate environmental poverty, and countries to the left, less than expected. Survey years vary by country; see statistical table 5 for details. Source: HDRO staff estimates based on data in statistical table 5.
Multidimensional poverty is estimated for 109 countries (see statistical table 5),4 and the results are striking. • Globally, at least 6 in 10 people experience one environmental deprivation, and 4 in 10 experience two or more.5 These deprivations are more acute among the multidimensionally poor. More than 9 in 10 face at least one deprivation: nearly 90 percent do not use modern cooking fuels, 80 percent lack adequate sanitation and 35 percent lack clean water. • Most suffer overlapping deprivations: 8 in 10 poor people experience two or more environmental deficits, and 29 percent face all three. • The rural poor are more afflicted. A striking 97 percent face at least one environmental deprivation, and about a third suffer all three. Comparable data for urban areas are 75 percent and 13 percent. • State- and provincial-level MPIs show wide disparities in environmental deprivations. Within Haiti the proportion of people who are both multidimensionally poor and deprived of clean water in Aire Métropolitaine/Ouest is 19 percent, while in the Centre it is 70 percent. Similarly, in Senegal the proportion of people who are both multidimensionally poor and deprived in cooking fuel is about 4 percent in Dakar and about 88 percent in Kolda. And in India deprivations in sanitation among multidimensionally poor people range from 3.5 percent in Kerala to more than 70 percent in Bihar. Environmental deprivations typically rise with the MPI, but the composition of multidimensional poverty varies, even for countries with similar poverty levels. Overall, environmental deprivations disproportionately
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Human Development RepoRt 2011
contribute to multidimensional poverty, accounting for 20 percent of the MPI—above their 17 percent weight in the index (figure 3.2, top panel).6 In rural areas the average is 22 percent of poverty, compared with 13 percent in urban areas. In Mongolia, Peru, Swaziland and Uganda such deprivations account for more than 30 percent of multidimensional poverty. But there are some good performers as well, with lower shares of environmental deprivation.7 In several Arab States (Jordan, Occupied Palestinian Territory, the Syrian Arab Republic and the United Arab Emirates) and European and Central Asian countries (Croatia, Estonia, Russian Federation and Ukraine) such deprivations are less than half their weight in the index. Brazil has also performed well. Regional patterns show that environmental deprivations are most acute in Sub-Saharan Africa: 99 percent of the multidimensionally poor face at least one environmental deprivation, and nearly 60 percent face all three (figure 3.2, bottom panel). Environmental deprivations are also severe, if less pervasive, in South Asia: 97 percent of the poor suffer at least one deficit, and 18 percent face all three. By contrast, in Europe and Central Asia 39 percent of the poor have one or more environmental deprivations (excluding Tajikistan, where the poor population is large and the share with one deprivation or more is an unusually high 82 percent). Few have all three—just over 1 percent, excluding Tajikistan. Deprivations are most widespread for access to cooking fuel (figure 3.3). In South Asia and Sub-Saharan Africa, the two poorest regions, more than 90 percent of the multidimensionally poor lack access to modern cooking fuel. More than 85 percent of poor people in both regions lack access to improved sanitation. In several Arab States water problems are paramount, affecting more than 60 percent of the multidimensionally poor. The extent of environmental deprivation is also associated with the country’s Human Development Index (HDI) value. More than 4 in 10 multidimensionally poor people in low
HDI countries face all three environmental deprivations. And these countries typically have above average environmental poverty— about 6 percentage points higher than if the environmental deprivations they face equalled their weight in the MPI. For example, 65 percent of the population in Madagascar lack access to clean water. The repercussions are extensive. Most schools in Madagascar have no running water for adequate hygiene and sanitation, so pupils fall sick regularly, missing classes and underperforming. Diarrhoea causes an estimated annual loss of 3.5 million school days in Madagascar.8 There is also good news, sometimes reflecting successful outreach by governments and nongovernmental organizations (NGOs). For example, South Asia stands out for having a relatively low share of its population (less than 15 percent) deprived in access to water.
Understanding the relations
FIGURE 3.3
environmental deprivations are greatest for access to modern cooking fuel
Share of multidimensionally poor with environmental deprivations, by region (percent) Water 22.6 Sanitation 19.5 26.8 Cooking fuel Europe and Central Asia 24.1 41.5
54.3
Latin America and the Caribbean 30.5 62.6
75.1
East Asia and the Pacific 19.4 South Asia 65.2 86.7 86.4 94.1
To better understand environmental deprivations, we analysed the data holding poverty levels constant.9 Countries were ordered by their share of multidimensionally poor people facing one or more environmental deprivations and the share facing all three. In both cases the share of the population with environmental deprivations rises with the MPI but with much variation around the trend (figure 3.4). Countries above the trend line have higher than average environmental poverty, and those below perform better. The countries with the lowest shares of their population facing at least one deprivation are concentrated in the Arab States and Latin America and the Caribbean (7 of the top 10), while those with the lowest share of the population with all three are concentrated in South Asia (5 of the leading 10; table 3.1). Brazil, Djibouti, Guyana, Morocco and Pakistan are in both top 10 lists. They perform well in having a low share of the population with at least one environmental deprivation and with all three. Some examples: • The Brazilian government has been expanding access to water and sanitation for several decades, investing in water
CHapteR 3
98.3
Sub-Saharan Africa
Note: Survey years vary by country; see statistical table 5 for details. Data are not shown for the Arab States because low poverty levels render the results potentially unreliable. Source: Calculated based on data in statistical table 5.
trACing the eFFeCtS—underStAnding the relAtiOnS
47
FIGURE 3.4
the share of the population with environmental deprivations rises with the Mpi but with much variation around the trend
Share of multidimensionally poor with at least one deprivation (percent)
100
Share of multidimensionally poor with three deprivations (percent)
100
80
• • • • •• • • • •• ••• •• •• • • •••• • •••• • ••• • • • •• •• •• • • • • • • •• • • • PAKISTAN •SENEGAL • • • • • MOROCCO • YEMEN •• • DJIBOUTI •
IRAQ
•
80
60
60
• • •
•
•
40
• GUYANA • BRAZIL
40
••
20
20
0 0 .1 .2 .3 .4 .5 .6 .7
0 0
• INDIA • • • • NEPAL ••• • MOROCCO • GAMBIA • DJIBOUTI • • PAKISTAN • • • TAJIKISTAN • • BHUTAN • BANGLADESH BRAZIL
.1 .2 .3
• • • •• • • • •• • • • • ••• • • • • • • • • •• • • • • • • • •• • • • • • • • •• • • •
•
.4
.5
.6
.7
MPI
Source: HDRO calculations based on data in statistical table 5.
MPI
Note: Survey years vary by country; see statistical table 5 for details. The figures depict deviations from the trend for the regression exercises described in the text.
TABlE 3.1
ten countries with the lowest share of environmental deprivations among the multidimensionally poor, most recent year available for 2000–2010
Lowest share of multidimensionally poor with at least one deprivation Brazil Guyana Djibouti Yemen Iraq Morocco Pakistan Senegal Colombia Angola
Note: Countries in bold are on both lists. Source: HDRO calculations based on data in statistical table 5.
Lowest share of multidimensionally poor with all three deprivations Bangladesh Pakistan Gambia Nepal India Bhutan Djibouti Brazil Morocco Guyana
supply and using cross-subsidies to benefit low-income households.10 Innovation has also been important. Brasilia has developed condominial sewerage systems that use narrow pipes installed at shallow depths instead of more expensive conventional construction.11 Almost all Brazilian households (98 percent) use liquefied petroleum gas (LPG) fuel, thanks to policies beginning in the late 1960s for
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Human Development RepoRt 2011
a national LPG delivery system and crosssubsidies for LPG through taxes on other fuels.12 • In Bangladesh only 4 percent of the multidimensionally poor lack access to clean water, thanks to the country’s thousands of hand tubewells. But there are caveats. Coverage rates include access to a public standpipe, and wait times can be long. Dhaka has only one public tap for every 500 slum dwellers.13 Moreover, arsenic levels exceed World Health Organization (WHO) recommendations in about a third of hand tubewells, jeopardizing the health of tens of millions of Bangladeshis.14 • The Djibouti government made water and sanitation a priority in the mid-1990s.15 Reforms included priority funding and new construction.16 More than 8 in 10 Djibouti households use modern sources of cooking fuel, though use of wood and charcoal is now reportedly rising because of higher kerosene costs.17 • In Nepal water access is also fairly high among the multidimensionally poor (around 78 percent). This has been attributed to the lead role local communities and women, empowered through NGOs, have
played in planning, designing and implementing small subprojects for water supply, sanitation, health and hygiene.18 The worst performers by share of the multidimensionally poor with environmental deprivations are located across several regions, with Sub-Saharan African countries featuring prominently. Among the countries performing relatively poorly in this respect, weak institutional capacity emerges as one explanation. Some examples: • The share of Peru’s population with access to water and sanitation is among the lowest in Latin America.19 Institutional capacity, planning and quality control have impeded progress.20 Low rural electrification rates mean that more than 80 percent of rural households rely on fuelwood for cooking. The availability of modern fuel is limited in many rural areas because of poor transportation networks and high upfront costs.21 • In Mongolia large rural–urban disparities in access to clean water and sanitation are exacerbated by weak institutional capacity and lack of investment. In theory the government gives priority to the water needs of the poor, but in practice lack of regulations has resulted in price structures that provide water at low cost to business and industry while disregarding the poor. Per litre, rural consumers and small businesses pay 84 times more for clean water than do industrial and mining companies.22 The MPI sheds light on the patterns of environmental deprivations facing households (box 3.1). It shows the prevalence of overlapping deprivations but also, more optimistically, highlights countries that have done relatively well, including through programmes we explore in the next chapter. In addition to how countries perform relative to each other, this year we also explore how some have fared over time. These findings should be interpreted with care, however. Last year’s HDR recognized several limitations of the MPI as a measurement tool. The datasets cover different years, limiting comparability. In some cases the surveys may not reflect recent improvements. Additional caveats apply to the analysis here. The
three environmental deprivations were selected as the best comparable measures across countries, but other environmental threats may be equally or more acute at the local or national level. Flooding may be a more pressing concern for poor households in Bangladesh, for example, than access to water. And it is important to underline that good performance (or bad) with respect to these specific indicators is not necessarily indicative of environmental degradation more broadly. Some countries, such as Syria, have a very low MPI (and low contribution of environmental deprivation) but still face pressing environmental stresses relating to water availability, land deterioration and agricultural productivity. And, as we explore in chapter 4, addressing household-level deprivations needs to be done in a way that minimizes environmental degradation more broadly. Chapter 2 argues that as countries develop, the nature and severity of their environmental problems tend to evolve. The types of direct environmental threats experienced at the individual and household levels—those we explore here—tend to be more severe and widespread in countries at low HDI levels, and they are experienced even more acutely by the poor. We have also highlighted a double burden of the multidimensionally poor: that they may be more exposed not only to these localized, household-level threats but also to environmental degradation writ large. We investigate this pattern further by looking at the relationship between the MPI and changes in climate. For 130 nationally defined administrative regions in 15 countries, we are able to compare area-specific MPIs with changes in temperature and precipitation —the “anomalies” discussed in chapter 2 (see map 2.1). The results are thought provoking. • In our sample, on average, temperature was 0.5°C higher in 2000–2008 than in 1951– 1980, while rainfall increased nearly 9 millimetres (4.6 millimetres, if we exclude some extreme changes in Indonesia). The temperature rose in 106 of 110 cases, and rainfall rose in nearly 85 cases (80 percent). • Overall, a strong positive association emerges between MPI levels and warming,
CHapteR 3
the MPI sheds light on the patterns of environmental deprivations facing households, showing the prevalence of overlapping deprivations but also, more optimistically, highlighting countries that have done relatively well
trACing the eFFeCtS—underStAnding the relAtiOnS
49
BOX 3.1
Trends in multidimensional poverty
Our concern with equity leads us to focus on the most disadvantaged. This year we use the Multidimensional Poverty Index (MPI) to reveal trends in the multiple deprivations that batter poor people at the same time for seven countries — Bolivia, Colombia, Jordan, Kenya, Lesotho, Madagascar and Nigeria — and find that poverty declined in all of them (see figure). The decline was fastest in absolute terms in Bolivia, Nigeria and Lesotho, while annualized percentage reductions were greater in Bolivia, Colombia and Jordan, where low poverty means that small reductions translate into large relative declines. Capturing reductions in both the incidence and intensity of poverty is one of the MPI’s key strengths, creating useful incentives to reduce both the number of people in poverty and the number of deprivations that they jointly face. The index thus overcomes a well known problem associated with traditional (“headcount only”) poverty measures, which can lead to a focus on moving people from just below to just above the poverty line. In our seven countries poverty has fallen by reducing both the number of multidimensionally poor people and the intensity of their poverty. Madagascar’s improvement, for example, was driven mainly by reducing poverty intensity, while in the other countries the biggest change was in the number of poor people.
Reduction in the MPI and in the multidimensional poverty headcount and intensity in seven countries, various years
(average annual percent change)
MPI 0.008
Headcount Intensity
0.022
–1.6 –1.1
0.089
0.156
–0.7 –1.9
0.229
–0.5
0.310
–0.2
0.357 –2.2
–3.0 –0.7 –1.6
–3.8 –6.9
–5.4
–3.4
–3.1
–5.5
–5.0
–9.1
2007–2009
–8.4
–9.8 Bolivia
–8.7
Jordan
Colombia
2005–2010
2003–2008
2004–2009
Lesotho
2003–2009
Kenya
2003–2008
Nigeria
Madagascar
2004–2009
Note: Values in bold are MPI levels for the most recent year available. Headcount refers to the percentage of the population that is multidimensionally poor; intensity refers to the average percentage of deprivations experienced by people in multidimensional poverty. Source: Alkire and others forthcoming.
Underlying the overall drops in poverty, different patterns emerge. For example, multidimensional poverty fell at a similar rate in Kenya and Nigeria, but Kenya’s progress was driven by improvements across all standard of living indicators, whereas Nigeria progressed most in water, sanitation and child mortality. Poverty reduction was widely distributed across Kenya. In Nigeria, by contrast, poverty worsened in the northeast, the poorest region, while the south saw the most substantial reduction.
Source: Alkire, Roche and Santos forthcoming; Demographic and Health Surveys (www.measuredhs.com).
suggesting that localities that have had the largest increases in temperature tend to be poorer than those that have had smaller changes.23 But for rainfall there is no strong pattern,24 and within countries, overall tendencies mask considerable variation. Nonetheless, the relationship is consistent with research exploring the effects of climate change on income poverty.25 Further study is needed to extend this work to a multidimensional setting. Where poverty and the effects of climate change intersect to constrain possibilities, the poor are especially vulnerable. But more generally, disadvantaged people and groups face
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particular threats from environmental degradation because their coping options are more limited. We go on to examine particular ways in which environmental degradation threatens human development and how it may harm already deprived groups the most.
environmental threats to people’s well-being
To better understand the channels through which environmental degradation impedes and damages capabilities, especially those of poor and disadvantaged groups, we look at adverse effects on health, education, livelihoods and
other aspects of well-being, including choices on how to spend time, where to live and freedom from conflict.
Harming health
FIGURE 3.5
deaths attributable to environmental risks are associated with high Mpi levels
MPI
0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 MOZAMBIQUE COMOROS
This section reviews the adverse health impacts of indoor and outdoor air pollution, dirty water and unimproved sanitation, and climate change. Environmental degradation affects people’s health through impacts on physical and social environments as well as through the knowledge, assets and behaviours of individuals and households. Interactions between dimensions of disadvantage also affect health—for instance, health risks are greatest where water and sanitation are inadequate. Our analysis of multidimensional poverty suggests that such deprivations often coincide with deaths due to environmental causes: 6 of the 10 countries with the highest rates of death attributable to environmental causes are among the 10 countries with the highest MPI (figure 3.5).26 The economic costs of the health impacts of environmental factors, including malnutrition, are also large. The World Bank recently estimated them at close to 6 percent of GDP in Ghana and more than 4 percent in Pakistan. Adding the longer term effects on education and income boosts the annual cost for each country to as much as 9 percent of GDP.27 The WHO’s study of the global burden of disease underlines the importance of environmental factors. Unsafe water, inadequate sanitation and insufficient hygiene are among the top 10 leading causes of disease worldwide. Each year at least 3 million children under age 5 die from environment-related diseases, including acute respiratory infection and diarrhoea—more than the entire under-five population of Austria, Belgium, the Netherlands, Portugal and Switzerland combined.28 And in low HDI countries about 14 percent of the disease burden has environmental causes, notably indoor air pollution.
Indoor air pollution
• NIGER
ETHIOPIA
•
•
• • •• • •• •• •
• •
LIBERIA•
• MALI • • SOMALIA • RWANDA
•
•
ANGOLA
•SIERRA LEONE
0
• • •• • •• • • • • • •• • CHINA •• • •••• • •••••• •• • • •
•• • CHAD • • • •• • • CAMEROON • • • • • • • •• • •• GHANA • • • TAJIKISTAN
1,000 2,000
3,000
4,000
5,000
Deaths due to environmental causes (per million people)
Note: Excludes very high HDI countries. Survey years vary by country; see statistical table 5 for details. Source: Calculations based on data from statistical table 5 and Prüss-Üstün and others 2008.
Half the people in the world still use traditional biomass for heating and cooking. In low HDI countries 94 percent of the multidimensionally poor rely on such fuels, producing smoke
associated with acute respiratory infections, lung cancer, reduced lung function, carbon monoxide poisoning and immune system impairment. Indoor smoke from solid fuel is linked to some 2 million deaths a year. About 36 percent of these deaths are in low HDI countries, with a further 28 percent in China and 25 percent in India. 29 Deaths related to indoor air pollution are concentrated among the rural poor, who rely on coal for cooking and heating. The uptake of modern cooking fuel has been faster in urban areas—in China, for instance, 82 percent of urban households use gas.30 Indoor pollution kills 11 times more people in low HDI countries than in other countries and 20 times more people than in very high HDI countries. It accounts for 5.4 percent of the disease burden in low HDI countries—as much as 10 percent in Afghanistan, the country most afflicted in absolute terms.31 Women and children in rural areas, who spend more time in houses that use fuelwood, suffer most.32 Burning wood contributes to deforestation, which in turn forces households to burn dung and crop residues instead, intensifying the exposure to indoor air pollution because these fires require constant tending and their smoke is more toxic.33
CHapteR 3 trACing the eFFeCtS—underStAnding the relAtiOnS
51
Background research shows that deaths related to indoor air pollution are strongly related to the national MPI,34 showing how deprivations in cooking fuel contribute to multidimensional poverty and to the ill health of the poor. Poor households know that burning wood irritates the eyes and damages the respiratory system. An older Bhutanese woman observed that burning wood caused eye problems and coughs for many elderly women in her village.35 In India Rabiya Khatun of Bihar commented: “We have always used twigs and branches from nearby trees as cooking fuel. Everyone here does that. It burns our eyes, but it has to be done”; in West Bengal Faizul Haque observed that his wife, who is not yet 30, has been “sick for the last few years . . . she is hardly able to breathe, because of all the fumes.”36 Improved stoves, better ventilation and clean fuel are expected to reduce indoor
BOX 3.2
pollution and mitigate health risks, alongside efforts to expand access to modern energy sources, as we explore in the next chapter.
Outdoor air pollution
Air pollution and its health consequences in China
Outdoor air pollution is high in China, especially in urban areas and the north. A recent official environmental assessment finds that almost one city in five does not meet government standards; far more would likely fail to reach World Health Organization (WHO) air quality standards. Outdoor air pollution is associated with some 300,000 deaths and 20 million cases of respiratory illness in China each year, with estimated health costs of about 3 percent of GDP annually. Among the many sources of outdoor air pollution in China are residential and industrial coal combustion and motor vehicle exhaust. About 70 percent of the country’s electricity is generated from coal, most of it high in sulphur. High sulphur dioxide emissions contribute to smog and acid rain, which affect more than half of China’s cities. Outdoor air pollution patterns suggest major challenges, particularly in cities. Vehicle emissions may be the fastest growing source of urban air pollution, with China’s Environmental Protection Agency estimating that vehicles account for 70 percent of sulphur in the air. With rising incomes and better roads, the country has seen its vehicular fleet jump 20 percent a year since 1990. And since in 2009 only 3 percent of people in China owned a car, the trend is likely to continue. In Beijing more than 1,000 new cars are added to the total each day. Air pollution in China has caused a dramatic rise in asthma. From 1990 to 2000 its prevalence among urban children rose 64 percent, affecting almost 2 percent of children. In Chongqing, one of the country’s fastest growing cities, nearly 5 percent of children under age 14 suffered from asthma in 2000. China’s efforts to reduce outdoor air pollution are closely integrated with its policies aimed at climate change, energy efficiency and renewable energy use. In 2000 the government began requiring lead-free petrol, which reduced the lead content of urban air, and has made developing new clean energy vehicles the priority of the country’s auto industry for the next five years. The country has pledged to reduce energy consumption and carbon emissions 18 percent per unit of industrial value added by 2015 and to increase consumption of non–fossil fuel energy to 15 percent by 2020, up from the current 8 percent, which should also reduce outdoor air pollution.
Source: China National People’s Congress 2011; Fang and Chan 2008; Liu and Raven 2010: 8329; Millman, Tang and Perera 2008; Watts 2006, 2011; Zhan and others 2010.
Long-term exposure to outdoor air pollution causes respiratory disorders, immune system damage and carbon monoxide poisoning, among other deleterious effects.37 In Mexico City studies have found a significant impact from outdoor pollution on the mortality of the high-risk population,38 and in Linfen, China, and Norilsk, Russian Federation, industries produce levels of air pollution that seriously threaten the health of their populations.39 Disadvantaged groups are both more exposed and more vulnerable to the effects: in Hong Kong Special Administrative Region of China and Shanghai mortality due to outdoor air pollution is higher among the economically disadvantaged and the least educated.40 The pattern holds across the globe. In England half of municipal incinerators are in the most deprived tenth of municipalities.41 People in the poorest households and ethnic minorities are most likely to breathe polluted air, while areas with the highest rate of car ownership enjoy the cleanest air.42 In Rijnmond, Netherlands, poorer and minority households endure more air pollution and live closer to waste disposal sites.43 In Kassel, Germany, the air is more polluted in neighbourhoods where the foreign-born population lives.44 And French communities with higher proportions of immigrants host more industrial and nuclear waste sites, incinerators and waste management facilities.45 The good news, as reviewed in chapter 2, is that air pollution is declining, though on average it remains much higher in cities in poorer countries. China again emerges as an important case: rising energy consumption, based largely on coal and other solid fuels, and vehicle pollution have taken a toll on air quality (box 3.2).
Dirty water and unimproved sanitation
Lack of adequate sanitation and clean water compromises the life chances of many people, mainly in poorer countries. In medium HDI countries half the people lack access to
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improved sanitation, and one in eight lacks access to improved water. In low HDI countries the figures are 65 percent for sanitation and 38 percent for water. Nearly 4 in 10 people worldwide lack sanitary toilets, but as many as 8 in 10 of the multidimensionally poor do. Urban and rural disparities are large: less than half the rural population had improved sanitation facilities in 2008, compared with almost three-quarters of the urban population.46 These deprivations exact a high toll on health. For children under age 5 environmental factors account for more than a third of the global disease burden.47 Diarrhoeal diseases account for some 2 million deaths of children under age 5 each year, and the most recent estimates indicate that improved sanitation and drinking water could save 2.2 million children a year, or some 5,500 a day.48 Half of all malnutrition is attributable to environmental factors, particularly poor water, sanitation and hygiene.49 Malnutrition from these causes is responsible for some 70,000 child deaths a year, while underweight children are more vulnerable to infectious disease and less likely to recover fully when they do fall sick.50 Childhood malnourishment also impairs cognitive development and education performance, reducing opportunities over a lifetime. Inadequate water and sanitation are linked to an even broader array of health problems, as the 2006 HDR exposed. Today, billions of people are affected by parasitic diseases: 1.5 billion with ascaris, 740 million with hookworm, 200 million with schistosomiasis and 40–70 million with liverfluke. Many millions are likely affected by tropical enteropathy, an intestinal disease caused by faecal bacteria that reduces nutrient absorption. These infections as well as hepatitis, typhoid and polio can be avoided through safe excreta disposal and other hygienic behaviours, as we discuss in chapter 4. Beyond the human costs, the financial repercussions are large. For instance, the economic costs of poor sanitation and hygiene in Cambodia (7.2 percent of GDP), Indonesia (2.3 percent), the Philippines (1.5 percent) and Viet Nam (1.3 percent) in 2007 amounted to around $9 billion (in 2005 prices) or 2 percent of their combined GDP.51 And access to basic
sanitation services is especially important for women, not only for the health gains52 but also for privacy, time savings and reduced risk of sexual violence.53
Climate change
The health risks posed by climate change are immense and diverse—from increased risks of extreme weather events to salinization of land and fresh water from rising sea levels and the changing dynamics of infectious disease caused by higher temperatures. Higher temperatures will broaden the spread and increase the transmission rates of vector- and rodentborne diseases, expanding endemic areas for malaria, tick-borne encephalitis and dengue fever.54 Estimates suggest that 260–320 million more people will be affected by malaria by 2080.55 And many more will be at risk of contracting dengue fever.56 A recent study of 19 African countries found that weather variations increased the prevalence of diarrhoea, acute respiratory infections and undernutrition in children under age 5. Heat stress will rise with temperatures, and more people will die from heatstroke— particularly urban residents and people with respiratory conditions. The incidence of diarrhoea will also rise with temperatures.57 By 2050 sea level rise, droughts, heat waves, floods and rainfall variation could increase the number of malnourished children by 25 million. Land and ecosystem degradation will also add to malnutrition.58 These projections are based on a business-as-usual scenario. More sustainable behaviours and practices, outlined in chapter 4, could deflect these trajectories in positive ways. Indigenous peoples may be especially susceptible to the adverse health effects of environmental degradation. In northern Australia, for example, higher temperatures and more frequent heat waves will assail indigenous peoples in remote areas, where cardiovascular and respiratory disease rates are already high. The health effects may be especially severe where indigenous peoples’ connection to ecosystems —as a place of ancestry, identity, language, livelihood and community—is a key determinant of health.59
CHapteR 3
Indigenous peoples may be especially susceptible to the adverse health effects of environmental degradation
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53
Impeding education
Environmental degradation can endanger the livelihoods of the millions of people around the world who depend directly on environmental resources for work
As highlighted in the 2010 HDR, the expansion of primary education is one of the great successes of the past 40 years. The share of children attending school rose from 57 percent to 85 percent, with near universal enrolment in many parts of the world. Yet gaps remain. Nearly 3 in 10 children of primary school age in low HDI countries are not enrolled in school.60 And a range of other constraints, some related to environmental factors, persist. Electricity access can improve schooling. Better lighting allows for more study time, and electricity at home and school increases the time children and adults spend reading and keeps children in school longer. 61 In northwestern Madagascar electricity made it easier for girls to do their homework and for their mothers to help them in the evening after household tasks were done.62 In Bangladesh the time children spent in school was correlated with access to electricity, even after controlling for family wealth (landholdings).63 And in Viet Nam communes connected to the electric grid between 2002 and 2005 saw school enrolment increase 17 percent for boys and 15 percent for girls.64 Having access to electricity and other modern fuels can reduce the time spent collecting biomass fuel. 65 In Malawi children often collect fuelwood and other resources, and their likelihood of attending school falls as time allocated to this work rises.66 In rural Ethiopia the probability of schooling as the main activity, especially for boys, falls as the time to reach a water source rises.67 A negative relationship was found between children’s resource collection and their likelihood of attending school, though not the performance of those attending school. In Kenya’s Central Province district of Kiambu, fuelwood collection averages more than 4 hours a day, ranging from half an hour to 10 hours.68 Girls were more likely to combine resource collection and schooling. In the Indian states of Andhra Pradesh, Gujarat, Rajasthan and Maharashtra, for example, the United Nations Children’s Fund and others are providing solar-powered lamps to schools and women’s literacy groups
to promote education for girls. In the words of 13-year-old Manasha, “When there is no light, we go to bed very early after dinner and get up early. Now at night I can study.”69 Interventions to improve access to electricity are explored in chapter 4.
Endangering livelihoods
Environmental degradation can endanger the livelihoods of the millions of people around the world who depend directly on environmental resources for work. About 1.3 billion people, or 40 percent of the economically active people worldwide, work in agriculture, fishing, forestry, and hunting or gathering. Almost 6 in 10 of the economically active people engaged in these activities live in low HDI countries, while just 3 percent live in very high HDI countries. In Bhutan, Burkina Faso and Nepal, 92 percent of economically active people depend directly on natural resources for their livelihoods; less than 1 percent do in Bahrain, Qatar, Singapore and Slovenia.70 The rural poor depend overwhelmingly on natural resources for their income.71 Even those who do not normally engage in natural resource–related activity may do so during times of hardship.72 The effects of environmental degradation on crop production, fish supply, extraction of forest goods, and hunting and gathering vary, hurting some groups more than others. How it affects people depends on whether they are net producers or consumers of natural resources and whether they produce for subsistence or the market (and how readily they can shift between the two). Women in poor countries engage disproportionately in subsistence farming and water collection, exposing them more to adverse repercussions.73 Indigenous peoples deserve special mention (box 3.3). While they make up about 5 percent of the world’s people,74 they own, occupy or use (generally by customary rights) up to 22 percent of the world’s land, which holds 80 percent of the planet’s biodiversity.75 Indigenous peoples and communities legally own around 11 percent of global forests,76 and an estimated 60 million of them depend totally on forest resources for their livelihoods.77 They often live in ecosystems particularly vulnerable
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Human Development RepoRt 2011
to the effects of climate change, such as small island developing states, arctic regions, on the coast or at high altitude, and depend on fishing, hunting and farming to survive.78 We turn now to the differentiated impacts of environmental trends on people engaged in agriculture, forestry and fishing.
Threatening agriculture
BOX 3.3
Indigenous peoples, land rights and livelihoods
Unusual weather patterns and storms hurt indigenous communities that rely on natural resources for their livelihoods. In northern Canada global warming has shortened the period when seaice access routes to hunting areas are open, reducing food security and safety among the Inuit in Nunavik, Quebec, and in Nunatsiavut, Labrador. In Peru freak cold spells have increased, with temperatures falling to an unprecedented –35°C in the high Andes. In 2004, 50 children and up to 70 percent of livestock died, and as many as 13,000 people became severely ill. Indigenous peoples’ relationship with their lands often has cultural and spiritual dimensions, which land management practices can disrupt. As outsiders increasingly seek indigenous peoples’ lands for conservation and resource extraction, decisions are being made about the use of these lands without meaningful participation by the affected peoples. Indigenous communities may want to keep their environment and resources intact, leading to tension and conflict. As chapter 4 shows, governments are increasingly recognizing the special nature of indigenous peoples’ relationships with their land and environment. In 2004 the Canadian Supreme Court recognized the government’s obligation to honour the environment-related rights of two native tribes in British Columbia. Most Latin American constitutions include a provision governing indigenous peoples’ lands, territories and natural resources. The 2009 Bolivian constitution recognizes the rights of indigenous peoples to their original communal lands, guaranteeing the use and improvement of sustainable natural resources — in line with an alternative vision of development (vivir bien) that seeks the spiritual and collective well-being of people as well as greater harmony with nature.
Source: Furgal and Seguin 2006; Simms, Maldonado and Reid 2006; World Bank 2008c; Colchester 2010; Green, King and Morrison 2009; Manus 2006; Aguilar and others 2010.
Agriculture is the main source of livelihood for most of the world’s poor.79 The natural environment delivers support functions to agricultural production, such as regulating the nutrient and water cycles. And as agriculture intensifies to meet the food needs of growing populations, healthy ecosystems remain an important foundation. Environmental degradation thus threatens livelihoods and food security. Among the many complex interactions, the focus here is on the effects of land degradation, water stress and climate change. Land degradation reduces arable land and crop yields and increases the frequency of flooding. Specifically: • Loss of fertile topsoil is reducing land productivity, with estimated yield losses as high as 50 percent in the most adverse scenarios.80 Sub-Saharan Africa (especially Angola, Gabon and Swaziland) and East Asia and the Pacific (especially China, Indonesia, Malaysia and Myanmar) are hit hardest. • Drylands, home to about a third of the world’s population, are threatened by desertification.81 Some areas are especially vulnerable, such as Sub-Saharan Africa’s drylands, where adaptive capacity is low.82 Other parts of the world have also been affected. Land degradation in northern China’s Minqin County led to the abandonment of more than 80 percent of its farmland.83 By 2025 water scarcity is expected to affect more than 1.8 billion people.84 Field research suggests that the direct impacts of water depletion on crop cultivation can be worse for poor farmers. For example, in rural Mexico poor farmers without the capital to adapt to falling water tables cannot buy more droughtresistant seeds or piped water. And government
financing programmes do not help the poor when the technical requirements and matching contributions are too onerous.85 The effects of climate change on farmer livelihoods vary with the crop, region and season. Researchers have studied the relation between climate change and crop and pasture yields using simulation models, statistical studies and hedonic approaches. Some results suggest that moderate temperature increases (no more than 2°C) might benefit yields in the short run in temperate regions but will have adverse effects in tropical and semiarid regions. Globally, maize production has decreased 3.8 percent and wheat production 5.1 percent since 1980 due to climate change, with considerable regional variation (and some countries even benefitting from a changing climate). For rice and soy, countries benefitting and losing largely balanced out. 86 Projections through 2030 suggest that maize and wheat production in Southern Africa will fall sharply, while rice yields are expected to be positively affected by climate change.87 Rainfed maize yields are predicted to increase in China’s northeast but to fall in its southern regions. Across the world the biophysical impacts of climate change on
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Because different types of environmental change have different effects on land, labour and food production, it is important to examine the joint effects, through detailed, local analysis
both irrigated and rainfed crops are likely to be negative by 2050.88 The variability of effects underlines the need for detailed, local analysis. So does the variability in household production and consumption patterns, access to resources, poverty levels and ability to cope.89 For instance, agriculture is the most common source of work for rural women in most developing regions, yet they have less access than men to assets, inputs and complementary services. Disparities in landholdings are particularly acute—just 20 percent of landholders in developing countries are women, and their landholdings are smaller than those of men.90 Food production must rise to meet the demands of growing populations, but the combined environmental effects of land degradation, water scarcity and climate change will restrict supply. Adverse environmental factors are expected to drive up world food prices in real terms 30–50 percent in the coming decades and increase price volatility.91 Income poverty and malnutrition could worsen if the prices of key staples rise—as vividly demonstrated during the 2007–2008 food price spike.92 The poor spend a large share of their income on staple foods, and to survive, they sacrifice nutrition and eat less.93 The effects of food price hikes depend on household consumption and production. People in urban areas and nonfarm rural households, who are net food consumers, tend to be relatively worse off. But the research results are mixed: • One modelling exercise covering 15 countries found that the effects on income poverty depend on a household’s location and whether it engages in agriculture.94 Price hikes were predicted to hurt nonagricultural households most, with 20–50 percent falling into poverty in parts of Africa and Asia. But households specializing in agriculture benefit, and many in Latin America and the Caribbean and elsewhere in Asia are lifted from poverty. • Another recent study of nine countries (Bolivia, Cambodia, Madagascar, Malawi, Nicaragua, Pakistan, Peru, Viet Nam and Zambia) found that rising food prices
increased income poverty overall, even if rural food producers did better.95 Similarly, food price hikes increased the incidence and intensity of poverty in Indonesia, the Philippines and Thailand.96 Because different types of environmental change have different effects on land, labour and food production, it is important to examine the joint effects. In India climate change could lead to a sharp drop in land productivity for some 17 percent of farmers, through the effect on cereal prices, but effects on consumption would be muted, as most rural households derive their income largely from wage employment. Costs would fall disproportionally on the poor in urban areas, who would pay more for food, and on wage earners and net consumers of food in rural areas.97
Pressuring forests
Around 350 million people living in or near forests depend on forest wood and nonwood resources for subsistence and income.98 Many people in developing countries rely on forests for fuelwood: in Asia and the Pacific more than 70 percent of wood removed from forests is for fuel; in Africa the share may be as high as 90 percent.99 Women are responsible for most fuelwood collection in many parts of the world. Though global data are lacking on the number of women working in forestry, evidence suggests that women, with fewer occupational options and less mobility, rely on forests more than men do.100 Forest resources also generate income, through employment and the sale of goods and services. Nonwood forest products—such as food, fuel for cooking and heating, animal fodder, wild game, medicinal herbs and shelter —provide local communities with subsistence and marketable goods. They also provide cash to pay for school, medicine, equipment, supplies and food. Poor people typically depend more on forests for cash and noncash incomes—and as safety nets.101 A review of case studies of rural communities living in or on the fringes of tropical forests found that poor households derived more than a fourth of their incomes from
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forest resources, compared with 17 percent for nonpoor households.102 Some examples: • In Arunachal Pradesh, India, poor households depended on community forests for basic survival, and households that had less land and less education and that were farther from markets depended more on forest products.103 • In southern Ethiopia forest income kept a fifth of the population above the poverty line, reducing income inequality some 15 percent.104 • In Viet Nam forest products provided rural households with a safety net when other sources of income failed. People stricken by illness and health shocks were more likely than others to extract forest products.105 It follows that poor people are more vulnerable to forest degradation and exclusion.106 In South Asia households relying on fuel collection responded to reduced access by increasing collection time, purchasing fuelwood and cooking less often. Wealthier households, by contrast, shifted to alternative fuels.107
Damaging fisheries
more men, who typically engage in deep-ocean fisheries and commercial fishing, while coastal erosion will hurt more women, who typically gather invertebrates closer to the shore. How people respond to the impacts of climate change on fisheries is likely to vary. In Kenya, for example, even with catch declines of up to 50 percent, subsistence fishers from poor households and with less diverse income sources were more likely to continue fishing than were fishers from households with more assets and diversified livelihoods.113 But not all the expected effects are negative. For countries near the Equator fresh water aquaculture of fish such as tilapia may benefit from greater fresh water availability and higher temperatures.114 And ocean warming and the retreat of sea ice at high latitudes are predicted to increase the potential catch in the long term —with the greatest benefits likely to accrue in Alaska, Greenland, Norway and the Russian Federation.115 * * * People can adjust their production and consumption strategies to environmental conditions—for instance, they may grow crops more suited to poorer soils or warmer temperatures or eat food that requires less cooking and thus uses less fuelwood. People often react to environmental degradation by pursuing alternative livelihood strategies in the same area or by moving.116 We now consider other adverse repercussions on well-being.
Other adverse repercussions
Countries most at risk from overfishing and climate change are also among those relying most on fish for dietary protein, livelihoods and exports
An estimated 45 million people directly engage in capture fisheries or aquaculture, at least 6 million of them women.108 More than 95 percent of small-scale fishers and postharvest workers live in developing countries and face precarious living and working conditions. Countries most at risk from overfishing and climate change are also among those relying most on fish for dietary protein, livelihoods and exports.109 More than 80 percent of the world’s poor fishers are in South and Southeast Asia. But two-thirds of the countries whose capture fisheries are most vulnerable to climate change are in tropical Africa.110 Climate change is predicted to reduce fishery resources in the Pacific Islands by as much as half by 2100 and to drastically reduce mangrove forests and coral reefs.111 Research commissioned by the United Nations Development Programme Pacific Centre emphasizes the centrality of fishing to livelihoods in the Pacific region for both subsistence and cash.112 Rising sea temperatures will adversely affect
Environmental degradation has additional, interacting repercussions on disadvantaged groups. Here, we explore the links with time use, migration and conflict. Environmental stress can increase the difficulties in making a living from natural resources—forcing people to go farther to collect them, to work more to obtain a similar livelihood or even to migrate. In some cases environmental stresses have been linked with greater likelihood of conflict.117
Time use
For people who lack access to modern fuels and safe water, collecting fuelwood and water takes
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widespread environmental stress increases time burdens for households, with adverse implications for their well-being
considerable time. Nearly half the households in low HDI countries, mostly in Sub-Saharan Africa, spend more than 30 minutes a day collecting water. The burden is especially high in rural areas. Trips average 82 minutes in Somalia, 71 minutes in Mauritania and 65 minutes in Yemen.118 Widespread environmental stress increases time burdens for households, with adverse implications for their well-being. Time-use surveys illuminate this burden, showing how tasks are allocated within households and how they can be affected by environmental degradation.119 Studies in India have found that fuelwood collection time has increased markedly in recent decades: in Kumaon, Uttar Pradesh, women and children travelled on average 1.6 hours and 1.6 kilometres to collect wood in the early 1970s and 3–4 hours and 4.5 kilometres in the 1990s.120 Women and children have primary responsibility for fetching wood and water. A recent study of seven low HDI countries found that 56–86 percent of rural women fetched water, compared with 8–40 percent of rural men.121 In rural Malawi, for instance, women spend more than eight times what men do fetching wood and water, and girls spend about three times what boys do on these chores (table 3.2). Collecting fuelwood and water has been linked in women to spinal damage, complications during pregnancy and maternal mortality.122 The demands on time can also have a high opportunity cost in forgone schooling or leisure time for children and labour market activity for adults. In rural Pakistan, for example, difficult access to water increases women’s
total work burden and reduces the time they devote to market-oriented activities.123 Thus, the gains from secure and sustainable access to these resources and more modern alternatives could be large. In Sierra Leone improved access to water and electricity reduced domestic work time about 10 hours a week.124 A study in the 1990s found that if all households in the Mbale district of Eastern Uganda had secure access to water and fuel—living 400 metres or less from potable water and no more than 30 minutes from a fuelwood source—they would gain more than 900 hours a year.125 And a recent study estimated that 63 percent of the economic benefits from reaching the Millennium Development Goal target for water supply would come from time savings.126
Migration
TABlE 3.2
Average time per week spent fetching wood and water, rural areas of selected Sub-Saharan African countries (hours)
Gender and ratio Women Men Girls Boys Women/men Girls/boys Guinea (2002–03) 5.7 2.3 4.1 4.0 2.5 1.0 Madagascar (2001) 4.7 4.1 5.1 4.7 1.1 1.1 Malawi (2004) 9.1 1.1 4.3 1.4 8.3 3.1 Sierra Leone (2003–04) 7.3 4.5 7.7 7.1 1.6 1.1
Source: HDRO calculations based on data from Bardasi and Wodon (2009) (Guinea); Blackden and Wodon (2006) (Madagascar); Beegle and Wodon (2006) (Malawi); and Wodon and Ying (2010) (Sierra Leone).
Environmental stress can also drive people to relocate, especially where families and communities are deprived in multiple dimensions and see better opportunities elsewhere. It is difficult to quantify how many people move due to environmental stresses, because other factors also constrain people’s freedoms. Some prominent estimates have been very high—the 1994 Almeria Statement observed that 135 million people might be at risk of displacement due to desertification.127 And the Stern Review suggested that 200 million people might be displaced by 2050.128 But other estimates are far lower. The UN High Commissioner for Refugees found that 24 million people had been displaced by floods, famine and other environmental factors.129 A recent detailed estimate suggests that temperature and rainfall variation drove some 2.35 million people in Sub-Saharan Africa to move between 1960 and 2000.130 As argued in the 2009 HDR, expanding people’s opportunities to choose where they live is an important way to expand their freedoms. Mobility can be associated with improved income-earning opportunities and better opportunities for children. The problems, of course, are that a degraded environment constrains choices—especially for those whose livelihoods depend on a healthy
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environment—and that legal constraints on movement make migration riskier.131
Conflict
Finally, climate change and limited natural resources have been linked to an increased likelihood of conflict, one of the most pernicious threats to human development. They may also undermine the prospects for peace. Most resource-related conflicts are domestic, but increasing scarcity of land, water and energy could spark international strife. An estimated 40  percent of civil wars over the past 60 years are associated with natural resources, and since 1990 at least 18  violent conflicts have been fuelled by the exploitation of natural resources and other environmental factors.132 Some cross-country evidence is illustrative. For example, greater variability in rainfall increases the risk of civil conflict, particularly in Sub-Saharan Africa, where a 1°C rise in temperature is associated with a greater than 10 percent increase in the likelihood of civil war the same year.133 Recent episodes support the link. Competition over land contributed to postelection violence in Kenya in 2008 and to tensions leading to the 1994 genocide in Rwanda. Water, land and desertification are major factors in the war in Darfur, Sudan. In Afghanistan conflict and the environment are caught up in a vicious cycle—environmental degradation fuels conflict, and conflict degrades the environment.134 Policy responses, when they are badly designed or fail to consider all parties’ interests, can also exacerbate the risk of conflict. Global and local resource scarcity may be key causes of conflict—a well known early study highlights the interplay between environmental degradation, population growth and unequal resource distributions in stirring up strife.135 And countries with high dependence on primary commodity exports may be at increased risk—an abundance of resources is a powerful incentive for conflict.136 But natural resources are rarely, if ever, the sole driver of violent conflict. They are threat multipliers that interact with other risks and vulnerabilities.137 The evidence does not suggest that there are direct links between
environmental scarcity and conflict but that resource scarcity has to be embedded in the context of the broader political economy: separating the processes and elements associated with environmental conflict from the structures within which they are embedded is “both difficult and a distortion of reality.”138
disequalizing effects of extreme events
People living in urban slums in low and medium HDI countries face the greatest risk from extreme weather events and rising sea levels, caused by a combination of high exposure and inadequate protective infrastructure and services.139 By 2050, with a projected 0.5 metre rise in sea level, Bangladesh is likely to lose about 11 percent of its land, affecting an estimated 15 million people.140 Over the same period rising sea levels could displace more than 14 million Egyptians as increased salinization of the Nile reduces the irrigated land available for agriculture.141 The United Nations estimates that 29 percent of the world’s slum dwellers live in low HDI countries—with an additional 24 percent in China and 15 percent in India (both medium HDI countries).142 Vulnerable groups in megacities are particularly exposed to natural disasters, because of both their precarious living conditions and the absence of public services and formal social security systems. But, as shown below, some substitution with social capital, which builds resilience, can reduce risk. Our own analysis suggests that a 10 percent increase in the number of people affected by an extreme weather event typically reduces a country’s HDI by almost 2 percent, with particularly strong effects on the income component of HDI and in medium HDI countries. In some countries poorer regions suffer most. In Ha Giang Province, Viet Nam, one of the country’s poorest regions and home to 22 ethnic minorities, irregular rainfall, massive flooding and unpredictable storms have submerged land and crops, drowned livestock and destroyed infrastructure.143 In Mexico natural disasters, particularly droughts and floods, set
CHapteR 3
People living in urban slums in low and medium HDI countries face the greatest risk from extreme weather events and rising sea levels, caused by a combination of high exposure and inadequate protective infrastructure and services
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the strikingly unequal gender effects of natural disasters suggest that inequality in exposure and sensitivity to risk —as well as disparities in access to resources, capabilities and opportunities—overlap and systematically disadvantage some groups
the HDI back in affected municipalities by about two years and increased extreme poverty almost 4 percentage points.144 The risk of injury and death from floods, high winds and landslides has been systematically higher among children, women and the elderly, especially the poor. In Bangladesh poorer groups tend to live closer to rivers and thus face a greater risk of flooding.145 Local case studies of a 1991 Bangladeshi cyclone, the 2003 European heat wave and the 2004 Asian tsunami affirm the greater vulnerability of women and children, as does broader cross-country evidence. Sri Lanka’s tsunami killed nearly 1 in 5 displaced women and almost 1 in 3 displaced children under age 5—more than two times and four times the mortality of displaced men (about 1 in 12), respectively.146 And in rural India the mortality differential between girls and boys increases during droughts.147 The strikingly unequal gender effects of natural disasters suggest that inequality in exposure and sensitivity to risk—as well as disparities in access to resources, capabilities and opportunities—overlap and systematically disadvantage some groups. In 141 countries over 22 years, higher female mortality from natural disasters and their aftermaths cannot be explained by biology and physiology.148 And major catastrophes, as approximated by the number of people killed relative to population size, have more severe impacts than smaller disasters on women’s life expectancy relative to that of men. The explanations lie in social norms and roles and, more generally, in the socioeconomic status of women in the specific context. The higher women’s socioeconomic status (measured by such factors as freedom of choice of employment, nondiscrimination at work and equal rights to marriage and education), the smaller the gender-differentiated impacts on life expectancy. In other words, it is the socially constructed vulnerability of women that leads to the higher mortality rates due to natural disasters.149 Along similar lines, countries that focused on female education suffered far fewer losses from extreme weather events than less progressive countries with equivalent income and weather conditions.150
The risks and impacts are largest overall in developing countries—but the patterns of structural disadvantage are not confined to them. Witness Hurricane Katrina in the United States. New Orleans’s poorest districts, composed mainly of black communities, bore the brunt of the 2005 hurricane—threequarters of people in flooded neighbourhoods were black.151 In the 2003 European heat wave, more women than men died, as did more elderly people than young people. Shocks can have longer term adverse effects that extend beyond the destruction of life and immediate damage to health and livelihoods. Children may suffer disproportionately from weather shocks through the lasting effects of reduced schooling and malnourishment. In response to transitory income shocks, families without assets or other income opportunities, such as wage labour, may pull children out of school. The perceived risk of income loss contributes in its own right. Further, schooling infrastructure may be affected, and teachers may be injured or killed.152 The relationship is not always straightforward, however. In Mexico, high-impact disasters were linked to increased school attendance and reduced dropout rates for primary school, and in Mozambique, to better school performance,153 possibly because the opportunity cost of sending children to school fell along with market wages. Weather shocks can also affect child health, notably through increases in malnutrition. One study in Zimbabwe found that children who were exposed to shocks (civil war and the 1982–1984 drought) at ages 12–24 months completed 0.85 grade of schooling less and were on average 3.4 centimetres shorter than those who were not. This stunting was shown to reduce lifetime earnings by 14 percent.154 In Nicaragua infant malnutrition more than tripled among households most exposed to rainfall during Hurricane Mitch.155 And Bangladesh experienced a resurgence of child poverty after 2000 in the low-lying coastal regions of the country most vulnerable to flooding.156 In Viet Nam evidence suggests that household responses vary by type of shock. Households exposed frequently to shocks such as drought or moderate flooding learn to
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adapt.157 But survey analysis suggests no adaptation to less frequent storms and hurricanes —hurricanes can halve consumption in households near large cities, especially since disaster relief largely neglects those areas.
disempowerment and environmental degradation
Inequality, as manifested in unequal access to resources and decision-making, can harm human development and the environment. We assess the implications of gender disparities, focusing on reproductive health and participation in decision-making. We then focus on empowerment as a driver of environmental challenges to inform the policy discussions in chapters 4 and 5.
Gender equality
country and one high HDI country included in the GII perform as badly. We focus on two intersections between gender equity and environmental sustainability: reproductive choice and participation in decision-making. Contraceptive prevalence and the ability to make reproductive choices carry ramifications for the environment and for women’s empowerment. And, as we show, women’s political empowerment is not only intrinsically important, but it also has consequences for proenvironment policy and practice.
Reproductive choice
Women’s economic opportunities and empowerment remain severely constrained. Access to reproductive healthcare has been improving in most regions, but not fast enough to achieve Millennium Development Goal 5 (to improve maternal health).158 Indicators under the target of universal access to reproductive healthcare include the adolescent birth rate, antenatal care and unmet need for family planning. Last year’s HDR introduced the Gender Inequality Index (GII) for 138 countries. This year it covers 145 countries, and our updated estimates confirm that the largest losses due to gender inequality are in Sub-Saharan Africa, followed by South Asia and the Arab States. In Sub-Saharan Africa the biggest losses arise from gender disparities in education and from high maternal mortality and adolescent fertility rates. In South Asia women lag behind men in each dimension of the GII, most notably in education, national parliamentary representation and labour force participation. Women in Arab States are affected by unequal labour force participation (around half the global average) and low educational attainment. All the low HDI countries have high gender inequality across multiple dimensions. Of the 34 low HDI countries included in the 2011 GII, all but four also have a GII score in the worst quartile. By contrast, only one very high HDI
Poor reproductive health is a major contributor to gender inequality around the world. Lack of access to reproductive health services results in debilitating outcomes for women and children—and to fatalities in excess of those caused by the most devastating natural disasters. An estimated 48 million women give birth without skilled assistance, and 2 million give birth alone. An estimated 150,000 women and 1.6 million children die each year between the onset of labour and 48 hours after birth.159 For the bottom 20 countries in the GII the population-weighted maternal mortality ratio averages about 327 deaths per 100,000 live births, and the adolescent fertility rate averages 95 births per 1,000 women ages 15–19, both roughly double the global averages of 157 deaths and 49 births. In these countries contraceptive use is low, averaging only 46.4 percent. More broadly, an estimated 215 million women in developing countries have unmet need for family planning.160 Every country, developed or developing, that offers women a full range of reproductive health options has fertility rates at or below replacement.161 Cuba, Iran, Mauritius, Thailand and Tunisia have fertility rates of less than two births per woman.162 And Addis Ababa’s is also less than two births per woman, while Ethiopia’s rural fertility rate remains above six. In much of rural Bangladesh, despite widespread poverty, fertility is now at the replacement rate.163 And family sizes have fallen as rapidly in Iran as they have in China, but without government limits on family size.164
CHapteR 3
women’s ability to make reproductive choices carries ramifications for the environment and for women’s empowerment, and women’s political empowerment has consequences for proenvironment policy and practice
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As table 2.1 in chapter 2 illustrates, population growth seriously strains the limits of world resources. A range of studies suggest that lower population growth could offset at least some of the higher greenhouse gas emissions associated with rising incomes. One early estimate was that by 2020 carbon dioxide emissions would be about 15 percent lower than they would be without family planning.165 A more recent study of 34 developed and developing countries with 61 percent of the world’s population finds that halving 2010’s population growth could provide 16–29 percent of the carbon dioxide emissions reductions needed by 2050 and 37–41 percent needed by the end of the century to avoid dangerous climate change.166 Another study estimated that meeting unmet need for family planning would avert 53 million unintended pregnancies a year and cut carbon emissions by 34 gigatonnes, or about 17 percent of the world’s current yearly total, as of 2050.167 The environmental pay-offs are thus clearly enormous, over and above the benefits to women’s empowerment. Gender inequality and contraceptive prevalence are closely linked (figure 3.6). Where women have greater standing, as in Japan, the Netherlands and Norway, most couples use some form of contraception. But where gender
FIGURE 3.6
gender equality and contraceptive prevalence are closely linked
Contraceptive prevalence rate (percent)
100
• • •• CHINA • • • • • •• •• • 80 • • • • • • • • ••• • • • • • • •• NETHERLANDS • • • • • • 60 • • • •• JAPAN • • • •• • • • • •• TRINIDAD AND TOBAGO • 40 • • • •
20
NORWAY
IRELAND
• THE FORMER YUGOSLAV
0 .1 .2 .3
REPUBLIC OF MACEDONIA
0
• •• • • • •• •• • NICARAGUA • • • • • • • •• • • • • • • •• • INDIA • •• • • • IRAQ• KENYA • •• •• ••• • •• PAPUA NEW GUINEA • •• • • • YEMEN ••• • • • ••• MAURITANIA • •• • • NIGER • • • •• MALI BURUNDI SUDAN • SIERRA LEONE • CHAD
.4 .5 .6 .7 .8 .9 1.0
BRAZIL
Gender Inequality Index
Note: Contraceptive prevalence rates are for the most recent year available from the World Health Organization for each country during 2000–2008; see statistical table 4 for details. The Gender Inequality Index is for 2011. Source: HDRO calculations based on data from the World Health Organization.
inequality is high, as in Mali, Mauritania and Sierra Leone, contraceptive prevalence is below 10 percent. Data collected between 2000 and 2009 show that fewer than 3 in 10 women of reproductive age in low HDI countries use modern contraception, compared with 88 percent in Norway and 84 percent in the United Kingdom. Further analysis highlights the importance of national HDI levels, especially education and health achievements, in explaining the relationship between gender inequality and contraceptive prevalence. However, the same does not apply for income—if we control for income alone, gender inequality and contraceptive prevalence continue to be strongly linked. This underlines the importance of investments in health and education in furthering reproductive health choices. The reported unmet demand for family planning is very low in Chad, the Democratic Republic of the Congo and Niger (below 5 percent), alongside very high average fertility.168 This can happen because of cultural or religious objections by women, their husbands or other family members; a lack of knowledge of contraceptive methods or fear of their side effects; or preference for larger families.169 Low unmet need can be associated with low contraceptive prevalence at low levels of development (where fertility preferences are high) and with high contraceptive prevalence at high levels of development (where fertility preferences are low). This means that family planning programmes must go beyond supplying contraception at affordable prices to raising awareness of its use and health effects and addressing the structural constraints facing poor women (see chapter 4). Some studies link fertility decisions to deforestation and difficult access to water, which require women and children to spend more time collecting fuelwood and water.170 Unmet need is often high—more than 30 percent of people in some countries, including Haiti, Liberia, Mali and Uganda, would like to use family planning but do not.171 Multidimensional poverty is correlated with unmet need for contraception. The incidence of people living in households with unmet family planning needs is always higher among
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the multidimensionally poor (figure 3.7). In Bolivia 27 percent of the multidimensionally poor have unmet need for family planning, more than twice the share among the nonpoor (12 percent), and in Ethiopia unmet need among the multidimensionally poor (29 percent) is almost three times the share among the nonpoor (11 percent). Fertility is also affected by women’s education. A recent study covering more than 90 percent of the world’s people found that women who have never gone to school average 4.5 children, those with even a few years of primary school average just 3, and those with one or two years of secondary school average 1.9. And when women enter the workforce, start businesses or inherit assets, their desire for a large family also tends to diminish.172 The principles and routes—removing barriers to the use of family planning and rightsbased population policies—are not new. They were directly envisioned by conferees in Cairo in 1994 and committed to by nearly all governments. Chapter 4 argues that progress has been too slow and highlights some promising avenues to consider.
Women’s participation in decision-making
FIGURE 3.7
unmet contraceptive need is higher among the multidimensionally poor
Population with unmet contraceptive need (percent)
0 MALDIVES LIBERIA MALI UGANDA GABON HAITI PAKISTAN BENIN
◆ ◆ ◆ ◆ ◆
10
20
30
◆
40
50
— — — — — — —
Among the nonpoor
◆
◆ ◆
—
Among the poor
ETHIOPIA
GUINEA SÃO TOMÉ AND PRÍNCIPE TIMOR-LESTE NEPAL PHILIPPINES AZERBAIJAN RWANDA
— — — — — ◆ — — — — — — — — — —
◆ ◆ ◆ ◆ ◆ ◆
BOLIVIA
KENYA CAMBODIA CAMEROON NIGERIA CONGO, DEM. REP. OF THE ZAMBIA MALAWI SWAZILAND LESOTHO NIGER CONGO GHANA MADAGASCAR EGYPT MOZAMBIQUE NAMIBIA NICARAGUA ARMENIA INDIA TURKEY JORDAN UKRAINE COLOMBIA ZIMBABWE INDONESIA MOROCCO DOMINICAN REPUBLIC PERU VIET NAM BANGLADESH MOLDOVA
◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆
◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ◆
— —
— — — — — — — — — ◆ — —
Gender inequalities are also reflected in women’s low participation in national and local political fora. This has ramifications for sustainability if, as some research suggests, women express more concern for the environment, support more proenvironmental policy and vote for proenvironmental leaders. • Countries with higher female parliamentary representation are more likely to set aside protected land areas, as a study of 25 developed and 65 developing countries reveals.173 • Countries with higher female parliamentary representation are more likely to ratify international environmental treaties, according to a study of 130 countries with about 92 percent of the world’s people.174 • Of the 49 countries that reduced carbon dioxide emissions between 1990 and 2007, 14 were very high HDI countries, 10 of which had higher than average female parliamentary representation.
◆ ◆ ◆ ◆ ◆ ◆ ◆
— — — — — — — — —
— —
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Note: Data are for most recent year available during 2000–2010 and are based on the Demographic and Health Survey second definition of unmet need (DHS 2008). Source: Calculated based on data on MPI from statistical table 5 and from Demographic and Health Surveys.
But women continue to be underrepresented in national parliaments, on average occupying only 19 percent of seats and accounting
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Disempowerment and power imbalances add to environmental challenges
for just 18 percent of ministers.175 Higher positions are even more elusive: only 7 of 150 elected heads of state and only 11 of 192 heads of government are women. The situation is similar in local government.176 Other evidence suggests that gender empowerment and environmental awareness may be related. The number of women’s and environmental NGOs per capita was negatively correlated with deforestation in a study of 61 countries between 1990 and 2005. That may be partly because of women’s incentives to avert the negative effects of deforestation on their workload, income and health.177 In developed countries survey data show that women are more likely than men to engage in environmentally sensitive behaviours, such as recycling, conserving water and avoiding environmentally harmful products.178 But the relationship, far from straightforward, varies with development. As we saw in box 2.5 in chapter 2, analysis of Gallup World Poll data on environmental attitudes suggests that concerns about environmental problems are not very high. On average, the attitudes of men and women differ little,179 but some variation appears across HDI groups (table 3.3). In very high HDI countries women express more concern for environmental issues (climate change, water and air quality) than do men, while men express more concern in low HDI countries. The medium and high HDI countries (and most developing regions) fall in between.
TABlE 3.3
Attitudes towards the environment, by gender, low and very high hdi countries, 2010 (percent, unless otherwise noted)
Low HDI countries Difference (percentage points) 1.71 1.55 3.16 2.70 12.30 Very high HDI countries Difference (percentage points) 4.29 3.41 2.72 2.02 7.70
While overall levels of education influence attitudes, the ratio of the share of women to men in secondary and tertiary education does not. The implication: women’s greater concern for the environment in rich countries is not a function of their having more education, nor is the converse true in very poor countries. Some evidence suggests that women’s involvement is associated with better local environmental management. Yet women’s mere presence in institutions is not enough to overcome entrenched disparities—additional changes and flexibility in institutional forms are needed to ensure that women can participate effectively in decision-making. In some cases including women and other marginal groups is perceived as a way of maintaining the status quo rather than achieving any specific outcomes or questioning inequalities.180 What matters, then, is not simply women’s presence but the nature of their participation. Consider forestry management (box 3.4). A recently published study of community forestry institutions in India and Nepal found that women’s proportional strength in forest management committees affects the effectiveness of their participation.181 The more women on the management committee, the greater is the likelihood that they will attend committee meetings, speak up and become office holders. The arguments here are not new. But they point to an important part of a reform package to address inequality and environmental degradation—with major expansions of women’s freedoms.
Power inequalities
Attitude Climate change is a serious threat Dissatisfied with: Air quality Water quality Government environmental policy Government emissions policy
Male 47.76 22.81 50.48 54.82 61.46
Female 46.05 21.27 47.32 52.12 49.16
Male 27.18 17.95 13.56 46.36 53.13
Female 31.46 21.36 16.28 48.38 60.83
Source: HDRO calculations based on data from Gallup World Poll (http://worldview.gallup.com).
As a critical dimension of people’s freedoms, empowerment is an important end in itself. But disempowerment and power imbalances add to environmental challenges. We build on the 2010 HDR, where we addressed several components of empowerment: agency, political freedoms, civil liberties and accountability. Box 2.1 in chapter 2 already highlighted some recent changes. Here we focus on the political arena—on national and local governments, accountability and democracy, and civil society.
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History, power relations and context all affect the links between democracy and environmental public goods. State activity can usefully be seen as a continuum from “oligarchic, extractive, exploitive and divisive” to “inclusive, innovative, accountable, responsive and effective at mediating distributional conflict.”182 Where state activity falls along the continuum is determined by the underlying social contract—historically shaped interactions between political and economic elites and other social groups—as manifest in formal and informal institutions. As economic processes, both state action and capitalism are often weak in sustaining the environment —capitalism, intrinsically so, given the short time horizon of most firms and the importance of externalities. The state, despite its role in providing public goods and managing externalities, can often be limited by short political and electoral time horizons. These factors can interact with political and social structures to have harmful effects on the environment, especially where the adverse impacts affect mainly disempowered groups. Studies have shown that democracies are typically more accountable to voters and more likely to allow civil liberties, enabling people to be more informed on environmental problems (thanks to a free press), to organize and to express concerns. At the national level the extent of democracy has been associated with environmental quality.183 But even in democratic systems, the people and groups most adversely affected are those who are less well-off and less empowered. Policy priorities may not reflect their interests and needs. In many countries and contexts power inequalities affect environmental outcomes, mediated through political and social institutions. State-level evidence across the United States suggests that greater inequality in power (measured by lower voter participation and educational attainment and weaker fiscal policies) leads to weaker environmental policies and more environmental degradation.184 Cross-country evidence supports this view. In 180 countries variables such as literacy, political rights and civil liberties improve environmental quality in high- and low-income
BOX 3.4
Women’s participation in community forest management
Participation of women in community decision-making is important for resource conservation and regeneration, particularly for community forest management. However, preexisting and structural gender inequalities (in income, assets and political endowments) often weaken women’s ability to participate. Even in communities where women are not formally excluded from decision-making bodies, their ability to participate in policy-making may be limited by social inequalities. Requiring female representation on committees and ensuring that women are consulted are necessary but insufficient conditions — ultimately the issue is one of challenging and changing power relations. In villages where women are not actively involved in decision-making, they are more adversely affected by forest management decisions such as forest closures than in communities where they are more involved. Prior equality is not necessary for women to assert themselves in committee meetings. In fact, women from disadvantaged households are more outspoken in public forums than women from better-off households, a finding attributable to their opportunity to gain more if decisions go in their favour. This outcome was found to be more likely where a large number of women were present or where women had already been exposed to women’s empowerment programmes. Other studies affirm that allowing women to participate, even in a limited role, changes cultural perceptions as to women’s capacity to make decisions, in turn prompting the formation of other initiatives and cooperatives for women, allowing them to become more active outside the home.
Source: Agarwal 2001, 2009; see also Tole (2010), Gupte (2004) and Timsina (2003).
countries185 and positively influence clean water and improved sanitation.186 New cross-national analyses of more than 100 countries commissioned for this Report confirmed the strong correlation between proxies for the distribution of power and environmental quality.187 Empowerment is linked with access to improved water, less land degradation and fewer deaths due to indoor and outdoor air pollution and dirty water. And empowerment variables are even more important than income in explaining many key dimensions of environmental quality, including access to improved water, deaths due to pollution and mortality in children under age 5. The implication is that while powerful economic interests can distort policies, societies can do much to limit that power. Investigations of environmental data over time for a large number of countries have found this relation to hold. Most studies focus on pollution, a public bad from which the state is expected to protect its population.188 The general finding is that literacy and political rights are associated with less air and water pollution. A recent contribution highlights the importance of long-term democracy in lowering sulphur and carbon dioxide
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greater equality between men and women and within populations may have transformative potential in advancing environmental sustainability
emissions.189 This makes sense: it takes time for democracy to yield tangible instrumental gains. Other work in more than 100 countries links a higher level of democracy to less deforestation, less land degradation and less air and water pollution.190 Various studies suggest that democracy increases the likelihood of state commitment to goals to address climate change, transboundary air pollution and river management, if not policy implementation. But while democracies tend to be more committed to positive outcomes for climate change, the relationship is not very strong—given that the benefits are perceived to be external and beyond the time horizon of current voters (and politicians).191 This widens the gaps between words and deeds. Even within democracies, political institutions vary widely. Some are centralized, and others decentralized. Likewise, political representation is affected by the role of political parties, the existence of quotas for particular groups, the duration of electoral cycles and other factors. Some countries have a strong independent agency charged with protecting the environment; others may have only a weak line ministry. The strength of labour unions contributes to lower environmental air quality; the strength of green parties has the opposite effect.192 Civil society groups can organize and exert real impact on the decisions of policy-makers, offsetting the often disproportionate influence of powerful economic interests and lobbies. The possibility of developing this “countervailing power”193 depends on whether institutions in a society allow for open and free participation. As Sweden’s environmental policies show, strong democratic participation can translate into policies that reflect popular concern. But such concerns may be countervailed by other vested interests—as reported for the Russian Federation in the problems civil society faces in mobilizing public support around greening
industry.194 Where civil society is active, it has been shown to bring about significant change: • A recent study modelling environmental NGO impact in a framework of interest group participation and influence in 104 countries found that the number of environmental advocacy groups in a country had a statistically significant negative relation with the lead content in gasoline.195 • A study using cross-country panel data for 1977–1988 found a statistically significant negative relation between the number of environmental NGOs and air pollution levels and weaker relations between democracy and pollution and between literacy rates and pollution.196 Civil society, in turn, can thrive only with popular support. Where civil society groups are active, power imbalances can be overcome. In the 1990s activists in poor, racial minority neighbourhoods in Chicago, United States, succeeded in getting the national Environmental Protection Agency to act against illegal waste dumping in their communities. Community policing programmes were established, and city regulations and enforcement of illegal dumping were also strengthened, including new harsher penalties.197 Civil society groups in a range of contexts have successfully opposed activities likely to be a detriment to the environment and the livelihoods of people who directly rely on it. * * * We have outlined the ways environmental deprivations and environmental degradation can constrain choices—showing how they seriously jeopardize health, education, livelihoods and other aspects of well-being and at times worsen prevailing inequalities. We have also suggested that greater equality between men and women and within populations may have transformative potential in advancing sustainability. We go on to explore this possibility and promising approaches and policies.
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4
positive synergies—winning strategies for the environment, equity and human development
In facing the challenges laid out in chapters 2 and 3, a host of governments, civil society, private sector and development actors have sought to integrate environmental and equity concerns and promote human development —win-win-win strategies. An example at the global level is the 1987 Montreal Protocol, which bans ozone-depleting chemicals, thereby benefiting sustainability (through protection of the ozone layer), equity (through technology transfer to developing countries) and human development (through positive impacts on health).1 This chapter showcases local and national strategies to address environmental deprivations and build resilience, thereby demonstrating positive synergies. An important backdrop to this discussion is the need for healthy ecosystems and the services they provide, especially for the poor. Ecosystems build the foundation for water quality, food security, flood protection and natural climate regulation.2 Scaling up successful community and local initiatives is a prime focus. Key elements at the national level are policies that bring together social, economic and environmental concerns; coordination mechanisms aligned with budget frameworks; a culture of innovation; and strong institutions, alongside mechanisms that ensure accountability. Some countries have overcome siloed arrangements through medium-term plans that allow cross-sectoral coordination across government agencies and with development partners. Senior core ministries—such as finance and planning— are often critical, as are line agencies, especially working with other ministries. In Malawi the Ministry of Agriculture helped create demand for measures to reduce poverty and protect the environment, and in Rwanda the Ministry of State, Lands and the Environment garnered presidential and cabinet support for
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integrating environmental concerns into the country’s Economic Development and Poverty Strategy. And crucial at the local level are strong institutions, particularly those that pay attention to disadvantaged groups and promote community management. The policy agenda is vast. This Report cannot do it full justice or cover all the challenges raised in the preceding chapters. Several recent global reports provide important details.3 The value added here is in identifying win-winwin strategies that successfully address the world’s social, economic and environmental challenges by managing, or even bypassing, trade-offs so that the approaches are good not only for the environment but also for equity and human development more broadly. This effort provides concrete experience and important motivation for the forward-looking final chapter.
Scaling up to address environmental deprivations and build resilience
We begin by highlighting promising winwin-win routes in energy and in water and sanitation.
Energy
Energy is central to a range of services supporting human development, from modern medical care, transportation, information and communications to lighting, heating, cooking and mechanical power for agriculture. Equitable and sustainable development requires making energy available for all, controlling emissions and shifting to new and cleaner energy sources.
Addressing energy deprivations
Some 1.5 billion people, more than one in five, lack access to electricity, and 2.6 billion cook
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FIGURE 4.1
large regional differences in the share of multidimensionally poor people lacking electricity
Percent
0.4
Europe and Central Asia
3.3
East Asia and the Pacific
11.1
Latin America and the Caribbean
27.7
South Asia
62.3
Sub-Saharan Africa
Note: Excludes very high HDI countries. Source: HDRO staff calculations based on data from the Oxford Poverty and Human Development Initiative.
with wood, straw, charcoal or dung.4 Major energy inequalities persist across regions, countries, gender and classes. Acknowledging that energy distribution cannot be considered apart from political and social exclusion,5 the 65th United Nations General Assembly proclaimed 2012 as the International Year of Sustainable Energy for All.6 One multidimensionally poor person in three (32 percent) lacks electricity, and there is a strong regional pattern to this deprivation (figure 4.1). More than 60 percent of the multidimensionally poor in Sub-Saharan Africa lack electricity, compared with less than 1 percent in Europe and Central Asia. Progress in electrification has been slow in Africa. Electricity generation capacity per person in SubSaharan Africa today is similar to levels in the 1980s but just a tenth that in South and East Asia. And rural electrification has stagnated at below 10 percent—while growing to 50 percent for developing countries as a whole.7 Electrification can reduce poverty by increasing productivity, employment and time spent in school and reducing environmental pressures. For instance, in South Africa electrification is associated with a 13 percent greater likelihood of women participating in the labour market,8 while in Viet Nam it increased income, consumption and schooling outcomes.9 Bhutanese villagers attest enthusiastically to the difference electricity makes in their lives, citing the ability to work in the evenings and cook without wood, which reduced respiratory problems and time spent fetching fuel.10 Expanding energy access and mitigating climate change can be presented as trade-offs. For instance, the World Bank’s recent $3.75 billion loan to South Africa to build one of the world’s largest coal-fired plants will expand access, but the project raised concerns about greenhouse gas emissions and environmental degradation as well as carbon lock-in when the longevity of infrastructure prolongs the use of obsolete technologies.11 But the prospect of win-win-win options enables us to go beyond trade-offs. Recent World Energy Outlook estimates indicate that providing everyone with basic modern energy
services would increase carbon dioxide emissions only 0.8 percent by 2030.12 Off-grid and decentralized options are important and technically feasible. While difficult to quantify, the number of rural households already served by renewable energy is estimated in the tens of millions, through such schemes as microhydropower in villages and county-scale minigrids, an important source of energy in Brazil, China and India.13 There have been some successes in extending energy access to the poor, including through decentralized energy systems. The challenge is to make such innovations happen at a scale and speed that will improve the lives of poor women and men now and in the future.14 Governments can do more to support entrepreneurship and capital acquisition for alternative energy startups.15 As Latvia and other countries have shown, the right legal framework can boost growth in the nonrenewable energy sector and limit emissions from traditional energy sources. Increasing efficiency is important too. And innovations are proceeding, from improved stoves—which have reduced fuelwood requirements some 40 percent in parts of Kenya and dramatically cut pollution levels and improved child health in Guatemala16 —to more energyefficient buildings—which can reduce heating and cooling loads.17
Making energy cleaner
Any long-run strategy for broadening energy access must include actions to promote cleaner energy.18 There are encouraging signs. By 2010 more than 100 countries—up from 55 in 2005 —had enacted some policy target or promotion policy for renewable energy, including all 27 EU members. Many countries specify a target share of renewables in electricity production, typically 5–30 percent, but within a range of 2 percent to 90 percent. In several countries renewables constitute a rapidly growing share of total energy supply. The share is 44 percent of energy in Sweden, one of the better performers identified in chapter 2. As of 2008 Brazil produced almost 85 percent of its electricity from renewables, and Austria 62 percent. And hydropower accounts
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for close to 70 percent of electricity generated in Sub-Saharan Africa (excluding South Africa).19 According to the Renewable Energy Policy Network for the 21st Century, global energy supply reached a tipping point in 2010, as renewables accounted for a quarter of global power capacity and delivered almost a fifth of electricity supply20 (see statistical table 6). Virtually every renewable technology has seen consistently strong growth. Some highlights: • Wind. Despite the 2008 global economic crisis, new wind power installations reached a record 38 gigawatts in 2009, a 41 percent increase over 2008 and equivalent to nearly a quarter of total global installations. • Solar. Grid-connected solar photovoltaic systems have grown at an annual average of 60 percent over the past decade, increasing 100-fold since 2000, with major expansions in the Czech Republic, Germany and Spain. Unit prices have declined sharply— some dropping 50–60 percent, to less than $2 a watt. Generous feed-in tariffs are one reason. An estimated 3 million households in rural areas get power from small solar photovoltaic systems, and an estimated 70 million households worldwide have solar hot water heating. Since 2004 global renewable energy capacity for many technologies has grown 4–60 percent a year, spurred by new technology, high and volatile oil prices, climate change concerns, and local, national and global policy developments.21 Developing countries are adopting renewable energy and now have more than half of global renewable power capacity. China leads the world in several indicators of market growth, including wind power capacity and biomass power, while India stands fifth in wind and is fast expanding such rural renewables as biogas and solar. Brazil produces much of the world’s sugar-derived ethanol and is adding new biomass and wind power plants. The continuing roll-out of renewable energy sources will require large private investments, but corruption and lack of regulation can slow the momentum. A recent
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Transparency International study, for example, reported that almost 70 percent of potential energy investors in North Africa consider regulatory risk, including corruption, a serious impediment to investment.22 Technical limitations must also be overcome. For example, intermittency raises capital costs for wind and solar power and requires supplementation by other sources. Improved storage technologies are also needed. Currently, more than 90 percent of clean energy investments are in the G-20 countries. 23 To expand equity and sustainability in clean energy globally, concerted efforts are needed to improve conditions in other countries that would enable future investments. 24 In the next chapter we call for addressing perverse incentives and market distortions, reducing risks and increasing rewards, and increasing accountability in global environmental governance. Beyond facilitating greater access and lowering emissions, clean energy can create new industries and jobs. Installing 1 megawatt of wind turbine capacity creates an estimated 0.7–2.8 times the permanent employment of a comparable natural gas combined-cycle power plant; installing 1 megawatt of solar capacity creates up to 11 times more. 25 An estimated 3 million people worldwide already work in renewable energy industries, about half of them in biofuels.26
Reining in global emissions
Developing countries are adopting renewable energy and now have more than half of global renewable power capacity
Policies to cut emissions nationally entail both potential advantages and concerns about equity and capacity. Table 4.1 lists illustrative policy instruments to cut carbon dioxide emissions and their key equity effects. Typically, instruments must be combined to deal with the broad range of market failures. Pricing can powerfully affect behaviour. An obvious candidate is the reduction of fossil fuel subsidies, which are expensive (amounting to about $312 billion in 2009 in 37 developing countries)27 and encourage consumption. The Organisation for Economic Co-operation and Development estimates that phasing out the subsidies could free fiscal resources and reduce global greenhouse gas emissions 10 percent by
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2050 —more than 20 percent in oil-exporting countries. 28 Similarly, subsidized electricity prices for agriculture often encourage greater groundwater extraction, risking overexploitation. 29 These types of perverse subsidies favour medium and large producers over smaller farmers because smaller farmers rarely pump water and instead use wheels, surface water or rainfall.30
TABlE 4.1
Key equity aspects of a menu of instruments to reduce carbon dioxide emissions
Policy instrument Cap-and-trade permits Examples • EU trading scheme Key equity aspects • If permits are given away, this favours incumbent firms and does not raise revenue Other considerations • Potentially high monitoring and enforcement costs • Carbon permit prices can be volatile. • If electricity is generated with fossil fuels, targets will cause prices to rise • Poor people spend a larger proportion of their income on energy • Fiscal revenue potentially as high as 1–3 percent of GDP in Organisation for Economic Co-operation and Development countries by 2020a
Emissions targets
• Voluntary targets • Depends on pattern of European Union, of consumption and Indonesia and the production Russian Federation to reduce emissions
Taxes or charges
• Fuel and coal taxes • Motor vehicle taxes
• Depends on pattern of consumption and production
Subsidies for renewables • Hybrid cars • Depends on purchase • Potentially expensive; • Subsidies for electric patterns, but unlikely more than $7,000 per vehicles to be progressive; vehicle in Belgium, could be targeted Canada, China, the (means tested) Netherlands, the United Kingdom and the United States Subsidy cuts • Fossil fuels • Electricity for irrigation • Eliminating subsidies • Fossil fuel subsidies would create cost around $558 substantial fiscal billion in 2008 and and environmental $312 billion in 2009 benefits • Complete phase-out by 2020 could reduce emissions 20 percent in non-European countries, the Russian Federation and the Arab States • May raise costs and limit access of the poor • Does not allow firms to reduce emissions at the lowest possible cost
Performance standards
• Limits on car emissions • Energy efficiency standards • Building and zoning codes
Technology standards
• Care needed to avoid • Importance of cost increases that appropriate are prohibitive for technology the poor • Ensure outreach • Group identity of and accessibility to users matters disadvantaged groups
Better information
• Public awareness campaign • Emission and energy use disclosure requirements
a. At $50 per tonne of carbon dioxide equivalent greenhouse gas emissions. Source: Based on OECD (2010c).
But the optimal policy here, as elsewhere, depends on context. Careful investigation and targeted compensation are needed where the affected goods and services account for a large share of family spending. Redistribution can be implemented through social transfers or, if the tax base is broad enough, through tax cuts for the poor. To compensate for lower oil subsidies, Indonesia implemented a cash transfer scheme in late 2005 targeting 15.5 million poor and near-poor households (some 28 percent of the population). To offset higher energy prices, Mexico supplemented its conditional cash transfer programme in 2007. And Iran replaced oil-based subsidies on fuel, food and other essentials with a transitional monthly $40 cash grant to 90 percent of the population in 2010, leading to a drop of 4.5 percent in gas consumption and 28 percent in diesel consumption.31 Several large developing countries have committed to deep carbon cuts. For example, in 2009 China set a goal of lowering carbon intensity 40–45 percent from 2005 levels over the next decade, later announced further shortterm targets and is supporting renewable energy through subsidies, targets and tax incentives.32 In 2010 India announced voluntary targeted reductions of 20–25 percent in carbon intensity. These new commitments are important steps in the transition to a lower carbon economy. As we saw in table 2.1 in chapter 2, falling carbon intensity of production globally lowered total emissions growth between 1970 and 2007 well below what it would have been otherwise. But the announcements must be put in perspective. Reduced carbon intensity can run alongside rising greenhouse gas emissions if economic growth continues apace. Despite increased energy efficiency, US emissions have continued to grow—more than 7 percent from 1990 to 2009.33 China was already reducing carbon intensity at 1.4 percent a year over 1970–2007, but rapid economic growth meant that total emissions still grew 5.9 percent a year. The new target would more than double the rate of carbon intensity reduction to 3.8 percent a year, but again that does not mean that China’s total emissions will decline. In fact, if China’s economic growth through
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2020 exceeds 3.9 percent (as predicted), its total emissions would continue to rise; if the economy continues to grow at the 9.2 percent annual rate of the past decade, total emissions would increase 2.8 percent a year. Other countries have committed to reducing absolute emissions. Indonesia has announced a target of reducing carbon dioxide emissions 26 percent.34 Similarly, the European Union, as part of its 20/20/20 plan to be met by 2020, committed to cutting greenhouse gas emissions 20 percent from 1990 levels, increasing renewable energy use 20 percent and reducing energy consumption 20 percent through improved energy efficiency.35 * * * In sum, expanding access to modern energy for all and developing renewable energy sources are gaining traction, but involving the state, donors and international organizations is critical for investing in research and development and reducing disparities within and across countries. Moreover, strong efforts are needed to include the poor: if current trends continue, more people will lack access to modern energy in 2030 than today.36
Water access, water security and sanitation
Chapter 3 told of the devastating impacts of lack of access to potable water. Addressing this inequity calls for managing water resources differently to serve a growing world population. Water security, defined as a country’s ability to secure enough clean water to meet needs for household uses, irrigation, hydropower and other ends, has win-win-win possibilities. In poorer countries the greatest needs are for household and agricultural uses. While the two uses are closely linked, particularly for rural communities, the policy implications differ.
Household water
Asia and the Pacific and 2 in the Arab States.37 In July 2010 the UN General Assembly recognized the right to water and sanitation and acknowledged that clean drinking water and improved sanitation are integral to the realization of all human rights. In all countries, improving access to these facilities can be a key driver in poverty reduction. And there is cause for optimism. Innovative approaches are under way in many countries.38 Some highlights: • Providing affordable access. Small-scale, needs-driven technologies can provide households with low-cost potable water. In Cameroon cheap biosand filters, developed in South Africa, are used to make water safe to drink.39 In India the international nongovernmental organization (NGO) Water for People partnered with a local university to develop simple, locally manufactured filters that remove arsenic from the water at public wellheads in West Bengal.40 Governments have the obligation to connect their populations to modern waterworks through public, private or civil society service provision, but encouraging these types of local innovations can relieve water deprivation even before larger water infrastructure projects can be implemented. • Supporting local communities. Small grants can support local community efforts to manage water resources. The United Nations Development Programme’s Community Water Initiative and other small grant programmes have worked with governments in Guatemala, Kenya, Mauritania and Tanzania to support community water projects.41
Agricultural water
Expanding access to modern energy for all and developing renewable energy sources are gaining traction, but involving the state, donors and international organizations is critical for reducing disparities
A first step in increasing access to potable water is recognizing equal rights to water, regardless of ability to pay. Right-to-water legislation exists in 15 countries in Latin America, 13 in Sub-Saharan Africa, 4 in South Asia, 2 in East
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Agricultural water problems range from lack of access to overexploitation. But again there is cause for optimism—in efficiency gains and real-cost pricing that moves away from often regressive subsidies. Even in a water-abundant country such as the United States farmers use 15 percent less water now than 30 years ago to grow 70 percent more food; the country has doubled its water productivity since 1980.42
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Better access to safe water and sanitation can improve health directly and productivity indirectly and contributes to human dignity, self-respect and physical safety, particularly for women
Recognizing the problems of overexploitation of water and the need to ensure equitable access has led to promising new schemes. Several countries in the Arab States have water user associations that now operate and manage irrigation systems, establishing service levels and charges. In Yemen water-saving technologies and regulatory systems are designed in consultation with users to ensure that the technologies meet farmers’ needs and that regulatory systems are equitable. And in Egypt pilot programmes have reduced public subsidies; increased the efficiency of water use, operations and maintenance; and reduced pollution.43 Analysis of the distributional impacts of water investments is important. For example, irrigation investments can buffer weather shocks to smooth consumption over time, but the effects can be uneven. Recent analysis of large irrigation dams in India found that people living downstream were likely to benefit, while those living upstream were likely to lose.44 Healthy, intact ecosystems, such as forest headwaters, are vital for sustaining the flow and quality of water for human use. An estimated one-third of the world’s largest cities depend on intact protected forest areas for their water supply.45 In Venezuela water from 18 national parks meets the fresh water needs of 19 million people, or 83 percent of the urban population, and about 20 percent of irrigated lands depend on protected areas for water.46 This is also critical for rural areas. Indonesia’s Lore Lindu National Park provides water for irrigation and fish to support rural livelihoods.
Sanitation
Almost half the people in developing countries lack access to basic sanitation services.47 Expanding access can improve health directly and productivity indirectly and, as discussed in chapter 3, contributes to human dignity, self-respect and physical safety, particularly for women. Our own analysis confirms that better access to safe water and sanitation are also positively associated with women’s health outcomes relative to men—in other words, women benefit disproportionately
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from access to safe water and sanitation, all else equal. Several innovative approaches have provided small-scale access to sanitation: • Manaus, Brazil, recently used a $5  million grant to connect 15,000 mainly poor households to a modern sewage system, by subsidizing services to poor households that otherwise could not afford the service. To encourage take-up, the project worked to raise awareness of the benefits, since the failure of even a small number of households to adopt modern sewage systems can result in contamination of water sources.48 • SaniMarts (Sanitation Markets) in eastern Nepal help households buy materials to construct or upgrade latrines. Piloted in Southern India, SaniMarts are local shops staffed by trained sanitation promoters who sell latrine construction materials at affordable prices.49 • The Sanitation Marketing Pilot Project in Cambodia sought to enhance the adoption of latrines in the provinces of Kandal and Svay Rieng by demonstrating that selling them could be a profitable business enterprise. The “easy latrine” was sold as a complete package that households could easily install themselves. The commercial viability of the product led private businesses to invest their own resources to address demand.50 Despite some regional successes, most such programmes have not been scaled up, largely because they lack strong local leadership or interest, because skills are weak and because monitoring and evaluation are insufficient.51 One exception is an initiative known as the Global Scaling up Rural Sanitation Project, supported by the World Bank in rural India, Indonesia and Tanzania, which has reached an estimated 8.2 million people over four years. Its success is traceable, at least in part, to better performance monitoring, which shifts the focus to outcomes.52 While most approaches focus on supply, Community-led Total Sanitation targets demand (box 4.1). Along with increasing the use of toilets, other behavioural interventions,
such as promoting hand washing,53 are reducing faecal bacterial contamination in Africa and Asia. * * * In sum, greater public policy efforts are needed to increase investments in water and sanitation to improve access. Current patterns of natural resource exploitation are creating huge environmental hardships for the poor, who are often excluded from even minimal levels of service. Access can be increased by building on the successes of a range of countries, many at the local and community levels, and by involving national governments and development partners.
BOX 4.1
From subsidy to self-respect—the revolution of Community-led Total Sanitation
Chapter 3 reviewed how faecal-related infections, now rare in richer countries, are stubbornly endemic in others. Some 2.6 billion people lack sanitary toilets, and 1.1 billion people defecate in the open. That the Millennium Development Goal for sanitation is the farthest off track results partly from a failed reliance on hardware subsidies. The top-down approach, with subsidized standard designs and materials, has provided inadequate toilets that cost too much, delivered them to people who are not the most poor, achieved only partial coverage and use, and engendered dependence. Community-led Total Sanitation (CLTS) turns all this on its head. There is no hardware subsidy, no standard design, no targeting the poor from outside. Collective action is key. Pioneered by Kamal Kar and the Village Education Resource Centre in partnership with WaterAid in Bangladesh in 2000, CLTS teaches communities to map and inspect their defecation areas, calculate how much they deposit and identify pathways between excreta and mouth. It helps communities “face the shit” (the crude local word is always used). Disgust, dignity and selfrespect trigger self-help through digging pits and adopting hygienic behaviours. With followup encouragement, community members also address equity. Children and schools are often involved. Sustainability is enhanced by social pressures to end open defecation. There are challenges, and few communities have done away with it completely. Sandy pit walls can collapse — and floods devastate — but households and communities have bounced back and moved themselves up the sanitation ladder, installing better, more durable toilets. Where governments and communities have endorsed CLTS and enabled quality training and well led campaigns, outcomes have been remarkable. In Himachal Pradesh, India, the number of people in rural areas who had toilets rose from 2.4 million in 2006 to 5.6 million in 2010 out of a total population of 6 million. CLTS has spread to more than 40 countries: more than 10 million people in Africa and Asia already live in open defecation–free communities, and many more have benefited from toilets. In some countries CLTS is making the sanitation Millennium Development Goal look not just achievable but surpassable. In a 2007 British Medical Journal poll sanitation was voted the most important medical advance of the past 150 years. And CLTS won the journal’s competition in 2011 for the idea most likely to have the greatest impact on healthcare by 2020. The quality of training, facilitation and follow-up are all critical as CLTS is scaled up. CLTS expansion could reduce the suffering and enhance the health, dignity and well-being of hundreds of millions of deprived people.
Source: Chambers 2009; Mehta and Movik 2011.
Averting degradation
We turn now to three keys to reducing degradation pressures: expanding reproductive choice, supporting community management of natural resources and conserving biodiversity while promoting equity.
Expanding reproductive choice
Reproductive rights, including access to reproductive health services, are a precondition for women’s health and empowerment and essential to the enjoyment of other fundamental rights. They form a foundation for satisfying relationships, harmonious family life and opportunities for a better future. Moreover, they are important for achieving international development goals, including the Millennium Development Goals. Important in themselves, fully realized reproductive rights can also have positive spillover effects on the environment if they slow population growth and reduce environmental pressures. Recent projections put the world’s population at 9.3 billion by 2050 and 10 billion by 2100, assuming that fertility in all countries converges to replacement levels.54 However, calculations also suggest that simply addressing unmet family planning need in 100 countries could shift global fertility below replacement levels, putting the world on a path to an earlier peak in population and then a gradual decline.55 This can be done through initiatives
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that empower women and increase their access to contraceptives and other reproductive health services. It follows that greater worldwide availability and adoption of reproductive health and family planning services raise the prospect of a win-win-win for sustainability, equity and human development. Of course the environmental gains depend on carbon footprints at the individual level. For instance, an average citizen in Australia or the United States accounts for as much carbon dioxide emissions in two days as an average citizen of Malawi or Rwanda in a year. Reproductive health and family planning are critical in Malawi and
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greater worldwide availability and adoption of reproductive health and family planning services raise the prospect of a win-winwin for sustainability, equity and human development
Rwanda—where women still have an average of five children—but will not significantly reduce carbon dioxide emissions. By contrast, innovative programmes such as Family PACT in California, which reimburses physicians for providing reproductive healthcare to lowincome women and prevents almost 100,000 unintended births each year, not only improve the lives and health of women and their families but also reduce the future carbon footprint by some 156 million tonnes a year.56 Reproductive rights include choosing the number, timing and spacing of one’s children and having the information and means to do so. A rights-based approach means addressing demand—by informing, educating and empowering—and ensuring access to the supply of reproductive health services. Many reproductive choice initiatives are under way worldwide—though most focus more on the supply side.57 The incremental infrastructure requirements of reproductive services are typically modest because service delivery can often piggyback on other health programmes. Several initiatives exploit synergies among population, health and environment programmes at the community level. These include a United States Agency for International Development pilot programme in Nepal covering some 14,000 community forest user groups58 and the PATH Foundation’s Integrated Population and Coastal Resource Management Initiative in the Philippines, which show how to bring reproductive health services into existing community-run programmes. Cambodia and Uganda have similar initiatives.59 ProPeten, an organization devoted to preventing deforestation in Guatemala, augmented its deforestation prevention initiatives with an integrated approach to population, health and environment that was associated with a decline in average fertility in the region from 6.8 births per woman to 4.3 over a decade.60 Better management and more effective targeting of resources often bring large gains, even in resource-poor areas. A local sustained leadership development programme for health workers in Aswan, Egypt, led to more frequent prenatal and childcare visits by health
workers, with large benefits in reduced maternal mortality.61 A number of governments have reformed policy frameworks and programmes to improve reproductive health. In Bangladesh the fertility rate fell from 6.6 births per woman in 1975 to 2.4 in 2009, a huge drop attributed to the introduction of a major policy initiative in 1976 that emphasized population and family planning as integral to national development. Measures included community outreach and subsidies to make contraceptives more easily available, efforts to influence social norms through discussions with the community (religious leaders, teachers, NGOs), education of both men and women and development of reproductive health research and training activities.62 In many cases partnerships across different groups and with a range of service providers have brought gains. In three rural districts and two urban slums in Kenya, poor families were given vouchers to pay for reproductive health and gender-based violence recovery services. 63 In Viet Nam a long-term collaboration of the government, provincial health institutions and several NGOs has led to dramatic improvements in the quality of reproductive health services, provision of new services and establishment of a sustainable clinical training network in reproductive health.64 Similarly, in Iran efforts to introduce reproductive health services began in the late 1980s, when rapid population growth was recognized as an obstacle to development. Today, nearly 80 percent of married women use contraception65 —the country also has a maternal mortality ratio that is less than 8 percent of that in South Africa, which has a similar per capita income. In 2009 Mongolia endorsed a national strategy for reproductive health, included the services in the midterm budget framework and committed to fully funding contraceptive supply by 2015. Lao PDR’s Ministry of Health implemented a community-based distribution model for providing family planning services in three poor southern provinces. The programme sharply increased contraceptive prevalence, in some
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regions from less than 1 percent in 2006 to over 60 percent in 2009.66 Several initiatives show encouraging evidence of the effect of raising awareness of reproductive healthcare. ProPeten sponsored a radio soap opera to disseminate information on the environment, gender issues and reproductive health. 67 Using the extensive mobile phone networks now common in developing countries—more than 76 percent of the world’s population68 and more than 1 billion women in low- and middle-income countries currently have access 69—multiple initiatives, including the Mobile Alliance for Maternal Action, provide customized health information to expectant and new mothers in Bangladesh, India and South Africa.70 These approaches have enormous potential, though their widespread effectiveness has yet to be demonstrated. Concerted government efforts are needed to achieve universal access to reproductive healthcare, which yields rich dividends in lower fertility rates and better health and education outcomes. Bangladesh’s success suggests that the bottleneck is not resources but priorities and political will. The incremental infrastructure requirements are low, but just increasing provision is not enough. Information and training are needed to boost uptake of these programmes in ways that respect tradition and social mores. Community-based programmes have great potential, as do new forms of communications and connectivity.
Supporting community management of natural resources
Support is growing for community management of natural resources as an alternative to centralized control, especially where communities depend on local natural resources and ecosystems for their livelihoods. Increasing interest in reforestation in countries as diverse as Costa Rica, Estonia and India reflects the potential for success.71 While participatory management of common resources has been widely embraced as a promising concept, a detailed review commissioned for this Report shows that the reality is more nuanced.72 Local structural factors
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affect who benefits from community management. The distribution of wealth (including land tenure rights) and knowledge and participation in decision-making are especially important. For example, when influential stakeholders benefit from a common resource, they might invest heavily in restricting access, thus enhancing sustainability but at a cost to equity. As we discuss below, evidence suggests that more equal and socially cohesive communities are more likely to organize and agree on how to deal with collective action problems.73 A major threat to equity is women’s exclusion from decision-making. With no community voice, women are often excluded from the benefits of common resources while bearing a disproportionate share of the costs, as in some parts of India.74 For example, deciding to close forests without considering women’s needs can deprive women of fuelwood, increase the time they spend finding alternative sources of fuelwood and fodder and reduce their income from livestock products. More generally, our analysis suggests a causal link between our Gender Inequality Index and deforestation in more than 100 countries between 1990 and 2010. And as chapter 3 notes, empirical evidence stresses the importance of the nature and extent of women’s participation in management decisions.75 One of the most successful and equitable models of community management of natural resources is the community-conserved area —land or water protected by legal or other means and owned and managed by a community. Around 11 percent of the world’s forests are known to be under community ownership or administration,76 but this is likely a severe underestimate.77 Community-conserved areas help ensure equitable access to resources, sustain human development through essential ecosystem services and maintain ecosystem integrity. Locally managed marine areas—areas of near-shore waters and their associated coastal and marine resources—also provide win-winwin solutions. Pacific Island communities, such as Fiji, have dozens of such areas where island communities have long practiced traditional management systems that include
as an alternative to centralized control, community-conserved areas help ensure equitable access to resources, sustain human development through essential ecosystem services and maintain ecosystem integrity
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BOX 4.2
Culture, norms and environmental protection
The values and beliefs that shape people’s relationships with their natural environment are central to environmental sustainability, as are accumulated traditional knowledge and community practices of environmental management. The environmental management skills of local people may include multiuse strategies of appropriation, small-scale production with little surplus and low energy use, and a variety of custodial approaches to land and natural resources that avoid waste and resource depletion. Case studies suggest that traditional values can protect natural resources. Over three decades in the Zambezi Valley of Zimbabwe, for instance, forests considered sacred lost less than half the cover of those that were not. In Ghana conservative traditions and practices led to the designation of sacred areas and to periodic restrictions on farming, harvesting and fishing. Local knowledge also informs natural disaster responses. Chile reported only 8 fisher victims out of an estimated population of about 80,000 following the February 2010 tsunami, thanks mostly to lessons from previous tsunamis passed down through elders’ stories and neighbours’ evacuation alerts. Though such knowledge is often downplayed and overlooked, traditional values have also informed policy. In Andavadoaka, a small fishing village in Madagascar, the community initiated a sustainable octopus fishing initiative that inspired other villages and became the country’s first locally managed marine area, involving 24 villages. And in Afghanistan the government is drawing on elements of long-standing mirab systems — in which locally elected leaders manage water rights — in creating water use associations.
Source: Byers and others 2001; Marín and others 2010; Thomas and Ahmad 2009; Sarfo-Mensah and Oduro 2007; UN 2008.
ecosystems. In some cases—including Costa Rica and the Philippines—greater decentralization and comanagement of natural resources have helped alleviate tensions.
Conserving biodiversity while promoting equity
seasonal fishing bans and temporary no-take areas. Community-conserved marine areas provide enormous value to local communities in the forms of fish protein and sustainable livelihoods.78 Communities can manage natural resources using a variety of mechanisms, including payments for ecosystem services and community-conserved areas. Cultural or traditional norms emerge as important (box 4.2). Success requires broad stakeholder inclusion in returns—from the resources themselves as well as from their management. Local processes and national commitment are also important. Sweden’s experience in the 1960s, reviewed in box 2.10 in chapter 2, shows that national environmental protection mandates can support community management. Where the livelihoods of multiple stakeholders are closely tied to natural resources, community-based management is susceptible to conflict. As discussed in chapter 3, scarcity of natural resources and environmental stresses can contribute to the eruption and escalation of conflict. In some cases public policies exacerbate the sources of conflict, especially when policies worsen horizontal inequality79 or negatively affect people living within particular
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In recent years perceived trade-offs between preserving livelihoods and maintaining biodiversity have been replaced by a clearer understanding of the potential synergies. For instance, preserving natural ecosystems and biodiversity can help secure livelihoods, food, water and health. Many countries (including Botswana, Brazil and Namibia) and international organizations (including the United Nations Development Programme) are calling for investments to preserve biodiversity for its potential development benefits. One instrument is to assign and enforce protected area status to ecosystems, putting in place measures to avert or reverse land degradation and ecotourism. Ecotourism in particular is a promising route to protecting biodiversity while enhancing livelihood opportunities for the local community. The primary challenge is to ensure equitable participation, including by women.80 A recent survey found that nature-based tourism is one of several conservation mechanisms that can reduce poverty.81 In Namibia, for example, an ecotourism programme has protected nearly 3 million hectares of land and marine areas housing great biodiversity. Especially important for equity, the programme has improved livelihoods immensely. And with roughly 29 percent of the wealth generated by these protected areas going to labour and another 5 percent to traditional agriculture, the programme shows the potential of protected areas to reduce poverty as well. 82 Similarly, an initiative to conserve biodiversity at the level of landholders in the island state of Vanuatu led to the establishment of 20 conservation sites, which reduced poaching and enhanced fishstocks and incomes for local communities. And in Ecuador the government entered into an agreement with the United Nations Development Programme in 2010 to establish an international trust fund to
protect Yasuní National Park, an area rich in biodiversity and home to the indigenous Tagaeri and Taromenane people, from oil drilling. Though too early to assess the results, the initiative offers a model for preserving such ecosystems through developed country compensation of poorer countries.83 Another example of promoting livelihoods while maintaining biodiversity is agroforestry, which entails an integrated approach of combining trees, shrubs and plants with crops and livestock to create more diverse, productive, profitable, healthy and sustainable land-use systems. Agro-forestry production can be seen in the Yungas region on the eastern slope of Peru’s Central Andes, among an indigenous community of around 32,000 inhabitants. This enables the community to conserve genetically important species while providing for a range of nutritional, medicinal and commercial purposes.84 Integrated conservation and development projects aim to conserve biodiversity while promoting rural development. For example, in Nepal’s western Terai Complex communities reduce pressures on natural forests by focusing on biodiversity-friendly and sustainable land and resource use practices. Such projects ensure that communities, particularly women and the poor, have viable alternatives for income, while reducing pressures on natural ecosystems.85
Addressing climate change— risks and realities
Finally in this review of promising approaches, we consider two key policy directions to offset the impacts of climate change on people: equitable and adaptive disaster responses and innovative social protection.
Equitable and adaptive disaster responses
As chapters 2 and 3 show, natural disasters are disequalizing, reflecting economic and power relations at the local, national and global levels. But planning and targeted responses can reduce the disparities. Two promising avenues are community-based disaster risk mapping
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and progressive distribution of reconstructed public assets. Experience has led to a shift from top-down models of disaster recovery to decentralized approaches. Community-based disaster risk programmes are generally better than centralized programmes at tapping local knowledge of capacities and constraints for emergency relief and longer term recovery and reconstruction. Local organizations are also often better able to reach remote and restricted areas—as demonstrated in Aceh, Indonesia, and Sri Lanka, where periods of armed conflict made it difficult for international aid workers to operate.86 Some attention is needed to avoid depending exclusively on local organizations, which could intensify disparities and exclusion. Community-led vulnerability and resource mapping has demonstrated effectiveness:87 • In Mount Vernon, one of the poorest communities in Jamaica, community-led disaster mapping highlighted flooding problems and led to agreement on the need for footbridges. • A community-led mapping of women’s access to resources and services in Jinja, Uganda, identified corrupt land distribution and denial of women’s rights to land as impediments to women’s access. Grassroots leaders responded by setting up savings clubs and rotating loan schemes, which improved women’s access to land titles and helped them develop their property. Community involvement can be enormously empowering for poorer communities, as shown by disaster training programmes in 176 districts in the 17 most hazard-prone Indian states. Female master trainers reached out to women in their communities and served as role models. Engaging women in community risk-mapping involved them in decisionmaking, giving them greater voice and control over their lives. In the words of Mitali Goswami of Ngoan District in Assam, “We feel very useful and are filled with pride when we see ourselves fulfilling our responsibilities towards the family and community.”88 Poor rural communities are disproportionately affected by ecosystem degradation and disproportionately benefit from their
Poor rural communities are disproportionately affected by ecosystem degradation and disproportionately benefit from their protection and restoration
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protection and restoration. Sometimes the most efficient and equitable ways to avoid and mitigate disasters are to manage, restore and protect the ecosystems that buffer the community. For example, villages with healthy mangroves, coral reefs and lowland forests were better protected from the 2004 tsunami in India, Indonesia, Malaysia and Sri Lanka.89 Structural inequalities are often embedded in patterns of infrastructure and social investments and reflected in the outcomes. Rebuilding after environmental disasters can address past biases and other factors that perpetuate poverty and inequality. When Northern California was recovering from the 1989 Loma Pietra earthquake, the community opposed rebuilding the freeway along the original route, which divided neighbourhoods and exposed them to vehicular pollution. The freeway was rerouted through nearby industrial land, and
TABlE 4.2
agreements were reached to promote local hiring and contracting on reconstruction.90
Innovative social protection
Social protection for adaptation and disaster risk reduction: benefits and challenges
Programme and example Targeted cash transfers Ethiopia: Productive Safety Net Programme Benefits • Targets the most vulnerable • Stabilizes consumption • Allows adaptive risk-taking and investment • Enhances flexibility to cope with climate shocks Challenges • Ensuring adequate size and predictability of transfers • Reducing risk through long-term focus • Demonstrating the economic case for cash transfers associated with climate shocks • Using socioeconomic vulnerability indices for targeting • Ensuring adequate benefits • Accountability and transparency • Increasing awareness to ensure high participation • Controlling costs and avoiding the risk of exclusion
Employment schemes • Provides 100 days of India: Mahatma Gandhi National employment on demand in Rural Employment Guarantee Act rural areas • Constructs infrastructure, including projects that enhance community resilience against climate change impacts • Provides a guaranteed income to combat seasonal variations in income Weather-based crop insurance Government of Malawi and partners: weather-indexed crop insurance for groundnut production • Guards against risk-taking associated with insurance • Frees up assets for investment in adaptive capacity • Can be linked to trends and projections for climate change • Supports adaptive flexibility
• Targeting marginal farmers • Tackling differentiated gender impacts • Keeping premiums affordable for the poor • Subsidizing capital costs • Integrating climate projections into financial risk assessment • Establishing guarantee mechanisms for reinsurance • Ensuring provision commensurate with the threats faced • Ensuring local appropriateness of assets • Integrating changing natural environmental stresses in asset selection
Asset transfers Bangladesh: Reducing Vulnerability to Climate Change project
• Targets the most vulnerable • Can be integrated into livelihood programmes
Source: Adapted from Davies and others in OECD (2009).
Growing evidence shows that social protection programmes—assistance and transfers to enhance the capacity of poor and vulnerable people to escape poverty and manage risks and shocks—can help families maintain stable consumption and meet broader distributive goals.91 As many as 1 billion people in developing countries live in households that receive some form of social transfer.92 Table 4.2 shows four types of social protection measures that, appropriately combined, can promote both equity and environmental objectives. We highlight both the potential benefits and the challenges of targeted cash transfers, employment schemes, weather-based crop insurance and asset transfers. Social protection programmes can help people access modern energy sources, clean water and adequate sanitation. A recent study illuminates the impacts of cash transfers to poor households under Mexico’s Oportunidades programme that go beyond the well studied effects on health and education. The transfers have affected both short-run spending on energy services and long-run spending on new appliances (refrigerators, gas stoves). They have enabled families to switch from wood or charcoal to the cleaner, more expensive electricity and liquefied petroleum gas.93 Countries should consider more integrated approaches to social protection— approaches that address environmental sustainability, equity and human development. A recent survey of social protection, disaster risk reduction and climate change adaptation schemes in South Asia revealed that few countries integrate such programmes. Of the 124 programmes surveyed, just 16 percent combined all three elements.94 One example is South Africa’s Working for Water, part of an Expanded Public Works Programme launched in 2004. The project, the first of its kind to include an environmental component, increased stream flows and water availability, improved land productivity and biodiversity in some ecologically sensitive areas and inspired
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similar initiatives for wetlands, coastal areas and waste management.95 When reviews of the first phase (2004–2009) found that public works programmes were too short and wages too low to substantially reduce poverty, the government set a new minimum wage for the next phase of the programme. Public works programmes need to provide options for women and for people unable to work. South Africa’s Working for Water has quotas for women (60 percent) and for people with disabilities (2 percent).96 In India women and members of scheduled castes and scheduled tribes account for (an overlapping) 50 percent of participants in the National Rural Employment Guarantee Act. Involving the community in designing and managing adaptive social protection programmes is important. A review of the India National Rural Employment Guarantee Act illustrates how villagers have been empowered to identify projects and negotiate with local authorities.97 How widespread participation in governance and decision-making contributes to strong and accountable institutions and equitable outcomes is discussed further in the following chapter.
Ultimately, how adaptive social protection is implemented turns largely on political preferences for equity and the environment and on how well society is mobilized behind programmes for building long-term resilience as part of social protection and poverty reduction. * * * This review of promising approaches provides strong grounds for optimism. It is possible to identify and implement strategies that improve both sustainability and equity—strategies that fall in quadrant 1 of figure 1.1 in chapter 1—to address many of the challenges outlined in chapters 2 and 3. And we have seen successes in such approaches around the world, with tangible benefits for poor and disadvantaged people and the environment. But such outcomes are not automatic. More concerted efforts are needed to integrate equity into policy and programme design and engage people in discussions and decisions that affect their lives. Such approaches must be resourced appropriately, in ways that ensure a progressive distribution of responsibilities. It is to these challenges that we turn in chapter 5. we have seen successes around the world with strategies that improve both sustainability and equity
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5
rising to the policy challenges
This Report has focused on the large disparities across people, groups and countries— disparities that coexist with and worsen environmental degradation and loss of ecosystem services that the world’s poor depend on. Yes, the challenges are massive. But in several respects conditions today are more conducive to progress than ever. Global public awareness is higher, and the new calls for democracy sweeping parts of the world augur well for reform. Taking the debate further entails bold thinking, especially on the eve of the 2012 UN Conference on Sustainable Development (Rio+20). This Report advances a new vision for promoting human development through the joint lens of sustainability and equity. For that vision to become a reality, institutions must be strengthened, capacities enhanced, policies reformed and democratic governance fortified. The vision calls for an expansive rethinking of the role of the state and communities —and their capacity to identify and exploit emerging opportunities. Building on the insights of Amartya Sen and the key principles of the human development approach, this vision stresses an approach to sustainability and equity rooted in inclusion, participation and reasoned public debate, while recognizing diverse values, conditions and objectives. Beyond the Millennium Development Goals the world needs a post-2015 development framework that reflects equity and sustainability: Rio+20 stands out as a great opportunity to reach a shared understanding about how to move forward. This chapter proposes key reforms at the national and global levels: • At the national level it stresses the need to bring equity to the forefront of policy and programme design, and the potential
chap ter
multiplier effects of greater empowerment in the legal and political arenas. • At the global level it calls for greater resources to be devoted to pressing environmental threats and for more equitable representation of disadvantaged countries and groups in accessing finance. Concerted actions can bring equity and sustainability closer to the centre of human development. Too often development plans invoke unnecessary trade-offs—sacrificing a healthy environment or equitable distribution of wealth for the sake of economic growth. Implicit is the notion that one aim is a luxury, less important than the other. Power imbalances and political constraints loom large. And too often the plans are incomplete, not designed to promote equity. But policies can maximize the synergies among healthy communities, healthy economies and a healthy environment. The chapter reinforces the central contention of this Report: that integrating the approaches to sustainability and equity can produce innovative solutions and concrete guidelines to promote human development.
Business-as-usual is neither equitable nor sustainable
The conventional focus on maximizing growth has been associated with a model that ignores the environmental impacts and externalities of economic activity. This is true in a command and control system (the former Soviet Union), in a liberalizing socialist economy (China in the 1990s) and in fairly free market economies (Australia and the United States over much of the 20th century). Especially since the Second World War, accelerations in economic growth have been carbon-intensive, and economic regulation has been scaled back. As chapter 2
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worsening environmental degradation could soon break the 40-year pattern of convergence in human development across countries
shows, untrammelled growth without regard for the environment has brought the world to the point where the concentration of carbon dioxide in the atmosphere already exceeds 350 parts per million and is heading to levels that risk multiple catastrophes. In the face of daunting environmental challenges that endanger prospects for continuing progress in human development, concerted global action too often falls far short of what is needed. This chapter reviews the scale of the challenges and points to a fundamental contradiction: business-as-usual is neither sustainable nor equitable, but attempts to move forward are beset by political economy constraints. It proposes key principles for countries to promote change and then addresses key elements at the global level. Worsening environmental degradation could soon break the 40-year pattern of convergence in human development across countries. Consider the potential trade-offs between economic costs and environmental damage given today’s technology and carbon intensity of production. Simulations for this report suggest that if no country or region is prepared to bear a loss of more than 1 percent in total future income, or more than 5 percent of its income in any five-year period, carbon dioxide levels will trigger a temperature increase of 3°C above preindustrial levels by 2100.1 But a temperature rise above the 2°C threshold would be catastrophic for many developing countries, 2 as chapter 2 describes. So, we highlight the potential outcomes of alternative paths and a framework to induce global cooperation. Systematic thinking about how to share the costs of adjustment and promote greener growth is critical, alongside concerted public action to support innovations in technology and enhance voice and accountability. A fundamental rethinking of the conventional growth model is well under way. The 2008 global financial crisis and its aftermath reinforced the growing consensus that deregulation went too far and that the pendulum should swing back.3 Indeed, compounding the economic failures of conventional policies are the other costs they can introduce —such as greater inequality and environmental
degradation. As chapter 1 argues, lessons from the recent financial crisis can be applied to the potential effects of climate change (see box 1.1). More active public policy is critical, not least because development must be decoupled from carbon emissions and the true value of ecosystem services should be incorporated into national development plans. The good news is that there is growing recognition, or rediscovery, of industrial policy—of proactive policies and interventions to restructure an economy towards more dynamic activities— even at such institutions as the World Bank, long a proponent of free market approaches.4 Overcoming pervasive market imperfections requires, among other things, internalizing the externalities in decision-making and in some cases creating markets where none exist —as for some ecosystem services. Because of the costs and risks created by greenhouse gas emissions, the loss of ecosystem services due to environmental degradation and underinvestment in innovations, more support should go to promoting innovative renewable energy technologies. If firms underestimate the long-term benefits of investing in new technologies or if they cannot appropriate the benefits, they will invest less than is optimal socially and globally. As chapter 4 shows, well designed, well implemented incentives can elicit change. For example, Japan’s 2009 buy-back system for residential rooftop photovoltaics promoted investment and provided incentives for customers to reduce electricity use. Similarly, tax incentives have encouraged renewable energy investments in Canada, Denmark, India, Sweden and the United States.5 But price-based incentives, especially for scarce resources, need careful calibration to avoid impoverishing or excluding already disadvantaged groups. A key constraint to public action on environmental problems is lack of awareness. About a third of the world’s people seem unaware of climate change, and only about half consider it a serious threat or know that it is caused at least partly by human activity (see box 2.5 in chapter 2). But even with raised awareness, serious political constraints would remain—in other words, our collective failure to act also reflects the complexity of the politics and the power
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of groups opposing change. Chapters 2 and 3 show how many countries and communities most affected by climate change lack power and influence. So understanding these constraints is a vital first step in framing strategies with a real chance of meaningful change. As chapter 4 discusses, national planning processes are critical, but capacity constraints and siloed approaches can limit effectiveness. In the western Balkan countries, for example, a major barrier impeding implementation of climate change mitigation policies is the lack of national coordination mechanisms. 6 It is clear that equity issues go well beyond developed versus developing countries—and beyond mitigation costs alone—to the burden of adjustment. Procedural justice requires that all parties be able to participate effectively7 —some of the groups that lobby nationally, including those pushing for more equitable policies for women and indigenous peoples, also merit a voice on the global stage. Similarly, global environmental finance and governance mechanisms must be informed by principles of equity and fair representation that go beyond country governments.
rethinking our development model—levers for change
The required transformations involve a progressive approach that integrates the pillars of sustainable human development. Due consideration must be given to differences in country contexts: one-size-fits-all thinking is rarely effective when formulating policy or implementing programmes. Proposed here are two major avenues to guide such efforts—one is the integration of equity concerns into policy and programme design and evaluation, the other is empowerment in the legal and political arenas. For each avenue the chapter sets forth basic principles and highlights the experiences of selected countries.
Integrating equity concerns into green economy policies
assessments are often silent on the winners and losers of a policy or programme. 8 But distributional aspects require explicit consideration because effects on the poor or the rich might differ from average effects—and sometimes from intended outcomes. It is important to consider differences between the rich and the poor, between men and women, among indigenous peoples and across regions. Such considerations are consistent with the stated objectives of green economy policies, but they warrant a sharper focus in practice. Integrating distributional aspects into cost–benefit analysis has long been recognized as important9 but has rarely been practiced, resulting in neglect of equity in project and policy analysis. In the absence of transfers, policies and projects that pass cost–benefit tests might not make everyone better off— and might even reduce the welfare of some groups (box 5.1). But appropriately valuing environmental and resilience-promoting benefits is difficult. This is true especially of the ecosystems for which the value of services is not fully known. The distributional analysis of economic policy reforms has advanced in the past decade —examining effects on the well-being of different groups, especially the poor and vulnerable. The World Bank has supported many such analyses, though sometimes the timing is too late to inform decision-making or policy-makers fail to adequately incorporate the results of such assessments.10 And distributional analyses still tend to be restricted to income, using conventional economic tools and focusing on such transmission mechanisms as prices and employment. Because such analyses can miss important parts of the picture, we propose that the approach be expanded and deepened.
Key principles
Equity issues go well beyond developed versus developing countries— and beyond mitigation costs alone—to the burden of adjustment
The need to integrate equity concerns more fully into environmental policy is a major theme of this Report. Conventional
Environmental regulations and subsidies can affect people’s capabilities as individuals, family members, workers, entrepreneurs and farmers (figure 5.1). Policy can affect people’s endowments, opportunities and agency—and through them the distribution of a range of assets.
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FIGURE 5.1
integrating equity into policy design
Endowments Opportunities Agency Farms Institutional framework Firms Communities KEY DISTRIBUTIONAL ASPECTS
Sources of livelihoods, assets, land, skills, social capital, opportunities
PEOPLE’S CAPABILITIES
Monitoring outcomes and distributional impacts DESIGN ASPECTS
Coverage, costs, source of financing, benefits, incidence, compensation
Environmental policy instruments
Both vertical and horizontal equity are important. Vertical equity looks at the treatment of individuals across the distribution— for example, how a tax on gasoline would affect people at the bottom of the distribution differently from those at the top. Horizontal equity relates to differences across groups or areas.
BOX 5.1
Distributional impacts of policies to cut pollution
Current discussions often raise concerns that policies to reduce pollution can be regressive, but rarely is systematic impact analysis brought to bear. The type of analysis needed can be illustrated for a carbon permit system such as cap-and-trade — which raises the price of products that use fossil fuels intensively, such as electricity. It draws attention to first- and second-round effects: 1. Everyone faces real income losses, but the effect is regressive if low-income households spend a higher fraction of their income on these goods. 2. If technologies are capital-intensive, a mandate to abate pollution can induce firms to substitute capital for polluting inputs, depressing demand for labour and relative wages. Low-income households receive a larger share of their income from wages, so they may again be more affected. 3. Unemployment may be concentrated among certain regions, industries and groups, such as coal miners. When the industry shrinks, workers with industry-specific human capital lose that investment, while premiums go to skilled workers in renewables and other energy-efficient technologies. These effects raise important empirical questions to be investigated case by case. Research in Organisation for Economic Co-operation and Development (OECD) countries points to few truly “green” skills and suggests that most green jobs resemble familiar occupations. This is good news for displaced workers in developed countries, but it warrants investigation elsewhere. Low-skilled workers are more likely to be displaced by carbon taxes. In OECD countries these workers stay unemployed for longer after job losses than do higher skilled workers and are less likely to find employment that pays as well. So, governments need to watch out for adversely affected groups when implementing environmental regulations, particularly when regulations will affect already disadvantaged groups. Policies must include redistributive and backstop mechanisms to avoid these problems.
Source: Fullerton 2011.
Key priorities for integrating equity into green economy policy design include: • Mainstreaming the nonincome dimensions of well-being. Building on the Multidimensional Poverty Index could broaden understanding of disadvantage and highlight the impacts of policy changes across all dimensions of deprivation. For instance, higher charges for water could reduce access, harming health, while more expensive kerosene could push households back to using biomass for cooking, bad for health and the environment. • Understanding direct and indirect effects. Direct effects can be followed by a second round of indirect changes (see box 5.1). • Considering compensation mechanisms. Countries with well developed tax-andtransfer systems can use income tax schedules or social benefits to offset negative effects. For example, South Africa provides an income tax deduction for communal and private landowners who set aside land with high biodiversity value and manage it as a protected area.11 But where such systems are less feasible, alternative compensation or exemptions are needed. • Understanding the risk of extreme events. However small the probability, it is essential to consider the huge adverse consequences of extreme weather events, especially for the most vulnerable—and to reduce the risks.12 Such analysis may reveal that investing in land use planning and ecosystems can be a cost-effective buffer for
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vulnerable groups against climate risks, as demonstrated by mangrove restoration in Viet Nam.13 So, rather than accept or reject an individual policy, it is important to consider a range of designs and to determine which can improve outcomes for equity. There are always constraints in data, analysis, capacity and time, so flexibility is needed in meeting the main goals. Stakeholder analysis is critical. Political economy factors and the influence of various actors can affect both design and implementation of policy. For instance, the oil industry in the United States spent almost $1.5 billion on federal lobbying in 2010.14 And in Tanzania the proposed reform of charcoal production, trade and use highlights the needs and influence of dealer-transporter-wholesaler networks.15 Policy design and implementation must address such influences and their likely impacts. Institutional arrangements must guard against rent-seeking and official corruption— and more than this, against distortions of scientific facts, breaches of principles of fair representation and false claims about the green credentials of consumer products.16 Countries need industrial policies that support inclusive green growth while being mindful of the pitfalls and challenges of state promotion of selected types of economic activity. The features of a new industrial policy are relevant for policies to reduce the carbon intensity of development—limited incentives to new activities, automatic sunset provisions (so that the subsidies are temporary) and clear benchmarks for success. This requires the right institutions, a political champion and systematic deliberations that engage the private sector.17
Country experience
More countries are using distributional analysis to inform environmental policy design. South Africa’s plans to introduce environmental taxes as part of its fiscal reforms were informed by stakeholder analyses of likely quantitative and qualitative effects.18 Viet Nam announced new taxes following impact assessments simulating price and sectoral effects.19
Policies to drive structural change, such as pollution pricing, will inevitably have winners and losers. Some companies will claim unfair adverse impacts. Policy measures to respond to such concerns, such as exemptions and compensation, can be costly, and the distributional impacts need to be understood. Alternatives, such as more effective consultations and public communications, should also be contemplated.20 Consumption and production profiles can shape distributional effects. Two examples from the energy sector: • Ghana’s electricity sector was draining the government budget. In 2002 public utility company deficits approached 11 percent of government spending, or 4 percent of GDP. Distributional analysis found that subsidies benefited mainly middle-class urban customers: only 7 percent of the rural poor used electric light. The lack of rural electrification in the poorest northern regions warranted reducing subsidies, raising public awareness of energy efficiency and increasing efforts to improve market efficiency.21 • In Lao PDR, which experienced rapid expansion of access to modern energy services after the late 1980s, key equity aspects were incorporated in programme design. A “power to the poor” component provides interest-free credits to connect poor households to the grid, benefiting female-headed households in particular. Local communities and rural households also receive support for electricity use for income-generating activities.22 While some insights can be drawn from such interventions, the effects are always contextspecific and require local analysis. Data constraints can limit understanding. The joint analysis of human development and equity impacts requires individual and household information, as well as qualitative data, to build statistical capacity. This underlines the importance of continuing to improve disaggregated data, especially in developing countries. Ex ante assessments need to be followed by results monitoring. In rural Bangladesh home
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Constitutionally recognizing equal rights to a healthy environment promotes equity because such access is no longer limited to those who can afford it
solar power systems were estimated to displace kerosene use equivalent to 4 percent of total annual carbon emissions. 23 Surveys showed that solar subsidies—amounting to almost $400 million and allocated through a private microcredit agency—were progressive when accurately targeted, because the bottom two income groups spent about three times more on kerosene than the top two. Benefits also included better lighting, good for children’s education, and reduced indoor air pollution, with benefits for health.
Empowering people to bring about change
are not equivalent to legal rights, although they can motivate legislation and thus provide the basis for legal action. Some rights are procedural—as with the right to information discussed below—and must encompass both opportunity and process aspects.27 Constitutionally recognizing equal rights to a healthy environment promotes equity because such access is no longer limited to those who can afford it. 28 And embodying such rights in the legal framework can influence government priorities and resource allocations.
Growing country experience
This Report argues for empowerment to bring about greater equity and environmental benefits—and as an important outcome in itself. What does this mean in practice? Consider two spheres where enhancing voice and representation has important links to sustainability—the legal, with enabling institutions and rights to a clean and safe environment, and the political, with more participation and accountability.
A clean and safe environment— a right, not a privilege
That all people, born and yet to be born, have the right to a clean and safe environment is a powerful idea, grounded in the framework in chapter 1. Despite the slow progress in securing such rights globally, 24 constitutions in at least 120 countries address environmental norms or the state’s obligation to prevent environmental harm.25 And many countries without explicit environmental rights interpret general constitutional provisions for personal rights as including a fundamental right to a clean, safe and healthy environment. That right derives from people’s rights to bodily health and integrity and to enjoyment of the natural world. Amartya Sen, Martha Nussbaum and others have noted a close relationship between the capabilities approach and rights-based approaches to human development. 26 But unlike the idea of freedom or capability in itself, an acknowledged human right also incorporates corresponding obligations. Notwithstanding such obligations, human rights
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Many EU countries recognize fundamental environmental rights as a matter of natural law—as inherent universal rights. In the United Kingdom the Human Rights Act includes the right to a healthy environment. 29 And although the European Convention on Human Rights does not mention environmental rights, it establishes that serious environmental damage may violate the right to respect for private life and family life.30 Sweden recognizes the right of public access through its constitutional “Don’t disturb; don’t destroy” policy: people have the right to roam freely in the countryside as long as they do not inconvenience others.31 Kenya’s 2010 Constitution grants the right to a clean environment and requires the government to maintain its natural resources.32 At least 31 other African countries express environmental rights in their constitutions, and some—such as Ethiopia and Namibia—also stress that economic development should not harm the environment.33 The enforceability of environmental rights in Africa is largely untested, however, except in South Africa. Some countries have structural impediments. In Cameroon citizens do not have the right to appeal to the country’s constitutional council, which limits enforceability.34 And in Namibia environmental rights can be enforced only by someone with a private interest, barring claims in the public interest.35 Several Latin American countries, including Chile, Costa Rica, Ecuador and Peru, have
enforceable environmental rights. The Chilean Supreme Court voided a government-issued timber licence because it had been approved without sufficient evidence of environmental viability, thus violating the right of all Chileans—not just those directly affected—to live free of environmental contamination.36 Many Latin American constitutions recognize environmental rights for indigenous peoples.37 Paraguay guarantees that the state will defend them against habitat degradation and environmental contamination.38 In Guyana environmental rights exist alongside recognition of the rights of indigenous peoples.39 Bolivia’s proposed Law of Mother Nature takes this recognition a step further, giving the natural world equal rights with people. The proposal is heavily influenced by a resurgent indigenous Andean spiritual world view that places the environment and the earth deity Pachamama at the centre of life.40 Among Asian countries India is notable for allowing aggrieved individuals to challenge state action or inaction related to the environment.41 The Indian judiciary has broadly interpreted environmental rights in the constitution to protect public health as well. For example, environmental advocates successfully argued that environmental laws obliged the government to reduce air pollution in New Delhi in the interests of public health, resulting in an order mandating conversion of city buses from diesel to compressed natural gas. 42 Bhutan has pioneered placing environmental conservation at the centre of its development strategy, reflecting traditional norms and culture. 43 Article 5 of the 2008 Constitution emphasizes the responsibility of all Bhutanese to protect the environment, conserve its biodiversity and prevent ecological degradation. It also stipulates that at least 60 percent of the country remain forested in perpetuity. Even if rights provide only what Immanuel Kant called imperfect obligations, they can still empower groups and individuals to take public action to protect their environment. As Amartya Sen wrote, “because of the importance of communication, advocacy, exposure and informed public discussion, human rights can have influence without necessarily
depending on coercive legislation.”44 Indeed, procedural human rights linked to environmental protection often receive more attention than substantive environmental rights.45
Enabling institutions
Alongside legal recognition of equal rights to a healthy, well functioning environment, enabling institutions are needed, including a fair and independent judiciary and the right to information from governments. For example: • In the United States conservation groups have used information on emissions levels to bring public nuisance actions against private companies.46 • One Million Acts of Green, launched by Cisco in partnership with the Canadian Broadcasting Corporation and GreenNexxus in Canada in 2008, uses television, Facebook®, Twitter™ and other Internet resources to engage Canadians in conversations on environmental issues and encourage “green acts.” The initiative elicited nearly 2 million green acts within a year.47 An institutional context conducive to civil liberties is a necessary backdrop. But recent Gallup data suggest that a majority of the people in close to half of nearly 140 countries surveyed lack confidence in their judicial system and courts.48 This underlines the importance of implementing broader reforms and improving the context for enforcing rights. Rights to government information are spreading. At least 49 national constitutions recognize them, and at least 80 legislatures have enacted right-to-information laws. South Africa’s 1996 Constitution guarantees all “the right of access to any information held by the state and held by another person that is required for the exercise or protection of any rights.” In Argentina, Canada, France, India, Israel and the Republic of Korea higher courts have held that constitutional guarantees of free expression implicitly recognize a constitutional right of access to information.49 But legislation is just a first step. Implementation and enforcement are equally critical. Civil society organizations are important for implementation by helping citizens understand and use legal rights of access to
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Democracy is important, but to enable civil society and foster popular access to information, national institutions need to be accountable and inclusive— especially with respect to women and other affected groups
information, by training public officials in information disclosure and by monitoring implementation. In Bulgaria a nongovernmental organization, the Access to Information Programme, provided legal assistance and disseminated information to the wider public about the right-to-information law and the scope of citizens’ rights.50 Information disclosure is very important to environmental protection and citizen empowerment. Ensuring that polluters disclose information on emissions and discharges can reduce violations and complement regulation. British Columbia’s public disclosure strategy had a larger impact on emissions and compliance than the sanctions traditionally imposed by Canada’s Ministry of the Environment. Stricter standards and larger penalties were also influential—suggesting that both information and regulation can reduce emissions.51 And in China programmes to rate and publicly disclose companies’ environmental performance have prompted facilities to reduce air and water pollution, improving firms’ market competitiveness and relationships with communities and other stakeholders.52 The Czech Republic, Egypt, Indonesia and Mexico recorded similar results with the new mandated Pollutant Release and Transfer Registers.53 The international community is increasingly recognizing a right of access to environmental information.54 This in turn supports a broad interpretation of national constitutional rights to information. The complex cross-sectoral challenges of sustainable human development have a long time horizon and require long-term commitments.55 Changing decisions, mobilizing investment and developing new strategic plans can take years if not decades. This may involve major institutional reforms to mainstream environmental considerations in government planning. The government of Rwanda recognized the need to integrate environmental and natural resource management plans into the country’s development strategy. Its Environmental Management Authority works closely with the national and local governments as well as civil society to promote sustainable development and the right to live in a clean and
productive environment by requiring that all sectors of society manage the environment efficiently and use natural resources rationally.56
Participation and accountability
Process freedoms, which enable people to advance goals that matter to them, are central to human development and—as discussed in last year’s HDR—have both intrinsic and instrumental value. Major disparities in power are reflected in unsustainable outcomes, but the converse is that greater empowerment can bring about positive environmental change equitably, as chapter 3 argues. Democracy is important, but to enable civil society and foster popular access to information, national institutions need to be accountable and inclusive— especially with respect to women and other affected groups.
Forums to facilitate participation
A prerequisite for participation is open, transparent and inclusive deliberative processes. Consider energy. As work commissioned for this Report demonstrates, most energy decisions are made behind closed doors and rarely in democratic fora.57 Because of concerns for commercial confidentiality or geostrategic sensitivities about energy supplies, the public has participated little in negotiating energy policy decisions. “Consultations” can provide limited or incomplete information, neglect equity and impact assessments, and fail to report results effectively. Even where public participation or comment is formally invited, its role is often to legitimize prior policy choices and decisions, not to shape them.58 In Australia, for example, cases have demonstrated a lack of open exchanges among local government, polluting industries and local communities and a failure to inform citizens of the risks of living and working near toxic sites.59 Where governments are responsive to popular concerns, change is more likely. In the United States, for example, 23 states allow citizens to petition for a direct vote on a policy initiative, a mechanism that some states have used to adopt environmental and energy policies (such as Washington in 2006). 60 Some groups have pursued accountability of
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private corporations in emissions and climate change. 61 But such concerns may be offset by other vested interests—as reported for the Russian Federation in the problems civil society faced in mobilizing public support around greening industry. 62 And where civil society is active, as chapter 3 shows, it can bring about positive outcomes. An active press raises awareness and facilitates public participation. In Rwanda the government launched radio and television promotions highlighting national environmental issues and targeting all levels of society. Media coverage increased support from the Environmental Management Agency and other government ministries to jointly explore ways to integrate environmental concerns into planning and to enhance cooperation for environmental protection. 63 For climate change and other global environmental problems, procedural justice implies an equal opportunity for all countries to affect the direction and content of international negotiations. But weak capacity often means that few developing country governments are represented, let alone able to represent their citizens’ interests adequately in arenas with high demands for legal and scientific expertise. Although 194 countries attended the UN Climate Change Conference in Copenhagen in 2010, only a powerful handful negotiated the terms of the Copenhagen Accord. In international summits the top five polluting countries usually field more than three times the delegates of the five countries most affected by climate change.64 The news is not all bad, however. Governance of the Climate Investment Funds is already moving towards more equitable voice and participation—with an equal number of representatives from donor and developing country governments on the governing committees for each of the trust funds and with decisions made by consensus. The Climate Investment Funds have also institutionalized formal observer roles for civil society, the private sector and in some cases indigenous peoples, while making the role of observers more meaningful by enabling them to suggest agenda items and contribute to discussions.65
The United Nations Collaborative Programme on Reducing Emissions from Deforestation and Forest Degradation in Developing Countries goes even farther, since its board, which decides on strategic directions and budget allocations, includes representatives of indigenous peoples and civil society as full members, not just as observers.66 Still, barriers to effective participation persist in many national and local contexts. Some groups, such as women, have traditionally been excluded from governance institutions. But here again, there have been changes, with documented results not only on equity but on sustainable management of environmental resources. 67 For example, in Europe local authorities in jurisdictions with the highest recycling rates had a higher than average percentage of female managers. 68 And extensive fieldwork in India has documented that active participation by women in community forest management significantly improved forest protection. 69
Community management
For climate change and other global environmental problems, procedural justice implies an equal opportunity for all countries to affect international negotiations, but weak capacity often means that few developing country governments are represented
Chapter 4 illustrates the growing recognition of the benefits of community management of natural resources. To ensure that such approaches do not exclude poor people, women, the elderly and other marginalized groups, governments and other organizations that sponsor community-based projects need to involve all groups in decision-making and implementation. For example, initiatives to mentor community forest groups in Nepal sensitized them to issues of equity and participation, ultimately increasing the participation and influence of women and the poor.70 Where women and other marginalized groups are included in community decisionmaking, the benefits can be substantial. For example, Bhutanese community forests have the dual purpose of engaging locals in managing forests and regulating access to forest resources for sustainable livelihood activities. Enabling access to fuelwood, which benefits women more than men, is one benefit of this approach. Household surveys of Bhutanese communities have found that poorer households and female-headed households were
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usually assigned a larger share of trees than richer households, and women were able to collect more fuelwood from community forests.71 * * * In sum, implementing a joint equity–sustainability approach at the national level involves integrating equity into policy and programme design and evaluation, bolstering empowerment through legal rights and corresponding institutions, and promoting greater participation and accountability.
Development assistance reaches only 1.6 percent of even the lower bound estimate of needs for low-carbon energy and around 11 percent for climate change
Financing investment and the reform agenda
Policy debates about sustainability raise major questions about investment and financing, particularly on how much is needed, who should have access and who should be responsible for financing what. Development finance constrains the equitable transition to a global green economy in two ways. First, it falls far short of global requirements. Second, countries and sectors have unequal access, so they do not always receive the financing they need to address environmental deprivations; the poorest countries often miss out. Global capital markets, with some $178 trillion in financial assets, have the size and depth to step up to the challenge.72 Over the medium to long term, and with sufficient public sector support, the United Nations Environment Programme estimates that private investment in clean energy technologies could reach $450  billion by 2012 and $600 billion by 2020.73 The Global Environment Facility’s experience suggests that private investment can be substantial: public funding for climate mitigation has leveraged private investment by 7 to 1 or more.74 This leveraging requires public efforts to catalyse investment flows, by developing an appropriate investment environment and building local capacity. These issues are covered in depth in a recent UNDP report that highlights policies for building developing country capacity to mobilize the public and private investment flows needed to finance the transition towards a low-emission,
climate-resilient society.75 Medium-term plans, budgets and investments can be a foundation for consolidating good intentions and providing cross-sectoral mechanisms for effective coordination across donors and government agencies. Lively debates about the future of official development assistance continue. While recognizing the growing importance of private flows and the likelihood that aid will shrink as a share of development finance for most countries, rich countries must not shirk their responsibilities. Strong equity arguments warrant substantial transfers of resources from rich countries to poor to meet equity goals and guarantee equal access to financing. And strong economic arguments support measures to solve global collective action problems, such as climate change.
Where does the world stand?
Although evidence on global needs 76 and official aid commitments and disbursements is patchy and magnitudes are uncertain, the overall picture is clear. Development assistance reaches only 1.6 percent of even the lower bound estimate of needs for low-carbon energy and around 11 percent for climate change (figure 5.2). These numbers are slightly better for water and sanitation, where aid commitments are more than twice the lower estimate of needs and close to 20 percent of the upper estimate. Access to financing is uneven and generally correlated with a country’s level of development. Many resources go to the countries developing fastest. Low-income countries account for a third of the 161 countries receiving Global Environment Facility allocations, but they receive only 25 percent of the funding (and least developed countries, only 9 percent).77 In 2010, under the Climate Investment Funds, Mexico and Turkey accounted for about half the approved project funding in clean technology.78 Evidence also suggests that the resources have been allocated less equally over time.79
What development assistance can do
Official development assistance is a vital source of external finance for many developing countries. Recent years have seen much progress in increasing the quality and quantity of official aid, which rose some 23 percent from 2005 to 2009.
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But the contributions still do not meet the world’s development challenges. The $129 billion committed in 2010 was 76 percent of the estimated cost of achieving the Millennium Development Goals—and not all aid goes to achieving the goals.80 Rich countries have consistently failed to meet their stated pledges, including that of the G-8 at Gleneagles in 2005 (to increase aid by $50 billion a year by 2010), the European Union (to increase aid from 0.43 percent of gross national income to 0.56 percent) and the United Nations (the long-standing target of 0.7 percent of gross national income). Developed countries have pledged $100 billion a year by 2020 to finance climate change mitigation and adaptation in developing
FIGURE 5.2
countries. It is unclear, however, whether the funding would really be additional—one concern is that current aid will simply be diverted to meet the new targets. 81
Access to energy and climate change investments
As this Report has already noted, providing clean energy to the 1.5 billion people who lack electricity and the 2.6 billion who rely on traditional biomass for cooking is a major winwin-win. Clean energy offers the potential to alleviate poverty, reduce health impacts from indoor air pollution and drive social and economic development, while mitigating energy’s impact on the climate.
Official development assistance falls far short of needs
Estimated future needs and existing official development assistance (ODA) Annual expenditures ($ billions)
1,500
High estimate of need
1,000
ODA commitments and disbursements, 2010
($ billions) 50 500 40 30 20 10
Low estimate of need
ODA commitments ODA disbursements
ODA
50 0 0
Climate change
2010–2030
Low-carbon energy
2010–2035
Water and sanitation
by 2015
Climate change
Low-carbon Water and energy sanitation
Source: Based on data from IEA (2010), UN Water (2010a), UNDESA (2010a) and OECD Development Database on Aid Activities: CRS online.
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though large, the amounts needed to address climate change are below current spending on defence, on recent financial sector bailouts and on perverse subsidies, indicating the scope for reassessing priorities
International financial institutions have overseen sweeping reforms of the energy sector in many parts of the world, with a view to opening markets and guaranteeing equitable access to funds. And countries have positioned themselves to mobilize and attract private investments to the energy sector. But policymakers have yet to steer energy finance towards tackling energy poverty82 or climate change on a larger scale, especially in places less attractive to the private sector. Redirecting energy finance will require greater political will and exceptional leadership. Moreover, addressing energy poverty needs to stay at the head of the agenda because doing so is central to maintaining public support and development assistance for achieving the Millennium Development Goals and beyond. A key dimension of climate policy discussions relates to the size, direction and source of financing. The World Bank recently outlined the difficulties in tracking such investments, including limited and inconsistent information in reporting systems, the ambiguous purpose of some flows, the confidential nature of some transactions and double counting. 83 Costing is difficult, in both theory and practice, and the scope of the estimates differs along with the methods. Underlying assumptions matter—especially those regarding the discount rate. So do assumed consumption and production elasticities to changing prices. With these caveats in mind, we review the available evidence and find: • Recent estimates of the investments needed to reduce the concentration of greenhouse gases (mitigation costs) range widely, from 0.2 percent of annual global GDP to 1.2 percent by 2030.84 • Estimating adaptation costs is even harder, and it is difficult to distinguish them from related development investments. This Report’s updated estimates of annual investment requirements for adaptation are of the order of $105 billion,85 within the $49–$171 billion range proposed by the United Nations Framework Convention on Climate Change by 2030. Other estimates, which account for the costs of adaptating to
the impact of climate change on ecosystems, are two to three times higher.86 • Estimates of total annual mitigation and adaptation costs to address climate change by 2030 range from $249 billion to $1,371 billion. Why the large difference? Because the costs of integrating renewable energies are context- and site-specific and thus difficult to estimate globally. The amounts needed are clearly large, if uncertain. But they are below current spending on defence, on recent financial sector bailouts and on perverse subsidies, indicating the scope for reassessing priorities. In 2009 global military expenditure neared 3 percent of world GDP, while some countries spent much more, including the United States (4.7 percent of GDP) and the Russian Federation (4.3 percent of GDP).87 The bailouts in the wake of the recent financial crisis were close to $700 billion in the United States under the Troubled Asset Relief Program, while EU commitments were close to $1 trillion (about 6  percent of annual GDP in both cases). As the previous chapter shows, there is enormous scope for reducing environmentally harmful subsidies. Uzbekistan, for example, spends over 10 times more on fossil fuel consumption subsidies than on health (32 percent of GDP, compared with 2.5  percent), while Iran spends 20 percent of GDP on fossil fuel consumption subsidies, compared with less than 5 percent on education. 88 Are developed countries meeting the financing commitment implied by their “common but differentiated responsibilities” under the Framework Convention on Climate Change? No. Almost $32 billion has been pledged for climate change actions (about 19 percent of total official development assistance).89 But the pledges fall well short of estimated needs, and disbursements fall well short of pledges: most of the “new and additional” funds pledged at the 2009 UN Climate Change Conference in Copenhagen have not been delivered, and less than 8 percent of pledges for climate change were disbursed in 2010. Governments have yet to agree how to track spending or determine whether funding is truly additional—accurate monitoring requires an aid baseline.
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Some 24 special climate change funds already exist, ranging from international sources of funding such as the Hatoyama Initiative (which has received 48 percent of total pledges to date—35 percent from public sources and 13 percent from private sources) to national trust funds that can receive donor funds, such as the Indonesia Climate Change Trust Fund (0.06 percent of pledges). The funds differ in structure and include both bilateral and multilateral arrangements, making reliable monitoring of spending very difficult. Given this fragmentation, climate finance must incorporate the lessons of aid delivery to improve how assistance is organized and delivered. The 2005 Paris Declaration on Aid Effectiveness and the 2008 Accra Agenda for Action agreed on principles to promote country ownership, aid alignment and harmonization, results, and mutual accountability. The 2007 Bali Action Plan shows how these principles can be incorporated into climate change finance. This state of affairs does not imply that there should be one global superfund, which is neither feasible nor desirable, but it did show the scope for reducing complexity and enhancing access and transparency. Equally important is avoiding parallelism in funding, as far as possible, instead integrating provisions for climate change in national planning and budgets.
Water supply and sanitation
For 20 developing countries reporting drinking water and sanitation expenditures, GLAAS 2010 estimates median government domestic spending at $65 million in 2008 (0.48 percent of GDP). For 2009, the most recent year with data, aid commitments totalled $14.3 billion and disbursements $7.8 billion. Investor belief that the water and sanitation sector in developing countries is a highrisk, low-return investment makes marketbased financing difficult to mobilize. And while reforms in governance, institutions and tariffs are critical to the sector’s financial sustainability, innovative schemes are bridging the financing gaps in the interim (box 5.2).91 Again, greater efforts are needed. Government clearly is important, but reliance on financial aid is high, covering much national spending on sanitation and drinking-water —in some countries, near 90 percent. And even with cost-effective innovative approaches, as in community sanitation, public commitment is too low. Refocusing assistance is called for, alongside mobilizing more domestic and private resources for scaling up investments. Although the gap in aid allocations between high HDI and low HDI countries is smaller for water and sanitation than for low-carbon energy, the disparities are still large. Part of the constraint relates to capacity, though more predictable donor funding would help.92
BOX 5.2
How much will it cost to meet the Millennium Development Goal targets for safe drinking water and basic sanitation? Assessments depend on baseline and demographic assumptions and on whether they include maintenance costs and use low-technology options. Moreover, definitions of “water supply” and “basic sanitation” differ, and consistent data are often lacking. The 2010 Global Annual Assessment of Sanitation and Drinking Water (GLAAS) estimates for achieving the Millennium Development Goal water and sanitation targets, which take several earlier cost estimates into account, range from $6.7 billion to $75 billion a year.90 Much more would be needed to achieve universal access. The amounts now being spent from domestic and international sources are much lower.
Innovative financing schemes for water and sanitation
A review of financing schemes to promote investment in water and sanitation reveals some promising new avenues. Some schemes supported by donors encourage private investment. Indonesia’s Master Meter Scheme uses microcredit to connect the urban poor to water, and the Coca-Cola Company and the United States Agency for International Development sponsored the installation of locally made rope pumps in Zinder, Niger. In Kenya an innovative combination of commercial finance (through a microcredit institution) and a subsidy that ties public funding to achieving specified goals has improved water supply and connected poor households to piped water. Other financing schemes include blended grants and repayable financing (as funded by the World Bank in Senegal and the European Investment Bank in Mozambique), revolving funds for water and sanitation (as funded by the World Bank, Denmark and Finland in Viet Nam and by UFUNDIKO, a small nongovernmental organization, in Tanzania) and pooled funds (as in Tamil Nadu, India), which disbursed bond-issue funds to municipalities as subloans. Market-based finance is also becoming more common. For instance, several US cities and Johannesburg, South Africa, have used municipal bonds to fund water infrastructure.
Source: Nelson 2011; Coca-Cola Company 2010; World Bank 2010a; International Water and Sanitation Centre and Netherlands Water Partnership (2009); OECD 2010c.
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Social protection
the prime candidate to close the financing gap is a currency transaction tax
Estimates put global allocations to social protection at a sizeable 17 percent of GDP.93 But much of this spending bypasses the most disadvantaged groups. High-income countries spend on average nearly 20 percent of GDP, while low-income countries spend around 4 percent.94 Clearly, there is enormous scope for increasing the coverage of social protection schemes in the poorest countries, as part of national and global efforts. It makes sense, then, to take these needs into account in discussions on financing the sustainability and equity agenda. Setting a social protection floor—a set of essential social transfers, in cash and in kind, to provide a minimum income and secure livelihood—is promising. Such programmes need not be expensive. Brazil’s Bolsa Familia and Mexico’s Oportunidades cost their governments about 0.4 percent of GDP and cover about a fifth of their populations. India’s Mahatma Gandhi National Rural Employment Guarantee Act cost about 0.5 percent of GDP in 2009 and benefited 45 million households, about a tenth of the labour force.95 For several African and Asian countries the International Labour Organization (ILO) estimated in 2008 that a scheme guaranteeing workers 100 days of employment a year could cost less than 1 percent of GDP on average.96 The ILO estimates that less than 2 percent of global GDP would provide all the world’s poor with a minimum package of social benefits and services—defined as access to basic healthcare, basic education and basic income transfers in case of need.97 Broadening the scope to include adaptation to climate change by bolstering local resilience and supporting livelihood diversification strategies would cost more.98 Based on admittedly heroic assumptions, this could increase the cost to a still manageable 2.5 percent of global GDP.99 * * * In sum, the financing challenges loom large, but there is cause for optimism. The priorities for governments around the world are clear: • Ensure that appropriate institutional and regulatory features are in place to enable
scaling up private investments, especially in poorer countries, which have largely missed out on private finance. • Have all governments re-examine their spending priorities so that sustainability and equity objectives are well reflected in budget allocations. • Mobilize additional resources to narrow the large gaps in addressing the environmental deprivations facing billions of poor people around the world and to solve the major global collective action problem presented by climate change. • Ensure that national and community partners have the capability to define policies and budgets and implement programmes that promote and support sustainability, equity and inclusiveness.
innovations at the global level
Environmental sustainability and equity challenges have major implications at the global level, including for financing and governance, the two key areas addressed here.
Innovative new sources to meet the financing gap
As outlined above, massive new investments are needed to avoid business-as-usual trajectories, but sufficient funding has not been forthcoming, especially for poor countries. And the fiscal outlook is difficult. Many government budgets are under pressure in the wake of the 2008 global financial crisis and given longer term structural problems, while climate change is intensifying the development challenges facing poor countries. Domestic commitments are important, though the scale of the investments needed suggests that more international public funds will be required to attract large additional private funds. It follows that innovative sources of financing are vital, alongside stronger commitments and concrete actions from developed countries. The prime candidate to close the financing gap is a currency transaction tax. Originally proposed and promoted in the 1994 Human Development Report (HDR), the idea is increasingly being accepted as a practical
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policy option. What is new today is its greater feasibility. The infrastructure for global realtime settlements, introduced after the most recent global financial crisis, makes it straightforward to implement. The foreign exchange settlement infrastructure is now more organized, centralized and standardized (box 5.3). Recent innovations—notably real-time gross settlement and measures to reduce settlement risk—mean that existing systems now capture individual transactions. The tax can be a simple proportional levy on individual foreign exchange transactions assessed on foreign exchange dealers and collected through existing financial clearing or settlement systems. Because the financial infrastructure is now in place, a currency transaction tax can be implemented relatively quickly and easily. The tax has high-level endorsement from the Leading Group on Innovative Financing for Development.100 Belgium and France already have legislative frameworks in place for instituting a currency transaction tax. And Brazil, Chile, Japan, Norway and Spain have started to move in that direction. The tax also enjoys broader support from nongovernmental stakeholders, such as the Bill and Melinda Gates Foundation and the Citizen’s Coalition for Economic Justice. Such a tax could address a major anomaly in the financial sector: many of its transactions are not taxed.101 That, along with the large scale of financial activity, makes a strong case for a small levy on foreign exchange transactions to fund global public goods, such as mitigating and adapting to climate change in poor countries. The incidence of the tax would be progressive, as the countries with larger currency transactions tend to be more developed. The allocation of revenues should also be progressive, as discussed below. Distributional issues, such as a potential minimum tax threshold, need to be considered, so as not to unduly burden individual remittance transfers. Such details need to be examined during design and monitoring. The tax could also substantially reduce the macroeconomic volatility caused by the high volume of short-term speculative funds flowing through world financial markets.
Appropriately designed and monitored, the tax would allow those who benefit most from globalization to help those who benefit least— and help finance the global public goods that can sustain globalization. The tax rate should not impose too heavy a burden but should reduce speculative flows. Estimates of revenue generation depend on, among other things, assumptions about the effect of the tax on trading volumes. In updated analysis prepared for this Report, the North–South Institute estimates that a tax of 0.005 percent would yield around $40 billion a year.102 The revenue potential is thus huge. The Center for Global Development estimates donor spending on global public goods at around $11.7 billion in 2009. The bulk of the spending is on UN peacekeeping; excluding this important function lowers global public good expenditure to about $2.7 billion.103 The currency transaction tax would mobilize nearly 15 times as much each year. Even a unilateral currency transaction tax (limited to the Euro) could mobilize $4.2–$9.3 billion in additional financing. Clearly, then, a currency transaction tax could, even under very
BOX 5.3
The currency transaction tax: newfound feasibility
Today, there are many ways to trade foreign currency in the wholesale market: on an exchange, online, through a human or electronic broker or by phone or fax. But there are just two ways to make the payments to settle a deal. One is by sending both payments to a continuous linked settlement bank, which matches and exchanges them simultaneously. The other is by sending them to the Society for Worldwide Interbank Financial Communication (SWIFT), where they are matched and then forwarded to the correspondent banks in the two currencyissuing countries. These two highly organized clearing and settlement systems are the core infrastructure of today’s foreign exchange industry. They keep detailed records of nearly every foreign exchange transaction around the world. How would a tax work? SWIFT keeps itemized records of the details of global foreign exchange trading activity in the world’s frequently traded currencies as it clears or settles foreign exchange transactions. A copy of the transaction details would be sent to the usual tax authority or its agent. The authority would calculate the tax due from each trader and add it to a running tally. Traders would pay their currency transaction tax obligations to the tax authority periodically. Incentive and compliance issues are surmountable. It is unlikely that trading banks would opt out of SWIFT’s communications platform to avoid paying the tax. Doing so would cost more than the tax. Further, there are only a few large traders in the wholesale market for foreign exchange, so they could easily be audited for tax purposes. There would be no intrusion on individual privacy, because the currency tax would be assessed on the large banks, investment funds and corporations participating in the wholesale foreign exchange market.
Source: Schmidt and Bhushan 2011.
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any truly transformational effort to scale up climate change mitigation and adaptation will require blending resources—domestic and international, private and public, and grant and loan
conservative assumptions, dramatically scale up global public good expenditure. This is also an occasion to reconsider a broader financial transaction tax. The International Monetary Fund (IMF) recently pointed out that many G-20 countries have already implemented some form of financial transaction tax.104 While the revenue potential depends on the tax’s design and the response of traders, a broad-based, low-rate financial transactions tax of 0.01–0.05 percent could generate nearly €200 billion a year at the European level and $650 billion at the global level.105 Other estimates suggest that in the United States alone the tax could raise more than 1 percent of GDP (about $150 billion in 2011), even with very substantial reductions in trading volume.106 Taxes on currency and financial transactions would not have prevented the recent financial crisis, which originated in the United States and spread to the rest of the world. But in addition to the revenue potential, such taxes are tools for discouraging the short-term reckless behaviour that drove the global economy into crisis. Transaction taxes need not be the only instrument to close the financing gap. Using the IMF’s Special Drawing Rights (SDRs) for innovative financing and climate change adaptation is another avenue worth exploring.107 Monetizing part of the IMF’s surplus could raise up to $75 billion at little or no budgetary cost for contributing governments.108 IMF analysis of the possible role of SDRs as seed finance for a new global green fund suggests that issuing additional SDRs and other reserve assets could mobilize $100 billion a year by 2020. The SDRs have the added appeal of acting as a monetary rebalancing instrument; demand is expected to come from emerging market economies looking to diversify their reserve holdings. Because the SDR is not a sovereign currency, it would not be subject to the currency transaction tax, thus avoiding double taxation. Several public and private sources could also be tapped to close the financing gap. Already, innovative financing instruments— such as the Clean Technology Fund and the Strategic Climate Fund—are blending funding from multilateral development banks, governments, climate finance instruments and the
private sector. They have raised an additional $3.7 billion for development and can leverage substantial additional funds.109 Considerable private funding has also been leveraged.
Ensuring equity and voice in governing and in access to finance
Bridging the gap separating policy-makers, negotiators and decision-makers from the people most vulnerable to environmental degradation requires closing the accountability gap in global environmental governance. Accountability alone cannot meet the challenge, but it is fundamental for building a socially and environmentally effective global governance system that delivers for people. Private resources are critical, but because most financial flows into the energy sector, for example, are private, the greater risks and lower returns of some regions of the world affect the patterns of flows. In the absence of reform, access to financing across countries will remain unevenly distributed, and indeed add to existing inequalities.110 This underlines the importance of ensuring that flows of public investments are equitable and create conditions to attract future private flows. Failing to ensure equitable access to climate finance would also constrain the capacity of industries to capitalize on low-cost opportunities to improve efficiency and reduce greenhouse gas emissions cost-effectively. The building sector, for example, could not take advantage of cost-effective energy efficiency improvements. This is particularly important over the next 5–10 years as low-income countries invest in long-lived power generation and urban infrastructure. Limited access to climate financing would lock these countries into high-emission development paths, constraining the world’s capacity to limit increases in global temperature. The implications are clear. Principles of equity should guide and encourage international financial flows. Support for institution building should help developing countries establish appropriate policies and incentives. And the associated governance mechanisms for international public financing must allow for voice and social accountability.
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Any truly transformational effort to scale up climate change mitigation and adaptation will require blending resources—domestic and international, private and public, and grant and loan. To facilitate both equitable access and efficient use of international financial flows, this Report advocates empowering national stakeholders to blend climate finance at the country level. Bringing about long-term, efficient results and accountability to local populations and partners will require four sets of tools (figure 5.3): • Low-emission, climate-resilient strategies —to align human development, equity and climate change goals. • Public-private partnerships—to catalyse capital from businesses and households. • Climate deal-flow facilities—for equitable access to international public finance. • Coordinated implementation and monitoring, reporting and verification systems. Most climate control activities today are discrete and incremental mitigation or adaptation projects. But broader strategic approaches are also needed. Low-emission, climateresilient development strategies could prove a critical institutional innovation for incorporating equity and climate change into development planning. Involving all stakeholders, such strategies can help manage uncertainty by identifying development trajectories resilient to a range of climate outcomes. These strategies can incorporate priorities for win-win mitigation and adaptation initiatives. And they can assess the policy changes and capacity development required to implement them.111 A comprehensive strategy to attract investments in green and equitable development must come to grips with the large distortions in energy markets—in favourable tax treatment, regulatory privileges and legacy monopolies. The investment climate can be improved by reducing risks (say, through greater policy predictability or guarantee instruments) and increasing rewards (say, through tax credits).112 Strategies need to involve municipalities: since cities account for the majority of greenhouse gas emissions, actions by subnational governments will be key to reining in temperature change. This calls for coordinated
planning and robust collaboration with a variety of traditional and new development actors, including national and regional technical centres of expertise, the private sector, communities and civil society organizations. A second key institutional innovation could be market-making public-private partnerships. These partnerships aim at market transformation and apply to both climate change mitigation (renewable energy technologies, energy efficiency appliances and the like) and adaptation (weather indices, climateresilient agricultural commodities, climateresilient buildings and the like). They would build on recent experience but go beyond traditional service delivery and infrastructure to bring together the potentially diverging interests of a wide range of stakeholders and blend various sources of finance. The public policies and measures underlying such partnerships will need to provide incentives and support to improve the risk and reward profile of climate investments, consistent with national development goals. The third set of tools involves establishing climate deal-flow facilities to help national and subnational project proponents assemble bankable projects and tap international public climate finance. Carbon finance, as in the Clean Development Mechanism, has shown that limited capacity to prepare bankable projects can be a major barrier to catalysing private climate finance in many locations. Similarly, the complexity of application and reporting requirements for international public funds makes it difficult to determine eligibility and appropriateness, posing obstacles to use, monitoring and evaluation. So, the climate deal-flow facilities should enhance the capacity of countries to gain access to international sources of both private and public finance. The fourth set of tools in the proposed framework for equitable and efficient climate finance addresses the need for coordinated implementation and reporting. Climate finance on a scale sufficient to rein in temperature changes to 2°C demands unprecedented efforts to implement, monitor, verify and report—over several decades, with multiple actors, diverse sets of actions and a variety of
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FIGURE 5.3
Key elements in transforming climate financing efforts
Low-emission, climate-resilient development strategies
Market-making public-private partnerships
Climate deal-flow facility
Implementation and reporting instruments
Source: Adapted from Glemarec and others 2010.
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financing sources. National climate funds can facilitate the operational blending and monitoring of domestic and international, private and public, and grant and loan resources— essential to ensuring domestic accountability and positive distributional effects.
Enabling universal access to energy
It is time to launch a high-profile global initiative for universal access to energy in developing countries
Central to moving to universal access in energy is addressing the barriers to investing in clean energy. While potentially earning an attractive return, most technologies for renewable energy and energy efficiency require substantial upfront investment. Even if offset by lower operational costs, these upfront capital costs can be prohibitive. The financial constraints that businesses and consumers face are often more severe than those implied by national discount rates or long-term interest rates. And they are usually compounded by behavioural, technical, regulatory or administrative barriers. Take wind power: no country will attract private investment if independent power producers face barriers in access to grids, uncertain licensing processes, limited local expertise or lack of long-term price guarantees. Achieving universal energy access requires a response strategy on multiple levels from various partners—here again, there is no onesize-fits-all solution. National and local governments must set the stage for other players ranging from civil society and the private sector at the national and subnational levels to global finance and energy companies. It is time to launch a high-profile global initiative for universal access to energy in developing countries. It could have two parts: first, a global advocacy and awareness-raising campaign; second, investments on the ground through dedicated support to sectoral approaches in clean energy. Together, they can kick-start a shift from incremental to transformative change. A global campaign to promote a participatory and informed initiative, key in both donor and developing countries, can harness existing capacities for advocacy, analysis, planning, knowledge management and communications.
The time is right for such a campaign. The UN General Assembly has designated 2012 as the International Year of Sustainable Energy For All while the Rio+20 conference will provide a unique opportunity to define a global approach for universal access to energy, bringing together the energy, green economy and climate agendas. This global approach can then be developed through regional and national energy dialogues. Complementing the campaign, support to developing countries for climate-resilient development strategies could identify barriers, benefits and impacts for disadvantaged groups—and create favourable investment conditions. Major market failures heighten the importance of public policies to attract private finance. Such policies can improve clean energy investment risk-reward profiles by reducing risks (stable regulatory context, local supply of expertise, streamlined administrative arrangements, guarantee instruments and the like) and by increasing rewards (premium prices, tax credits and the like). For example, a commercially unattractive renewable energy investment could become profitable by guaranteeing independent power producers access to the grid and a price premium. Support from the Universal Energy Access Initiative could include assistance for determining priority energy access technologies, ideally in the context of formulating a lowemission, climate-resilient strategy; identifying key barriers to technology diffusion; selecting an appropriate mix of policy instruments to remove barriers; and accessing funding options to deploy the selected mix of policies. * * * This Report calls for a new vision that jointly considers equity and environmental sustainability. It elaborates ways to attain synergies between the two objectives that are crucial for shaping our understanding of how to move forward and guide policy. Taking up this challenge will expand choices for people today and in the future—the hallmark of human development.
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notes
Chapter 1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 UN 2002, 2010. Sen 2003: 330. Weikard (1999) as cited in Scholtes (2011). Scholtes 2011. 1990 HDR: 38 (UNDP–HDRO 1990; see inside back cover for a list of HDRs). 1994 HDR: 19 (UNDP–HDRO 1994; see inside back cover for a list of HDRs). 2010 HDR: 2; emphasis added (UNDP–HDRO 2010; see inside back cover for a list of HDRs). WCED 1987: 57–59; emphasis added. Solow 1973. USEIA 2008. Commission on Sustainable Development 1997, paragraph 12. Baumol, Litan and Schramm 2007. FAO 1996. UNDESA 2011a. Brown and others 2001. On strong sustainability, see Barbier, Markandya and Pearce (1990) and Ross (2009). Daly 2005. UNEP 2011; OECD 2010a. UNDESA 2011a. Perrings and Pearce 1994; Barbier, Burgess and Folke 1994. See Nordhaus (2004), who estimates a slowdown of 0.86 percent a year. Babbage 2010. See Weitzman (2009a), Stern and Taylor (2007), IPCC (1997), and Dietz and Neumayer (2007). Weitzman 2009b. This stands in contrast to the Stern Review’s proposal of a long-term discount rate of 1–2 percent (Stern 2007), itself much lower than commonly used rates of 4–5 percent. Solow 1993: 168. Economists have defined sustainability in terms of living standards, consumption or utility. Consumptionbased definitions are favoured by advocates of weak sustainability, such as Dasgupta and Heal (1974), Hartwick (1977) and Solow (1974). Utility-based definitions, such as that offered by Neumayer (2010a), consider a path to be sustainable if people become progressively more efficient at attaining greater utility. Anand and Sen 1994, 2000; Sen 2010. The concept originated in the work of Adams (1965), Homans (1961) and Blau (1964). Rawls 1971. The priority of poverty eradication in the search for sustainable development has been reaffirmed in several UN declarations, including the 1992 Rio Declaration on Environment and Development (UN 1992), the resolution on the Programme for the Further 32 33 34 35
Implementation of Agenda 21 (UN 1997) and the 2002 Johannesburg Declaration (UN 2002). Anand and Sen (2000: 2,038), emphasis in original. Of course, some policies can be neutral in impacts, but these are omitted for simplicity. See Brown (2003). A caveat arises for solutions not in quadrant 1 because major improvements in one dimension cause small deteriorations in the other. Would any solution that improves both dimensions slightly be preferred? It can be argued that a policy that improves both dimensions should be preferred only if it benefits groups that are objectively worse off. In other words, a policy that enhances sustainability but worsens equity should be preferred only if the most disadvantaged future generations that will benefit from the change would have been worse off than the poorest today.
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Chapter 2
1 2 3 2010 HDR: chapter 2 (UNDP–HDRO 2010; see inside back cover for a list of HDRs). On this issue, see UNECE (2011) for a recent review. The ratio of per capita greenhouse gas emissions in very high to those in low, medium and high HDI countries was 3.7 in 1990 and 3.3 in 2005. Underlying the small drop in the ratio, total greenhouse gas emissions have grown much faster in developing countries, partly because of their faster population growth. The differences are 4.4 times for carbon dioxide emissions, 1.3 times for methane and 2.1 times for nitrous oxide. The strong correlations between both the levels and changes in environmental impacts and the HDI also suggest that the link between these two phenomena has not changed much over time. This contrasts, for example, with life expectancy and income, where levels but not changes are correlated, indicating changes over time in the underlying processes. See 2010 HDR (UNDP–HDRO 2010; see inside back cover for a list of HDRs) and Georgiadis, Pineda and Rodríguez (2010). Grossman and Krueger 1995. Hughes, Kuhn and others 2011. Grossman and Kruger (1995) suggested a peak, in most cases, before a country reached a per capita income of $8,000 (in 1985 dollars). Other studies have identified different thresholds. See statistical table 6. Gross national income (GNI) per capita data are from the World Bank (http:// data.worldbank.org/indicator/NY.GNP.PCAP.PP.CD). See statistical table 6. An exogenous variable is independent of the state of other variables in a causal model—that is, its value
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is determined by factors outside the causal system examined (Wooldridge 2003). Doubling net forest depletion as a percentage of GNI increases overall inequality 2 percent (or 0.42 percentage point), while doubling particulate emission damage as a percentage of GNI increases overall inequality by a massive 26 percent (or 5.6 percentage points). The number of years since women received the formal right to vote and the contraceptive prevalence rate are instruments for the Gender Inequality Index (GII). In particular, a 10 percent increase in gender inequality (measured by the GII) leads to a 1.13 point (or 150 percent) increase in net forest depletion as a percentage of GNI. For details on the method and results, see Fuchs and Kehayova (2011). The IHDI is a measure of the average level of human development in a society once inequality is taken into account. It captures the HDI of the average person in society, which is less than the aggregate HDI when there is inequality in the distribution of health, education and income. Under perfect equality, the HDI and IHDI are equal; the greater the difference between the two, the greater the inequality. See Alkire and Foster (2010). As we reviewed in last year’s report, global inequality across people is an important measure, but most studies are limited to income. Almost all agree that inequality is high, though there is no consensus on recent trends (Anand and Segal 2008). Sala-i-Martin (2006), providing estimates for 1970–2000 by integrating the income distributions of 138 countries, found that mean per capita incomes had risen, but inequality had not. Other studies—such as Milanovic (2009)—concluded the opposite. Still others—such as Bourguignon and Morrisson (2002)—found no change. Pradhan, Sahn and Younger 2003. O’Donnell and others 2008. This is consistent with earlier studies (for example, Neumayer 2003 and Becker, Philipson and Soares 2003). Becker, Philipson and Soares monetize life expectancy and create a measure of “full” income— which rose 140 percent in developed countries from 1965 to 1995 and 192 percent in developing countries. 2010 HDR: 32 (UNDP–HDRO 2010; see inside back cover for a list of HDRs). Other studies have highlighted similar points; see, for example, McGillivray (2011). According to the 2010 HDR (UNDP–HDRO 2010; see inside back cover for a list of HDRs), primary completion rates have risen from 84 percent in 1991 to 94 percent today. Expected years of schooling have also risen —from 9 years in 1980 to 11 years today. Hertz and others 2007. For example, in a study over 1960–1995, Checchi (2001) found that inequality in years of schooling
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remained almost constant at low levels in Organisation for Economic Co-operation and Development countries, despite increases in average education attainment. Atkinson, Piketty and Saez 2011. HDRO calculations based on data from Milanovic (2011). We include a group of 29 developed countries for which we have income inequality observations for 1990, 1995, 2000 and 2005. OECD 2011a. OECD 2010a. HDRO calculations based on data from Milanovic (2011) and Lopez-Calva and Lustig (2010: 10). Lopez-Calva and Lustig 2010. OECD 2010a. Hughes, Irfan and others 2011. Not only does the logarithmic term on income contribute mechanically to such slowing, so does the inevitable slowing of rising years of formal education, of advances in life expectancy in better off countries, and of convergence of low- and middle-income countries as their health and education gaps with rich countries narrow. Environmental risks are modeled with the Environmental Risks Scenario, developed by Hughes, Irfan and others (2011). Inequality and insecurity factors are modeled with the Security First Scenario, developed by the United Nations Environment Programme (UNEP 2007). This involves socioeconomic and environmental stresses, economic and personal insecurity, significant domestic and global inequality, high levels of protectionism, barriers to migration, and more militarism and conflict. Global warming potential measures the relative radioactive effect of a given substance. For the latest estimates, see IPCC (2007: chapter 2). Of the scientists publishing most actively in the field, 98 percent support the idea that climate change is caused by human activity (Anderegg and others 2010). While some studies have pointed to mistakes in the Intergovernmental Panel on Climate Change reports (Khilyuk and Chilingar 2006; Church and others 2008), none has seriously questioned its key conclusions. Raupach and others 2007. Aichele and Felbermayr 2010; Grether and Mathys 2009. Carbon dioxide can remain in the atmosphere for thousands of years, unlike methane, which lasts about 12 years, and nitrous oxide, which lasts about 114 years. See Archer and Broikin (2008) and IPCC (2007). See the Climate Analysis Indicators Tool of the World Resources Institute (http://cait.wri.org). Areas above the 45th parallel north and below the 45th parallel south experienced a 2.66°C increase in average temperature for November–April during the 2000s over that during 1951–1980; areas between the coordinates saw a 0.66°C increase. Cooper 2008. Very high HDI countries had a more than 2 percent decline in precipitation. For example, estimates show that rainfall is very likely (90 percent probability) to increase in high latitude areas and likely (66 percent probability) to fall in most subtropical regions and to increase in variability in equatorial areas (IPCC 2007; Dore 2005). Christensen and others 2007.
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The Intergovernmental Panel on Climate Change (IPCC 2007) projects increases of 0.18–0.59 metre under six scenarios, while other studies suggest that the increase could be as much as 2 metres. Ice thinning is expected to ultimately break up ice shelves, which is likely to accelerate sea level rise (Gregory and Huybrechts 2006; Jevrejeva and others 2006; Thomas and others 2004). Anthoff 2010. Wheeler 2011. Vankoningsveld and others 2008. Dasgupta and others 2009. These figures refer to climatological, hydrological and meteorological natural disasters, as estimated from the Centre for Research on the Epidemiology of Disasters Emergency Events Database: International Disaster Database. An event is classified as a disaster if it meets at least one of the following criteria: 10 or more people died, 100 or more people were affected, a state of emergency was declared or international assistance was requested. But data may not be fully consistent across countries. Population growth increases the number of people affected and thus the number of the events classified as disasters. See also Neumayer and Barthel (2011) on the effects of awareness and reporting bias. IPCC 2007. Changes in atmospheric moisture affect moisture absorption capacity, leading to a greater probability of intense precipitation and associated natural disasters. Knutson and others 2010. The numbers could also reflect people’s greater exposure to natural hazards (for example, settlement in previously uninhabited areas) and increased vulnerability. Wood, Sebastian and Scherr 2000. Two UN bodies—the Food and Agriculture Organization and the Secretariat of the United Nations Convention to Combat Desertification—produce estimates, but their approach has been criticized in academic circles; see Veron, Paruelo and Oesterheld (2006). Hanasaki and others (2008); UNEP (2009). World Water Assessment Programme 2009. Ball 2001. These shares are the total land area–weighted average for each HDI group. Estimates differ by method and data coverage: assessments based on satellite images in 2002 indicate 23 percent lower deforestation rates than those reported in FAO (2001). Source data from official or informal institutions are often inaccurate and incomplete, and detailed information is lacking on forest composition, maturity, disturbance, canopy cover and quality. See Grainger (2010). Some countries, such as Brazil, have made major achievements in reducing deforestation (www.undp.org/latinamerica/ biodiversity-superpower/). See Meyfroidt, Rudel and Lambin (2010). Bhutan and El Salvador have reportedly used more land abroad than they have reforested within their boundaries. Gan and McCarl 2007. Mayer and others 2005, 2006. Würtenberger, Koellner and Binder 2005. In 2007 annual average per capita consumption was 28.7 kilograms in developed countries and 9.5 kilograms in least developed countries (FAO 2010a).
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Data on current catch are from FAO Fisheries and Aquaculture Information and Statistics Service 2009; sustainable yield is from FAO (2005). FAO 2010a. FAO 2010a. For instance, Peru’s introduction of individual fishing rights over its anchovy fishery, the anchoveta, is cited as key to improving the sustainability of its fishing stock (Fréon and others 2008; Schreiber forthcoming). Grossman and Krueger 1995. McGranahan and others 2001. OECD 2010b. Bettencourt and others 2007. Dodman 2009. Lehrer 2010. See www.unesco.org/water/wwap/facts_figures/ basic_needs.shtml. Tachamo and others 2009; Pepper 2007. Urban pollution is defined as suspended particulates less than 10 microns in diameter (PM10), expressed in micrograms per cubic metre (World Bank 2011a). Calculations are based on urban population-weighted averages. See UNDESA (2006). The thresholds for greenhouse gases are total accumulated emissions over the next 50 years likely to keep temperature change within 2°C (1,678 gigatonnes), no deforestation and global fresh water withdrawals of 5,000 cubic kilometres a year, which we expressed in per capita terms for our analysis. There is considerable uncertainty and estimated variance around these thresholds in the scientific community. For more information on global environmental thresholds, see, for example Rockström and others (2009) and Meinshausen and others (2009). Greenhouse gas emissions combine 2005–2007 averages for carbon dioxide and 2005 data, the latest available, for methane, nitrous oxide and other greenhouse gases. Forest data from 2000 and 2010 are used to calculate deforestation. Total water withdrawals are based on averages from the 2000s, and data on improved water access are for 2008. Data on air pollution are averages over 2006–2008. Thresholds for the local impacts are regional medians. See statistical table 6 for data sources. The earliest observation from the 1990s and latest from the 2000s were used to calculate changes over time. However, Costa Rica is among the few countries in Latin America that has experienced an increase in income inequality during the last decade despite the growth boom that preceded the global economic crisis of 2008. Inequality in health and education fell over the same period. UNEP 2010.
Chapter 3
1 Ash and others 2010; Brulle and Pellow 2006; Pastor 2007; Sze and London 2008; United Church of Christ 1987. When the plant exploded in 1957, nearby ethnic Russians were evacuated and resettled, but the Tatar people were left to suffer the effects of contamination (Agyeman, Ogneva-Himmelberger and Campbell 2009).
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The shares of the population with access to an improved water source and improved sanitation are Millennium Development Goal indicators relating to environmental sustainability (goal 7). A household is considered deprived if it relies on dung, wood or charcoal for cooking; if it lacks access to clean drinking water (or if the water is more than 30 minutes away); and if it lacks improved sanitation (or shares it with other households). See Alkire and Santos (2010). Since last year’s HDR, these estimates were updated for 19 countries and presented for the first time for an additional 5. Countries with MPI data include 11 in the Arab States, 9 in East Asia and the Pacific, 23 in Europe and Central Asia, 18 in Latin America and the Caribbean, 5 in South Asia and 37 in Sub-Saharan Africa. There are 103 countries that have complete data on environmental deprivations—the descriptive analysis focuses on these countries. Data for the Arab States are not given because low poverty levels render the results potentially unreliable. These aggregates are for the 2000s; the survey dates span 2000–2010. Population data correspond to each country’s survey year here and in the following analysis. The MPI reflects deprivations across three dimensions, each weighted equally, and 10 indicators. For more details, see Technical note 4. However, low poverty may conceal poverty that exists subnationally. In Ghana, for instance, poverty is 10 times higher in Greater Accra than in Northern Ghana, and other countries also exhibit sharp area-based differences. And in Europe and Central Asia, groups such as Roma are likely to be much more deprived than national poverty measures would suggest. UNICEF Madagascar Water Sanitation and Hygiene 2007. The exercise was also carried out with controls for HDI group and regional fixed effects, but they were not jointly significant and thus were dropped. The total sample consisted of 73 country-year observations. Fifty-two country-year observations were not included in the exercise: those whose poverty was based on lower or upper bounds (see Alkire and Santos 2010), those missing an environmental indicator and those whose MPI value was less than 0.032 because the small number of poor people in these countries (less than 8.5 percent) makes the results potentially unreliable. The 30 countries missing nonenvironmental indicators were retained, but the analysis controlled for their absence. De Oliveira 2008. Hall and Lobina 2008. Da Costa, Cohen and Schaeffer 2007; De Oliveira and Laan 2010. UN Habitat 2003 Milton and others 2010; UNICEF 2010; Argos and others 2010. UNDP Water Governance Programme 2010. UNDP Water Governance Programme 2010. IMF 2004; statistical table 5; see also Djibouti on the Austro-Arab Chamber of Commerce’s Arab Countries Profile (www.aacc.at). See IDA at work: Nepal (http://go.worldbank.org/ TXVG8IJ8L0). Peru Ministry of Housing, Construction and Santiation 2006. IADB 2008.
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Meier and others 2010. World Water Assessment Programme 2006. The Spearman correlation is .6 for temperature anomalies (1951–1980, compared with 2000–2008). When we consider only those statistically significant changes, which could be interpreted as suggestive of climate change, the result is nearly unchanged. A weak negative correlation disappears altogether when we exclude Indonesia from the sample and when we consider only statistically significant changes over time for the full sample. For a recent review, see Skoufias, Rabassa and Olivieri (2011). Environmental risk factors include indoor smoke from solid fuel use; outdoor air pollution; inadequate water, sanitation and hygiene; solar ultraviolet radiation; climate change; lead; mercury; occupational carcinogens; occupational airborne particulates; and second-hand smoke (Prüss-Üstün and others 2008). World Bank 2008a. Prüss-Üstün and others 2008. Prüss-Üstün and others 2008. Estimates are based on 2004 WHO country health statistics. The use of solid fuels is a reliable indicator of exposure to indoor air pollution, but over time, as improved stoves and decent ventilation come into widespread use, the two will not be as closely correlated. Between 1990 and 2005 the percentage of urban households with access to gas increased from 19 percent to 82 percent (Vennemo and others 2009). Data based on 2004 WHO burden of disease data. Smith, Mehta and Maeusezahl-Feuz 2004. Shandra, Shandra and London 2008. Correlation = .82, p < .05. Fieldwork by the Oxford Poverty and Human Development Initiative (www.ophi.org.uk/policy/ multidimensional-poverty-index/mpi-case-studies/). Fieldwork by Indrajit Roy (www.ophi.org.uk/policy/ multidimensional-poverty-index/mpi-case-studies/). Kjellstrom and others 2006. Riojas-Rodríguez and others 2006. Blacksmith Institute 2007. On Hong Kong Special Administrative Region, China, see Wong and others (2008, 2010); on Shanghai, see Kan and others (2008), as cited in HEI (2010). Friends of the Earth 2004. Mitchell and Dorling 2003; Brainard and others 2002. Kruize and Bouwman 2004. Kockler 2005. Viel and others 2010; Laurian 2008. UN Water 2010a. Data are from Prüss-Üstün and others (2008). Prüss-Üstün and Corvalán 2006. UN Water 2010a. Data are from Prüss-Üstün and others (2008). Prüss-Üstün and Corvalán 2006. Prüss-Üstün and others 2008. World Bank 2008b. UN Water 2010a. For example, sexual violence can result when women have to relieve themselves in the open after nightfall (UN Water 2006). Costello and others 2009. Lindsay and Martens 1998. Hales and others 2002. Checkley and others 2000, 2004; Speelmon and others 2000; Lama and others 2004.
58 59 60 61 62 63 64 65 66 67 68 69 70
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Nelson and others 2009. Green, King and Morrison 2009; Galloway McLean 2010. King, Smith and Gracey (2009) review the literature. 2010 HDR: statistical table 13 (UNDP–HDRO 2010; see inside back cover for a list of HDRs). Independent Evaluation Group 2008. Daka and Ballet 2011. Khandker and others 2009a. Khandker and others 2009b. Flora and Findis 2007. Nankhuni and Findeis 2004. Senbet 2010. Ndiritu and Nyangena 2010. Walker 2010. FAO (2010b) data. “Economically active population” refers to the number of people constituting the labour supply and refers to all employed and unemployed people (including those seeking work for the first time). World Resources Institute 2005. Aside from smallscale agriculture, the collection of wild foods, materials and medicines are the main sources of environmental income. Pattanayak and Sills 2001. Vincent 2011; UNFPA 2009. IWGIA 2008. Sobrevila 2008. Sobrevila 2008. World Bank 2008c. Galloway McLean 2010. Hertel and Rosch 2010. For a review, see Nellemann and others (2009). Nellemann and others 2009. Millennium Ecosystem Assessment 2005. Fraser and others 2010. Yonghuan and others 2007. 2007/2008 HDR (UNDP–HDRO 2008; see inside back cover for a list of HDRs). World Bank 2009. Lobell, Schlenker and Costa-Roberts 2011. Lobell and others 2008. Nelson and others 2010. Thornton and others 2009. The Food and Agriculture Organization estimates that if gender access to productive resources were equal, yields would increase 20–30 percent and agricultural output would rise 2.5–4 percent on average (FAO 2010b: 5). Nellemann and others 2009. FAO 2010b. Ulimwengu and Ramadan 2009. Hertel, Burke and Lobell 2010. Ivanic and Martin 2008. Cranfield, Preckel and Hertel 2007. Jacoby, Rabassa and Skoufias forthcoming. See www.fao.org/forestry/28811/en/. FAO 2011. Agarwal 2010b: 37; FAO 2010b: 16. Mayers 2007. Vedeld and others 2004: meta-study examining 54 case studies (33 in Africa). Mitra and Mishra 2011. Yemiru and others 2010. Based on surveys covering 2002–2008 (Volker and Waible 2010). Similar findings are reached by Pattanayak and Sills (2001) for Brazil and McSweeney (2004) and Takasaki, Barham and Coomes (2004) for Honduras.
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120 121 122 123 124 125 126
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Agarwal 2010b. Arnold, Kohlin and Persson 2006. FAO 2010a. Allison and others 2009. Allison and others 2005. See also Allison and others (2009). Secretariat of the Pacific Community 2011. AUSAid and UNDP Pacific Centre 2008. Cinner, Daw and McClanahan (2009), a small scale study of 434 households, from 9 coastal villages, from which there were 141 fishers. Secretariat of the Pacific Community 2011. Cheung and others 2009. Iftikhar 2003. Afifi and Warner 2008; Boano, Zetter and Morris 2008. See, for instance, Miguel, Satyanath and Sergenti (2004), Hendrix and Glaser (2005), Boano, Zetter and Morris (2008) and Burke and others (2010). Calculated on the basis of Demographic and Health Survey and Multiple Indicator Cluster Survey data, most recent year available since 2000. These surveys are available for only a small number of countries because they are expensive and difficult to conduct. The questionnaires differ, so the resulting data are illustrative rather than strictly comparable. Agarwal 2010b: 36, table 2.1. Koolwal and Van de Walle 2010. Kramarae and Spender 2000. Ilahi and Grimard 2000. Wodon and Ying 2010. Blackden and Wodon 2006. To estimate the economic benefits of improvements in water supply, Hutton, Haller and Bartram (2006) assume that expanding access to water supply would save 30 minutes for each household per day. See www.sidym2006.com/eng/eng_doc_interes.asp. Boano and others 2008. UNHCR 2002: 12. Marchiori and others 2011. 2009 HDR: chapter 4 (UNDP–HDRO 2009; see inside back cover for a list of HDRs). UNEP 2009. Miguel and others 2004; Hendrix and Glaser 2005; Raleigh and Urdal 2008; Fiola 2009; Burke and others 2010. Evans 2010. Homer-Dixon 1994. Collier 2006. Evans 2008; Collier 2007. Boano and others 2008: 22. Bartlett 2008. Wheeler 2011 Boano and others 2008. UN HABITAT Global Urban Indicators database (www. unhabitat.org/stats/). Slum households are defined as lacking in any of the following elements: access to improved water, access to improved sanitation, secure tenure, durable housing or sufficient living area. Asia Summit on Climate Change and Indigenous Peoples 2009; see also the Asia Summit on Climate Change and Indigenous People (www.tebtebba.org/ index.php?option=com_content&view=article&id= 47&Itemid=58). Rodriguez-Oreggia and others 2010. Brouwer, Akter and Brander 2007.
146 Nishikiori and others 2006. Oxfam International’s 2005 report on the 2004 Asian tsunami’s impact on women finds a similar pattern for floods. 147 Rose 1999. 148 Neumayer and Plumper 2007. 149 Neumayer and Plumper 2007. 150 Blankespoor and others 2010. 151 The probability of dying as a result of Hurricane Katrina was higher for people who were black and poor (Price 2008; 2007/2008 HDR: 81, box 2.3 [UNDP–HDRO 2008; see inside back cover for a list of HDRs]). 152 Baez, de la Fuente and Santos 2010. 153 Seballos and others 2011. 154 Alderman, Hoddinott and Kinsey (2006). Jensen (2000) found similar results in Côte d’Ivoire. 155 Baez and Santos (2007). 156 Alkire and Roche forthcoming. 157 Christiaensen, Do and Trung 2010. 158 UN 2010. 159 See the Mobile Alliance for Maternal Action (www. mobilemamaalliance.org/issue.html). 160 Engelman 2011. 161 Engelman 2009: 5. 162 UNDESA 2011b. 163 We note, however, that even after the large decline in fertility during the 1970s and 1980s, populationrelated problems in Bangladesh remain serious, and a sense of complacency has led to less rigorous policy implementation and programme performance in recent years (Khan and Khan 2010). 164 Potts and Marsh 2010: p. 5. 165 United States National Academy of Sciences 1992: 26. 166 O’Neill and others 2010. 167 Wire 2009. 168 Of 6.2 births per woman for Chad, 4.4 for the Democratic Republic of Congo and 7.1 for Niger; see statistical table 4. 169 Mills, Bos and Suzuki 2010. 170 Filmer and Pritchett (2002) find a partial correlation between indicators of fuelwood scarcity and fertility in Pakistan, and Biddlecom, Axinn and Barber (2005) link poorer environmental quality and a greater reliance on public natural resources with higher fertility in Western Chitwan Valley, Nepal. National data for Nepal, however, indicate that environmental scarcity is associated with less demand for children (Loughran and Pritchett 1997). 171 Based on the most recent Demographic and Health Survey data (www.measuredhs.com/accesssurveys/). 172 Engelman 2009. 173 Nugent and Shandra 2009. However, why this result came about was not clear. 174 Norgaard and York 2005. 175 See www.ipu.org/wmn-e/world.htm (accessed 14 July 2011). See statistical table 4 for country and regional data. 176 UNDESA 2010b. 177 Shandra, Shandra and London 2008. 178 Gallup World Poll data (www.gallup.com/se/126848/ worldview.aspx) for the most recent year available since 2007. 179 Differences between men and women are significant for perceived severity of climate change and government environmental efforts (at the 95 percent level) and for air quality and emissions policy (99 percent level) but not for satisfaction with water quality.
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Arora-Jonsson 2011. Agarwal 2009. Walton 2010: 36. Gallagher and Thacker 2008; Bernauer and Koubi 2009. Boyce and others 1999. Torras and Boyce 1998. Torras 2006. Power is assessed using the Gini index, political rights and civil liberties, literacy rate, higher education, population density, Internet user density and female representation in government. The principal components method was used to create an index of power equality using data on income inequality, adult literacy, Internet access, political rights and civil liberties, and political stability. The results are similar to those of Boyce and Torras (2002). All these studies tend to test a variety of outcomes and to use a variety of datasets and specifications. Gallagher and Thacker 2008; see also Torras and Boyce 1998. Li and Reuveny 2006. Neumayer 2002. Battig and Bernauer (2009) found similar results for 1990–2004 in 185 countries: democracy had a positive effect on political commitment to climate change mitigation, but the effects on policy outcomes—emissions levels and trends— were ambiguous. Bernauer and Koubi 2009. The term “countervailing power” was coined by Galbraith (1952). Crotty and Rodgers forthcoming. Fredrikkson and others 2005. Specifically, the results suggest that a 10 percent increase in the strength of NGOs (measured by number of environmental NGOs per capita) lowers sulphur dioxide levels 5.1–9.3 percent, smoke 5.7 percent and heavy particulates 0.8–1.5 percent. Additional estimates suggest an even greater impact after controlling for potential endogeneity and measurement error (Binder and Neumayer 2005). Pellow 2004.
Chapter 4
1 2 3 Barrett 2009. Ervin and others 2010. UNDESA 2009; OECD 2010c; IEA 2010; UN Rio Preparatory Committee Meeting 2011 publications (www.uncsd2012.org/rio20/index.php?page=view &type=13&nr=28&menu=24). REN21 2010: 47. Newell, Phillips and Mulvaney 2011. UN 2011. Bernard 2010: 1–2. Dinkelman 2008. Khandker and others 2009b. www.ophi.org.uk/policy/multidimensional-poverty -index/mpi-case-studies/. Zacune 2011. This is compared with the New Policies Scenario, which takes into account countries’ broad policy commitments and plans, even where not yet implemented. Under this scenario, through 2035, carbon dioxide emissions rise over 21 percent relative to 2008. Fossil fuels—mainly coal and natural gas— remain dominant in this scenario, but their share of total generation drops from 68 percent to 55 percent,
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as nuclear and renewable sources expand and the amount of carbon dioxide emitted per unit of electricity generated falls by a third (see IEA and others 2010). Renewable Energy Policy Network for the 21st Century 2011. Under the New Policies Scenario world primary energy demand increases some 36 percent between 2008 and 2035, or 1.2 percent a year. More than 80 percent of electricity demand is from non–Organisation for Economic Co-operation and Development (OECD) countries (IEA and others 2010: 4 and 8). OECD 2010c. On Kenya, Okello (2005); on Guatemala, Bruce and others (2004). AGECC 2010. Renewable Energy Policy Network for the 21st Century 2010. Eberhard and others 2008. Around 80 percent of renewable power generated in 2010 came from hydropower, which also accounted for around a third of new renewable capacity added between 2010 and 2011. Renewable Energy Policy Network for the 21st Century 2010. Geothermal power grew at an annual rate of 4 percent, ethanol production 23 percent, wind power 27 percent and solar photovoltaic 60 percent (Renewable Energy Policy Network for the 21st Century 2011: figure 2). Transparency International 2011. The Pew Charitable Trusts 2010. Glemarec 2011. Kammen, Kapadia and Fripp 2004. Renewable Energy Policy Network for the 21st Century 2010: 9. IEA, UNDP and UNIDO 2010. Burniaux and Chateau 2011. Badiani and Jessoe 2011. World Bank 2009. On Indonesia, Kojima and Bacon (2006); on Iran, Global Subsidies Initiative (2011). Norton Rose Group 2011. United States Environmental Protection Agency 2011. Emissions fell about 6 percent in 2008–2009, due mainly to the economic recession, which led to fuel switching as the price of coal rose and the price of natural gas fell. India Prime Minister’s Council on Climate Change 2008; Stern and Taylor 2010. ec.europa.eu/clima/policies/package/index_en.htm. IEA, UNDP and UNIDO 2010. See www.righttowater.info/progress-so-far/. Such legislation exists also in Kazakhstan and in four Western European countries. Leonhardt 2011. Klopfenstein and others 2011. Sarkar and others 2010. See www.undp.org/water/community-waterinitiative.shtml. Fishman 2011. World Bank 2007. Duflo and Pande 2007. Dudley and Stolton 2003. Mulongoy and Gidda 2008. www.unicef.org/wash/. Inter-American Development Bank 2010. Nepal Water for Health 2004. Baker and others 2011.
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Roseinweig 2008. World Bank 2011a. See Perez and others (2011); www.stanford.edu/ group/jennadavis/index.html; Lwin Oo 2010; Wilkinson, Moilwa and Taylor 2004. UNDESA 2010b. Engelman 2011. Potts and Marsh 2010. www.unfpa.org/stronger_voices. www.ehproject.org/phe/adra-nepalfinal.html. www.ehproject.org/phe/phe.html. Grandia 2005; Guatemala Instituto Nacional de Estadistica 1999, 2009. Mansour, Mansour and Swesy 2010. Bangladesh Ministry of Health and Family Welfare 2004; UNDESA 2009. Kenya National Coordinating Agency for Population and Development 2008. www.pathfind.org/site/PageServer?pagename= Programs_Vietnam_Projects_HIV_RH_Integration. Roudi 2009. UNFPA 2010. Lopez Carr and Grandia 2011. ITU 2011. The GSMA Development Fund, the Cherie Blaire Foundation for Women and Vital Wave Consulting 2010. www.mobilemamaalliance.org/opportunity.html. For example, Costa Rica went from a deforestation rate of 0.8 percent a year between 1990 and 2000 to a reforestation rate of 0.9 percent in the subsequent decade, and India increased its reforestation rate from of 0.2 percent a year between 1990 and 2000 to 0.5 percent a year between 2000 and 2010 (FAO 2011). Nagendra 2011. Ostrom 1992. Agarwal 2001; Gupte 2004. Agarwal 2010a. Molnar and others 2004. Corrigan and Granziera 2010. UNDP, UNEP, World Bank and WRI 2005. http://us.macmillan.com/horizontalinequalities andconflict. Leisher and others 2010. Leisher and others 2010. UNDP and GEF 2010. Baud and others 2011; Martin 2011. Ervin and others 2010. Ervin and others 2010. Roper, Utz and Harvey 2006. Gupta and Leung 2011. Government of India and UNDP Disaster Risk Management Programme 2008. Chung and others 2002. Duval-Diop and Rose 2008. See Grosh and others (2008) and Tucker (2010). UKaid–DFID 2011. Fuchs 2011. See Arnall and others (2010). Lieuw-Kie-Song 2009. South Africa Department of Environmental Affairs and UNEP 2011. UNDP 2011c.
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1 Frankel and Bosetti 2011.
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IPCC 2007. Chang and Grabel 2004; Rodrik 2006. See Aghion (2009); Rodrik (2005); Lin 2010. IPCC 2011. UNDP 2011a. Grasso 2004. Even if the importance of distributional aspects is increasingly recognized; see, for example, OECD (2010a). Atkinson and Stiglitz 1980. Oxfam International 2007. Cadman and others 2010. Weitzman 2009a, 2009b; Torras 2011. http://go.worldbank.org/5JP4U774N0. See www.opensecrets.org/influence/index.php. World Bank 2010c. Transparency International 2011. Rodrik, Subramanian and Trebbi 2004; Iyigun and Rodrik 2004. Speck 2010. Willenbockel 2011. OECD 2010c. Ghana Ministry of Energy and World Bank 2004. World Bank 2008b. Wang and others 2011. Gearty 2010. No such right has been recognized in the Universal Declaration of Human Rights or the International Covenant on Economic, Social and Cultural Rights. Earthjustice 2004, 2008. Debate over the recognition of environmental human rights is ongoing within the human rights community. Some argue that recognizing a third generation of rights (one in which the protection of humans is not the central focus) would devalue the concept of human rights and divert attention from the need to implement existing civil, political, economic and social rights fully. Others assert the inherent value of recognizing a right to have the environment protected. See Boyle (2010). Fukuda-Parr 2007; Nussbaum 1998, 2006; Sen 2009; Vizard, Fukuda-Parr and Elson 2011. Sen 2009 Boyce 2011. However, the legislation preserves Parliament’s discretion to authorize any interference with environmental rights: May (2006). See Pedersen (2008). See the Swedish Environment Protection Agency (www.naturvardsverket.se/en/In-English/Start/ Enjoying-nature/The-right-of-public-access/). Every person has the right to a clean and healthy environment, which includes the right to have the environment protected for the benefit of present and future generations through legislative and other measures (Constitution of Kenya 2010, Chapter 5, Part 2). Since 1972 more than half of UN member states have added constitutional guarantees concerning the environment (Earthjustice 2007). Article 44 of the 1994 Constitution of the Federal Democratic Republic of Ethiopia says that “government shall endeavor to ensure that all Ethiopians live in a clean and healthy environment” and Article 92 that “the design and implementation of programmes and of development shall not damage or destroy the environment.” Constitution of the Republic of Cameroon 1996, Article 47(2).
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Constitution of the Republic of Namibia 1990, Article 25(2). Bruch, Coker and VanArsdale 2007. Costa Rica, El Salvador and Honduras do not recognize environmental rights for indigenous peoples, and the constitutions of Guatemala, Panama, Paraguay and Peru refer to land but not natural resources (Aguilar and others 2010). Political Constitution of 1992, Republic of Paraguay, Article 66. According to the Constitution of the Co-operative Republic of Guyana Act 1980: “The state shall protect the environment for the benefits of present and future generations” (Article 149J.2); “Everyone has a right to an environment that is not harmful to his or her health or well-being” (Aricle 149J.1); and “Indigenous Peoples shall have the right to the protection and promulgation of their languages, cultural heritage and way of life” (Article 149G). Vidal 2011. May 2006. Other countries whose national courts have explicitly recognized the enforceability of such rights include Argentina, Columbia, Costa Rica and Portugal. Jackson and Rosencranz 2003. UNDP Bhutan 2008. Sen 2006. Shelton 2010. American Electric Power Co. v. Connecticut, 10-174. For discussion, see New York Times (2011). Biggar and Middleton 2010. Fifty percent or more of people in 61 of 137 countries surveyed do not have confidence in the judicial system and the courts (https://worldview.gallup.com). See Constitutional Protections of the Right to Information (http://right2info.org). Puddephatt 2009. Foulon, Lanoie and Laplante 2002. Jin, Wang and Wheeler 2010. Wang and others 2002; Bennear and Olmstead (2006) also confirmed this in the context of water utility suppliers in Massachusetts (United States) over 1990–2003. For example, the 1998 United Nations Economic Commission for Europe Convention on Access to Information, Public Participation in Decision-Making and Access to Justice in Environmental Matters (Aarhus Convention) and the Inter-American Strategy for the Promotion of Public Participation in Decision Making for Sustainable Development. UNEP 2007, chapter 8. See www.rema.gov.rw. Newell and others 2011. Newell and others 2011. Lloyd-Smith and Bell 2003. Byrne and others 2007. Newell 2008. Crotty and Rodgers forthcoming. UNDP–UNEP Poverty-Environment Initiative 2008. Transparency International calculations based on the Conference of Parties documentation, pollution data from 2006 (UN Stats Division 2010) and Climate Risk Index 2010 by Germanwatch (Transparency International 2011). Ballesteros and others 2009. www.un-redd.org/Home/tabid/565/Default.aspx. In Eastern Cameroon, for example, a United Nations Development Programme (UNDP) initiative gave the Baka people access to video cameras to document
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how climate change is damaging the forests where they live, and the resulting documentary was used in advocacy work at the 2009 Global Indigenous Summit on Climate Change (UNDP 2010). Buckingham 2010. Agarwal (2009, 2010b) found that the overall forest condition was significantly higher where executive committees had more than two women than where they had two women or fewer and that the higher the percentage of women on the executive committee, the lower the percentage of degraded forest area. Schreckenberg and Luttrell (2009). Buffum, Lawrence and Temphel 2010. Glemarec 2011. Bloomberg New Energy Finance and UNEP 2010. Kim and others 2009. Glemarec 2011. The global estimated needs exclude payments for ecosystem services. See Glemarec (2011). For the Global Environment Facility over 2007–2010 China attracted 12 percent of funds approved, India 10 percent and the Russian Federation 6 percent. But China and India have a per capita allocation of only $0.10 and $0.09, far below the median of $0.43, while the Russian Federation receives $0.51. See www.gefonline.org. See CIF 2011. GEF 2009. OECD 2011a; www.oecd.org/document/35/0, 3746,en_2649_34447_47515235_1_1_1_1,00.html. Percentage calculated based on UN Millennium Project (2005) table 7. There is not even a consensus on a working definition of new and additional finance. The European Commission has requested that all EU member states declare their own working definitions, with the goal of having a common and unified definition by 2013. See Bird, Brown and Schalatek (2011). Sanchez 2010. World Bank 2010b. At the lower end is the United Nations Framework Convention on Climate Change estimate of about $200 billion in additional financial flows by 2030. The McKinsey & Company (2009) estimate of $800 billion to stabilize carbon dioxide at 450 parts per million is in the middle of the range. The numbers reported by the Stern Review ranged from $600 billion to $1,200 billion a year, depending on the emission targets (see UNDESA 2009). A recent Intergovernmental Panel on Climate Change (2011) report estimated the annual infrastructure and technology investment costs of moving to a low greenhouse gas economy at $136–$510 billion a year for the next decade and at $149–$718 billion a year for 2021–2030. The higher cost scenario would stabilize atmospheric carbon dioxide concentration at 450 parts per million. This is an update of the $86 billion figure, equivalent to 0.2 percent of Organisation for Economic Co-operation and Development (OECD) GDP, in UNDP–HDRO 2007/08, using the latest information available. Parry, Lowe and Hanson 2009. Stockholm International Peace Research Institute 2010. See IEA (2010); calculations based on UNESCO Institute for Statistics (www.uis.unesco.org) and World Bank 2011b. Climate Funds Update 2011 (www.climatefundsupdate .org/graphs-statistics/pledged-deposited-disbursed). Not all these estimates can be broken out separately into water and sanitation, but those that can range
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from $4.5 billion to $13 billion for water and from $2.2 billion to $17 billion for sanitation (Fonesca and Cardone 2005). On innovative financing, see OECD (2010c). See UN Water 2010a. ILO 2010. Although worldwide nearly 40 percent of the workingage population is legally covered by contributory old-age pension schemes, only 26 percent have effective coverage. And while 75 percent of people over age 64 receive some kind of pension in high-income countries, less than 20 percent do in low-income countries, with a median of just over 7 percent (see ILO 2010). OECD 2010b. The ILO (2008) estimates the cost would not exceed 0.5 percent of GDP in Bangladesh, Cameroon, Guinea, India, Pakistan, Senegal and Viet Nam, for example; while for Burkina Faso, Ethiopia, Kenya, Nepal and Tanzania the costs are 0.7–0.8 percent of GDP. See Cichon and Hagemejer (2006). “Adaptive social protection” is a term coined by researchers at the Institute of Development Studies, Sussex, to bring together thinking about social protection, disaster risk reduction and climate change adaptation (Davies, Oswald and Mitchell 2009). Our calculations indicate that an additional $15–$28 billion is needed to incorporate adaptation into the Millennium Development Goals. Calculations based on Frankhauser and Schmidt-Traub (2010) and the UN Millennium Project: Estimated Costs of meeting the Millennium Development Goals in all countries (www.unmillenniumproject.org/reports/ costs_benefits2.htm) (table 7). Leading Group on Innovative Financing for Development 2010. Griffith-Jones, Ocampo and Stiglitz 2010. This estimate is slightly higher than Schmidt’s (2008) estimate for a tax of 0.005 percent of $34 billion a year. Other areas included are the Extractive Industries Transparency Initiative, Consultative Group on Agriculture, 3ie Evaluation Initiative, Global Environment Facility, UN Adaptation Fund, advanced market commitments, Montreal Protocol, International Finance Facility for Immunisation, Climate Investment Funds and International Monetary Fund surveillance. See Birdsall and Leo (2011). IMF 2010. European Parliament Committee on Economic and Monetary Affairs 2011. Baker 2011. SDR surpluses occur when a country’s holdings exceed allocations. The largest SDR surplus countries include the United States, China, Japan, Libya, Saudi Arabia, Kuwait and Botswana. Birdsall and Leo (2011). Willing governments would use a small portion of their SDR allocation to capitalize a third-party financing entity that would offer bonds on international capital markets backed by SDR reserves. Climate Funds Update 2011 (www.climatefundsupdate .org/graphs-statistics/pledged-deposited-disbursed). Newell and others 2011. UNDP, and others, have developed a series of methodologies to assist such efforts: see www.undp.org/ climatestrategies. Glemarec 2011.
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Statistical Annex
Human development statistical annex
Readers guide
123 126
Key to HDI countries and ranks, 2011 Statistical tables Technical notes 127
Calculating the human development indices—graphical presentation Technical note 1 Technical note 2 Technical note 3 Technical note 4 Regions 174 175 168 169 171 172
167
Statistical references
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Readers guide
The 10 statistical tables provide an overview of key aspects of human development at the country and regional levels as well as for key country groupings. The tables include composite indices estimated by the Human Development Report Office (HDRO), using the methods detailed in Technical notes 1–4. Data in the tables are those available to the HDRO as of 15 May 2011, unless otherwise noted. The tables include data for as many of the 192 UN member states as possible as well as Hong Kong Special Administrative Region of China and the Occupied Palestinian Territory. Data availability determines Human Development Index (HDI) country coverage. Where reliable data are unavailable or there is significant uncertainty about the validity of the data, countries are excluded from calculations in order to ensure the statistical credibility of the HDR. Countries and areas are ranked by their 2011 HDI value. The Key to countries on the inside back cover of the Report lists countries alphabetically with their HDI ranks. All the indicators are available online in several formats at http://hdr.undp.org/en/ statistics, which includes interactive tools, maps of all the human development indices and selected animations, descriptive materials such as country factsheets, and guidance on how to calculate the indices. These materials are also available in French and Spanish.
Definitions of indicators and sources for original data components are given at the end of each table, with full references in the Statistical references. For more detailed technical information about the indicators, the websites of the respective source agencies should be consulted; links to these sources are at http://hdr.undp. org/en/statistics.
comparisons over time and across editions of the Report Because international data agencies continually improve their data series, the data— including the HDI values and ranks— presented in this Report are not comparable to those published in earlier editions. For the HDI, trends using consistent data—calculated at five-year intervals for 1980–2011—are presented in table 2.
discrepancies between national and international estimates When compiling data series, international agencies apply international standards and harmonization procedures to make national data comparable across countries. When data for a country are missing, an international agency may produce an estimate if other relevant information is available. In some cases international data series may not incorporate the most recent national data. All these factors can lead to discrepancies between national and international estimates. When HDRO becomes aware of discrepancies, these are brought to the attention of national and international data authorities. The HDRO continues to advocate for improving international data and actively supports efforts to enhance data quality.
ReadeRs guide
sources and definitions The HDRO is primarily a user, not a producer, of statistics. It relies on international data agencies with the mandate, resources and expertise to collect and compile national data on specific indicators. Where data are not available from international data suppliers, data from other credible sources are used.
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country groupings and aggregates In addition to country-level data, several population-weighted aggregates are presented. In general, an aggregate is shown for a country grouping only when the relevant data are available for at least half the countries and represent at least two-thirds of the available population in that classification. Aggregates for each classification represent only the countries for which data are available, unless otherwise noted. Occasionally aggregates are those from the original source rather than weighted averages; these values are indicated with a superscript “T”.
Human development classification HDI classifications are relative—based on quartiles of HDI distribution across countries and denoted very high, high, medium and low HDI. Because there are 187 countries, the four groups do not have the same number of countries: the very high, high and medium HDI groups have 47 countries each, and the low HDI group has 46 countries. Country groupings Countries are grouped based on UNDP regional classification. Other groupings are based on UN classifications such as Least Developed Countries and Small Island Developing States. The composition of each region is presented in Regions.
country notes Data for China do not include Hong Kong Special Administrative Region of China, Macao Special Administrative Region of China or Taiwan Province of China, unless otherwise noted. Data for Sudan include South Sudan unless otherwise noted but are often based on information collected from the northern part of the country only.
symbols A dash between two years, as in 2005–2011, indicates that the data are the most recent year available in the period specified, unless otherwise noted. Growth rates are usually average annual rates of growth between the first and last years of the period shown. A slash between years such as 2005/2011 indicates average for the years shown, unless otherwise noted. The following symbols are used in the tables: Not available .. 0 or 0.0 Nil or negligible — Not applicable < Less than
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statistical tables
composite measures
1 Human Development Index and its components 2 Human Development Index trends, 1980–2011 3 Inequality-adjusted Human Development Index 4 Gender Inequality Index and related indicators 5 Multidimensional Poverty Index
dimensions of human development
6 Environmental sustainability 7 Human development effects of environmental threats 8 Perceptions about well-being and the environment 9 Education and health 10 Population and economy
statistical tables
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Key to Hdi countries and ranks, 2011
Afghanistan Albania Algeria Andorra Angola Antigua and Barbuda Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bhutan Bolivia, Plurinational State of Bosnia and Herzegovina Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Central African Republic Chad Chile China Colombia Comoros Congo Congo, Democratic Republic of the Costa Rica Côte d’Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Fiji Finland Former Yugoslav Republic of Macedonia France Gabon Gambia
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Human development report 2011
172 70 96 32 148 60 45 86 2 19 91 53 42 146 47 65 18 93 167 141 108 74 118 84 33 55 181 185 139 150 6 133 179 183 44 101 87 163 137 187 69 170 46 51 31 27 16 165 81 98 83 113 105 136 177 34 174 100 22 78 20 106 168
Georgia Germany Ghana Greece Grenada Guatemala Guinea Guinea-Bissau Guyana Haiti Honduras Hong Kong, China (SAR) Hungary Iceland India Indonesia Iran, Islamic Republic of Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Kiribati Korea, Republic of Kuwait Kyrgyzstan Lao People’s Democratic Republic Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Madagascar Malawi Malaysia Maldives Mali Malta Mauritania Mauritius Mexico Micronesia, Federated States of Moldova, Republic of Mongolia Montenegro Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway
75 9 135 29 67 131 178 176 117 158 121 13 38 14 134 124 88 132 7 17 24 79 12 95 68 143 122 15 63 126 138 43 71 160 182 64 8 40 25 151 171 61 109 175 36 159 77 57 116 111 110 54 130 184 149 120 157 3 5 129 186 156 1
Occupied Palestinian Territory Oman Pakistan Palau Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Qatar Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Samoa São Tomé and Príncipe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania, United Republic of Thailand Timor-Leste Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Vanuatu Venezuela, Bolivarian Republic of Viet Nam Yemen Zambia Zimbabwe
114 89 145 49 58 153 107 80 112 39 41 37 50 66 166 72 82 85 99 144 56 155 59 52 180 26 35 21 142 123 23 97 169 104 140 10 11 119 127 152 103 147 162 90 62 94 92 102 161 76 30 28 4 48 115 125 73 128 154 164 173
1
table
Human Development Index and its components
Human Development Index (HDI) Value 2011 Life expectancy at birth (years) 2011 Mean years of schooling (years) 2011a Expected years of schooling (years) 2011a Gross national income (GNI) per capita (constant 2005 PPP $) 2011 Nonincome HDI Value 2011
HDI rank
GNI per capita rank minus HDI rank 2011
VERY HIGH HUMAN DEVELOPMENT 1 Norway 2 Australia 3 Netherlands 4 United States 5 New Zealand 6 Canada 7 Ireland 8 Liechtenstein 9 Germany 10 Sweden 11 Switzerland 12 Japan 13 Hong Kong, China (SAR) 14 Iceland 15 Korea, Republic of 16 Denmark 17 Israel 18 Belgium 19 Austria 20 France 21 Slovenia 22 Finland 23 Spain 24 Italy 25 Luxembourg 26 Singapore 27 Czech Republic 28 United Kingdom 29 Greece 30 United Arab Emirates 31 Cyprus 32 Andorra 33 Brunei Darussalam 34 Estonia 35 Slovakia 36 Malta 37 Qatar 38 Hungary 39 Poland 40 Lithuania 41 Portugal 42 Bahrain 43 Latvia 44 Chile 45 Argentina 46 Croatia 47 Barbados HIGH HUMAN DEVELOPMENT 48 Uruguay 49 Palau 50 Romania 51 Cuba 52 Seychelles 53 Bahamas 54 Montenegro 55 Bulgaria 56 Saudi Arabia 57 Mexico
0.943 0.929 0.910 0.910 0.908 0.908 0.908 0.905 0.905 0.904 0.903 0.901 0.898 0.898 0.897 0.895 0.888 0.886 0.885 0.884 0.884 0.882 0.878 0.874 0.867 0.866 0.865 0.863 0.861 0.846 0.840 0.838 0.838 0.835 0.834 0.832 0.831 0.816 0.813 0.810 0.809 0.806 0.805 0.805 0.797 0.796 0.793 0.783 0.782 0.781 0.776 0.773 0.771 0.771 0.771 0.770 0.770
81.1 81.9 80.7 78.5 80.7 81.0 80.6 79.6 80.4 81.4 82.3 83.4 82.8 81.8 80.6 78.8 81.6 80.0 80.9 81.5 79.3 80.0 81.4 81.9 80.0 81.1 77.7 80.2 79.9 76.5 79.6 80.9 78.0 74.8 75.4 79.6 78.4 74.4 76.1 72.2 79.5 75.1 73.3 79.1 75.9 76.6 76.8 77.0 71.8 74.0 79.1 73.6 75.6 74.6 73.4 73.9 77.0
12.6 12.0 11.6 b 12.4 12.5 12.1 b 11.6 10.3 c 12.2 b 11.7 b 11.0 b 11.6 b 10.0 10.4 11.6 b 11.4 b 11.9 10.9 b 10.8 b 10.6 b 11.6 b 10.3 10.4 b 10.1 b 10.1 8.8 b 12.3 9.3 10.1 b 9.3 9.8 10.4 f 8.6 12.0 11.6 9.9 7.3 11.1 b 10.0 b 10.9 7.7 9.4 11.5 b 9.7 9.3 9.8 b 9.3 8.5 b 12.1 i 10.4 9.9 9.4 m 8.5 m 10.6 10.6 b 7.8 8.5
17.3 18.0 16.8 16.0 18.0 16.0 18.0 14.7 15.9 15.7 15.6 15.1 15.7 18.0 16.9 16.9 15.5 16.1 15.3 16.1 16.9 16.8 16.6 16.3 13.3 14.4 e 15.6 16.1 16.5 13.3 14.7 11.5 14.1 15.7 14.9 14.4 12.0 15.3 15.3 16.1 15.9 13.4 15.0 14.7 15.8 13.9 13.4 h 15.5 14.7 14.9 17.5 13.3 12.0 13.7 h 13.7 13.7 13.9
47,557 34,431 36,402 43,017 23,737 35,166 29,322 83,717 d 34,854 35,837 39,924 32,295 44,805 29,354 28,230 34,347 25,849 33,357 35,719 30,462 24,914 32,438 26,508 26,484 50,557 52,569 21,405 33,296 23,747 59,993 24,841 36,095 g 45,753 16,799 19,998 21,460 107,721 16,581 17,451 16,234 20,573 28,169 14,293 13,329 14,527 15,729 17,966 13,242 9,744 j,k 11,046 5,416 l 16,729 23,029 n 10,361 o 11,412 23,274 13,245
6 16 9 6 30 10 19 –6 8 4 0 11 –4 11 12 3 14 2 –4 4 11 0 6 6 –20 –22 14 –7 5 –27 2 –19 –25 13 8 4 –36 11 7 10 1 –14 12 14 9 5 –3 12 29 20 52 –4 –15 20 14 –19 2
0.975 0.979 0.944 0.931 0.978 0.944 0.959 0.877 0.940 0.936 0.926 0.940 0.910 0.943 0.945 0.926 0.939 0.914 0.908 0.919 0.935 0.911 0.920 0.914 0.854 0.851 0.917 0.879 0.902 0.813 0.866 0.836 0.819 0.890 0.875 0.866 0.757 0.862 0.853 0.853 0.833 0.806 0.857 0.862 0.843 0.834 0.818 0.828 0.853 0.841 0.904 0.794 0.768 0.831 0.822 0.765 0.808
STATISTICAL TAbLeS
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human development Index and its components
Human Development Index (HDI) Value 2011 Gross national income (GNI) per capita (constant 2005 PPP $) 2011 12,335 10,236 15,521 13,685 23,439 p 47,926 12,637 q 13,439 14,561 6,982 10,585 10,497 7,803 13,076 11,897 10,656 7,664 4,780 6,175 12,918 8,804 6,487 8,389 7,889 8,273 7,589 10,162 8,013 5,188 8,315 10,164 22,841 4,186 8,666 12,246 5,812 7,281
table
1
HDI rank
Life expectancy at birth (years) 2011
Mean years of schooling (years) 2011a
Expected years of schooling (years) 2011a
GNI per capita rank minus HDI rank 2011
Nonincome HDI Value 2011 0.811 0.824 0.786 0.790 0.750 0.705 0.795 0.785 0.777 0.829 0.786 0.785 0.804 0.760 0.762 0.771 0.797 0.843 0.810 0.745 0.776 0.802 0.775 0.779 0.773 0.776 0.748 0.766 0.806 0.752 0.731 0.671 0.808 0.733 0.704 0.766 0.745
58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94
Panama Serbia Antigua and Barbuda Malaysia Trinidad and Tobago Kuwait Libya Belarus Russian Federation Grenada Kazakhstan Costa Rica Albania Lebanon Saint Kitts and Nevis Venezuela, Bolivarian Republic of Bosnia and Herzegovina Georgia Ukraine Mauritius Former Yugoslav Republic of Macedonia Jamaica Peru Dominica Saint Lucia Ecuador Brazil Saint Vincent and the Grenadines Armenia Colombia Iran, Islamic Republic of Oman Tonga Azerbaijan Turkey Belize Tunisia
0.768 0.766 0.764 0.761 0.760 0.760 0.760 0.756 0.755 0.748 0.745 0.744 0.739 0.739 0.735 0.735 0.733 0.733 0.729 0.728 0.728 0.727 0.725 0.724 0.723 0.720 0.718 0.717 0.716 0.710 0.707 0.705 0.704 0.700 0.699 0.699 0.698 0.698 0.698 0.691 0.689 0.688 0.688 0.687 0.686 0.682 0.680 0.674 0.674 0.665 0.663 0.661 0.653 0.649 0.644 0.644 0.641 0.641 0.636 0.633 0.633
76.1 74.5 72.6 74.2 70.1 74.6 74.8 70.3 68.8 76.0 67.0 79.3 76.9 72.6 73.1 74.4 75.7 73.7 68.5 73.4 74.8 73.1 74.0 77.5 74.6 75.6 73.5 72.3 74.2 73.7 73.0 73.0 72.3 70.7 74.0 76.1 74.5 73.4 73.1 74.9 73.4 72.4 69.2 73.5 65.0 74.1 70.6 72.2 62.7 72.5 66.6 76.8 68.5 69.3 68.7 73.2 72.8 68.3 69.0 69.9 53.2
9.4 10.2 b 8.9 h 9.5 9.2 6.1 7.3 9.3 r 9.8 8.6 10.4 8.3 10.4 7.9 m 8.4 7.6 b 8.7 r 12.1 r 11.3 7.2 8.2 r 9.6 8.7 7.7 m 8.3 7.6 7.2 8.6 10.8 7.3 7.3 5.5 m 10.3 b 8.6 m 6.5 8.0 b 6.5 8.6 7.0 8.2 7.2 b 10.3 m 10.7 b 7.5 9.9 i 6.6 7.2 r 7.5 7.5 7.7 9.2 5.8 b 8.3 9.7 8.9 b 6.4 8.0 m 10.0 r 8.8 i 8.0 8.9
13.2 13.7 14.0 12.6 12.3 12.3 16.6 14.6 14.1 16.0 15.1 11.7 11.3 13.8 12.9 14.2 13.6 13.1 14.7 13.6 13.3 13.8 12.9 13.2 13.1 14.0 13.8 13.2 12.0 13.6 12.7 11.8 13.7 11.8 11.8 12.4 14.5 13.1 13.6 12.7 11.9 12.3 13.0 11.6 12.5 h 12.3 12.6 12.1 13.1 12.1 13.7 12.4 14.1 11.9 11.9 11.0 12.7 11.4 12.1 u 11.9 12.2
7 16 –8 –5 –26 –57 0 –8 –13 30 4 4 18 –10 –4 –2 16 36 24 –14 2 19 2 6 2 9 –7 1 22 –4 –12 –50 26 –10 –25 9 2 9 –5 12 –13 22 18 –7 –7 –14 –11 –4 –40 5 11 –3 17 21 11 –6 23 19 19 11 –56
MEDIUM HUMAN DEVELOPMENT 95 Jordan 96 Algeria 97 Sri Lanka 98 Dominican Republic 99 Samoa 100 Fiji 101 China 102 Turkmenistan 103 Thailand 104 Suriname 105 El Salvador 106 Gabon 107 Paraguay 108 Bolivia, Plurinational State of 109 Maldives 110 Mongolia 111 Moldova, Republic of 112 Philippines 113 Egypt 114 Occupied Palestinian Territory 115 Uzbekistan 116 Micronesia, Federated States of 117 Guyana 118 Botswana
5,300 7,658 4,943 8,087 3,931 s 4,145 7,476 7,306 7,694 7,538 5,925 12,249 4,727 4,054 5,276 3,391 3,058 3,478 5,269 2,656 k,t 2,967 2,935 v 3,192 13,049
0.773 0.739 0.768 0.720 0.788 0.781 0.725 0.724 0.714 0.712 0.724 0.667 0.729 0.742 0.714 0.743 0.746 0.725 0.686 0.750 0.736 0.729 0.715 0.602
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human development Index and its components
Human Development Index (HDI) Value 2011 0.632 0.625 0.625 0.624 0.619 0.617 0.617 0.615 0.607 0.593 0.589 0.582 0.574 0.573 0.568 0.547 0.541 0.537 0.533 0.524 0.523 0.522 0.522 Gross national income (GNI) per capita (constant 2005 PPP $) 2011 4,243 6,206 3,443 3,140 9,469 3,716 3,950 2,036 1,937 2,805 2,430 4,196 4,167 3,177 3,402 3,468 1,584 17,608 3,066 2,242 1,848 4,484 5,293
HDI rank
Life expectancy at birth (years) 2011
Mean years of schooling (years) 2011
a
Expected years of schooling (years) 2011
a
GNI per capita rank minus HDI rank 2011
Nonincome HDI Value 2011 0.686 0.643 0.694 0.701 0.604 0.674 0.668 0.734 0.726 0.662 0.669 0.606 0.595 0.616 0.603 0.568 0.633 0.458 0.555 0.569 0.584 0.512 0.500
table
1
119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141
Syrian Arab Republic Namibia Honduras Kiribati South Africa Indonesia Vanuatu Kyrgyzstan Tajikistan Viet Nam Nicaragua Morocco Guatemala Iraq Cape Verde India Ghana Equatorial Guinea Congo Lao People’s Democratic Republic Cambodia Swaziland Bhutan
75.9 62.5 73.1 68.1 52.8 69.4 71.0 67.7 67.5 75.2 74.0 72.2 71.2 69.0 74.2 65.4 64.2 51.1 57.4 67.5 63.1 48.7 67.2 67.9 57.1 64.7 65.4 68.9 62.5 51.1 65.2 51.6 66.7 58.2 62.8 65.5 59.3 51.9 68.8 62.1 58.6 48.2 54.1 57.1 61.1 49.0 57.9 55.4 56.1 58.5 61.5 55.4 54.2 48.7 51.4 59.3 51.4 48.1 61.6 54.1 48.4
5.7 b 7.4 6.5 7.8 8.5 b 5.8 6.7 9.3 9.8 5.5 5.8 4.4 4.1 5.6 3.5 i 4.4 7.1 5.4 r 5.9 4.6 5.8 7.1 2.3 r 4.5 i 7.0 4.2 i 4.9 4.8 2.8 i 4.4 r 4.0 5.9 5.2 i 5.1 4.3 2.5 4.5 5.0 r 3.2 4.9 3.7 5.9 b 4.7 5.3 2.8 i 6.5 3.8 r 3.3 3.3 2.8 3.1 3.3 4.2 3.3 7.2 1.5 i 2.0 b 2.3 r 3.4 1.6 w 3.5
11.3 11.6 11.4 12.1 13.1 13.2 10.4 12.5 11.4 10.4 10.8 10.3 10.6 9.8 11.6 10.3 10.5 7.7 10.5 9.2 9.8 10.6 11.0 9.1 11.0 10.8 6.9 8.1 11.2 9.1 9.2 10.3 10.7 9.1 5.8 8.6 7.5 8.9 8.8 7.6 u 8.1 9.9 10.8 9.6 10.7 7.9 5.1 11.1 9.2 9.0 4.4 6.3 8.9 9.1 9.9 8.5 8.3 9.1 4.8 8.6 6.6
–5 –21 4 8 –44 –2 –5 19 20 8 10 –15 –14 –3 –7 –10 20 –91 –6 4 11 –27 –36 10 15 7 –7 11 –14 –38 7 –4 26 10 –12 –11 –2 –12 8 12 –10 –6 7 16 9 0 –25 1 –6 –5 –21 –10 8 –13 11 0 –6 –3 6 –2 2
LOW HUMAN DEVELOPMENT 142 Solomon Islands 143 Kenya 144 São Tomé and Príncipe 145 Pakistan 146 Bangladesh 147 Timor-Leste 148 Angola 149 Myanmar 150 Cameroon 151 Madagascar 152 Tanzania, United Republic of 153 Papua New Guinea 154 Yemen 155 Senegal 156 Nigeria 157 Nepal 158 Haiti 159 Mauritania 160 Lesotho 161 Uganda 162 Togo 163 Comoros 164 Zambia 165 Djibouti 166 Rwanda 167 Benin 168 Gambia 169 Sudan 170 Côte d'Ivoire 171 Malawi 172 Afghanistan 173 Zimbabwe 174 Ethiopia 175 Mali 176 Guinea-Bissau 177 Eritrea 178 Guinea 179 Central African Republic
0.510 0.509 0.509 0.504 0.500 0.495 0.486 0.483 0.482 0.480 0.466 0.466 0.462 0.459 0.459 0.458 0.454 0.453 0.450 0.446 0.435 0.433 0.430 0.430 0.429 0.427 0.420 0.408 0.400 0.400 0.398 0.376 0.363 0.359 0.353 0.349 0.344 0.343
1,782 1,492 1,792 2,550 1,529 3,005 4,874 1,535 2,031 824 1,328 2,271 2,213 1,708 2,069 1,160 1,123 1,859 1,664 1,124 798 1,079 1,254 2,335 1,133 1,364 1,282 1,894 1,387 p 753 1,416 376 n 971 1,123 994 536 863 707
0.567 0.584 0.564 0.526 0.566 0.499 0.455 0.536 0.509 0.605 0.523 0.475 0.471 0.488 0.471 0.524 0.520 0.472 0.475 0.506 0.526 0.488 0.469 0.420 0.477 0.456 0.450 0.402 0.412 0.470 0.407 0.529 0.383 0.366 0.366 0.421 0.364 0.379
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human development Index and its components
Human Development Index (HDI) Value 2011 Gross national income (GNI) per capita (constant 2005 PPP $) 2011
table
1
HDI rank
Life expectancy at birth (years) 2011
Mean years of schooling (years) 2011a
Expected years of schooling (years) 2011a
GNI per capita rank minus HDI rank 2011
Nonincome HDI Value 2011 0.365 0.323 0.504 0.320 0.325 0.412 0.311 0.399
180 181 182 183 184 185 186 187
Sierra Leone Burkina Faso Liberia Chad Mozambique Burundi Niger Congo, Democratic Republic of the
0.336 0.331 0.329 0.328 0.322 0.316 0.295 0.286 .. .. .. .. .. .. .. 0.889 0.741 0.630 0.456 0.641 0.671 0.751 0.731 0.548 0.463 0.439 0.640 0.682
47.8 55.4 56.8 49.6 50.2 50.4 54.7 48.4 68.8 72.0 82.2 79.9 81.8 51.2 67.2 80.0 73.1 69.7 58.7 70.5 72.4 71.3 74.4 65.9 54.4 59.1 69.6 69.8
2.9 1.3 r 3.9 1.5 i 1.2 2.7 1.4 3.5 .. 9.8 i .. .. .. .. .. 11.3 8.5 6.3 4.2 5.9 7.2 9.7 7.8 4.6 4.5 3.7 7.3 7.4
7.2 6.3 11.0 7.2 9.2 10.5 4.9 8.2 .. 10.8 17.5 9.3 .. 2.4 10.8 15.9 13.6 11.2 8.3 10.2 11.7 13.4 13.6 9.8 9.2 8.3 10.8 11.3
737 1,141 265 1,105 898 368 641 280 .. .. .. .. .. .. .. 33,352 11,579 5,276 1,585 8,554 6,466 12,004 10,119 3,435 1,966 1,327 5,200 10,082
0 –15 5 –12 –9 0 –4 –1 .. .. .. .. .. .. .. — — — — — — — — — — — — —
OTHER COUNTRIES OR TERRITORIES Korea, Democratic People’s Rep. of Marshall Islands Monaco Nauru San Marino Somalia Tuvalu Human Development Index groups Very high human development High human development Medium human development Low human development Regions Arab States East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean South Asia Sub-Saharan Africa Least developed countries Small island developing states World
.. 0.752 .. .. .. .. .. 0.918 0.769 0.658 0.478 0.643 0.709 0.785 0.767 0.569 0.467 0.467 0.675 0.683
NOTES a. Data refer to 2011 or the most recent year available. b. Updated by HDRO based on UNESCO (2011) data. c. Assumes the same adult mean years of schooling as Switzerland before the most recent update. d. Estimated using the purchasing power parity (PPP) and projected growth rate of Switzerland. e. Calculated by the Singapore Ministry of Education. f. Assumes the same adult mean years of schooling as Spain before the most recent update. g. Estimated using the PPP and projected growth rate of Spain. h. Based on cross-country regression. i. Based on data on years of schooling of adults from household surveys from World Bank (2010). j. Based on UNESCAP (2011) and UNDESA (2011) projected growth rates. k. Based on unpublished estimates from the World Bank. l. PPP estimate based on cross-country regression; projected growth rate based on ECLAC (2011) and UNDESA (2011) projected growth rates. m. Based on UNESCO (2011) estimates of education attainment distribution. n. Based on PPP data from IMF (2011). o. Based on EBRD (2011) and UNDESA (2011) projected growth rates. p. Based on World Bank (2011b). q. Based on OECD and others (2011) and UNDESA (2011) projected growth rates. r. Based on data from UNICEF (2000–2010). s. Based on ADB (2011) projected growth rate. t. Based on UNESCWA (2011) and UNDESA (2011) projected growth rates. u. Refers to primary and secondary education only. United Nations Educational, Scientific and Cultural Organization Institute for Statistics estimate. v. Based on ADB (2011) and UNDESA (2011) projected growth rates. w. Based on data from ICF Macro (2011).
DEFINITIONS Human Development Index (HDI): A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge and a decent standard of living. See Technical note 1 for details on how the HDI is calculated. Life expectancy at birth: Number of years a newborn infant could expect to live if prevailing patterns of age-specific mortality rates at the time of birth stay the same throughout the infant’s life. Mean years of schooling: Average number of years of education received by people ages 25 and older, converted from education attainment levels using official durations of each level. Expected years of schooling: Number of years of schooling that a child of school entrance age can expect to receive if prevailing patterns of age-specific enrolment rates persist throughout the child’s life. Gross national income (GNI) per capita: Aggregate income of an economy generated by its production and its ownership of factors of production, less the incomes paid for the use of factors of production owned by the rest of the world, converted to international dollars using purchasing power parity (PPP) rates, divided by midyear population. GNI per capita rank minus HDI rank: Difference in rankings by GNI per capita and by the HDI. A negative value means that the country is better ranked by GNI than by the HDI. Nonincome HDI: Value of the HDI computed from the life expectancy and education indicators only. MAIN DATA SOURCES Column 1: HDRO calculations based on data from UNDESA (2011), Barro and Lee (2010b), UNESCO Institute for Statistics (2011), World Bank (2011a), UNSD (2011) and IMF (2011). Column 2: UNDESA (2011). Column 3: HDRO updates of Barro and Lee (2010b) estimates based on UNESCO Institute for Statistics data on education attainment (2011) and Barro and Lee (2010a) methodology. Column 4: UNESCO Institute for Statistics (2011). Column 5: HDRO calculations based on data from World Bank (2011a), IMF (2011) and UNSD (2011). Column 6: Calculated based on data in columns 1 and 5. Column 7: Calculated based on data in columns 2, 3 and 4.
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2
table
Human Development Index trends, 1980–2011
Human Development Index (HDI) HDI rank Changea 2009 2010 2011 Average annual HDI growth (%) Value 1980 1990 2000 2005
HDI rank
2006–2011 2010–2011 1980–2011 1990–2011 2000–2011
VERY HIGH HUMAN DEVELOPMENT 1 Norway 2 Australia 3 Netherlands 4 United States 5 New Zealand 6 Canada 7 Ireland 8 Liechtenstein 9 Germany 10 Sweden 11 Switzerland 12 Japan 13 Hong Kong, China (SAR) 14 Iceland 15 Korea, Republic of 16 Denmark 17 Israel 18 Belgium 19 Austria 20 France 21 Slovenia 22 Finland 23 Spain 24 Italy 25 Luxembourg 26 Singapore 27 Czech Republic 28 United Kingdom 29 Greece 30 United Arab Emirates 31 Cyprus 32 Andorra 33 Brunei Darussalam 34 Estonia 35 Slovakia 36 Malta 37 Qatar 38 Hungary 39 Poland 40 Lithuania 41 Portugal 42 Bahrain 43 Latvia 44 Chile 45 Argentina 46 Croatia 47 Barbados HIGH HUMAN DEVELOPMENT 48 Uruguay 49 Palau 50 Romania 51 Cuba 52 Seychelles 53 Bahamas 54 Montenegro 55 Bulgaria 56 Saudi Arabia 57 Mexico
0.796 0.850 0.792 0.837 0.800 0.817 0.735 .. 0.730 0.785 0.810 0.778 0.708 0.762 0.634 0.783 0.763 0.757 0.740 0.722 .. 0.759 0.691 0.717 0.728 .. .. 0.744 0.720 0.629 .. .. 0.750 .. .. 0.703 0.703 0.700 .. .. 0.639 0.651 .. 0.630 0.669 .. .. 0.658 .. .. .. .. .. .. .. 0.651 0.593
0.844 0.873 0.835 0.870 0.828 0.857 0.782 .. 0.795 0.816 0.833 0.827 0.786 0.807 0.742 0.809 0.802 0.811 0.790 0.777 .. 0.794 0.749 0.764 0.788 .. .. 0.778 0.766 0.690 0.747 .. 0.784 0.717 0.747 0.753 0.743 0.706 .. .. 0.708 0.721 0.693 0.698 0.697 .. .. 0.686 .. 0.700 0.677 .. .. .. 0.698 0.693 0.649
0.913 0.906 0.882 0.897 0.878 0.879 0.869 .. 0.864 0.894 0.873 0.868 0.824 0.863 0.830 0.861 0.856 0.876 0.839 0.846 0.805 0.837 0.839 0.825 0.854 0.801 0.816 0.833 0.802 0.753 0.800 .. 0.818 0.776 0.779 0.799 0.784 0.775 0.770 0.749 0.778 0.773 0.732 0.749 0.749 0.748 .. 0.736 0.774 0.704 0.681 0.764 0.752 .. 0.715 0.726 0.718
0.938 0.918 0.890 0.902 0.899 0.892 0.898 .. 0.895 0.896 0.890 0.886 0.850 0.893 0.866 0.885 0.874 0.873 0.860 0.869 0.848 0.875 0.857 0.861 0.865 0.835 0.854 0.855 0.856 0.807 0.809 .. 0.830 0.821 0.810 0.825 0.818 0.803 0.791 0.793 0.789 0.795 0.784 0.779 0.765 0.780 0.787 0.748 0.788 0.748 0.725 0.766 0.766 0.757 0.749 0.746 0.741
0.941 0.926 0.905 0.906 0.906 0.903 0.905 .. 0.900 0.898 0.899 0.895 0.888 0.897 0.889 0.891 0.884 0.883 0.879 0.880 0.876 0.877 0.874 0.870 0.863 0.856 0.863 0.860 0.863 0.841 0.837 .. 0.835 0.828 0.829 0.827 0.818 0.811 0.807 0.802 0.805 0.805 0.798 0.798 0.788 0.793 0.790 0.773 0.777 0.778 0.770 0.767 0.769 0.768 0.766 0.763 0.762
0.941 0.927 0.909 0.908 0.908 0.907 0.907 0.904 0.903 0.901 0.901 0.899 0.894 0.896 0.894 0.893 0.886 0.885 0.883 0.883 0.882 0.880 0.876 0.873 0.865 0.864 0.863 0.862 0.862 0.845 0.839 0.838 0.837 0.832 0.832 0.830 0.825 0.814 0.811 0.805 0.808 0.805 0.802 0.802 0.794 0.794 0.791 0.780 0.779 0.779 0.773 0.771 0.770 0.769 0.768 0.767 0.767
0.943 0.929 0.910 0.910 0.908 0.908 0.908 0.905 0.905 0.904 0.903 0.901 0.898 0.898 0.897 0.895 0.888 0.886 0.885 0.884 0.884 0.882 0.878 0.874 0.867 0.866 0.865 0.863 0.861 0.846 0.840 0.838 0.838 0.835 0.834 0.832 0.831 0.816 0.813 0.810 0.809 0.806 0.805 0.805 0.797 0.796 0.793 0.783 0.782 0.781 0.776 0.773 0.771 0.771 0.771 0.770 0.770
0 0 5 –1 0 3 –3 .. –2 –2 1 1 14 –3 3 –2 –1 –1 1 –1 4 –7 0 –3 –3 3 –1 0 –5 3 5 .. –2 –2 0 –3 –1 0 2 0 2 –3 –1 3 3 0 –2 5 –5 2 10 –3 –3 –3 0 0 2
0 0 0 0 0 0 0 0 0 0 0 0 1 –1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 –1 0 0 0 1 –1 0 0 0 0 0 0 0 1 1 2 0
0.55 0.29 0.45 0.27 0.41 0.34 0.68 .. 0.69 0.45 0.35 0.47 0.77 0.53 1.13 0.43 0.49 0.51 0.58 0.66 .. 0.49 0.77 0.64 0.56 .. .. 0.48 0.58 0.96 .. .. 0.36 .. .. 0.54 0.54 0.50 .. .. 0.76 0.69 .. 0.79 0.57 .. .. 0.56 .. .. .. .. .. .. .. 0.55 0.85
0.53 0.30 0.41 0.21 0.44 0.28 0.71 .. 0.62 0.49 0.38 0.41 0.64 0.51 0.91 0.48 0.49 0.42 0.55 0.62 .. 0.51 0.76 0.64 0.45 .. .. 0.50 0.56 0.97 0.56 .. 0.32 0.73 0.53 0.48 0.54 0.70 .. .. 0.64 0.54 0.72 0.68 0.64 .. .. 0.63 .. 0.52 0.65 .. .. .. 0.48 0.50 0.82
0.29 0.23 0.29 0.13 0.31 0.30 0.40 .. 0.43 0.09 0.30 0.33 0.78 0.36 0.72 0.35 0.34 0.10 0.48 0.40 0.85 0.48 0.42 0.52 0.13 0.71 0.53 0.33 0.64 1.06 0.44 .. 0.22 0.66 0.62 0.37 0.53 0.48 0.50 0.70 0.35 0.38 0.87 0.65 0.57 0.57 .. 0.56 0.09 0.95 1.19 0.11 0.23 .. 0.68 0.55 0.64
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human development Index trends, 1980–2011
Human Development Index (HDI) HDI rank 1980
table
HDI rank Changea 2010 2011
Average annual HDI growth (%)
Value 1990 2000 2005 2009
2006–2011 2010–2011 1980–2011 1990–2011 2000–2011
2
58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94
Panama Serbia Antigua and Barbuda Malaysia Trinidad and Tobago Kuwait Libya Belarus Russian Federation Grenada Kazakhstan Costa Rica Albania Lebanon Saint Kitts and Nevis Venezuela, Bolivarian Republic of Bosnia and Herzegovina Georgia Ukraine Mauritius Former Yugoslav Republic of Macedonia Jamaica Peru Dominica Saint Lucia Ecuador Brazil Saint Vincent and the Grenadines Armenia Colombia Iran, Islamic Republic of Oman Tonga Azerbaijan Turkey Belize Tunisia
0.628 .. .. 0.559 0.673 0.688 .. .. .. .. .. 0.614 .. .. .. 0.623 .. .. .. 0.546 .. 0.607 0.574 .. .. 0.591 0.549 .. .. 0.550 0.437 .. .. .. 0.463 0.619 0.450 0.541 0.454 0.539 0.532 .. 0.566 0.404 .. 0.486 .. 0.466 0.522 0.544 0.507 .. .. .. 0.550 0.406 .. .. .. 0.501 0.446 0.497 ..
0.660 .. .. 0.631 0.676 0.712 .. .. .. .. .. 0.656 0.656 .. .. 0.629 .. .. 0.707 0.618 .. 0.637 0.612 .. .. 0.636 0.600 .. .. 0.594 0.534 .. 0.649 .. 0.558 0.651 0.542 0.591 0.551 0.583 0.577 .. 0.624 0.490 .. 0.566 .. 0.524 0.605 0.572 0.560 .. 0.540 .. 0.571 0.497 .. .. .. 0.489 0.594 0.548 0.564
0.718 0.719 .. 0.705 0.701 0.754 .. .. 0.691 .. 0.657 0.703 0.691 .. .. 0.656 .. .. 0.669 0.672 .. 0.680 0.674 0.699 .. 0.668 0.665 .. 0.643 0.652 0.636 .. 0.681 .. 0.634 0.668 0.630 0.646 0.624 0.633 0.640 0.657 0.668 0.588 .. 0.626 .. 0.619 0.621 0.612 0.612 0.576 0.555 0.586 0.602 0.585 .. .. .. 0.579 0.585 0.583 0.577
0.740 0.744 .. 0.738 0.728 0.752 0.741 0.723 0.725 .. 0.714 0.723 0.721 0.711 .. 0.692 0.717 0.707 0.712 0.703 0.704 0.702 0.691 0.709 .. 0.695 0.692 .. 0.689 0.675 0.671 0.694 0.696 .. 0.671 0.689 0.667 0.673 0.667 0.662 0.658 0.676 0.678 0.633 0.654 0.656 0.659 0.652 0.648 0.635 0.649 0.619 0.611 0.631 0.622 0.611 .. 0.611 0.633 0.606 0.601 0.621 0.593
0.760 0.761 .. 0.752 0.755 0.757 0.763 0.746 0.747 .. 0.733 0.738 0.734 0.733 .. 0.732 0.730 0.724 0.720 0.722 0.725 0.724 0.714 0.722 .. 0.716 0.708 .. 0.712 0.702 0.703 0.703 0.701 .. 0.690 0.696 0.692 0.694 0.691 0.680 0.680 0.685 0.685 0.674 0.677 0.673 0.674 0.669 0.664 0.651 0.656 0.650 0.642 0.638 0.636 0.638 .. 0.631 0.635 0.624 0.626 0.630 0.617
0.765 0.764 0.763 0.758 0.758 0.758 0.770 0.751 0.751 0.746 0.740 0.742 0.737 0.737 0.735 0.734 0.731 0.729 0.725 0.726 0.726 0.726 0.721 0.723 0.720 0.718 0.715 0.715 0.714 0.707 0.707 0.704 0.703 0.699 0.696 0.698 0.698 0.697 0.696 0.686 0.686 0.686 0.687 0.682 0.681 0.680 0.677 0.672 0.670 0.662 0.660 0.658 0.647 0.644 0.641 0.644 0.640 0.636 0.635 0.629 0.631 0.631 0.622
0.768 0.766 0.764 0.761 0.760 0.760 0.760 0.756 0.755 0.748 0.745 0.744 0.739 0.739 0.735 0.735 0.733 0.733 0.729 0.728 0.728 0.727 0.725 0.724 0.723 0.720 0.718 0.717 0.716 0.710 0.707 0.705 0.704 0.700 0.699 0.699 0.698 0.698 0.698 0.691 0.689 0.688 0.688 0.687 0.686 0.682 0.680 0.674 0.674 0.665 0.663 0.661 0.653 0.649 0.644 0.644 0.641 0.641 0.636 0.633 0.633 0.632 0.625
2 –2 .. 2 2 –8 –5 1 –1 .. 2 –1 –1 3 .. 7 –2 1 –3 1 1 –2 4 –7 .. 0 3 .. –3 4 2 –2 –5 .. 2 –3 3 1 2 2 2 –6 –5 6 1 –1 –3 –1 0 1 –3 2 4 –2 1 2 .. 2 –5 1 1 –6 2
1 1 1 3 1 –1 –10 0 0 0 1 –1 1 –1 0 0 0 0 3 0 –2 –1 1 –1 0 0 1 –1 0 1 –1 0 0 0 3 –1 –1 –1 0 1 2 0 –3 0 0 0 0 0 0 0 0 0 0 0 1 –1 0 0 0 2 –1 –1 1
0.65 .. .. 1.00 0.40 0.32 .. .. .. .. .. 0.62 .. .. .. 0.54 .. .. .. 0.93 .. 0.59 0.75 .. .. 0.64 0.87 .. .. 0.83 1.57 .. .. .. 1.34 0.39 1.43 0.83 1.40 0.80 0.83 .. 0.63 1.73 .. 1.10 .. 1.20 0.83 0.65 0.87 .. .. .. 0.51 1.50 .. .. .. 0.76 1.14 0.78 ..
0.73 .. .. 0.90 0.56 0.31 .. .. .. .. .. 0.60 0.57 .. .. 0.74 .. .. 0.15 0.78 .. 0.64 0.81 .. .. 0.59 0.86 .. .. 0.85 1.35 .. 0.39 .. 1.08 0.34 1.21 0.80 1.13 0.81 0.84 .. 0.47 1.62 .. 0.89 .. 1.21 0.52 0.71 0.81 .. 0.91 .. 0.58 1.24 .. .. .. 1.23 0.30 0.68 0.49
0.62 0.58 .. 0.69 0.74 0.07 .. .. 0.81 .. 1.15 0.51 0.61 .. .. 1.04 .. .. 0.78 0.73 .. 0.62 0.67 0.33 .. 0.69 0.69 .. 0.99 0.77 0.97 .. 0.30 .. 0.90 0.42 0.94 0.70 1.03 0.80 0.67 0.43 0.27 1.43 .. 0.78 .. 0.79 0.75 0.76 0.73 1.27 1.49 0.92 0.62 0.88 .. .. .. 0.81 0.71 0.73 0.72
MEDIUM HUMAN DEVELOPMENT 95 Jordan 96 Algeria 97 Sri Lanka 98 Dominican Republic 99 Samoa 100 Fiji 101 China 102 Turkmenistan 103 Thailand 104 Suriname 105 El Salvador 106 Gabon 107 Paraguay 108 Bolivia, Plurinational State of 109 Maldives 110 Mongolia 111 Moldova, Republic of 112 Philippines 113 Egypt 114 Occupied Palestinian Territory 115 Uzbekistan 116 Micronesia, Federated States of 117 Guyana 118 Botswana 119 Syrian Arab Republic 120 Namibia
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human development Index trends, 1980–2011
Human Development Index (HDI) HDI rank 1980 1990 2000 Value 2005 2009 2010 2011 HDI rank Changea Average annual HDI growth (%)
2006–2011 2010–2011 1980–2011 1990–2011 2000–2011
121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141
Honduras Kiribati South Africa Indonesia Vanuatu Kyrgyzstan Tajikistan Viet Nam Nicaragua Morocco Guatemala Iraq Cape Verde India Ghana Equatorial Guinea Congo Lao People’s Democratic Republic Cambodia Swaziland Bhutan
0.451 .. 0.564 0.423 .. .. .. .. 0.457 0.364 0.428 .. .. 0.344 0.385 .. 0.465 .. .. .. .. .. 0.420 .. 0.359 0.303 .. .. 0.279 0.370 .. .. 0.313 .. 0.317 .. 0.242 0.332 0.332 0.418 .. 0.347 .. 0.401 .. 0.275 0.252 0.272 0.264 0.347 0.270 0.198 0.366 .. 0.174 .. .. .. 0.283 0.248 .. 0.335 ..
0.513 .. 0.615 0.481 .. .. .. 0.435 0.473 0.435 0.462 .. .. 0.410 0.418 .. 0.502 0.376 .. 0.526 .. .. 0.456 .. 0.399 0.352 .. .. 0.298 0.427 .. 0.352 0.368 .. 0.365 .. 0.340 0.397 0.353 0.470 0.299 0.368 .. 0.394 .. 0.232 0.316 0.317 0.298 0.361 0.291 0.246 0.425 .. 0.204 .. .. .. 0.310 0.241 .. .. ..
0.569 .. 0.616 0.543 .. 0.577 0.527 0.528 0.533 0.507 0.525 .. 0.523 0.461 0.451 0.488 0.478 0.448 0.438 0.492 .. 0.479 0.443 .. 0.436 0.422 0.404 0.384 0.380 0.427 0.427 0.364 0.423 0.374 0.399 .. 0.398 0.421 0.410 0.427 0.372 0.408 .. 0.371 .. 0.313 0.378 0.360 0.357 0.374 0.343 0.230 0.372 0.274 0.275 .. .. .. 0.306 0.252 .. 0.306 0.286
0.597 .. 0.599 0.572 .. 0.595 0.575 0.561 0.566 0.552 0.550 0.552 0.543 0.504 0.484 0.516 0.506 0.484 0.491 0.493 .. 0.502 0.467 0.483 0.480 0.462 0.448 0.445 0.436 0.449 0.465 0.420 0.435 0.422 0.432 0.429 0.424 0.429 0.432 0.417 0.401 0.419 0.428 0.394 0.402 0.376 0.409 0.384 0.383 0.383 0.351 0.340 0.347 0.313 0.319 0.340 .. 0.326 0.311 0.306 0.302 0.300 0.312
0.619 .. 0.610 0.607 .. 0.611 0.600 0.584 0.582 0.575 0.569 0.565 0.564 0.535 0.527 0.534 0.523 0.514 0.513 0.515 .. 0.504 0.499 0.503 0.499 0.491 0.487 0.481 0.474 0.475 0.483 0.454 0.457 0.452 0.453 0.449 0.449 0.449 0.447 0.440 0.438 0.429 0.430 0.419 0.425 0.419 0.422 0.413 0.403 0.397 0.387 0.387 0.349 0.353 0.352 0.348 .. 0.341 0.334 0.329 0.326 0.320 0.323
0.623 0.621 0.615 0.613 0.615 0.611 0.604 0.590 0.587 0.579 0.573 0.567 0.566 0.542 0.533 0.534 0.528 0.520 0.518 0.520 0.518 0.507 0.505 0.506 0.503 0.496 0.491 0.482 0.479 0.479 0.481 0.461 0.462 0.460 0.457 0.454 0.455 0.449 0.451 0.446 0.442 0.433 0.431 0.425 0.427 0.425 0.425 0.418 0.406 0.401 0.395 0.394 0.364 0.358 0.356 0.351 0.345 0.342 0.339 0.334 0.329 0.325 0.326
0.625 0.624 0.619 0.617 0.617 0.615 0.607 0.593 0.589 0.582 0.574 0.573 0.568 0.547 0.541 0.537 0.533 0.524 0.523 0.522 0.522 0.510 0.509 0.509 0.504 0.500 0.495 0.486 0.483 0.482 0.480 0.466 0.466 0.462 0.459 0.459 0.458 0.454 0.453 0.450 0.446 0.435 0.433 0.430 0.430 0.429 0.427 0.420 0.408 0.400 0.400 0.398 0.376 0.363 0.359 0.353 0.349 0.344 0.343 0.336 0.331 0.329 0.328
–1 .. –1 2 .. –1 –1 1 –1 0 2 –1 –1 1 5 –2 0 3 –1 –1 .. –5 2 –1 –1 1 1 1 2 0 –5 7 1 4 –2 –4 0 –2 –4 1 3 0 –3 2 0 2 –4 –1 0 0 0 0 0 2 2 –2 .. –2 0 0 1 1 –2
–1 0 1 1 –2 0 0 0 0 0 0 0 0 0 1 –1 0 1 2 –2 –1 0 1 –1 0 0 0 0 1 1 –2 1 –1 0 0 1 –1 1 –1 0 0 0 0 1 –1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 –1
1.06 .. 0.30 1.23 .. .. .. .. 0.83 1.52 0.95 .. .. 1.51 1.10 .. 0.44 .. .. .. .. .. 0.62 .. 1.10 1.63 .. .. 1.78 0.85 .. .. 1.29 .. 1.20 .. 2.08 1.02 1.01 0.24 .. 0.73 .. 0.23 .. 1.44 1.71 1.41 1.41 0.45 1.27 2.28 0.09 .. 2.37 .. .. .. 0.62 0.99 .. –0.06 ..
0.94 .. 0.03 1.19 .. .. .. 1.50 1.05 1.39 1.04 .. .. 1.38 1.23 .. 0.28 1.59 .. –0.03 .. .. 0.52 .. 1.12 1.69 .. .. 2.32 0.58 .. 1.35 1.12 .. 1.10 .. 1.43 0.64 1.20 –0.22 1.93 0.80 .. 0.42 .. 2.97 1.44 1.35 1.52 0.50 1.52 2.32 –0.58 .. 2.74 .. .. .. 0.48 1.61 .. .. ..
0.86 .. 0.05 1.17 .. 0.59 1.30 1.06 0.92 1.26 0.81 .. 0.75 1.56 1.66 0.88 0.99 1.44 1.62 0.54 .. 0.58 1.27 .. 1.33 1.55 1.86 2.18 2.21 1.11 1.07 2.27 0.87 1.93 1.28 .. 1.30 0.68 0.92 0.47 1.65 0.58 .. 1.37 .. 2.92 1.10 1.41 1.23 0.61 1.41 5.10 0.11 2.57 2.47 .. .. .. 1.05 2.65 .. 0.64 1.26
table
2
LOW HUMAN DEVELOPMENT 142 Solomon Islands 143 Kenya 144 São Tomé and Príncipe 145 Pakistan 146 Bangladesh 147 Timor-Leste 148 Angola 149 Myanmar 150 Cameroon 151 Madagascar 152 Tanzania, United Republic of 153 Papua New Guinea 154 Yemen 155 Senegal 156 Nigeria 157 Nepal 158 Haiti 159 Mauritania 160 Lesotho 161 Uganda 162 Togo 163 Comoros 164 Zambia 165 Djibouti 166 Rwanda 167 Benin 168 Gambia 169 Sudan 170 Côte d'Ivoire 171 Malawi 172 Afghanistan 173 Zimbabwe 174 Ethiopia 175 Mali 176 Guinea-Bissau 177 Eritrea 178 Guinea 179 Central African Republic 180 Sierra Leone 181 Burkina Faso 182 Liberia 183 Chad
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human development Index trends, 1980–2011
Human Development Index (HDI) HDI rank 1980
table
HDI rank Changea 2010 2011
Average annual HDI growth (%)
Value 1990 2000 2005 2009
2006–2011 2010–2011 1980–2011 1990–2011 2000–2011
2
184 185 186 187
Mozambique Burundi Niger Congo, Democratic Republic of the
.. 0.200 0.177 0.282 0.766 0.614 b 0.420 b 0.316 0.444 0.428 b 0.644 b 0.582 0.356 0.365 0.288 b 0.529 b 0.558 b
0.200 0.250 0.193 0.289 0.810 0.648 b 0.480 0.347 0.516 0.498 b 0.680 b 0.624 0.418 0.383 0.320 b 0.565 b 0.594
0.245 0.245 0.229 0.224 0.858 0.687 0.548 0.383 0.578 0.581 0.695 0.680 0.468 0.401 0.363 0.596 b 0.634
0.285 0.267 0.265 0.260 0.876 0.716 0.587 0.422 0.609 0.622 0.728 0.703 0.510 0.431 0.401 0.616 0.660
0.312 0.308 0.285 0.277 0.885 0.734 0.618 0.448 0.634 0.658 0.744 0.722 0.538 0.456 0.431 0.635 0.676
0.317 0.313 0.293 0.282 0.888 0.739 0.625 0.453 0.639 0.666 0.748 0.728 0.545 0.460 0.435 0.638 0.679
0.322 0.316 0.295 0.286 0.889 0.741 0.630 0.456 0.641 0.671 0.751 0.731 0.548 0.463 0.439 0.640 0.682
0 0 0 0 — — — — — — — — — — — — —
0 0 0 0 — — — — — — — — — — — — —
.. 1.49 1.67 0.05 0.48 0.61 1.31 1.19 1.19 1.46 0.50 0.73 1.40 0.77 1.37 0.62 0.65
2.28 1.12 2.05 –0.04 0.44 0.64 1.30 1.31 1.04 1.43 0.47 0.76 1.31 0.90 1.51 0.59 0.66
2.49 2.33 2.33 2.25 0.33 0.70 1.28 1.59 0.94 1.31 0.71 0.66 1.45 1.31 1.73 0.65 0.66
Human Development Index groups Very high human development High human development Medium human development Low human development Regions Arab States East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean South Asia Sub-Saharan Africa Least developed countries Small island developing states World
NOTES a. A positive value indicates improvement in rank. b. Based on less than half the countries in the group or region. DEFINITION Human Development Index (HDI): A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge and a decent standard of living. See Technical note 1 for details on how the HDI is calculated. MAIN DATA SOURCES Columns 1–7: HDRO calculations based on data from UNDESA (2011), Barro and Lee (2010b), UNESCO Institute for Statistics (2011), World Bank (2011a), UNSD (2011) and IMF (2011). Columns 8–12: Calculated based on Human Development Index values in the relevant year.
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3
table
Inequality-adjusted Human Development Index
Human Development Index (HDI) Value 2011 Inequality-adjusted HDI Value 2011 Overall loss (%) 2011 Change in ranka 2011 Inequality-adjusted life expectancy index Value 2011 Loss (%) 2011 Inequality-adjusted education index Value 2011 Loss (%) 2011 Inequality-adjusted income index Value 2011 Loss (%) 2011 Quintile income ratio Income Gini coefficient
HDI rank
2000–2011b 2000–2011b
VERY HIGH HUMAN DEVELOPMENT 1 Norway 2 Australia 3 Netherlands 4 United States 5 New Zealand 6 Canada 7 Ireland 8 Liechtenstein 9 Germany 10 Sweden 11 Switzerland 12 Japan 13 Hong Kong, China (SAR) 14 Iceland 15 Korea, Republic of 16 Denmark 17 Israel 18 Belgium 19 Austria 20 France 21 Slovenia 22 Finland 23 Spain 24 Italy 25 Luxembourg 26 Singapore 27 Czech Republic 28 United Kingdom 29 Greece 30 United Arab Emirates 31 Cyprus 32 Andorra 33 Brunei Darussalam 34 Estonia 35 Slovakia 36 Malta 37 Qatar 38 Hungary 39 Poland 40 Lithuania 41 Portugal 42 Bahrain 43 Latvia 44 Chile 45 Argentina 46 Croatia 47 Barbados HIGH HUMAN DEVELOPMENT 48 Uruguay 49 Palau 50 Romania 51 Cuba 52 Seychelles 53 Bahamas 54 Montenegro 55 Bulgaria 56 Saudi Arabia 57 Mexico
0.943 0.929 0.910 0.910 0.908 0.908 0.908 0.905 0.905 0.904 0.903 0.901 0.898 0.898 0.897 0.895 0.888 0.886 0.885 0.884 0.884 0.882 0.878 0.874 0.867 0.866 0.865 0.863 0.861 0.846 0.840 0.838 0.838 0.835 0.834 0.832 0.831 0.816 0.813 0.810 0.809 0.806 0.805 0.805 0.797 0.796 0.793 0.783 0.782 0.781 0.776 0.773 0.771 0.771 0.771 0.770 0.770
0.890 0.856 0.846 0.771 .. 0.829 0.843 .. 0.842 0.851 0.840 .. .. 0.845 0.749 0.842 0.779 0.819 0.820 0.804 0.837 0.833 0.799 0.779 0.799 .. 0.821 0.791 0.756 .. 0.755 .. .. 0.769 0.787 .. .. 0.759 0.734 0.730 0.726 .. 0.717 0.652 0.641 0.675 .. 0.654 .. 0.683 .. .. 0.658 0.718 0.683 .. 0.589
5.6 7.9 7.0 15.3 .. 8.7 7.2 .. 6.9 5.9 7.0 .. .. 5.9 16.5 6.0 12.3 7.6 7.4 9.1 5.3 5.6 8.9 10.9 7.8 .. 5.0 8.4 12.2 .. 10.1 .. .. 7.9 5.7 .. .. 7.0 9.7 9.8 10.2 .. 10.9 19.0 19.5 15.1 .. 16.4 .. 12.6 .. .. 14.7 6.9 11.4 .. 23.5
0 0 –1 –19 .. –7 0 .. 0 5 0 .. .. 5 –17 4 –8 –1 1 0 7 7 2 –2 3 .. 9 4 –2 .. –2 .. .. 2 7 .. .. 3 0 0 0 .. –1 –11 –13 –3 .. –7 .. 1 .. .. –3 7 3 .. –15
0.928 0.931 0.917 0.863 0.907 0.914 0.915 .. 0.915 0.937 0.943 0.965 0.961 0.945 0.916 0.887 0.934 0.905 0.920 0.930 0.898 0.909 0.929 0.938 0.913 0.936 0.874 0.903 0.900 0.836 0.901 .. 0.862 0.813 0.825 0.892 0.854 0.809 0.834 0.765 0.893 0.815 0.782 0.871 0.796 0.844 0.814 0.815 .. 0.770 0.883 .. 0.782 0.803 0.776 0.753 0.801
3.7 4.7 4.3 6.6 5.2 5.0 4.3 .. 4.0 3.3 4.1 3.5 2.9 3.0 4.3 4.4 3.9 4.4 4.2 4.2 4.1 3.9 4.1 3.9 3.5 2.9 3.9 4.8 4.8 6.3 4.1 .. 5.8 6.0 5.7 5.1 7.2 5.7 5.8 7.2 4.9 6.2 7.1 6.6 9.7 5.5 9.2 9.3 .. 9.6 5.4 .. 10.9 6.8 7.8 11.5 10.9
0.964 0.964 0.895 0.905 .. 0.897 0.933 .. 0.911 0.869 0.854 .. .. 0.888 0.696 0.895 0.835 0.825 0.838 0.791 0.904 0.858 0.826 0.758 0.724 .. 0.912 0.797 0.738 .. 0.678 .. .. 0.891 0.861 .. .. 0.831 0.768 0.847 0.697 .. 0.840 0.688 0.708 0.697 .. 0.681 .. 0.789 .. .. 0.618 0.782 0.754 .. 0.567
2.2 1.7 3.9 3.7 .. 3.2 3.2 .. 1.8 3.9 2.0 .. .. 2.6 25.5 3.1 7.9 6.5 2.4 9.1 3.1 2.1 5.5 11.4 6.2 .. 1.3 2.2 14.3 .. 15.0 .. .. 2.7 1.6 .. .. 4.0 6.6 4.1 5.6 .. 3.8 13.7 12.1 10.4 .. 10.8 .. 5.0 .. .. 7.9 2.5 5.9 .. 21.9
0.789 0.698 0.739 0.587 .. 0.696 0.701 .. 0.717 0.756 0.735 .. .. 0.718 0.659 0.751 0.607 0.735 0.715 0.705 0.723 0.740 0.666 0.665 0.771 .. 0.695 0.688 0.649 .. 0.704 .. .. 0.627 0.686 .. .. 0.650 0.619 0.601 0.616 .. 0.561 0.462 0.468 0.523 .. 0.505 .. 0.524 .. .. 0.588 0.589 0.543 .. 0.451
10.6 16.6 12.5 32.4 .. 17.1 13.8 .. 14.5 10.3 14.3 .. .. 11.8 18.4 10.2 23.7 11.7 15.1 13.9 8.5 10.6 16.7 16.8 13.5 .. 9.6 17.3 17.1 .. 10.9 .. .. 14.5 9.6 .. .. 11.2 16.3 17.5 19.3 .. 21.0 34.1 34.4 27.8 .. 27.8 .. 22.2 .. .. 24.5 11.3 19.9 .. 35.6
3.9 7.0 5.1 8.5 6.8 5.5 5.7 .. 4.3 4.0 5.4 3.4 9.6 .. 4.7 4.3 7.9 4.9 4.4 5.6 4.8 3.8 6.0 6.5 .. 9.8 3.5 7.2 6.2 .. .. .. .. 6.3 4.0 .. 13.3 4.8 5.6 6.7 7.9 .. 6.3 3.6 12.3 5.2 .. 8.7 .. 4.9 .. 2.7 .. 4.6 10.2 .. 14.4
25.8 .. .. 40.8 .. 32.6 34.3 .. 28.3 25.0 33.7 .. 43.4 .. .. .. 39.2 33.0 29.1 .. 31.2 26.9 34.7 36.0 .. .. .. .. 34.3 .. .. .. .. 36.0 .. .. 41.1 31.2 34.2 37.6 .. .. 35.7 52.1 45.8 33.7 .. 42.4 .. 31.2 .. 19.0 .. 30.0 45.3 .. 51.7
STATISTICAL TAbLeS
135
Inequality-adjusted human development Index
Human Development Index (HDI) Value 2011 Inequality-adjusted HDI Value 2011 Overall loss (%) 2011 Change in ranka 2011 Inequality-adjusted life expectancy index Value 2011 Loss (%) 2011 Inequality-adjusted education index Value 2011 Loss (%) 2011 Inequality-adjusted income index Value 2011 Loss (%) 2011
HDI rank
Quintile income ratio
Income Gini coefficient
2000–2011b 2000–2011b
table
3
58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94
Panama Serbia Antigua and Barbuda Malaysia Trinidad and Tobago Kuwait Libya Belarus Russian Federation Grenada Kazakhstan Costa Rica Albania Lebanon Saint Kitts and Nevis Venezuela, Bolivarian Republic of Bosnia and Herzegovina Georgia Ukraine Mauritius Former Yugoslav Republic of Macedonia Jamaica Peru Dominica Saint Lucia Ecuador Brazil Saint Vincent and the Grenadines Armenia Colombia Iran, Islamic Republic of Oman Tonga Azerbaijan Turkey Belize Tunisia
0.768 0.766 0.764 0.761 0.760 0.760 0.760 0.756 0.755 0.748 0.745 0.744 0.739 0.739 0.735 0.735 0.733 0.733 0.729 0.728 0.728 0.727 0.725 0.724 0.723 0.720 0.718 0.717 0.716 0.710 0.707 0.705 0.704 0.700 0.699 0.699 0.698 0.698 0.698 0.691 0.689 0.688 0.688 0.687 0.686 0.682 0.680 0.674 0.674 0.665 0.663 0.661 0.653 0.649 0.644 0.644 0.641 0.641 0.636 0.633 0.633
0.579 0.694 .. .. 0.644 .. .. 0.693 0.670 .. 0.656 0.591 0.637 0.570 .. 0.540 0.649 0.630 0.662 0.631 0.609 0.610 0.557 .. .. 0.535 0.519 .. 0.639 0.479 .. .. .. 0.620 0.542 .. 0.523 0.565 .. 0.579 0.510 .. .. 0.534 .. 0.537 0.518 0.495 0.543 0.505 0.437 0.495 0.563 0.569 0.516 0.489 .. 0.544 0.390 0.492 ..
24.6 9.5 .. .. 15.3 .. .. 8.3 11.3 .. 11.9 20.5 13.9 22.8 .. 26.6 11.6 14.1 9.2 13.3 16.4 16.2 23.2 .. .. 25.8 27.7 .. 10.8 32.5 .. .. .. 11.4 22.5 .. 25.2 19.0 .. 16.2 25.9 .. .. 22.3 .. 21.3 23.8 26.6 19.5 24.0 34.1 25.2 13.8 12.2 19.9 24.1 .. 15.1 38.6 22.3 ..
–15 9 .. .. –2 .. .. 10 7 .. 5 –7 0 –9 .. –16 7 2 14 5 2 4 –5 .. .. –10 –13 .. 13 –24 .. .. .. 11 –2 .. –7 5 .. 9 –9 .. .. –1 .. 2 –3 –11 8 –4 –12 –6 15 18 4 –5 .. 17 –12 –1 ..
0.776 0.788 .. 0.798 0.659 0.803 0.781 0.736 0.687 0.798 0.621 0.863 0.797 0.718 .. 0.753 0.794 0.720 0.684 0.760 0.784 0.710 0.726 .. 0.773 0.753 0.723 0.710 0.728 0.731 0.701 0.776 0.712 0.636 0.742 0.776 0.751 0.732 0.716 0.785 0.707 0.717 0.676 0.730 0.520 0.768 0.678 0.698 0.486 0.680 0.550 0.832 0.622 0.691 0.652 0.723 0.725 0.577 0.624 0.616 0.396
12.4 8.3 .. 6.7 16.6 6.7 9.7 7.4 10.8 9.6 16.2 7.8 11.2 13.5 .. 12.2 9.6 15.1 10.5 9.8 9.4 15.3 14.8 .. 10.4 14.1 14.4 14.0 14.9 13.7 16.1 7.2 13.8 20.6 12.8 12.2 12.6 13.1 14.5 9.4 16.0 13.4 13.0 13.5 26.7 10.1 15.0 15.2 27.8 17.8 25.1 7.3 18.8 11.2 15.2 13.9 13.1 24.3 19.2 21.7 24.3
0.611 0.712 .. .. 0.665 .. .. 0.735 0.696 .. 0.790 0.543 0.635 0.528 .. 0.567 0.685 0.812 0.806 0.570 0.574 0.704 0.535 .. .. 0.535 0.492 .. 0.710 0.515 .. .. .. 0.615 0.423 .. 0.396 0.551 .. 0.558 0.451 .. .. 0.478 .. 0.490 0.508 0.431 0.612 0.515 0.542 0.334 0.680 0.673 0.592 0.331 .. 0.701 0.534 0.574 ..
17.8 9.9 .. .. 6.6 .. .. 5.4 11.2 .. 5.3 17.7 11.9 24.1 .. 18.1 5.2 3.3 6.1 13.5 17.5 8.3 24.0 .. .. 22.1 25.7 .. 6.5 22.8 .. .. .. 8.3 27.4 .. 38.7 22.4 .. 17.9 26.8 .. .. 23.2 .. 18.0 20.1 32.4 7.3 19.8 27.6 41.2 5.8 6.1 13.5 40.9 .. 1.4 22.4 11.7 ..
0.410 0.595 .. .. 0.610 .. .. 0.617 0.628 .. 0.576 0.442 0.510 0.489 .. 0.368 0.502 0.428 0.526 0.581 0.502 0.454 0.444 .. .. 0.379 0.392 .. 0.504 0.292 .. .. .. 0.610 0.506 .. 0.480 0.449 .. 0.442 0.417 .. .. 0.436 .. 0.411 0.403 0.403 0.536 0.368 0.280 0.436 0.422 0.397 0.356 0.487 .. 0.399 0.179 0.337 ..
40.5 10.3 .. 0.0 21.9 .. .. 12.1 11.9 .. 13.8 33.7 18.3 30.0 .. 44.9 19.3 22.7 10.9 16.6 21.8 24.1 30.0 .. .. 38.8 40.7 .. 10.8 53.9 .. .. .. 4.5 26.5 .. 21.8 21.1 .. 20.8 33.8 .. .. 29.5 .. 34.0 34.9 31.1 22.1 33.4 47.2 23.2 16.4 18.9 30.0 14.2 .. 17.9 63.1 32.1 ..
15.8 4.1 .. 11.4 8.3 .. .. 4.0 8.2 .. 4.6 13.2 5.3 .. .. 10.0 6.4 8.9 3.9 .. 9.3 9.8 13.5 .. .. 12.8 17.6 .. 4.5 24.8 7.0 .. .. 5.3 8.0 17.2 8.0 6.3 6.1 6.9 12.2 .. .. 8.4 7.9 15.0 .. 12.1 7.9 14.9 21.8 6.8 6.2 6.7 9.0 4.6 .. 6.2 .. .. 21.0
52.3 28.2 .. 46.2 .. .. .. 27.2 42.3 .. 30.9 50.3 34.5 .. .. 43.5 36.2 41.3 27.5 .. 44.2 45.5 48.0 .. 42.6 49.0 53.9 .. 30.9 58.5 38.3 .. .. 33.7 39.7 .. 40.8 37.7 .. 40.3 48.4 .. .. 41.5 .. 53.6 52.8 46.9 41.5 52.0 57.3 37.4 36.5 38.0 44.0 32.1 .. 36.7 .. 43.2 ..
MEDIUM HUMAN DEVELOPMENT 95 Jordan 96 Algeria 97 Sri Lanka 98 Dominican Republic 99 Samoa 100 Fiji 101 China 102 Turkmenistan 103 Thailand 104 Suriname 105 El Salvador 106 Gabon 107 Paraguay 108 Bolivia, Plurinational State of 109 Maldives 110 Mongolia 111 Moldova, Republic of 112 Philippines 113 Egypt 114 Occupied Palestinian Territory 115 Uzbekistan 116 Micronesia, Federated States of 117 Guyana 118 Botswana
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human development report 2011
Inequality-adjusted human development Index
Human Development Index (HDI) Value 2011 Inequality-adjusted HDI Value 2011 Overall loss (%) 2011 Change in ranka 2011 Inequality-adjusted life expectancy index Value 2011 Loss (%) 2011 Inequality-adjusted education index Value 2011 Loss (%) 2011 Inequality-adjusted income index Value 2011 Loss (%) 2011
HDI rank
Quintile income ratio
Income Gini coefficient
2000–2011b 2000–2011b
119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141
Syrian Arab Republic Namibia Honduras Kiribati South Africa Indonesia Vanuatu Kyrgyzstan Tajikistan Viet Nam Nicaragua Morocco Guatemala Iraq Cape Verde India Ghana Equatorial Guinea Congo Lao People’s Democratic Republic Cambodia Swaziland Bhutan
0.632 0.625 0.625 0.624 0.619 0.617 0.617 0.615 0.607 0.593 0.589 0.582 0.574 0.573 0.568 0.547 0.541 0.537 0.533 0.524 0.523 0.522 0.522 0.510 0.509 0.509 0.504 0.500 0.495 0.486 0.483 0.482 0.480 0.466 0.466 0.462 0.459 0.459 0.458 0.454 0.453 0.450 0.446 0.435 0.433 0.430 0.430 0.429 0.427 0.420 0.408 0.400 0.400 0.398 0.376 0.363 0.359 0.353 0.349 0.344 0.343
0.503 0.353 0.427 .. .. 0.504 .. 0.526 0.500 0.510 0.427 0.409 0.393 .. .. 0.392 0.367 .. 0.367 0.405 0.380 0.338 .. .. 0.338 0.348 0.346 0.363 0.332 .. .. 0.321 0.332 0.332 .. 0.312 0.304 0.278 0.301 0.271 0.298 0.288 0.296 0.289 .. 0.303 0.275 0.276 0.274 .. .. 0.246 0.272 .. 0.268 0.247 .. 0.207 .. 0.211 0.204
20.4 43.5 31.7 .. .. 18.3 .. 14.4 17.6 14.0 27.5 29.7 31.6 .. .. 28.3 32.2 .. 31.1 22.8 27.2 35.4 .. .. 33.6 31.5 31.4 27.4 32.9 .. .. 33.4 30.7 28.8 .. 32.3 33.8 39.3 34.3 40.2 34.2 35.9 33.6 33.5 .. 29.5 35.9 35.7 35.8 .. .. 38.6 32.0 .. 28.7 31.9 .. 41.4 .. 38.8 40.6
4 –14 –3 .. .. 8 .. 17 8 14 3 2 1 .. .. 1 –1 .. –1 6 3 –4 .. .. –2 1 1 5 –1 .. .. –2 2 1 .. 0 0 –6 0 –9 1 –1 2 2 .. 7 0 2 1 .. .. –3 2 .. 1 1 .. –4 .. –2 –3
0.793 0.528 0.693 .. 0.370 0.648 0.679 0.604 0.546 0.754 0.734 0.685 0.657 0.617 0.746 0.522 0.506 0.268 0.371 0.586 0.484 0.295 0.565 0.599 0.386 0.502 0.485 0.593 0.468 0.264 0.533 0.284 0.548 0.407 0.505 0.537 0.430 0.283 0.620 0.459 0.389 0.292 0.328 0.367 0.437 0.266 0.377 0.328 0.340 0.402 0.438 0.347 0.324 0.222 0.343 0.400 0.266 0.221 0.481 0.308 0.242
10.0 21.1 17.4 .. 28.4 16.8 15.6 19.8 27.2 13.4 13.9 16.7 18.6 20.3 12.7 27.1 27.5 45.4 37.0 21.7 28.8 35.0 24.1 20.7 34.1 28.8 32.3 23.2 30.2 46.1 25.3 43.0 25.6 32.4 25.2 25.1 30.7 43.8 19.5 30.9 36.2 34.3 39.1 37.2 32.6 41.9 36.9 41.3 40.3 33.9 33.0 37.8 39.9 50.9 30.6 35.4 46.3 50.1 26.6 42.7 46.0
0.366 0.445 0.392 .. 0.558 0.465 .. 0.637 0.638 0.417 0.350 0.242 0.280 .. 0.295 0.267 0.339 0.303 0.390 0.300 0.346 0.406 0.185 .. 0.403 0.365 0.207 0.252 0.195 .. .. 0.336 0.347 0.305 .. 0.155 0.211 0.247 0.201 0.241 0.208 0.384 0.322 0.277 0.193 0.366 0.156 0.282 0.212 .. .. 0.173 0.267 0.223 0.452 0.146 0.170 0.181 .. 0.143 0.174
31.5 27.8 31.8 .. 20.8 20.4 .. 11.1 9.4 17.1 33.3 45.8 36.1 .. 30.7 40.6 40.9 29.2 25.4 30.5 31.1 29.8 44.8 .. 30.7 19.1 46.4 39.4 47.4 .. .. 35.3 30.1 32.8 .. 49.8 45.1 44.2 43.6 40.7 43.2 24.3 32.2 41.5 47.4 23.8 47.0 30.7 42.0 .. .. 43.2 34.7 39.3 20.1 38.2 36.9 40.3 .. 42.0 45.9
0.439 0.187 0.287 .. .. 0.426 .. 0.379 0.360 0.423 0.303 0.412 0.329 .. .. 0.433 0.288 .. 0.342 0.376 0.328 0.322 .. .. 0.248 0.231 0.413 0.321 0.401 0.278 .. 0.345 0.193 0.294 .. 0.365 0.309 0.309 0.220 0.180 0.329 0.213 0.246 0.238 .. 0.287 0.355 0.228 0.286 .. .. 0.247 0.232 .. 0.124 0.258 .. 0.222 .. 0.213 0.201
18.3 68.3 43.4 .. .. 17.7 .. 12.2 15.3 11.4 33.6 23.0 38.5 .. .. 14.7 27.2 .. 30.3 15.5 21.4 40.9 .. .. 36.0 44.2 11.0 17.7 17.8 50.0 .. 19.9 36.1 20.6 .. 17.6 23.9 28.8 37.4 47.9 21.5 47.0 29.1 20.0 .. 20.8 21.3 34.5 23.6 .. .. 34.4 19.7 .. 34.5 20.8 .. 32.5 .. 31.1 28.1
5.7 52.2 30.4 .. 20.2 5.9 .. 4.9 4.2 6.2 15.0 7.4 17.0 .. .. 5.6 9.3 .. 10.6 5.9 7.8 12.4 .. .. 11.3 10.8 4.7 4.3 4.6 31.0 .. 9.1 8.6 6.6 12.5 6.3 7.4 9.5 8.9 25.2 7.4 18.8 8.7 8.7 .. 15.3 .. 13.9 6.7 11.0 .. 11.0 6.6 .. 12.1 4.2 7.1 6.0 .. 7.2 9.5
35.8 .. 57.7 .. 57.8 36.8 .. 33.4 29.4 37.6 52.3 40.9 53.7 .. 50.4 36.8 42.8 .. 47.3 36.7 44.4 50.7 46.7 .. 47.7 50.8 32.7 31.0 31.9 58.6 .. 44.6 47.2 37.6 .. 37.7 39.2 42.9 47.3 59.5 39.0 52.5 44.3 34.4 64.3 50.7 39.9 53.1 38.6 47.3 .. 46.1 39.0 .. .. 29.8 39.0 35.5 .. 39.4 43.6
table
3
LOW HUMAN DEVELOPMENT 142 Solomon Islands 143 Kenya 144 São Tomé and Príncipe 145 Pakistan 146 Bangladesh 147 Timor-Leste 148 Angola 149 Myanmar 150 Cameroon 151 Madagascar 152 Tanzania, United Republic of 153 Papua New Guinea 154 Yemen 155 Senegal 156 Nigeria 157 Nepal 158 Haiti 159 Mauritania 160 Lesotho 161 Uganda 162 Togo 163 Comoros 164 Zambia 165 Djibouti 166 Rwanda 167 Benin 168 Gambia 169 Sudan 170 Côte d'Ivoire 171 Malawi 172 Afghanistan 173 Zimbabwe 174 Ethiopia 175 Mali 176 Guinea-Bissau 177 Eritrea 178 Guinea 179 Central African Republic
STATISTICAL TAbLeS
137
Inequality-adjusted human development Index
Human Development Index (HDI) Value 2011 Inequality-adjusted HDI Value 2011 Overall loss (%) 2011 Change in ranka 2011 Inequality-adjusted life expectancy index Value 2011 Loss (%) 2011 Inequality-adjusted education index Value 2011 Loss (%) 2011 Inequality-adjusted income index Value 2011 Loss (%) 2011
HDI rank
Quintile income ratio
Income Gini coefficient
2000–2011b 2000–2011b
table
3
180 181 182 183 184 185 186 187
Sierra Leone Burkina Faso Liberia Chad Mozambique Burundi Niger Congo, Democratic Republic of the
0.336 0.331 0.329 0.328 0.322 0.316 0.295 0.286 .. .. .. .. .. .. .. 0.889 0.741 0.630 0.456 0.641 0.671 0.751 0.731 0.548 0.463 0.439 0.640 0.682
0.196 0.215 0.213 0.196 0.229 .. 0.195 0.172 .. .. .. .. .. .. .. 0.787 0.590 c 0.480 0.304 0.472 c 0.528 c 0.655 0.540 0.393 0.303 0.296 0.458 c 0.525
41.6 35.1 35.3 40.1 28.9 .. 34.2 39.9 .. .. .. .. .. .. .. 11.5 20.5 c 23.7 33.3 26.4 c 21.3 c 12.7 26.1 28.4 34.5 32.4 28.4 c 23.0
–3 3 3 –1 7 .. 0 0 .. .. .. .. .. .. .. — — — — — — — — — — — — —
0.240 0.326 0.362 0.224 0.282 0.261 0.314 0.224 0.640 .. .. .. .. 0.260 .. 0.897 0.734 0.633 0.393 0.654 0.709 0.715 0.743 0.529 0.331 0.403 0.633 0.637
45.3 41.7 37.6 52.0 40.8 45.6 42.6 50.0 16.9 .. .. .. .. 47.1 .. 5.2 12.4 19.2 35.6 18.0 14.3 11.7 13.4 26.9 39.0 34.7 19.1 19.0
0.160 0.117 0.235 0.124 0.181 .. 0.107 0.245 .. .. .. .. .. .. .. 0.838 0.580 c 0.396 0.238 0.307 c 0.477 c 0.681 0.528 0.266 0.276 0.233 0.417 c 0.450
47.4 37.3 46.4 43.4 18.2 .. 39.5 31.2 .. .. .. .. .. .. .. 6.2 18.9 c 29.4 39.2 40.8 c 21.9 c 10.7 23.2 40.9 35.6 36.8 29.6 c 26.2
0.197 0.260 0.113 0.272 0.233 .. 0.218 0.093 .. .. .. .. .. .. .. 0.648 0.482 0.441 0.300 0.524 c 0.435 c 0.578 0.401 0.430 0.306 0.277 0.364 c 0.506
31.0 25.3 19.0 21.0 25.8 .. 17.9 36.8 .. .. .. .. .. .. .. 22.2 28.2 c 22.3 24.2 17.8 c 26.8 c 15.7 39.3 15.1 28.4 25.3 35.6 c 23.4
8.1 6.7 7.0 7.4 9.9 4.8 5.2 9.2 .. .. .. .. .. .. .. — — — — — — — — — — — — —
42.5 39.6 52.6 39.8 45.6 33.3 34.0 44.4 .. .. .. .. .. .. .. — — — — — — — — — — — — —
OTHER COUNTRIES OR TERRITORIES Korea, Democratic People’s Rep. of Marshall Islands Monaco Nauru San Marino Somalia Tuvalu Human Development Index groups Very high human development High human development Medium human development Low human development Regions Arab States East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean South Asia Sub-Saharan Africa Least developed countries Small island developing states World
NOTES a. Change in rank is based on countries for which the Inequality-adjusted Human Development Index is calculated. b. Data refer to the most recent year available during the period specified. c. Based on less than half the countries in the group or region. DEFINITIONS Human Development Index (HDI): A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge and a decent standard of living. See Technical note 1 for details on how the HDI is calculated. Inequality-adjusted HDI (IHDI): HDI value adjusted for inequalities in the three basic dimensions of human development. See Technical note 2 for details on how the IHDI is calculated. Overall loss: The loss in potential human development due to inequality, calculated as the percentage difference between the HDI and the IHDI. Inequality-adjusted life expectancy index: The HDI life expectancy index adjusted for inequality in distribution of expected length of life based on data from life tables listed in Main data sources. Inequality-adjusted education index: The HDI education index adjusted for inequality in distribution of years of schooling based on data from household surveys listed in Main data sources. Inequality-adjusted income index: The HDI income index adjusted for inequality in income distribution based on data from household surveys listed in Main data sources. Quintile income ratio: Ratio of the average income of the richest 20 percent of the population to the average income of the poorest 20 percent of the population.
Income Gini coefficient: Measure of the deviation of the distribution of income (or consumption) among individuals or households within a country from a perfectly equal distribution. A value of 0 represents absolute equality, a value of 100 absolute inequality. MAIN DATA SOURCES Column 1: HDRO calculations based on data from UNDESA (2011), Barro and Lee (2010b), UNESCO Institute for Statistics (2011), World Bank (2011a) and IMF (2011). Column 2: Calculated as the geometric mean of the values in columns 5, 7 and 9 using the methodology in Technical note 2. Column 3: Calculated based on data in columns 1 and 2. Column 4: Calculated based on HDI rank and data in column 2. Columns 5, 7 and 9: HDRO calculations based on data from United Nations Department of Economic and Social Affairs life tables, the Luxembourg Income Study, Eurostat’s European Union Survey of Income and Living Conditions, the World Bank’s International Income Distribution Database, the United Nations Children’s Fund’s Multiple Indicator Cluster Surveys, ICF Macro Demographic and Health Surveys, the World Health Organization’s World Health Survey and the United Nations University’s World Institute for Development Economics Research’s World Income Inequality Database using the methodology in Technical note 2. The list of surveys and years of surveys used for each index are available at http://hdr.undp.org. Column 6: Calculated based on data in column 5 and the unadjusted life expectancy index. Column 8: Calculated based on data in column 7 and the unadjusted education index. Column 10: Calculated based on data in column 9 and the unadjusted income index. Columns 11 and 12: World Bank (2011a).
138
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4
table
Gender Inequality Index and related indicators
Population with at least secondary education (% ages 25 and older) REPRODUCTIVE HEALTH At least one antenatal visit (%) Births attended by skilled health personnel (%) Contraceptive prevalence Labour force rate, any participation rate method (%) (% of married women ages Male Female Male 15–49) 2010 2009 2009 2005–2009b
HDI rank
Seats in national Maternal mortality Adolescent parliament Rank Value ratio fertility rate (% female) Female 2011 2011 2008 2011a 2011 2010
Gender Inequality Index
Total fertility rate 2011a
2005–2009b 2005–2009b
VERY HIGH HUMAN DEVELOPMENT 1 Norway 2 Australia 3 Netherlands 4 United States 5 New Zealand 6 Canada 7 Ireland 8 Liechtenstein 9 Germany 10 Sweden 11 Switzerland 12 Japan 13 Hong Kong, China (SAR) 14 Iceland 15 Korea, Republic of 16 Denmark 17 Israel 18 Belgium 19 Austria 20 France 21 Slovenia 22 Finland 23 Spain 24 Italy 25 Luxembourg 26 Singapore 27 Czech Republic 28 United Kingdom 29 Greece 30 United Arab Emirates 31 Cyprus 32 Andorra 33 Brunei Darussalam 34 Estonia 35 Slovakia 36 Malta 37 Qatar 38 Hungary 39 Poland 40 Lithuania 41 Portugal 42 Bahrain 43 Latvia 44 Chile 45 Argentina 46 Croatia 47 Barbados HIGH HUMAN DEVELOPMENT 48 Uruguay 49 Palau 50 Romania 51 Cuba 52 Seychelles 53 Bahamas 54 Montenegro 55 Bulgaria
6 18 2 47 32 20 33 .. 7 1 4 14 .. 9 11 3 22 12 16 10 28 5 13 15 26 8 17 34 24 38 21 .. .. 30 31 42 111 39 25 29 19 44 36 68 67 27 65 62 .. 55 58 .. 54 .. 40
0.075 0.136 0.052 0.299 0.195 0.140 0.203 .. 0.085 0.049 0.067 0.123 .. 0.099 0.111 0.060 0.145 0.114 0.131 0.106 0.175 0.075 0.117 0.124 0.169 0.086 0.136 0.209 0.162 0.234 0.141 .. .. 0.194 0.194 0.272 0.549 0.237 0.164 0.192 0.140 0.288 0.216 0.374 0.372 0.170 0.364 0.352 .. 0.333 0.337 .. 0.332 .. 0.245
7 8 9 24 14 12 3 .. 7 5 10 6 .. 5 18 5 7 5 5 8 18 8 6 5 17 9 8 12 2 10 10 .. 21 12 6 8 8 13 6 13 7 19 20 26 70 14 64 27 .. 27 53 .. 49 15 13
9.0 16.5 5.1 41.2 30.9 14.0 17.5 7.0 7.9 6.0 4.6 5.0 3.2 14.6 2.3 6.0 14.0 14.2 12.8 7.2 5.0 9.3 12.7 6.7 10.1 4.8 11.1 29.6 11.6 26.7 6.6 8.4 25.1 22.7 20.2 17.3 16.2 16.5 14.8 19.7 16.8 14.9 18.0 58.3 56.9 13.5 42.6 61.1 13.8 32.0 45.2 51.3 31.8 18.2 42.8
39.6 28.3 37.8 16.8 c 33.6 24.9 11.1 24.0 31.7 45.0 27.6 13.6 .. 42.9 14.7 38.0 19.2 38.5 28.3 20.0 10.8 42.5 34.7 20.3 20.0 23.4 21.0 21.0 17.3 22.5 12.5 53.6 .. 19.8 16.0 8.7 0.0 f 9.1 17.9 19.1 27.4 15.0 20.0 13.9 37.8 23.5 19.6 14.6 6.9 9.8 43.2 23.5 17.9 11.1 20.8
99.3 95.1 86.3 95.3 71.6 92.3 82.3 .. 91.3 87.9 63.6 80.0 67.3 66.3 79.4 59.0 78.9 75.7 67.3 79.6 60.6 d,e 70.1 70.9 67.8 66.4 57.3 85.5 68.8 64.4 76.9 61.8 49.3 d,e 66.6 94.4 80.8 64.4 62.1 93.2 79.7 91.9 40.4 74.4 94.8 67.3 57.0 57.4 89.5 56.6 .. 83.8 73.9 41.2 d,e 48.5 d,e 79.7 d,e 69.1
99.1 97.2 89.2 94.5 73.5 92.7 81.5 .. 92.8 87.1 73.8 82.3 71.0 57.7 91.7 65.6 77.2 79.8 85.9 84.6 81.9 d,e 70.1 75.7 78.9 73.9 64.7 87.6 67.8 72.0 77.3 73.2 49.5 d,e 61.2 94.6 87.1 73.5 54.7 96.7 83.9 95.7 41.9 80.4 96.2 69.8 54.9 72.3 87.6 51.7 .. 90.5 80.4 45.4 d,e 54.5 d,e 69.5 d,e 70.6
63.0 58.4 59.5 58.4 61.8 62.7 54.4 .. 53.1 60.6 60.6 47.9 52.2 71.7 50.1 60.3 51.9 46.7 53.2 50.5 52.8 57.0 49.1 38.4 48.0 53.7 48.8 55.3 42.9 41.9 54.3 .. 59.7 54.8 51.2 31.6 49.9 42.5 46.2 50.2 56.2 32.4 54.3 41.8 52.4 46.3 65.8 53.8 .. 45.4 40.9 .. 68.3 .. 48.2
71.0 72.2 72.9 71.9 75.7 73.0 73.0 .. 66.8 69.2 73.7 71.8 68.9 83.1 72.0 70.6 62.5 60.8 68.1 62.2 65.4 64.9 68.5 60.6 63.3 75.6 67.6 69.5 65.0 92.1 70.8 .. 74.8 69.0 68.5 67.5 93.0 58.8 61.9 62.1 69.4 85.0 70.2 73.4 78.4 60.3 78.0 75.5 .. 60.0 66.9 .. 78.7 .. 61.2
88.0 71.0 69.0 73.0 75.0 74.0 89.0 .. 75.0 .. 82.0 54.0 84.0 .. 80.0 .. .. 75.0 51.0 71.0 74.0 .. 66.0 60.0 .. 62.0 72.0 84.0 61.0 28.0 .. .. .. 70.0 80.0 86.0 43.0 77.0 49.0 47.0 67.0 62.0 48.0 58.0 78.0 .. 55.0 78.0 21.0 70.0 78.0 .. 45.0 39.0 63.0
.. 100.0 .. .. 95.0 .. .. .. .. .. .. .. .. .. .. .. .. .. 100.0 99.0 98.0 100.0 .. .. .. .. 99.0 .. .. 97.0 .. .. 100.0 .. .. .. .. .. .. .. .. 97.0 .. 95.0 99.0 .. 100.0 96.0 100.0 94.0 100.0 .. 98.0 97.0 ..
.. 100.0 100.0 99.0 100.0 98.0 100.0 .. .. .. .. 100.0 .. .. 100.0 .. .. .. 100.0 99.0 100.0 100.0 .. .. 100.0 100.0 100.0 99.0 .. 99.0 .. .. 99.0 100.0 100.0 98.0 99.0 100.0 100.0 100.0 100.0 98.0 100.0 100.0 95.0 100.0 100.0 100.0 100.0 99.0 100.0 .. 99.0 99.0 g 100.0
2.0 2.0 1.8 2.1 2.1 1.7 2.1 .. 1.5 1.9 1.5 1.4 1.1 2.1 1.4 1.9 2.9 1.8 1.4 2.0 1.5 1.9 1.5 1.5 1.7 1.4 1.5 1.9 1.5 1.7 1.5 .. 2.0 1.7 1.4 1.3 2.2 1.4 1.4 1.5 1.3 2.4 1.5 1.8 2.2 1.5 1.6 2.0 .. 1.4 1.5 .. 1.9 1.6 1.6
STATISTICAL TAbLeS
139
Gender Inequality Index and related indicators
Population with at least secondary education (% ages 25 and older) REPRODUCTIVE HEALTH At least one antenatal visit (%) Births attended by skilled health personnel (%)
HDI rank
Seats in national Maternal mortality Adolescent parliament Rank Value ratio fertility rate (% female) Female 2008 2011a 2011 2010
Gender Inequality Index
Contraceptive prevalence Labour force rate, any participation rate method (%) (% of married women ages Male Female Male 15–49) 2010
Total fertility rate 2011a
table
4
56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94
2011 2011 Saudi Arabia 135 0.646 Mexico 79 0.448 Panama 95 0.492 Serbia .. .. Antigua and Barbuda .. .. Malaysia 43 0.286 Trinidad and Tobago 53 0.331 Kuwait 37 0.229 Libya 51 0.314 Belarus .. .. Russian Federation 59 0.338 Grenada .. .. Kazakhstan 56 0.334 Costa Rica 64 0.361 Albania 41 0.271 Lebanon 76 0.440 Saint Kitts and Nevis .. .. Venezuela, Bolivarian Republic of 78 0.447 Bosnia and Herzegovina .. .. Georgia 73 0.418 Ukraine 57 0.335 Mauritius 63 0.353 Former Yugoslav Republic of Macedonia 23 0.151 Jamaica 81 0.450 Peru 72 0.415 Dominica .. .. Saint Lucia .. .. Ecuador 85 0.469 Brazil 80 0.449 Saint Vincent and the Grenadines .. .. Armenia 60 0.343 Colombia 91 0.482 Iran, Islamic Republic of 92 0.485 Oman 49 0.309 Tonga .. .. Azerbaijan 50 0.314 Turkey 77 0.443 Belize 97 0.493 Tunisia 45 0.293
24 85 71 8 .. 31 55 9 64 15 39 .. 45 44 31 26 .. 68 9 48 26 36 9 89 98 .. .. 140 58 .. 29 85 30 20 .. 38 23 94 60 59 120 39 100 .. 26 38 77 48 100 110 260 95 180 37 65 32 94 82 ..
11.6 70.6 82.6 22.1 55.5 14.2 34.7 13.8 3.2 22.1 30.0 42.4 30.0 65.6 17.9 16.2 42.6 89.9 16.4 44.7 30.8 35.4 22.0 77.3 54.7 20.0 61.7 82.8 75.6 58.9 35.7 74.3 29.5 9.2 22.3 33.8 39.2 78.7 5.7 26.5 7.3 23.6 108.7 28.3 45.2 8.4 19.5 43.3 39.5 82.7 89.9 72.3 78.2 12.2 20.8 33.8 54.1 46.6 53.5
0.0 f 25.5 8.5 21.6 19.4 14.0 27.4 7.7 7.7 32.1 11.5 21.4 13.6 38.6 16.4 3.1 6.7 17.0 15.8 6.5 8.0 18.8 32.5 16.0 27.5 h 12.5 20.7 32.3 9.6 14.3 9.2 13.8 2.8 9.0 3.6 i 16.0 9.1 11.1 23.3 12.2 7.0 5.3 19.1 4.1 .. 21.3 16.8 14.0 9.8 19.0 16.1 13.6 30.1 6.5 3.9 18.8 21.5 .. j ..
50.3 55.8 63.5 61.7 .. 66.0 67.6 52.2 55.6 .. 90.6 .. 92.2 54.4 83.2 32.4 .. 33.4 .. 63.8 d,e 91.5 45.2 55.6 d 74.0 57.6 11.2 d,e .. 44.2 48.8 .. 94.1 48.0 39.0 26.7 84.0 65.4 d,e 27.1 35.2 33.5 57.1 36.3 56.0 49.7 64.2 d,e 86.6 54.8 .. 25.6 .. 40.5 53.8 45.4 55.1 31.3 83.0 85.8 65.9 43.4 36.5 d,e
57.9 61.9 60.7 70.7 .. 72.8 66.6 43.9 44.0 .. 95.6 .. 95.0 52.8 89.2 33.3 .. 29.6 .. 58.9 d,e 96.1 52.9 40.2 d 71.1 76.1 10.3 d,e .. 45.8 46.3 .. 94.8 47.6 57.2 28.1 87.8 61.9 d,e 46.7 32.8 48.0 74.2 49.3 57.6 41.8 60.0 d,e 88.6 70.4 .. 33.7 .. 47.5 34.7 50.4 67.9 37.3 81.8 92.3 63.7 59.3 29.0 d,e
2009 21.2 43.2 48.4 .. .. 44.4 55.1 45.4 24.7 54.8 57.5 .. 65.7 45.1 49.3 22.3 .. 51.7 54.9 55.1 52.0 40.8 42.9 56.1 58.2 .. 51.0 47.1 60.1 56.0 59.6 40.7 31.9 25.4 54.6 59.5 24.0 47.4 25.6
2009
2005–2009b
2005–2009b 2005–2009b
79.8 80.6 80.7 .. .. 79.2 78.1 82.5 78.9 66.5 69.2 .. 76.3 79.9 70.4 71.5 .. 80.3 68.3 73.8 65.4 74.8 65.2 74.0 76.0 .. 75.8 77.7 81.9 78.8 74.6 77.6 73.0 76.9 74.7 66.8 69.6 80.6 70.6 73.9 79.6 75.1 79.8 75.4 78.4 79.7 74.0 80.7 66.0 76.7 81.1 86.6 82.0 77.0 78.2 53.1 78.5 75.3 68.4
24.0 73.0 .. 41.0 53.0 55.0 43.0 52.0 45.0 73.0 80.0 54.0 51.0 80.0 69.0 58.0 54.0 77.0 36.0 47.0 67.0 76.0 14.0 69.0 73.0 50.0 47.0 73.0 81.0 48.0 53.0 78.0 79.0 32.0 23.0 51.0 73.0 34.0 60.0 59.0 61.0 68.0 73.0 25.0 35.0 85.0 48.0 77.0 46.0 73.0 33.0 79.0 61.0 39.0 55.0 68.0 51.0 60.0 50.0
90.0 94.0 72.0 98.0 100.0 79.0 96.0 95.0 81.0 99.0 .. 100.0 100.0 90.0 97.0 96.0 100.0 94.0 99.0 96.0 99.0 .. 94.0 91.0 94.0 100.0 99.0 84.0 97.0 100.0 93.0 94.0 98.0 100.0 .. 77.0 92.0 94.0 96.0 99.0 89.0 99.0 99.0 .. .. 91.0 99.0 98.0 90.0 94.0 94.0 96.0 86.0 81.0 100.0 98.0 91.0 74.0 99.0
91.0 93.0 92.0 99.0 g 100.0 99.0 98.0 98.0 94.0 g 100.0 g 100.0 99.0 100.0 g 99.0 99.0 98.0 100.0 95.0 100.0 g 98.0 99.0 98.0 100.0 g 97.0 g 83.0 g 100.0 100.0 98.0 g 97.0 99.0 100.0 96.0 g 97.0 99.0 95.0 88.0 g 91.0 95.0 g 95.0 99.0 95.0 99.0 98.0 100.0 99.0 99.0 100.0 97.0 90.0 g 96.0 86.0 82.0 71.0 84.0 99.0 100.0 g 62.0 79.0 99.0
2.6 2.2 2.4 1.6 .. 2.6 1.6 2.3 2.4 1.5 1.5 2.2 2.5 1.8 1.5 1.8 .. 2.4 1.1 1.5 1.5 1.6 1.4 2.3 2.4 .. 1.9 2.4 1.8 2.0 1.7 2.3 1.6 2.2 3.8 2.2 2.0 2.7 1.9 2.9 2.1 2.2 2.5 3.8 2.6 1.6 2.3 1.5 2.3 2.2 3.2 2.9 3.2 1.7 2.5 1.5 3.1 2.6 4.3
MEDIUM HUMAN DEVELOPMENT 95 Jordan 96 Algeria 97 Sri Lanka 98 Dominican Republic 99 Samoa 100 Fiji 101 China 102 Turkmenistan 103 Thailand 104 Suriname 105 El Salvador 106 Gabon 107 Paraguay 108 Bolivia, Plurinational State of 109 Maldives 110 Mongolia 111 Moldova, Republic of 112 Philippines 113 Egypt 114 Occupied Palestinian Territory
83 71 74 90 .. .. 35 .. 69 .. 93 103 87 88 52 70 46 75 .. ..
0.456 0.412 0.419 0.480 .. .. 0.209 .. 0.382 .. 0.487 0.509 0.476 0.476 0.320 0.410 0.298 0.427 .. ..
23.3 37.2 34.2 50.5 37.9 38.7 67.4 62.4 65.5 38.5 45.9 70.0 57.0 62.1 57.1 67.8 46.5 49.2 22.4 16.5
140
human development report 2011
Gender Inequality Index and related indicators
Population with at least secondary education (% ages 25 and older) REPRODUCTIVE HEALTH At least one antenatal visit (%) Births attended by skilled health personnel (%)
HDI rank
Seats in national Maternal mortality Adolescent parliament Rank Value ratio fertility rate (% female) Female 2011 2011 2008 2011a
Gender Inequality Index
Contraceptive prevalence Labour force rate, any participation rate method (%) (% of married women ages Male Female Male 15–49) 2010
Total fertility rate 2011a
115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141
Uzbekistan Micronesia, Federated States of Guyana Botswana Syrian Arab Republic Namibia Honduras Kiribati South Africa Indonesia Vanuatu Kyrgyzstan Tajikistan Viet Nam Nicaragua Morocco Guatemala Iraq Cape Verde India Ghana Equatorial Guinea Congo Lao People’s Democratic Republic Cambodia Swaziland Bhutan
.. .. 106 102 86 84 105 .. 94 100 .. 66 61 48 101 104 109 117 .. 129 122 .. 132 107 99 110 98 .. 130 .. 115 112 .. .. 96 134 .. 119 140 146 114 .. 113 123 126 108 116 124 .. 131 .. 82 133 127 128 136 120 141 118
.. .. 0.511 0.507 0.474 0.466 0.511 .. 0.490 0.505 .. 0.370 0.347 0.305 0.506 0.510 0.542 0.579 .. 0.617 0.598 .. 0.628 0.513 0.500 0.546 0.495 .. 0.627 .. 0.573 0.550 .. .. 0.492 0.639 .. 0.590 0.674 0.769 0.566 .. 0.558 0.599 0.605 0.532 0.577 0.602 .. 0.627 .. 0.453 0.634 0.610 0.611 0.655 0.594 0.707 0.583
30 .. 270 190 46 180 110 .. 410 240 .. 81 64 56 100 110 110 75 94 230 350 280 580 580 290 420 200 100 530 .. 260 340 370 610 240 600 440 790 250 210 410 840 380 300 550 530 430 350 340 470 300 540 410 400 750 470 510 1,400 790
13.8 25.4 68.3 52.1 42.8 74.4 93.1 22.2 59.2 45.1 54.0 34.1 28.4 26.8 112.7 15.1 107.2 98.0 81.6 86.3 71.1 122.9 118.7 39.0 41.8 83.9 50.2 70.3 100.2 66.1 31.6 78.9 65.8 171.1 16.3 127.8 134.3 130.4 66.9 78.8 105.9 118.3 103.4 46.4 79.2 73.5 149.9 65.3 58.0 146.8 22.9 38.7 111.7 76.6 61.9 129.4 119.2 118.7 64.6
2011 19.2 0.0 30.0 7.9 12.4 25.0 18.0 4.3 42.7 18.0 3.8 23.3 17.5 25.8 20.7 6.7 12.0 25.2 20.8 10.7 8.3 10.0 9.2 25.0 19.0 21.9 13.9
2010
.. .. 42.6 73.6 24.7 49.6 31.9 .. 66.3 24.2 .. 81.0 93.2 24.7 30.8 20.1 15.6 22.0 .. 26.6 33.9 .. 43.8 22.9 11.6 49.9 16.2 d,e .. 20.1 .. 23.5 30.8 .. .. 18.0 21.1 .. 5.6 12.4 7.6 10.9 .. 17.9 22.5 8.0 24.3 9.1 15.3 .. 25.7 .. 7.4 11.3 16.9 12.8 13.6 10.4 5.8 48.8
.. .. 43.7 77.5 24.1 46.1 36.3 .. 68.0 31.1 .. 81.2 85.8 28.0 44.7 36.3 21.0 42.7 .. 50.4 83.1 .. 48.7 36.8 20.6 46.1 19.4 d,e .. 38.6 .. 46.8 39.3 .. .. 17.6 34.9 .. 9.2 24.4 24.4 19.4 .. 39.9 36.3 20.8 20.3 20.8 45.1 .. 44.2 .. 8.0 25.9 31.4 18.2 25.2 20.4 34.0 62.0
2009 58.4 .. 44.7 72.3 21.1 51.8 40.1 .. 47.0 52.0 79.3 54.8 57.0 68.0 47.1 26.2 48.1 13.8 53.5 32.8 73.8 39.7 62.9 77.7 73.6 53.1 53.4
2009
2005–2009b
2005–2009b 2005–2009b
71.0 .. 81.2 80.9 79.5 62.6 80.2 .. 63.4 86.0 88.3 79.1 77.7 76.0 78.4 80.1 87.9 68.9 81.3 81.1 75.2 92.0 82.6 78.9 85.6 74.9 70.6 50.0 88.1 76.0 84.9 82.5 82.8 88.4 85.1 80.7 88.7 90.6 74.2 73.5 88.6 73.4 80.3 82.9 81.0 77.7 90.6 85.7 85.4 79.2 78.7 85.1 77.9 85.2 73.9 82.1 78.8 84.5 74.3
65.0 45.0 43.0 53.0 58.0 55.0 65.0 22.0 60.0 57.0 38.0 48.0 37.0 80.0 72.0 63.0 54.0 50.0 61.0 54.0 24.0 .. 44.0 38.0 40.0 51.0 35.0 27.0 46.0 38.0 30.0 53.0 22.0 6.0 41.0 29.0 40.0 26.0 32.0 28.0 12.0 15.0 48.0 32.0 9.0 47.0 24.0 17.0 26.0 41.0 23.0 36.0 17.0 18.0 8.0 13.0 41.0 10.0 65.0
99.0 .. 92.0 94.0 84.0 95.0 92.0 88.0 92.0 93.0 84.0 97.0 89.0 91.0 90.0 68.0 93.0 84.0 98.0 75.0 90.0 86.0 86.0 35.0 69.0 85.0 88.0 74.0 92.0 98.0 61.0 51.0 61.0 80.0 80.0 82.0 86.0 76.0 79.0 47.0 87.0 58.0 44.0 85.0 75.0 92.0 94.0 84.0 75.0 94.0 92.0 96.0 84.0 98.0 64.0 85.0 92.0 16.0 93.0
100.0 g 88.0 92.0 g 95.0 g 93.0 g 81.0 67.0 g 63.0 91.0 75.0 g 74.0 98.0 g 88.0 g 88.0 g 74.0 63.0 51.0 80.0 78.0 g 53.0 g 57.0 65.0 g 83.0 20.0 g 44.0 69.0 g 71.0 70.0 44.0 82.0 39.0 g 24.0 g 18.0 47.0 g 64.0 63.0 44.0 g 43.0 g 53.0 36.0 52.0 g 39.0 g 19.0 26.0 g 61.0 g 62.0 g 42.0 62.0 g 62.0 g 47.0 g 93.0 g 52.0 g 74.0 g 57.0 g 49.0 g 57.0 54.0 14.0 60.0
2.3 3.3 2.2 2.6 2.8 3.1 3.0 .. 2.4 2.1 3.8 2.6 3.2 1.8 2.5 2.2 3.8 4.5 2.3 2.5 4.0 5.0 4.4 2.5 2.4 3.2 2.3 4.0 4.6 3.5 3.2 2.2 5.9 5.1 1.9 4.3 4.5 5.5 3.8 4.9 4.6 5.4 2.6 3.2 4.4 3.1 5.9 3.9 4.7 6.3 3.6 5.3 5.1 4.7 4.2 4.2 6.0 6.0 3.1
table
4
LOW HUMAN DEVELOPMENT 142 Solomon Islands 143 Kenya 144 São Tomé and Príncipe 145 Pakistan 146 Bangladesh 147 Timor-Leste 148 Angola 149 Myanmar 150 Cameroon 151 Madagascar 152 Tanzania, United Republic of 153 Papua New Guinea 154 Yemen 155 Senegal 156 Nigeria 157 Nepal 158 Haiti 159 Mauritania 160 Lesotho 161 Uganda 162 Togo 163 Comoros 164 Zambia 165 Djibouti 166 Rwanda 167 Benin 168 Gambia 169 Sudan 170 Côte d'Ivoire 171 Malawi 172 Afghanistan 173 Zimbabwe
0.0 9.8 18.2 21.0 18.6 29.2 38.6 4.0 13.9 12.1 36.0 0.9 0.7 29.6 7.3 33.2 4.2 19.2 22.9 37.2 11.1 3.0 14.0 13.8 50.9 8.4 7.5 24.2 8.9 20.8 27.6 17.9
24.2 76.4 44.5 21.7 58.7 58.9 74.5 63.1 53.5 84.2 86.3 71.6 19.9 64.8 39.2 63.3 57.5 59.0 70.8 78.3 63.6 73.7 59.5 61.5 86.7 67.4 70.6 30.8 50.8 75.0 33.1 60.0
STATISTICAL TAbLeS
141
Gender Inequality Index and related indicators
Population with at least secondary education (% ages 25 and older) REPRODUCTIVE HEALTH At least one antenatal visit (%) Births attended by skilled health personnel (%)
HDI rank
Seats in national Maternal mortality Adolescent parliament Rank Value ratio fertility rate (% female) Female 2011 2011 2008 2011a
Gender Inequality Index
Contraceptive prevalence Labour force rate, any participation rate method (%) (% of married women ages Male Female Male 15–49) 2010
Total fertility rate 2011a
table
4
174 175 176 177 178 179 180 181 182 183 184 185 186 187
Ethiopia Mali Guinea-Bissau Eritrea Guinea Central African Republic Sierra Leone Burkina Faso Liberia Chad Mozambique Burundi Niger Congo, Democratic Republic of the
.. 143 .. .. .. 138 137 121 139 145 125 89 144 142 .. .. .. .. .. .. .. .. .. .. ..
.. 0.712 .. .. .. 0.669 0.662 0.596 0.671 0.735 0.602 0.478 0.724 0.710 .. .. .. .. .. .. .. 0.224 0.409 0.475 0.606
470 830 1,000 280 680 850 970 560 990 1,200 550 970 820 670 250 .. .. .. .. 1,200 .. 16 51 135 532 192 79 29 80 252 619 537 .. 176
72.4 186.3 111.1 66.6 157.4 106.6 143.7 124.8 142.6 164.5 149.2 18.6 207.1 201.4 0.7 53.5 1.6 31.2 2.5 70.1 23.3 23.8 51.6 50.1 98.2 44.4 19.8 28.0 73.7 77.4 119.7 106.1 66.4 58.1
2011 25.5 10.2 10.0 22.0 .. k 9.6 h 13.2 15.3 13.8 14.3 39.2 36.1 13.1 9.4
2010
.. 3.2 .. .. .. 10.3 9.5 34.7 d,e 15.7 0.9 d,e 1.5 5.2 2.5 10.7 .. .. .. .. .. .. .. 82.0 61.0 41.2 18.7 32.9 48.1 78.0 50.5 27.3 22.2 16.8 50.3 50.8
.. 8.4 .. .. .. 26.2 20.4 35.1 d,e 39.2 9.9 d,e 6.0 9.2 7.6 36.2 .. .. .. .. .. .. .. 84.6 64.6 57.7 32.4 46.2 61.3 83.3 52.2 49.2 34.9 27.4 54.9 61.7
2009 80.7 37.6 59.6 62.5 79.2 71.6 65.4 78.2 66.6 62.7 84.8 91.0 38.9 56.5
2009 90.3 67.0 83.8 83.4 89.2 86.7 67.5 90.8 75.8 78.2 86.9 87.5 87.5 85.6
2005–2009b
2005–2009b 2005–2009b
15.0 8.0 10.0 8.0 9.0 19.0 8.0 17.0 11.0 3.0 16.0 9.0 11.0 21.0 69.0 45.0 .. 36.0 .. 15.0 31.0 69.5 72.4 67.7 27.8 46.1 76.9 67.7 74.8 52.1 24.3 28.7 53.3 61.6
28.0 70.0 78.0 70.0 88.0 69.0 87.0 85.0 79.0 39.0 92.0 92.0 46.0 85.0 97.0 81.0 .. 95.0 .. 26.0 97.0 98.6 94.4 85.1 64.9 76.4 90.7 95.3 94.8 71.3 73.6 63.7 90.8 82.7
6.0 49.0 g 39.0 g 28.0 g 46.0 g 44.0 g 42.0 g 54.0 46.0 14.0 55.0 g 34.0 33.0 74.0 g 97.0 86.0 .. 97.0 .. 33.0 g 98.0 99.2 96.1 78.1 39.6 76.1 91.9 97.9 92.0 50.5 47.7 38.2 74.3 76.4
3.9 6.1 4.9 4.2 5.0 4.4 4.7 5.8 5.0 5.7 4.7 4.1 6.9 5.5 2.0 .. .. .. .. 6.3 .. 1.8 1.9 2.1 4.2 3.1 1.8 1.7 2.2 2.6 4.8 4.1 2.7 2.4
OTHER COUNTRIES OR TERRITORIES Korea, Democratic People’s Rep. of Marshall Islands Monaco Nauru San Marino Somalia Tuvalu Human Development Index groups Very high human development High human development Medium human development Low human development Regions Arab States East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean South Asia Sub-Saharan Africa Least developed countries Small island developing states World
15.6 3.0 26.1 0.0 16.7 6.8 0.0 21.5 13.5 17.3 18.2 12.0 20.2 13.4 18.7 12.5 19.8 20.3 20.6 17.7
55.1 .. .. .. .. 56.5 .. 52.8 47.8 51.1 54.6 26.0 64.2 49.7 51.7 34.6 62.9 64.4 52.6 51.5
77.5 .. .. .. .. 84.7 .. 69.8 75.0 80.0 82.7 77.1 80.3 67.8 79.9 81.2 81.2 84.0 75.8 78.0
.. 0.563 .. .. .. 0.311 .. 0.445 .. 0.601 .. 0.610 .. 0.594 .. .. .. 0.492
NOTES a. Annual average for 2010–2015. b. Data refer to the most recent year available during the period specified. c. The denominator of the calculation refers to voting members of the House of Representatives only. d. UNESCO Institute for Statistics (2011). e. Refers to an earlier year than that specified. f. For purposes of calculating the Gender Inequality Index, a value of 0.1 percent was used. g. Includes deliveries by cadres of health workers other than doctors, nurses and midwives. h. Data are for 2010. i. No women were elected in 2010; however, one woman was appointed to the cabinet. j. The People’s Assembly and the Shoura Assembly were dissolved by the Egypt Supreme Council of Armed Forces on 13 February 2011. k. The parliament was dissolved following the December 2008 coup. DEFINITIONS Gender Inequality Index: A composite measure reflecting inequality in achievements between women and men in three dimensions: reproductive health, empowerment and the labour market. See Technical note 3 for details on how the Gender Inequality Index is calculated. Maternal mortality ratio: Ratio of the number of maternal deaths to the number of live births in a given year, expressed per 100,000 live births. Adolescent fertility rate: Number of births to women ages 15–19 per 1,000 women ages 15–19. Seats in national parliament: Proportion of seats held by women in a lower or single house or an upper house or senate, expressed as percentage of total seats. Population with at least secondary education: Percentage of the population ages 25 and older that have reached secondary education.
Labour force participation rate: Proportion of a country’s working-age population that engages in the labour market, either by working or actively looking for work, expressed as a percentage of the working-age population. Contraceptive prevalence rate, any method: Percentage of women of reproductive age (ages 15–49) who are using, or whose partners are using, any modern or traditional form of contraception. At least one antenatal visit: Percentage of women who used antenatal care provided by skilled health personnel for reasons related to pregnancy at least once during pregnancy, as a percentage of live births. Births attended by skilled health personnel: Percentage of deliveries attended by personnel (including doctors, nurses and midwives) trained to give the necessary care, supervision and advice to women during pregnancy, labour and postpartum; to conduct deliveries on their own; and to care for newborns. Total fertility rate: Number of children that would be born to each woman if she were to live to the end of her child-bearing years and bear children at each age in accordance with prevailing age-specific fertility rates. MAIN DATA SOURCES Columns 1 and 2: HDRO calculations based on UNICEF (2011), UNDESA (2011), IPU (2011), Barro and Lee (2010b), UNESCO (2011) and ILO (2011). Column 3: WHO, UNICEF, UNFPA and World Bank (2010). Columns 4 and 13: UNDESA (2011). Column 5: IPU (2011). Columns 6 and 7: HDRO updates of Barro and Lee (2010b) estimates based on UNESCO Institute for Statistics data on education attainment (2011) and Barro and Lee (2010a) methodology. Columns 8 and 9: ILO (2011). Columns 10–12: UNICEF (2011).
142
human development report 2011
5
table
Multidimensional Poverty Index
Population in multidimensional povertya Multidimensional Poverty Index Headcount (%) Population Population Intensity of vulnerable in severe deprivation to poverty poverty (%) (%) (thousands) (%) Share of multidimensional poor with deprivations in environmental services Clean water (%) Improved sanitation (%) Modern fuels (%) Population below income poverty line PPP $1.25 a day (%) National poverty line (%)
HDI rank
Yearb
Valuea
2000–2009c 2000–2009c
VERY HIGH HUMAN DEVELOPMENT 21 Slovenia 27 Czech Republic 30 United Arab Emirates 34 Estonia 35 Slovakia 38 Hungary 39 Poland 40 Lithuania 43 Latvia 44 Chile 45 Argentina 46 Croatia HIGH HUMAN DEVELOPMENT 48 Uruguay 50 Romania 52 Seychelles 54 Montenegro 55 Bulgaria 57 Mexico 58 Panama 59 Serbia 61 Malaysia 62 Trinidad and Tobago 65 Belarus 66 Russian Federation 68 Kazakhstan 69 Costa Rica 70 Albania 73 Venezuela, Bolivarian Republic of 74 Bosnia and Herzegovina 75 Georgia 76 Ukraine 78 Former Yugoslav Republic of Macedonia 79 Jamaica 80 Peru 83 Ecuador 84 Brazil 86 Armenia 87 Colombia 88 Iran, Islamic Republic of 91 Azerbaijan 92 Turkey 93 Belize 94 Tunisia MEDIUM HUMAN DEVELOPMENT 95 Jordan 97 Sri Lanka 98 Dominican Republic 100 Fiji 101 China 103 Thailand 104 Suriname 105 El Salvador 106 Gabon 107 Paraguay 108 Bolivia, Plurinational State of 109 Maldives
2003 (W) 2003 (W) 2003 (W) 2003 (W) 2003 (W) 2003 (W) .. .. 2003 (W) .. 2005 (N) 2003 (W) 2003 (W) .. .. 2005 (M) .. 2006 (N) .. 2005 (M) .. 2006 (M) 2005 (M) 2003 (W) 2006 (M) .. 2009 (D) .. 2006 (M) 2005 (M) 2007 (D) 2005 (M) .. 2004 (D) 2003 (W) 2006 (N) 2005 (D) 2010 (D) .. 2006 (D) 2003 (D) 2006 (M) 2003 (W) 2009 (D) 2003 (W) 2007 (D) .. 2003 (W) 2005 (M) 2006 (M) .. 2000 (D) 2003 (W) 2008 (D) 2009 (D)
0.000 d 0.010 0.002 0.026 0.000 d 0.016 .. .. 0.006 e .. 0.011 f 0.016 0.006 .. .. 0.006 .. 0.015 .. 0.003 .. 0.020 0.000 0.005 e 0.002 .. 0.005 .. 0.003 0.003 0.008 0.008 .. 0.086 0.009 0.011 0.004 0.022 .. 0.021 0.028 0.024 0.010 e 0.008 0.021 e 0.018 .. 0.056 0.006 0.039 .. 0.161 d 0.064 0.089 0.018
0.0 d 3.1 0.6 7.2 0.0 d 4.6 .. .. 1.6 e .. 3.0 f 4.4 1.7 .. .. 1.5 .. 4.0 .. 0.8 .. 5.6 0.0 1.3 e 0.6 .. 1.4 .. 0.8 0.8 2.2 1.9 .. 19.9 2.2 2.7 1.1 5.4 .. 5.3 6.6 5.6 2.8 e 2.4 5.3 e 4.6 .. 12.5 1.6 8.2 .. 35.4 d 13.3 20.5 5.2
0d 316 20 97 0d 466 .. .. 37 e .. 1,160 f 196 56 .. .. 9 .. 4,313 .. 79 .. 74 0 1,883 e 92 .. 45 .. 30 36 1,018 39 .. 5,421 286 5,075 34 2,500 .. 461 4,378 16 272 e 145 1,027 e 438 .. 161,675 1,067 41 .. 437 d 755 1,972 16
0.0 d 33.4 35.3 36.5 0.0 d 34.3 .. .. 37.9 e .. 37.7 f 36.3 34.7 .. .. 41.6 .. 38.9 .. 40.0 .. 35.1 35.1 38.9 e 36.9 .. 37.7 .. 37.2 35.2 35.5 40.9 .. 43.2 41.6 39.3 36.2 40.9 .. 39.4 42.0 42.6 37.1 e 34.4 38.7 e 39.4 .. 44.9 38.5 47.2 .. 45.5 d 48.5 43.7 35.6
0.4 d 0.0 2.0 1.3 0.0 d 0.0 .. .. 0.0 e .. 5.7 f 0.1 0.1 .. .. 1.9 .. 5.8 .. 3.6 .. 0.4 0.8 0.8 e 5.0 .. 7.4 .. 7.0 5.3 1.0 6.7 .. 16.9 2.1 7.0 3.9 6.4 .. 12.5 7.3 7.6 4.9 e 1.3 14.4 e 8.6 .. 6.3 9.9 6.7 .. 22.4 d 15.0 18.7 4.8
0.0 d 0.0 0.0 0.2 0.0 d 0.0 .. .. 0.0 e .. 0.2 f 0.3 0.0 .. .. 0.3 .. 0.5 .. 0.1 .. 0.3 0.0 0.2 e 0.0 .. 0.1 .. 0.1 0.0 0.2 0.3 .. 6.0 0.6 0.2 0.0 1.1 .. 0.6 1.3 1.1 0.2 e 0.1 0.6 e 0.7 .. 4.5 0.2 3.3 .. 13.2 d 6.1 5.8 0.3
0.0 0.0 0.1 0.3 0.0 0.0 .. .. 0.0 .. 0.2 f 0.1 0.0 .. .. 0.2 .. 0.6 .. 0.1 .. 0.3 0.0 0.1 0.3 .. 0.3 .. 0.1 0.4 0.1 0.4 .. 14.1 0.7 1.0 0.2 2.4 .. 3.1 2.0 1.9 1.2 0.2 3.0 1.5 .. 3.0 0.5 5.2 .. 19.4 8.8 8.2 0.2
0.0 0.0 0.1 0.6 0.0 0.0 .. .. 0.8 .. 2.2 f 0.3 0.0 .. .. 0.4 .. 2.1 .. 0.2 .. 0.5 0.0 0.4 0.1 .. 0.4 .. 0.1 0.3 0.1 0.8 .. 19.4 0.6 1.1 0.4 2.6 .. 2.4 3.2 2.5 1.4 0.0 2.6 2.7 .. 7.7 0.5 6.5 .. 32.6 11.2 19.8 0.4
0.0 0.0 0.0 2.4 0.0 0.0 .. .. 0.1 .. 2.2 f 1.2 0.3 .. .. 0.9 .. 2.8 .. 0.7 .. 0.0 0.0 0.1 0.5 .. 1.1 .. 0.5 0.8 0.3 1.5 .. 19.2 0.3 .. 0.3 3.6 .. 1.6 .. 4.1 0.5 0.0 5.3 2.9 .. 9.1 1.2 5.3 .. 26.9 12.4 17.7 0.9
0.0 .. .. 0.0 .. 0.0 0.0 0.0 0.0 0.8 0.9 0.0 0.0 0.5 0.3 0.0 1.0 3.4 9.5 0.1 0.0 .. 0.0 0.0 0.2 0.7 0.6 3.5 0.0 14.7 0.1 0.3 0.2 5.9 5.1 3.8 1.3 16.0 1.5 1.0 2.7 .. 2.6 0.4 7.0 4.3 .. 15.9 10.8 .. 5.1 4.8 5.1 14.0 1.5
.. .. .. .. .. .. 16.6 .. 5.9 15.1 .. 11.1 20.5 13.8 .. 4.9 12.8 47.4 32.7 6.6 3.8 .. 5.4 11.1 15.4 21.7 12.4 29.0 14.0 23.6 7.9 19.0 9.9 34.8 36.0 21.4 26.5 45.5 .. 15.8 18.1 33.5 3.8 13.3 15.2 50.5 31.0 2.8 8.1 .. 37.8 32.7 35.1 60.1 ..
STATISTICAL TAbLeS
143
multidimensional poverty Index
Population in multidimensional povertya Multidimensional Poverty Index HDI rank Yearb Valuea Headcount (%) Population Population Intensity of vulnerable in severe deprivation to poverty poverty (%) (%) (thousands) (%) Share of multidimensional poor with deprivations in environmental services Clean water (%) Improved sanitation (%) Modern fuels (%) Population below income poverty line PPP $1.25 a day (%) National poverty line (%)
2000–2009c 2000–2009c
table
5
110 111 112 113 114 115 117 118 119 120 121 123 124 125 126 127 128 129 130 131 132 133 134 135 137 138 139 140 141
Mongolia Moldova, Republic of Philippines Egypt Occupied Palestinian Territory Uzbekistan Guyana Botswana Syrian Arab Republic Namibia Honduras South Africa Indonesia Vanuatu Kyrgyzstan Tajikistan Viet Nam Nicaragua Morocco Guatemala Iraq Cape Verde India Ghana Congo Lao People’s Democratic Republic Cambodia Swaziland Bhutan
2005 (M) 2005 (D) 2008 (D) 2008 (D) 2007 (N) 2006 (M) 2005 (D) .. 2006 (M) 2007 (D) 2006 (D) 2008 (N) 2007 (D) 2007 (M) 2006 (M) 2005 (M) 2002 (D) 2006 (D) 2007 (N) 2003 (W) 2006 (M) .. 2005 (D) 2008 (D) 2009 (D) 2006 (M) 2005 (D) 2007 (D) 2010 (M) 2009 (D) 2009 (D) 2007 (D) 2007 (D) 2009 (D) 2001 (M) 2000 (M) 2004 (D) 2009 (D) 2008 (D) 2006 (M) 2005 (D) 2008 (D) 2006 (D) 2006 (D) 2007 (M) 2009 (D) 2006 (D) 2006 (M) 2000 (M) 2007 (D) 2006 (M) 2005 (D) 2006 (D) 2006 (M) 2005 (D) 2004 (D) .. 2006 (D) 2005 (D)
0.065 0.007 0.064 0.024 0.005 0.008 0.053 .. 0.021 d 0.187 0.159 0.057 0.095 0.129 0.019 0.068 0.084 0.128 0.048 e 0.127 e 0.059 .. 0.283 0.144 0.208 0.267 0.251 0.184 0.119 0.229 0.154 0.264 e 0.292 0.360 0.452 0.154 e 0.287 0.357 0.367 0.283 0.384 0.310 0.350 0.299 0.352 e 0.156 0.367 0.284 0.408 d 0.328 0.139 0.426 0.412 0.324 0.353 0.381 .. 0.180 0.562
15.8 1.9 13.4 6.0 0.4 2.3 13.4 .. 5.5 d 39.6 32.5 13.4 20.8 30.1 4.9 17.1 17.7 28.0 10.6 e 25.9 e 14.2 .. 53.7 31.2 40.6 47.2 52.0 41.4 27.2 47.8 34.5 49.4 e 57.8 68.1 77.4 31.8 e 53.3 66.9 65.2 52.5 66.9 54.1 64.7 56.4 61.7 e 35.3 72.3 54.3 73.9 d 64.2 29.3 80.2 71.8 60.4 61.5 72.1 .. 39.7 88.6
402 72 12,083 4,699 52 603 100 .. 1,041 d 855 2,281 6,609 48,352 67 249 1,104 14,249 1,538 3,287 e 3,134 e 3,996 .. 612,203 7,258 1,600 2,757 6,946 469 197 18,863 56 81,236 e 83,207 749 11,137 14,297 e 9,149 13,463 27,559 11,176 7,273 81,510 18,008 5,346 1,982 e 759 21,235 3,003 416 d 7,740 241 7,380 5,652 935 11,083 8,993 .. 4,974 65,798
41.0 36.7 47.4 40.7 37.3 36.2 39.5 .. 37.5 d 47.2 48.9 42.3 45.9 42.7 38.8 40.0 47.2 45.7 45.3 e 49.1 e 41.3 .. 52.7 46.2 51.2 56.5 48.4 44.5 43.9 48.0 44.7 53.4 e 50.4 52.9 58.4 48.3 e 53.9 53.3 56.3 53.9 57.4 57.3 54.0 53.0 57.1 e 44.1 50.7 52.4 55.2 d 51.2 47.3 53.2 57.4 53.6 57.4 52.8 .. 45.3 63.5
20.6 6.4 9.1 7.2 8.8 8.1 6.7 .. 7.1 d 23.6 22.0 22.2 12.2 33.5 9.2 23.0 18.5 17.4 12.3 e 9.8 e 14.3 .. 16.4 21.6 17.7 14.1 21.3 24.4 17.2 27.4 24.3 11.0 e 21.2 18.2 10.7 13.4 e 19.3 17.9 23.0 13.0 11.6 17.8 15.6 18.8 15.1 e 26.7 19.4 21.6 16.0 d 17.2 16.1 14.9 13.2 17.6 15.3 20.0 .. 24.0 6.1
3.2 0.1 5.7 1.0 0.1 0.1 2.1 .. 0.5 d 14.7 11.3 2.4 7.6 6.5 0.9 3.1 6.0 11.2 3.3 e 14.5 e 3.1 .. 28.6 11.4 22.9 28.1 22.0 13.0 8.5 19.8 10.7 27.4 e 26.2 38.7 54.8 9.4 e 30.4 35.4 43.7 31.9 44.4 33.9 37.1 32.3 40.7 e 11.1 39.7 28.7 43.8 d 34.8 12.5 50.6 47.2 35.5 39.3 40.4 .. 14.8 72.3
11.6 0.5 2.9 0.3 0.6 0.6 1.6 .. 1.7 14.7 11.9 4.6 10.2 7.9 1.6 10.5 15.3 20.4 4.4 3.7 6.4 .. 11.9 12.2 17.2 27.8 28.6 24.0 2.6 30.8 9.4 6.9 2.5 35.7 51.3 25.2 32.5 49.4 47.3 31.9 31.7 35.7 14.4 35.6 45.4 18.4 60.3 33.4 45.0 49.8 6.7 63.5 33.2 20.8 25.0 44.0 .. 24.2 53.8
13.7 1.0 6.1 1.0 0.2 0.1 4.6 .. 1.0 36.4 23.0 9.6 13.2 20.1 1.0 3.4 10.0 27.7 6.5 6.6 5.1 .. 48.2 29.9 38.9 38.6 48.3 37.8 16.9 42.6 29.6 32.1 48.2 47.6 68.5 19.1 48.5 66.5 64.1 25.7 51.4 39.6 56.3 52.2 54.5 31.2 69.1 52.9 72.8 57.4 16.3 65.7 69.5 32.1 51.9 71.6 .. 31.6 83.7
15.7 1.5 11.0 .. 0.1 0.9 2.5 .. 0.1 37.5 29.6 8.0 15.5 29.5 2.8 10.1 .. 27.4 4.9 23.0 2.7 .. 51.1 31.0 35.9 47.1 51.6 37.8 22.1 47.6 31.3 40.5 56.7 67.6 71.0 .. 52.5 66.9 65.0 28.4 53.2 52.8 63.4 56.2 53.4 32.8 72.3 54.2 72.3 63.0 8.8 80.2 71.3 60.3 .. 72.0 .. 39.0 88.3
22.4 1.9 22.6 2.0 .. 46.3 .. .. 1.7 .. 23.3 17.4 18.7 .. 1.9 21.5 13.1 15.8 2.5 16.9 4.0 21.0 41.6 30.0 54.1 33.9 28.3 62.9 26.2 19.7 28.6 22.6 49.6 37.4 54.3 .. 9.6 67.8 67.9 17.5 33.5 64.4 55.1 54.9 21.2 43.4 28.7 38.7 46.1 64.3 18.8 76.8 47.3 34.3 23.8 73.9 .. .. 39.0
35.2 29.0 26.5 22.0 21.9 .. .. 30.6 .. 38.0 60.0 23.0 13.3 .. 43.1 47.2 14.5 46.2 9.0 51.0 22.9 26.6 27.5 28.5 50.1 27.6 30.1 69.2 23.2 45.9 53.8 22.3 40.0 49.9 .. .. 39.9 68.7 33.4 34.8 50.8 54.7 30.9 77.0 46.3 56.6 24.5 61.7 44.8 59.3 .. 58.5 39.0 58.0 42.7 52.4 36.0 72.0 38.9
LOW HUMAN DEVELOPMENT 143 Kenya 144 São Tomé and Príncipe 145 Pakistan 146 Bangladesh 147 Timor-Leste 148 Angola 149 Myanmar 150 Cameroon 151 Madagascar 152 Tanzania, United Republic of 154 Yemen 155 Senegal 156 Nigeria 157 Nepal 158 Haiti 159 Mauritania 160 Lesotho 161 Uganda 162 Togo 163 Comoros 164 Zambia 165 Djibouti 166 Rwanda 167 Benin 168 Gambia 170 Côte d'Ivoire 171 Malawi 172 Afghanistan 173 Zimbabwe 174 Ethiopia
144
human development report 2011
multidimensional poverty Index
Population in multidimensional povertya Multidimensional Poverty Index HDI rank Yearb Valuea Headcount (%) Population Population Intensity of vulnerable in severe deprivation to poverty poverty (%) (%) (thousands) (%) Share of multidimensional poor with deprivations in environmental services Clean water (%) Improved sanitation (%) Modern fuels (%) Population below income poverty line PPP $1.25 a day (%) National poverty line (%)
2000–2009c 2000–2009c
175 176 178 179 180 181 182 183 184 185 186 187
Mali Guinea-Bissau Guinea Central African Republic Sierra Leone Burkina Faso Liberia Chad Mozambique Burundi Niger Congo, Democratic Republic of the
2006 (D) .. 2005 (D) 2000 (M) 2008 (D) 2006 (M) 2007 (D) 2003 (W) 2009 (D) 2005 (M) 2006 (D) 2007 (D) 2006 (M)
0.558 .. 0.506 0.512 0.439 0.536 0.485 0.344 0.512 0.530 0.642 0.393 0.514
86.6 .. 82.5 86.4 77.0 82.6 83.9 62.9 79.3 84.5 92.4 73.2 81.2
11,771 .. 7,459 3,198 4,321 12,078 2,917 5,758 18,127 6,127 12,437 44,485 6,941
64.4 .. 61.3 59.3 57.0 64.9 57.7 54.7 64.6 62.7 69.4 53.7 63.3
7.6 .. 9.3 11.8 13.1 8.6 9.7 28.2 9.5 12.2 4.0 16.1 9.5
68.4 .. 62.3 55.4 53.2 65.8 57.5 44.1 60.7 61.9 81.8 46.5 65.6
43.7 .. 37.7 53.6 50.3 43.0 33.5 42.9 44.1 51.6 64.1 55.5 70.0
79.5 .. 75.6 53.3 71.1 69.6 78.9 58.4 63.2 63.1 89.3 62.0 69.1
86.5 .. 82.5 86.1 76.9 82.4 83.9 61.3 78.7 84.3 92.3 72.8 81.0
51.4 48.8 43.3 62.8 53.4 56.5 83.7 61.9 60.0 81.3 43.1 59.2 ..
47.4 64.7 53.0 62.0 66.4 46.4 63.8 55.0 54.7 66.9 59.5 71.3 ..
table
OTHER COUNTRIES OR TERRITORIES Somalia
5
NOTES a. Not all indicators were available for all countries; caution should thus be used in cross-country comparisons. Where data are missing, indicator weights are adjusted to total 100 percent. For details on countries missing data, see Alkire and others (2011). b. D indicates data are from Demographic and Health Surveys, M indicates data are from Multiple Indicator Cluster Surveys, W indicates data are from World Health Surveys and N indicates data are from national surveys. c. Data refer to the most recent year available during the period specified. d. Upper bound estimate. e. Lower bound estimate. f. Refers to only part of the country. DEFINITIONS Multidimensional Poverty Index: Percentage of the population that is multidimensionally poor adjusted by the intensity of the deprivations. See Technical note 4 for details on how the Multidimensional Poverty Index is calculated. Multidimensional poverty headcount: Percentage of the population with a weighted deprivation score of at least 33 percent. Intensity of deprivation of multidimensional poverty: Average percentage of deprivation experienced by people in multidimensional poverty. Population vulnerable to poverty: Percentage of the population at risk of suffering multiple deprivations —that is, those with a deprivation score of 20–33 percent. Population in severe poverty: Percentage of the population in severe multidimensional poverty—that is, those with a deprivation score of 50 percent or more. Share of multidimensional poor with deprivations in clean water: Percentage of the multidimensionally poor population without access to clean water that is less than a 30 minute walk from home. Clean water is defined using the Millennium Development Goal definition and includes piped water into dwelling, plot
or yard; public tap/standpipe; borehole/tube well; protected dug well; protected spring; rainwater collection; and bottled water (if a secondary available source is also improved). It does not include unprotected well, unprotected spring, water provided by carts with small tanks/drums, tanker truck-provided water and bottled water (if secondary source is not an improved source); or surface water taken directly from rivers, ponds, streams, lakes, dams or irrigation channels. Share of multidimensional poor with deprivations in improved sanitation: Percentage of the multidimensionally poor population without access to an improved sanitation facility. Improved sanitation facilities are defined using the Millennium Development Goal definition and include flush or pour-flush to piped sewer system or septic tank, ventilated improved pit latrine, pit latrine with slab and composting toilet. Facilities are not considered improved when they are shared with other households or open to the public. Share of multidimensional poor with deprivations in modern fuels: Percentage of the multidimensionally poor population without access to modern fuels. Households are considered deprived of modern fuels if they cook with wood, charcoal or dung. Population below PPP $1.25 a day: Percentage of the population living below the international poverty line $1.25 (in purchasing power parity terms) a day. Population below national poverty line: Percentage of the population living below the national poverty line, which is the poverty line deemed appropriate for a country by its authorities. National estimates are based on population-weighted subgroup estimates from household surveys. MAIN DATA SOURCES Columns 1 and 2: Calculated from various household surveys, including ICF Macro Demographic and Health Surveys, United Nations Children’s Fund Multiple Indicator Cluster Surveys and World Health Organization World Health Surveys conducted between 2000 and 2010. Columns 3–10: Calculated based on data on household deprivations in education, health and living standards from various household surveys as listed in column 1. Columns 11 and 12: World Bank (2011a).
STATISTICAL TAbLeS
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6
table
environmental sustainability
COMPOSITE MEASURES OF SUSTAINABILITY PRIMARY ENERGY SUPPLY a CARBON DIOxIDE EMISSIONS POLLUTION NATURAL RESOURCE DEPLETION AND BIODIVERSITY Fresh water withdrawals (% of total renewable water resources)
HDI rank
EnvironEcological mental Adjusted footprint performance net savings (hectares index (% of GNI) per capita) (0–100) 2005–2009b 2007 2010
Fossil Renewfuels ables (% of (% of total) total) 2007 2007
Greenhouse gas emissions Urban Per capita per capita pollution (tonnes (micro- Natural of carbon grams resource (average dioxide per cubic depletion annual % (tonnes) growth) equivalent) metre) (% of GNI) 2008 1970/2008 2005 2008 2009
Forest Endanarea Change gered (% of in forest species area (% of all land area) (%) species)
2003–2010b 2008 1990–2008 2010
VERY HIGH HUMAN DEVELOPMENT 1 Norway 2 Australia 3 Netherlands 4 United States 5 New Zealand 6 Canada 7 Ireland 8 Liechtenstein 9 Germany 10 Sweden 11 Switzerland 12 Japan 13 Hong Kong, China (SAR) 14 Iceland 15 Korea, Republic of 16 Denmark 17 Israel 18 Belgium 19 Austria 20 France 21 Slovenia 22 Finland 23 Spain 24 Italy 25 Luxembourg 26 Singapore 27 Czech Republic 28 United Kingdom 29 Greece 30 United Arab Emirates 31 Cyprus 32 Andorra 33 Brunei Darussalam 34 Estonia 35 Slovakia 36 Malta 37 Qatar 38 Hungary 39 Poland 40 Lithuania 41 Portugal 42 Bahrain 43 Latvia 44 Chile 45 Argentina 46 Croatia 47 Barbados HIGH HUMAN DEVELOPMENT 48 Uruguay 49 Palau 50 Romania 51 Cuba 52 Seychelles 53 Bahamas 54 Montenegro 55 Bulgaria
12.8 1.7 11.6 –0.8 8.0 5.8 –1.1 .. 11.4 16.0 21.6 12.1 .. 4.1 20.0 10.7 12.2 13.2 15.0 7.0 13.6 8.1 9.7 6.1 7.6 33.0 11.3 2.2 –7.9 .. 0.4 .. –1.8 14.4 19.8 .. .. 4.5 9.7 6.0 –1.8 10.6 20.4 3.2 10.6 12.3 .. 6.1 .. 18.8 .. .. .. .. 6.1
5.6 6.8 6.2 8.0 4.9 7.0 6.3 .. 5.1 5.9 5.0 4.7 .. .. 4.9 8.3 4.8 8.0 5.3 5.0 5.3 6.2 5.4 5.0 9.4 5.3 5.7 4.9 5.4 10.7 .. .. .. 7.9 4.1 .. 10.5 3.0 4.3 4.7 4.5 .. 5.6 3.2 2.6 3.7 .. 5.1 .. 2.7 1.9 .. .. .. 4.1
81.1 65.7 66.4 63.5 73.4 66.4 67.1 .. 73.2 86.0 89.1 72.5 .. 93.5 57.0 69.2 62.4 58.1 78.1 78.2 65.0 74.7 70.6 73.1 67.8 69.6 71.6 74.2 60.9 40.7 56.3 .. 60.8 63.8 74.5 76.3 48.9 69.1 63.1 68.3 73.0 42.0 72.5 73.3 61.0 68.7 .. 59.1 .. 67.0 78.1 .. .. .. 62.5
58.6 94.6 92.5 85.0 66.7 74.9 90.2 .. 80.1 33.1 52.7 83.0 94.9 17.1 81.2 80.4 96.6 73.8 71.6 51.0 69.4 48.0 81.7 89.9 88.0 100.0 81.2 90.2 92.8 100.0 96.0 .. 100.0 88.3 70.0 99.9 100.0 77.8 93.8 60.8 78.3 100.3 64.3 77.6 89.8 85.1 .. 64.9 .. 79.4 89.9 .. .. .. 76.2
45.3 5.4 4.4 5.4 33.1 17.0 3.8 .. 8.9 32.4 20.6 3.4 0.4 82.9 1.5 18.9 4.9 4.2 27.1 7.6 11.2 26.1 7.9 8.2 3.0 0.0 5.4 2.8 5.6 0.0 4.0 .. 0.0 12.0 5.7 0.1 0.0 6.3 6.3 9.3 18.3 0.0 30.8 22.1 7.1 8.7 .. 33.2 .. 14.1 10.1 .. .. .. 5.3
10.5 19.0 10.5 17.3 7.8 16.4 9.8 .. 9.6 5.3 5.3 9.5 5.5 7.1 10.6 8.4 5.4 9.9 8.1 6.1 8.5 10.7 7.4 7.5 21.9 7.0 11.3 8.5 8.8 34.6 9.9 6.4 27.0 13.6 7.0 6.3 53.5 5.5 8.3 4.5 5.3 29.0 3.4 4.4 4.8 5.3 5.3 2.5 10.4 4.4 2.8 8.1 6.4 3.1 6.7
1.0 1.3 –0.1 –0.6 1.2 0.1 1.1 .. .. –2.0 –0.5 0.7 2.6 0.1 5.0 –1.1 –0.1 –0.7 0.5 –0.9 .. 0.5 2.0 0.8 –1.6 –0.6 .. –0.8 3.1 –1.8 3.4 .. –2.2 .. .. 3.0 –0.6 –0.6 –0.3 .. 3.1 2.4 .. 1.4 0.9 .. 2.9 0.5 .. –0.8 0.7 7.4 –2.3 .. –0.2
5.8 9.6 2.4 3.7 10.0 4.7 5.8 .. 1.9 2.1 1.2 1.0 0.5 3.3 1.2 2.9 1.1 1.8 1.9 2.3 2.6 3.4 1.7 1.4 3.5 1.4 2.1 1.8 1.4 6.2 1.3 .. 17.9 2.3 1.4 0.9 18.0 1.6 2.7 2.5 1.8 4.3 2.3 1.6 3.9 1.5 .. 8.1 .. 1.7 1.4 .. .. .. 2.0
16 14 31 19 12 15 13 17 16 11 22 27 .. 14 31 16 28 21 29 13 29 15 28 23 13 31 18 13 32 89 34 17 51 13 13 .. 35 16 35 17 21 49 13 62 68 27 38 160 .. 12 21 .. .. .. 51
10.6 5.1 0.8 0.7 0.9 2.3 0.1 .. 0.1 0.2 .. 0.0 .. .. 0.0 1.5 0.2 0.0 0.1 0.0 0.2 0.1 0.0 0.1 .. .. 0.3 1.2 0.2 .. .. .. .. 0.7 0.3 .. .. 0.2 1.0 0.2 0.1 .. 0.3 10.0 4.9 0.8 .. 0.4 .. 1.3 .. .. .. .. 1.1
0.8 .. 11.7 15.6 .. .. .. .. 21.0 1.5 .. .. .. 0.1 .. 10.8 101.9 34.0 .. 15.0 3.0 1.5 29.0 .. .. .. 14.8 8.8 12.7 2,032.0 19.3 .. .. 14.0 1.4 .. 455.2 5.4 19.4 9.6 .. 219.8 .. .. .. 0.6 .. .. .. 3.2 .. .. .. .. 28.7
32.4 19.7 10.8 33.2 31.5 34.1 10.5 43.1 31.8 68.7 30.8 68.5 .. 0.3 c 64.3 12.7 7.1 22.3 47.0 29.0 62.0 72.9 35.7 30.6 33.5 3.3 34.3 11.8 29.8 3.8 18.7 34.0 72.8 52.6 40.2 0.9 0.0 22.4 30.5 34.2 37.7 0.6 53.6 21.7 10.9 34.2 19.4 9.5 87.6 28.3 26.3 88.5 51.4 40.4 35.1
8.6 –2.2 5.8 2.3 7.3 0.0 55.1 6.2 3.1 3.4 6.9 0.0 .. 223.0 –2.1 21.3 17.0 .. 2.7 9.1 .. 1.2 29.0 18.5 .. 0.0 .. 9.8 16.5 28.7 7.4 0.0 –7.1 .. .. 0.0 0.0 11.6 4.5 .. 3.6 145.0 .. 5.8 –14.1 .. 0.0 79.8 .. 2.0 36.1 0.0 0.0 .. 14.7
7 22 5 21 25 7 7 1 9 5 6 15 9 9 10 6 12 5 11 14 13 4 16 14 2 17 5 10 16 9 8 3 9 3 5 7 8 8 5 4 19 8 4 10 9 13 8 12 13 9 18 18 10 11 9
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environmental sustainability
COMPOSITE MEASURES OF SUSTAINABILITY PRIMARY ENERGY SUPPLY a CARBON DIOxIDE EMISSIONS NATURAL RESOURCE DEPLETION AND BIODIVERSITY Fresh water withdrawals (% of total renewable water resources) 2003–2010b 943.3 17.5 .. .. .. .. .. .. .. .. .. .. .. .. .. 28.1 .. .. 0.9 2.6 .. 26.4 16.1 .. .. .. .. .. 0.7 .. 36.4 .. 67.7 86.6 .. 35.2 18.8 .. ..
POLLUTION
HDI rank
Adjusted net savings (% of GNI) 2005–2009b –3.9 9.1 28.4 .. .. 15.4 –32.4 15.7 .. 16.9 –0.8 .. –1.2 15.2 8.2 2.7 .. 2.9 .. –7.1 5.6 8.0 11.6 6.9 8.6 .. .. 4.4 4.6 –8.8 9.6 5.4 .. –7.9 .. 5.4 2.9 9.2 14.6
Environmental Ecological Fossil Renewfootprint performance fuels ables index (hectares (% of (% of per capita) (0–100) total) total) 2007 5.1 3.0 2.9 2.4 .. 4.9 3.1 6.3 3.1 3.8 4.4 .. 4.5 2.7 1.9 2.9 .. 2.9 2.7 1.8 2.9 4.3 5.7 1.9 1.5 .. .. 1.9 2.9 .. 1.8 1.9 2.7 5.0 .. 1.9 2.7 .. 1.9 2010 55.3 67.3 71.4 .. 69.8 65.0 54.2 51.1 50.1 65.4 61.2 .. 57.3 86.4 71.4 57.9 .. 62.9 55.9 63.6 58.2 80.6 60.6 58.0 69.3 .. .. 69.3 63.4 .. 60.4 76.8 60.0 45.9 .. 59.1 60.4 69.9 60.6 2007 100.0 88.8 75.7 89.5 .. 95.1 99.9 100.0 99.1 92.1 90.9 .. 98.8 45.6 63.7 95.4 .. 87.6 92.8 66.6 81.8 .. 84.2 88.5 76.1 .. .. 83.9 52.6 .. 73.5 72.7 99.4 100.0 .. 98.9 90.6 .. 86.3 2007 0.0 9.9 24.1 10.5 .. 5.0 0.1 0.0 0.9 5.5 3.0 .. 1.1 54.5 26.2 3.7 .. 12.5 9.6 33.7 1.4 .. 8.2 11.5 23.9 .. .. 15.7 44.5 .. 5.2 27.7 0.7 0.0 .. 1.5 9.5 .. 13.7
Greenhouse gas emissions Urban Per capita per capita pollution (tonnes (micro- Natural of carbon grams resource (average dioxide per cubic depletion annual % (tonnes) growth) equivalent) metre) (% of GNI) 2008 1970/2008 17.2 2.1 4.4 1.8 2.0 0.9 5.1 .. 5.2 –0.7 7.7 4.7 37.3 3.7 26.3 –0.6 9.3 –1.5 6.5 .. 12.1 .. 2.4 4.4 15.3 .. 1.8 2.5 1.3 –0.7 4.1 2.5 4.9 .. 6.0 –0.4 8.3 .. 1.2 .. 7.0 .. 3.1 4.4 5.8 .. 4.5 1.4 1.4 0.1 1.9 4.4 2.3 3.4 2.0 2.7 2.1 2.0 1.9 4.7 1.8 .. 1.5 0.3 7.3 2.2 16.4 11.0 1.7 5.0 5.4 .. 3.9 3.2 1.4 0.9 2.5 3.2 2005 2.5 1.7 1.4 2.3 .. 2.4 7.8 6.3 2.7 2.4 4.9 .. 4.3 0.9 1.1 0.4 .. 3.0 1.2 1.4 2.1 .. 1.0 0.7 0.9 .. .. 1.7 4.0 .. 1.3 1.8 2.1 7.1 .. 4.7 1.4 .. 1.0 2008 104 33 34 .. 13 20 105 95 76 7 16 21 15 32 46 36 17 9 19 49 18 18 20 37 51 22 34 20 21 24 69 20 55 94 .. 33 37 13 26 2009 28.9 5.4 .. 0.4 .. 7.9 28.2 .. 30.5 0.9 14.5 .. 22.0 0.2 1.3 .. .. 9.8 1.6 0.1 3.8 0.0 0.1 0.7 5.9 0.0 .. 9.9 3.1 .. 0.5 6.2 17.9 .. 0.0 32.7 0.2 .. 4.6
Forest Endanarea Change gered (% of in forest species area (% of all land area) (%) species) 2008 1990–2008 2010 0.5 c 0.0 9 33.5 –7.4 17 44.0 –13.6 6 29.6 .. 7 22.3 –4.9 8 62.8 –7.8 18 44.4 –5.3 6 0.3 c 70.6 9 0.1 c 0.0 9 42.2 .. 4 49.4 .. 9 50.0 0.0 10 1.2 .. 8 50.1 –0.2 7 28.4 –1.3 15 13.4 4.4 10 42.3 0.0 8 53.1 –9.9 8 42.7 .. 10 39.5 .. 9 16.7 .. 8 17.2 –9.9 18 39.2 .. 14 31.2 –1.9 15 53.4 –2.7 8 60.3 –9.6 9 77.0 7.3 9 41.3 –25.7 12 61.9 –8.9 10 d 68.1 4.9 8 9.5 .. 7 54.7 –2.9 11 6.8 0.0 9 0.0 c 0.0 9 12.5 0.0 10 11.3 .. 8 14.4 14.6 15 61.9 –11.0 6 6.3 51.4 11
56 Saudi Arabia 57 Mexico 58 Panama 59 Serbia 60 Antigua and Barbuda 61 Malaysia 62 Trinidad and Tobago 63 Kuwait 64 Libya 65 Belarus 66 Russian Federation 67 Grenada 68 Kazakhstan 69 Costa Rica 70 Albania 71 Lebanon 72 Saint Kitts and Nevis 73 Venezuela, Bolivarian Republic of 74 Bosnia and Herzegovina 75 Georgia 76 Ukraine 77 Mauritius 78 Former Yugoslav Republic of Macedonia 79 Jamaica 80 Peru 81 Dominica 82 Saint Lucia 83 Ecuador 84 Brazil 85 Saint Vincent and the Grenadines 86 Armenia 87 Colombia 88 Iran, Islamic Republic of 89 Oman 90 Tonga 91 Azerbaijan 92 Turkey 93 Belize 94 Tunisia MEDIUM HUMAN DEVELOPMENT 95 Jordan 96 Algeria 97 Sri Lanka 98 Dominican Republic 99 Samoa 100 Fiji 101 China 102 Turkmenistan 103 Thailand 104 Suriname 105 El Salvador 106 Gabon 107 Paraguay 108 Bolivia, Plurinational State of 109 Maldives 110 Mongolia 111 Moldova, Republic of 112 Philippines 113 Egypt 114 Occupied Palestinian Territory 115 Uzbekistan 116 Micronesia, Federated States of
table
6
3.0 .. 16.4 0.4 .. 3.4 39.7 .. 20.5 .. 3.7 1.8 5.2 6.2 31.4 24.9 16.2 28.0 3.1 .. .. ..
2.1 1.6 1.2 1.5 .. .. 2.2 3.9 2.4 .. 2.0 1.4 3.2 2.6 .. .. 1.4 1.3 1.7 .. 1.7 ..
56.1 67.4 63.7 68.4 .. 65.9 49.0 38.4 62.2 68.2 69.1 56.4 63.5 44.3 65.9 42.8 58.8 65.7 62.0 .. 42.3 ..
98.0 1.7 99.8 0.2 43.4 56.6 79.2 20.8 .. .. .. .. 86.9 12.3 100.7 0.0 80.6 19.3 .. .. 38.4 61.6 43.8 56.2 28.2 163.1 82.1 17.9 .. .. 96.2 3.3 89.1 2.8 56.9 43.1 96.1 4.0 .. .. 98.1 1.9 .. ..
3.5 3.2 0.6 2.2 0.9 1.5 5.2 9.5 4.3 4.7 1.0 1.7 0.7 1.3 3.0 4.1 1.3 0.9 2.6 0.5 4.6 0.6
3.3 2.9 1.9 3.1 3.9 1.1 4.6 .. 6.3 0.2 2.5 –2.1 2.1 2.1 .. 1.6 .. 0.8 3.9 .. .. ..
0.5 1.8 0.6 0.9 .. .. 1.5 6.7 1.6 .. 0.8 6.4 4.1 4.9 .. 3.7 1.1 0.8 0.9 .. 1.9 ..
33 69 74 16 .. 19 66 65 55 24 28 7 67 74 29 111 36 19 97 .. 40 ..
1.1 16.9 0.5 0.5 0.3 .. 3.1 30.4 3.2 .. 0.5 29.2 .. 11.2 .. 11.1 0.2 1.0 7.3 .. 17.8 ..
99.4 .. 24.5 .. .. .. 19.5 .. 13.1 .. .. .. .. .. 15.7 .. .. 17.0 .. 49.9 .. ..
1.1 0.6 30.1 40.8 60.4 55.1 21.6 8.8 37.1 94.6 14.3 85.4 45.2 53.4 3.0 7.1 11.5 25.3 0.1 c 1.5 7.7 91.5
0.0 –9.4 –19.6 43.3 31.5 5.7 28.1 .. –3.1 –0.1 –21.5 0.0 –15.2 –7.9 0.0 –11.8 .. 15.0 56.4 1.0 .. ..
10 13 19 17 12 15 12 8 14 3 3 6 4 4 10 7 6 19 10 .. 7 15
STATISTICAL TAbLeS
147
environmental sustainability
COMPOSITE MEASURES OF SUSTAINABILITY PRIMARY ENERGY SUPPLY a CARBON DIOxIDE EMISSIONS NATURAL RESOURCE DEPLETION AND BIODIVERSITY Fresh water withdrawals (% of total renewable water resources) 2003–2010b .. .. 99.8 .. .. .. .. .. .. .. .. 9.3 .. .. .. .. .. 40.1 .. .. .. .. 0.5 .. 0.4
POLLUTION
HDI rank
Adjusted net savings (% of GNI) 2005–2009b –0.4 9.6 –14.1 21.9 9.5 .. 0.4 11.0 12.4 9.4 6.2 16.6 3.4 25.0 4.0 .. .. 24.1 –4.7 .. –44.7 17.8 13.0 –0.9 ..
Environmental Ecological Fossil Renewfootprint performance fuels ables index (hectares (% of (% of per capita) (0–100) total) total) 2007 .. 2.7 1.5 2.2 1.9 .. 2.3 1.2 .. 1.2 1.0 1.4 1.6 1.2 1.8 1.3 .. 0.9 1.8 .. 1.0 1.3 1.0 1.5 .. 2010 59.2 41.3 64.6 59.3 49.9 .. 50.8 44.6 .. 59.7 51.3 59.0 57.1 65.6 54.0 41.0 .. 48.3 51.3 41.9 54.0 59.6 41.7 54.4 68.0 2007 .. 67.2 98.7 71.6 54.1 .. 87.2 65.6 .. 69.2 42.3 54.0 38.5 93.6 42.9 99.4 .. 71.1 27.8 .. 43.5 .. 29.7 .. .. 2007 .. 22.3 1.3 18.1 45.9 .. 10.5 34.4 .. 32.4 54.7 45.6 61.5 3.9 57.2 0.2 .. 28.1 72.5 .. 53.7 .. 69.7 .. ..
Greenhouse gas emissions Urban Per capita per capita pollution (tonnes (micro- Natural of carbon grams resource (average dioxide per cubic depletion annual % (tonnes) growth) equivalent) metre) (% of GNI) 2008 1970/2008 2.0 –0.3 2.5 .. 3.4 3.1 1.9 .. 1.2 2.2 0.3 –0.8 8.8 0.7 1.8 4.8 0.4 –0.4 1.1 .. 0.5 .. 1.5 2.1 0.8 0.7 1.5 3.1 0.9 1.9 3.4 1.0 0.6 4.1 1.5 3.8 0.4 0.5 7.3 11.3 0.6 0.7 0.5 0.3 0.3 1.8 1.0 0.4 1.1 12.5 2005 .. 4.1 0.9 4.4 1.2 .. 1.9 1.5 .. 1.0 0.9 1.3 1.7 0.5 1.1 0.7 .. 0.7 0.6 .. 2.7 .. 1.9 .. .. 2008 22 69 69 48 42 .. 22 72 15 26 43 53 23 27 60 138 .. 59 24 7 68 39 41 35 22 2009 3.4 2.8 10.2 0.3 0.4 .. 5.4 6.5 .. 0.5 0.2 7.2 0.8 1.4 1.2 45.7 .. 4.2 6.9 66.0 50.6 .. 0.2 0.1 5.3
Forest Endanarea Change gered (% of in forest species area (% of all land area) (%) species) 2008 1990–2008 2010 77.2 0.0 3 20.4 –15.5 2 2.6 28.8 13 9.0 –15.1 5 48.5 –33.2 7 15.0 0.0 14 7.6 0.0 15 52.9 –19.2 16 36.1 0.0 14 4.8 .. 6 2.9 .. 6 43.6 44.3 12 27.0 –27.9 4 11.5 1.2 16 35.2 –20.6 8 1.9 2.6 9 21.0 46.1 13 22.9 6.6 13 22.7 –30.6 5 58.8 –11.3 6 65.7 –1.3 4 68.9 –8.1 9 58.6 –20.0 13 32.2 17.4 2 84.1 6.3 7
table
6
117 Guyana 118 Botswana 119 Syrian Arab Republic 120 Namibia 121 Honduras 122 Kiribati 123 South Africa 124 Indonesia 125 Vanuatu 126 Kyrgyzstan 127 Tajikistan 128 Viet Nam 129 Nicaragua 130 Morocco 131 Guatemala 132 Iraq 133 Cape Verde 134 India 135 Ghana 136 Equatorial Guinea 137 Congo 138 Lao People’s Democratic Republic 139 Cambodia 140 Swaziland 141 Bhutan LOW HUMAN DEVELOPMENT 142 Solomon Islands 143 Kenya 144 São Tomé and Príncipe 145 Pakistan 146 Bangladesh 147 Timor-Leste 148 Angola 149 Myanmar 150 Cameroon 151 Madagascar 152 Tanzania, United Republic of 153 Papua New Guinea 154 Yemen 155 Senegal 156 Nigeria 157 Nepal 158 Haiti 159 Mauritania 160 Lesotho 161 Uganda 162 Togo 163 Comoros 164 Zambia 165 Djibouti 166 Rwanda 167 Benin 168 Gambia 169 Sudan 170 Côte d'Ivoire 171 Malawi 172 Afghanistan 173 Zimbabwe 174 Ethiopia 175 Mali 176 Guinea-Bissau 177 Eritrea
–3.7 13.1 .. 10.7 27.1 .. –29.2 .. 6.8 3.9 13.5 .. .. 7.8 .. 29.1 .. .. 24.4 8.6 .. .. 1.4 .. 8.8 4.1 12.9 –7.1 7.3 .. .. .. 8.3 13.5 .. ..
.. 1.1 .. 0.8 0.6 0.4 1.0 1.8 1.0 1.8 1.2 2.1 0.9 1.1 1.4 3.6 0.7 2.6 1.1 1.5 1.0 .. 0.9 .. 1.0 1.2 3.4 1.7 1.0 0.7 0.6 1.2 1.1 1.9 1.0 0.9
51.1 51.4 57.3 48.0 44.0 .. 36.3 51.3 44.6 49.2 47.9 44.3 48.3 42.3 40.2 68.2 39.5 33.7 .. 49.8 36.4 .. 47.0 60.5 44.6 39.6 50.3 47.1 54.3 51.4 .. 47.8 43.1 39.4 44.7 54.6
.. 16.2 .. 61.8 68.4 .. 33.5 31.0 23.9 .. 10.6 .. 99.0 57.3 18.3 10.9 28.3 .. .. .. 14.3 .. 7.5 .. .. 37.1 .. 31.2 25.0 .. .. 26.1 6.7 .. .. 19.9
.. 83.8 .. 37.7 31.6 .. 66.5 69.0 76.1 .. 89.4 .. 1.0 42.4 81.7 89.1 71.7 .. .. .. 83.4 .. 92.3 .. .. 61.0 .. 68.8 75.5 .. .. 69.1 93.3 .. .. 80.1
0.4 0.3 0.8 0.9 0.3 0.2 1.4 0.3 0.3 0.1 0.1 0.3 1.0 0.4 0.6 0.1 0.3 0.6 .. 0.1 0.2 0.2 0.1 0.6 0.1 0.5 0.3 0.3 0.3 0.1 0.0 0.7 0.1 0.0 0.2 0.1
1.0 –0.2 3.8 2.2 .. .. 2.2 1.0 3.1 –0.8 0.3 0.5 .. 0.7 1.3 4.7 3.1 1.4 .. –0.9 1.4 .. –4.7 –0.8 4.2 4.1 2.2 0.1 –0.9 –0.8 –3.5 –2.0 0.7 0.2 1.2 ..
.. 0.9 .. 1.1 0.7 .. 5.1 2.2 1.6 .. 1.4 .. 0.5 1.0 1.1 1.0 0.6 .. .. .. 0.8 .. 3.8 .. .. 0.9 .. 3.0 1.0 .. .. 1.3 1.1 .. .. 0.8
26 30 29 109 134 .. 55 46 47 33 22 18 67 81 46 32 35 68 46 12 29 34 .. 49 26 45 62 159 32 35 37 .. 59 112 47 71
10.9 1.2 1.0 3.1 2.6 .. 29.1 .. 4.8 0.2 2.5 19.9 13.2 0.3 15.0 4.2 .. 18.8 1.4 4.7 3.6 1.0 11.5 0.3 2.4 1.2 1.0 11.1 3.1 0.9 .. 3.5 4.5 .. .. 0.8
.. 8.9 .. 81.5 3.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 9.2
79.5 6.1 28.1 2.3 11.1 51.4 47.1 49.6 43.1 21.8 38.6 64.1 1.0 44.4 10.8 25.4 3.7 0.2 c 1.4 16.1 6.0 2.0 67.0 0.2 c 16.8 42.1 47.6 29.5 32.7 35.1 2.1 42.1 12.6 10.4 72.6 15.3
–4.3 –5.9 0.0 –29.8 –3.1 –20.9 –3.7 –17.4 –16.3 –7.5 –17.5 –8.0 0.0 –8.5 –42.8 –24.5 –11.6 –39.3 9.0 –33.4 –52.3 –68.3 –5.7 0.0 30.5 –19.1 7.8 –8.3 1.8 –15.2 0.0 –26.6 .. –10.1 –7.9 ..
17 8 .. 9 9 5 4 8 11 23 12 12 10 6 7 6 19 7 3 7 4 13 3 9 6 4 4 5 7 9 5 3 7 2 5 8
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environmental sustainability
COMPOSITE MEASURES OF SUSTAINABILITY PRIMARY ENERGY SUPPLY a CARBON DIOxIDE EMISSIONS NATURAL RESOURCE DEPLETION AND BIODIVERSITY Fresh water withdrawals (% of total renewable water resources) 2003–2010b .. .. .. .. .. .. .. .. .. ..
POLLUTION
HDI rank
Adjusted net savings (% of GNI) 2005–2009b –4.2 .. 1.2 2.3 –18.3 .. 2.0 –6.8 16.2 ..
Environmental Ecological Fossil Renewfootprint performance fuels ables index (hectares (% of (% of per capita) (0–100) total) total) 2007 1.7 1.3 1.1 1.3 1.3 1.7 0.8 0.9 2.3 0.8 2010 44.4 33.3 32.1 47.3 .. 40.8 51.2 43.9 37.6 51.6 2007 .. .. .. .. .. .. 7.3 .. .. 4.0 2007 .. .. .. .. .. .. 95.9 .. .. 96.2
Greenhouse gas emissions Urban Per capita per capita pollution (tonnes (micro- Natural of carbon grams resource (average dioxide per cubic depletion annual % (tonnes) growth) equivalent) metre) (% of GNI) 2008 1970/2008 0.1 –0.9 0.1 –1.2 0.3 –0.6 0.1 3.9 0.1 –5.0 0.0 0.2 0.1 –2.7 0.0 1.9 0.1 1.0 0.0 –3.3 2005 .. .. .. .. .. .. 1.1 .. .. 1.9 2008 53 34 38 64 31 81 26 31 96 40 2009 6.6 0.0 2.1 1.6 11.0 25.2 3.8 10.6 1.2 10.7
Forest Endanarea Change gered (% of in forest species area (% of all land area) (%) species) 2008 1990–2008 2010 26.9 –8.9 8 36.4 –2.3 1 38.6 –11.3 7 21.1 –15.7 3 45.6 –11.0 8 9.3 –10.9 3 50.2 –9.1 7 6.8 –39.2 5 1.0 –36.8 3 68.3 –3.5 6
178 Guinea 179 Central African Republic 180 Sierra Leone 181 Burkina Faso 182 Liberia 183 Chad 184 Mozambique 185 Burundi 186 Niger 187 Congo, Democratic Republic of the OTHER COUNTRIES OR TERRITORIES Korea, Democratic People’s Rep. of Marshall Islands Monaco Nauru San Marino Somalia Tuvalu Human Development Index groups Very high human development High human development Medium human development Low human development Regions Arab States East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean South Asia Sub-Saharan Africa Least developed countries Small island developing states World
.. .. .. .. .. .. .. 6.6 5.0 27.2 .. .. .. 4.7 6.2 22.9 4.7 .. .. 18.3
1.3 .. .. .. .. 1.4 .. 5.9 3.1 1.6 1.2 2.1 .. 3.5 2.6 1.0 1.3 1.2 .. 2.4
41.8 .. .. .. .. .. .. 68.2 63.5 50.3 46.3 56.4 .. 60.4 65.2 49.0 45.7 46.7 .. 54.4
88.9 .. .. .. .. .. .. 81.9 81.2 77.3 .. 88.9 .. 87.7 69.2 69.8 .. .. .. 72.3
11.1 .. .. .. .. .. .. 7.2 15.9 22.2 .. 10.9 .. 6.7 30.4 29.7 .. .. .. 25.1
3.3 1.6 .. 14.2 .. 0.1 .. 11.3 5.9 3.2 0.4 4.6 4.2 7.8 2.9 1.5 0.9 0.2 2.6 4.4
–1.2 .. .. .. .. 0.5 .. 0.3 1.8 3.9 0.6 2.3 4.2 .. 1.5 3.4 0.2 0.1 1.9 2.5
1.0 .. .. .. .. .. .. 2.7 2.9 1.2 .. 1.5 .. 2.9 2.7 0.8 .. .. .. 1.7
59 .. .. .. 8 31 .. 24 30 61 69 89 .. 25 33 70 43 68 .. 52
.. .. .. .. .. .. .. 0.8 8.7 4.4 8.7 .. .. 6.8 .. 6.2 9.8 10.0 .. 2.4
.. .. .. .. .. 22.4 .. .. .. .. .. .. .. .. .. 30.1 .. .. .. ..
49.2 70.2 .. 0.0 0.0 11.0 33.3 5.8 10.2 2.9 1.6 1.1 8.5 24.3 12.2 5.5 1.6 2.0 14.2 1.7
–27.8 .. .. 0.0 0.0 –16.7 0.0 1.2 –3.4 8.3 –13.9 1.8 12.6 .. –7.5 –1.3 –13.8 –12.2 1.1 –1.2
9 12 8 14 0 7 15 14 11 13 8 10 13 9 11 12 7 8 15 12
table
6
NOTES a. The sum of the shares of fossil fuels and renewable energy resources may be greater than 100 percent because some countries generate more electricity than they consume and export the excess. b. Data refer to the most recent year available during the period specified. c. Less than 1 percent. d. For certain amphibian species endemic to Brazil, there was not time for the Global Amphibian Assessment (GAA) Coordinating Team and the experts on the species in Brazil to reach agreement on the Red List Categories. The data for amphibians included in the data displayed here are those that were agreed at the GAA Brazil workshop in April 2003. However, a subsequent GAA check found that many of the assessments were inconsistent with the approach adopted elsewhere in the world, and a “consistent Red List Category” was also assigned to these species. Therefore, data displayed here may not match data in the Global Species Assessment. DEFINITIONS Adjusted net savings: Rate of savings in an economy that takes into account investments in human capital, depletion of natural resources and damage caused by pollution (including particulate emissions), expressed as a percentage of gross national income (GNI). A negative value implies an unsustainable path. Ecological footprint: Amount of biologically productive land and sea area that a country requires to produce the resources it consumes and to absorb the waste it generates. Environmental performance index: Index comprising 25 performance indicators across 10 policy categories covering both environmental public health and ecosystem vitality. Primary energy supply, fossil fuels: Percentage of total energy supply that comes from natural resources formed from biomass in the geological past (such as coal, oil and natural gas). Primary energy supply, renewables: Percentage of total energy supply that comes from constantly replenished natural processes, including solar, wind, biomass, geothermal, hydropower and ocean resources and some waste. Nuclear energy is not included. Carbon dioxide emissions, per capita: Human-originated carbon dioxide emissions stemming from the burning of fossil fuels, gas flaring and the production of cement, divided by midyear population. Greenhouse gas emissions per capita: Emissions from methane, nitrous oxide and other greenhouse gases, including hydrofluorocarbons, perfluorocarbons and sulfur hexafluoride, divided by midyear population. Carbon dioxide emissions are not included.
Urban pollution: Particulate matter concentrations in terms of fine suspended particulates of humanmade or natural origin less than 10 microns (PM10) in diameter that are capable of penetrating deep into the respiratory tract. Data are urban population–weighted PM10 levels in residential areas of cities with more than 100,000 residents. The estimates represent the average annual exposure level of an urban resident to outdoor particulate matter. Natural resource depletion: Monetary expression of energy, mineral and forest depletion, expressed as a percentage of total gross national income (GNI). Fresh water withdrawals: Total fresh water withdrawn in a given year, expressed as a percentage of total renewable water resources. Forest area: Percentage of total land area spanning more than 0.5 hectares with trees higher than 5 metres and a canopy cover of more than 10 percent, or trees able to reach these thresholds, unless under agricultural or urban land use. Change in forest area: Percentage change in area under forest cover. Endangered species: Percentage of animal species (including mammals, birds, reptiles, amphibians, fish and invertebrates) classified as either critically endangered, endangered or vulnerable by the International Union for the Conservation of Nature. MAIN DATA SOURCES Columns 1 and 9: World Bank (2011a). Column 2: Global Footprint Network (2010). Column 3: Emerson and others (2010). Columns 4 and 5: HDRO calculations based on data on total primary energy supply from IEA (2011). Columns 6 and 7: HDRO calculations based on data from Boden, Marland and Andres (2009). Column 8: HDRO calculations based on data from World Bank (2011a) and UNDESA (2011). Column 10: HDRO calculations based on World Bank (2011a). Column 11: FAO (2011a). Columns 12 and 13: HDRO calculations based on data on forest and total land area from FAO (2011a). Column 14: IUCN (2010).
STATISTICAL TAbLeS
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7
table
Human development effects of environmental threats
IMPACT OF NATURAL DISASTERS Population under age 5 suffering from Number of Population affected deaths (average (average annual per annual per million people) million people) 2001/2010 2001/2010 Deaths due to Water pollution (per million people) 2004 Indoor air pollution (per million people) 2004 Outdoor air pollution (per million people) 2004 Malaria (per million people) 2009 Dengue (per million people) 2001–2010a Population living on degraded land (%) 2010
HDI rank
Stunting (%) 2000–2009a
Wasting (%) 2000–2009a
VERY HIGH HUMAN DEVELOPMENT 1 Norway 2 Australia 3 Netherlands 4 United States 5 New Zealand 6 Canada 7 Ireland 8 Liechtenstein 9 Germany 10 Sweden 11 Switzerland 12 Japan 13 Hong Kong, China (SAR) 14 Iceland 15 Korea, Republic of 16 Denmark 17 Israel 18 Belgium 19 Austria 20 France 21 Slovenia 22 Finland 23 Spain 24 Italy 25 Luxembourg 26 Singapore 27 Czech Republic 28 United Kingdom 29 Greece 30 United Arab Emirates 31 Cyprus 32 Andorra 33 Brunei Darussalam 34 Estonia 35 Slovakia 36 Malta 37 Qatar 38 Hungary 39 Poland 40 Lithuania 41 Portugal 42 Bahrain 43 Latvia 44 Chile 45 Argentina 46 Croatia 47 Barbados HIGH HUMAN DEVELOPMENT 48 Uruguay 49 Palau 50 Romania 51 Cuba 52 Seychelles 53 Bahamas
.. .. .. 3.9 .. .. .. .. 1.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 4.4 2.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.0 8.2 .. .. 13.9 .. 12.8 4.6 .. ..
.. .. .. 1.3 .. .. .. .. 1.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 3.3 2.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.5 2.3 .. .. 6.0 .. 3.5 3.9 .. ..
0 3 12 1 0 0 0b .. 12 0 14 1 0 .. 1 0 1 20 4 34 15 0 33 33 34 .. 5 1 1 .. 0 .. .. 0 2 .. .. 7 3 1 26 .. 3 1 0 18 0 1 .. 3 0 0 4
33 1,378 0b 6,689 175 54 11 .. 404 0 77 709 271 .. 1,158 0 270 31 735 891 52 7 14 29 0 .. 2,098 617 112 .. 4 .. .. 7 212 .. .. 467 318 0 1,418 .. 0 3,051 1,790 59 1,968 4,548 .. 764 87,392 7,860 5,979
.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 12 8 .. .. .. .. .. 18 .. ..
.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0b .. .. .. .. .. .. .. .. .. .. .. 0b .. 0b .. 18 53 .. ..
65 35 203 138 0b 85 0b .. 124 56 109 196 .. 0b 152 111 216 203 147 81 150 19 136 137 .. 264 167 189 224 55 197 .. .. 74 74 .. 0b 208 162 204 190 0b 0b 149 342 225 .. 422 .. 439 160 .. ..
.. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 .. .. .. .. .. .. .. 0.0
.. 0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0 0 .. 0 0 49 .. 0 .. 0
0.2 b 9.0 5.4 1.1 5.3 2.7 0.5 b .. 8.1 0.3 b 0.5 b 0.3 b .. .. 2.9 8.5 12.9 10.5 2.7 3.9 8.4 0.0 b 1.4 2.2 .. .. 4.2 2.7 1.1 1.9 11.4 .. .. 5.0 9.1 .. 0.1 b 17.1 13.2 4.8 2.3 .. 1.8 1.1 1.7 17.5 .. 5.7 .. 13.5 17.0 .. ..
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human development effects of environmental threats
IMPACT OF NATURAL DISASTERS Population under age 5 suffering from HDI rank Stunting (%) 2000–2009a Wasting (%) 2000–2009a Number of Population affected deaths (average (average annual per annual per million people) million people) 2001/2010 2001/2010 Deaths due to Water pollution (per million people) 2004 Indoor air pollution (per million people) 2004 Outdoor air pollution (per million people) 2004 Malaria (per million people) 2009 Dengue (per million people) 2001–2010a Population living on degraded land (%) 2010
54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94
Montenegro Bulgaria Saudi Arabia Mexico Panama Serbia Antigua and Barbuda Malaysia Trinidad and Tobago Kuwait Libya Belarus Russian Federation Grenada Kazakhstan Costa Rica Albania Lebanon Saint Kitts and Nevis Venezuela, Bolivarian Republic of Bosnia and Herzegovina Georgia Ukraine Mauritius Former Yugoslav Republic of Macedonia Jamaica Peru Dominica Saint Lucia Ecuador Brazil Saint Vincent and the Grenadines Armenia Colombia Iran, Islamic Republic of Oman Tonga Azerbaijan Turkey Belize Tunisia
7.9 8.8 9.3 15.5 19.1 8.1 .. .. 5.3 .. 21.0 4.5 .. .. 17.5 .. 27.0 16.5 .. 15.6 11.8 14.7 22.9 .. 11.5 3.7 29.8 .. .. 29.0 7.1 .. 18.2 16.2 .. .. .. 26.8 15.6 22.2 9.0 12.0 15.9 17.3 10.1 .. .. 21.8 .. 15.7 .. 24.6 26.3 .. 27.1 31.9 27.5 11.3 33.8
2.2 1.6 5.3 3.4 3.9 1.8 .. .. 4.4 .. 5.6 1.3 .. .. 4.9 .. 6.6 4.2 .. 3.7 1.6 2.3 4.1 .. 1.8 2.2 5.4 .. .. 6.2 2.2 .. 4.2 5.1 .. .. .. 8.4 3.5 4.9 3.3 3.6 3.7 21.1 3.4 .. .. 6.8 .. 7.0 .. 6.1 8.8 .. 4.3 25.7 5.3 3.2 20.7
0 1 1 1 2 0 0 0 0 .. .. 0 40 38 1 2 0 0b .. 1 0 0b 2 0 2 3 6 7 6 1 1 4 0 4 1 5 0 0 0 13 0 0 4 2 9 5 8 1 .. 2 1 7 0 0 5 0 4 1 10
1,249 179 86 7,097 3,612 213 34,720 1,573 131 .. .. 19 1,332 59,003 442 7,367 19,215 414 .. 704 10,673 94 1,421 81 53,874 15,757 20,752 11,372 1,721 3,769 3,440 918 0 14,482 2,156 722 15,857 1,159 224 28,239 320 0 564 22,652 3,480 0 10,511 93,151 .. 58,220 6,013 9,436 149 7,307 18,429 522 59,135 6,532 48,370
.. .. .. 43 63 .. 0 35 .. .. .. .. 5 .. 193 24 32 50 .. 61 .. 89 2 .. .. 75 92 .. .. 83 137 .. 33 50 .. .. .. 212 97 .. 82 77 247 41 142 .. 0b 42 532 121 0b 116 298 86 378 0b 199 0b 182
.. 0b .. 41 63 .. .. 0b 0b .. 0b 10 4 .. 7 47 0b .. .. 8 0b 44 6 .. 0b 188 37 .. .. 0b 58 .. 131 57 4 .. .. 130 51 .. 10 .. 12 219 33 0b 0b 422 .. 159 .. 50 74 52 145 0b 119 78 86
.. 437 108 88 63 .. .. 23 0b 137 318 .. 231 .. 159 47 64 100 .. .. 79 288 305 80 148 75 117 .. .. 38 74 0b 882 61 132 126 .. 177 299 .. 82 134 65 51 88 .. .. 230 170 61 .. 50 .. 86 111 0b .. 261 54
.. .. 0.0 0.0 0.0 .. .. 0.0 .. .. .. .. 0.0 c .. .. 0.2 .. .. .. 0.0 .. 0.0 .. .. .. 0.0 0.1 .. .. 0.0 0.4 .. 0.0 0.3 0.0 0.7 .. 0.0 0.0 c 0.0 .. .. 0.0 0.0 1.4 .. .. 0.0 c 0.0 1.0 0.0 0.0 133.3 0.0 0.0 .. .. .. 0.3
.. .. .. 0 0 .. 0 4 9 .. .. .. .. 0 .. 0 .. .. 0 0 .. .. .. .. .. 0 0 0 0 0 0 0 .. 0 .. .. .. .. .. 0 .. .. .. 2 1 .. 0 0 .. 1 0 0 .. 1 0 0 .. .. 5
8.0 7.8 4.3 3.8 4.1 18.5 .. 1.2 .. 0.6 8.5 4.7 3.1 .. 23.5 1.3 5.7 1.2 .. 1.9 6.1 1.9 6.2 .. 7.1 3.3 0.7 .. .. 1.6 7.9 .. 9.6 2.0 25.1 5.8 .. 3.8 5.5 1.1 36.7 22.0 28.8 21.1 7.0 .. .. 8.6 11.1 17.0 .. 6.3 .. 1.3 2.0 .. 31.5 21.8 2.2
table
7
MEDIUM HUMAN DEVELOPMENT 95 Jordan 96 Algeria 97 Sri Lanka 98 Dominican Republic 99 Samoa 100 Fiji 101 China 102 Turkmenistan 103 Thailand 104 Suriname 105 El Salvador 106 Gabon 107 Paraguay 108 Bolivia, Plurinational State of 109 Maldives 110 Mongolia 111 Moldova, Republic of 112 Philippines
STATISTICAL TAbLeS
151
human development effects of environmental threats
IMPACT OF NATURAL DISASTERS Population under age 5 suffering from HDI rank Stunting (%) 2000–2009a Wasting (%) 2000–2009a Number of Population affected deaths (average (average annual per annual per million people) million people) 2001/2010 2001/2010 Deaths due to Water pollution (per million people) 2004 Indoor air pollution (per million people) 2004 Outdoor air pollution (per million people) 2004 Malaria (per million people) 2009 Dengue (per million people) 2001–2010a Population living on degraded land (%) 2010
table
7
113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141
Egypt Occupied Palestinian Territory Uzbekistan Micronesia, Federated States of Guyana Botswana Syrian Arab Republic Namibia Honduras Kiribati South Africa Indonesia Vanuatu Kyrgyzstan Tajikistan Viet Nam Nicaragua Morocco Guatemala Iraq Cape Verde India Ghana Equatorial Guinea Congo Lao People’s Democratic Republic Cambodia Swaziland Bhutan
30.7 .. 19.6 .. 18.2 29.1 28.6 29.6 29.9 .. .. 40.1 .. 18.1 33.1 30.5 18.8 23.1 54.3 27.5 .. 47.9 28.6 35.0 31.2 47.6 39.5 29.5 37.5 32.8 35.8 29.3 41.5 43.2 55.7 50.8 40.6 36.4 52.8 44.4 43.9 57.7 20.1 41.0 49.3 29.7 24.2 45.2 38.7 26.9 46.9 45.8 32.6 51.7 44.7 27.6 37.9 40.1 53.2
6.8 .. 4.4 .. 10.8 10.7 10.0 17.5 8.6 .. .. 19.6 .. 2.7 14.9 20.2 4.3 9.9 17.7 7.1 .. 43.5 14.3 10.6 11.8 31.6 28.8 6.1 12.0 11.5 16.5 13.1 31.3 41.3 40.6 27.5 29.6 16.6 36.8 16.7 18.1 43.1 14.5 26.7 38.8 18.9 16.7 16.6 16.4 20.5 25.0 14.9 29.6 18.0 20.2 15.8 31.7 16.7 15.5
0 0 0 43 5 0 1 7 4 0 1 2 2 2 3 3 7 1 14 0 1 2 1 .. 0 1 1 0 2 4 2 .. 3 6 0 2 290 0 5 0 4 2 0 0 7 66 1 0 2 1 0 1 6 1 1 1 1 0 4
5 12 5 7,771 54,311 499 6,371 40,481 13,628 85 30,398 1,364 24,519 37,899 47,642 19,794 11,487 419 26,888 226 6,048 41,245 2,925 .. 2,102 15,096 34,829 117,337 0 4,672 27,446 .. 18,218 47,203 1,177 4,989 6,551 204 17,121 13,270 3,987 135 7,377 1,295 9,738 12,565 41,693 45,203 9,460 4,972 381 32,196 82,450 9,919 12,662 4,106 13,909 96 64,924
137 .. 335 0b 269 486 89 98 178 .. 260 141 0b 259 751 72 168 140 314 879 214 405 961 1,187 435 406 826 456 467 219 683 665 380 469 308 3,014 432 1,066 1,175 865 471 734 1,219 1,304 520 619 776 195 988 908 479 1,135 630 1,854 1,271 753 477 1,246 1,459
8 .. 241 .. 0b 270 39 49 119 .. 68 202 0b 418 516 289 131 17 113 23 0b 435 308 .. 290 459 500 274 311 219 412 0b 360 356 .. 2,099 393 664 732 500 269 335 595 699 326 402 405 98 716 605 160 777 0b 1,387 770 411 371 705 1,042
213 .. 148 .. .. 0b 100 0b 89 .. 23 144 .. 80 47 81 19 30 40 387 0b 107 33 .. 145 0b 23 0b .. .. 17 .. 192 68 .. 169 96 128 35 32 .. 55 170 136 30 65 67 0b 4 38 0b 98 252 33 54 137 141 51 48
0.0 c .. 0.0 .. 0.0 3.0 0.0 20.5 0.1 .. 0.9 3.8 8.6 0.0 0.0 0.3 0.0 0.0 c 0.0 0.0 4.1 0.9 141.8 33.8 29.4 0.8 20.0 11.1 5.6 101.1 0.0 141.5 0.0 0.3 48.2 567.5 20.4 257.8 8.6 18.8 90.1 1.6 47.4 48.7 0.3 0.0 26.9 .. 194.5 263.6 0.0 303.5 0.0 78.5 159.9 142.7 32.9 938.3 451.9
.. .. .. .. 0 .. .. .. 1 .. .. 5 .. .. .. 1 2 .. 0 .. .. 0 .. .. .. 1 1 .. 0 .. .. .. .. 0 35 .. 3 .. .. .. 0 .. .. .. 0 .. .. .. .. .. .. .. .. .. .. .. .. .. ..
25.3 .. 27.0 .. .. 22.0 33.3 28.5 15.0 .. 17.5 3.1 .. 9.7 10.5 8.0 13.9 39.1 9.1 4.5 .. 9.6 1.4 .. 0.1 b 4.1 39.3 .. 0.1 b .. 31.0 .. 4.5 11.3 .. 3.3 19.2 15.3 0.0 b 25.0 .. 32.4 16.2 11.5 2.3 15.2 23.8 63.6 23.5 5.1 .. 4.6 7.5 10.1 1.6 17.9 39.9 1.3 19.4
LOW HUMAN DEVELOPMENT 142 Solomon Islands 143 Kenya 144 São Tomé and Príncipe 145 Pakistan 146 Bangladesh 147 Timor-Leste 148 Angola 149 Myanmar 150 Cameroon 151 Madagascar 152 Tanzania, United Republic of 153 Papua New Guinea 154 Yemen 155 Senegal 156 Nigeria 157 Nepal 158 Haiti 159 Mauritania 160 Lesotho 161 Uganda 162 Togo 163 Comoros 164 Zambia 165 Djibouti 166 Rwanda 167 Benin 168 Gambia 169 Sudan 170 Côte d'Ivoire 171 Malawi
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human development effects of environmental threats
IMPACT OF NATURAL DISASTERS Population under age 5 suffering from HDI rank Stunting (%) 2000–2009a Wasting (%) 2000–2009a Number of Population affected deaths (average (average annual per annual per million people) million people) 2001/2010 2001/2010 Deaths due to Water pollution (per million people) 2004 2,499 532 1,546 1,769 2,088 741 1,080 1,088 3,271 1,733 2,134 1,509 840 2,088 3,212 1,924 Indoor air pollution (per million people) 2004 2,023 302 998 b 1,198 1,268 440 641 759 2,181 1,197 1,261 1,013 548 1,449 2,192 1,356 Outdoor air pollution (per million people) 2004 Malaria (per million people) 2009 Dengue (per million people) 2001–2010a Population living on degraded land (%) 2010
172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187
Afghanistan Zimbabwe Ethiopia Mali Guinea-Bissau Eritrea Guinea Central African Republic Sierra Leone Burkina Faso Liberia Chad Mozambique Burundi Niger Congo, Democratic Republic of the
59.3 35.8 50.7 38.5 28.1 43.7 40.0 44.6 37.4 44.5 39.4 44.8 47.0 63.1 54.8 45.8 43.1 .. .. .. .. 42.1 10.0 .. .. 35.7 43.8 29.8 .. .. 15.8 46.8 42.9 45.5 .. ..
32.9 14.0 34.6 27.9 17.2 34.5 20.8 21.8 21.3 37.4 20.4 33.9 21.2 38.9 39.9 28.2 20.6 .. .. .. .. 32.8 1.6 .. .. 24.7 28.3 15.2 .. .. 4.4 41.2 24.5 29.6 .. ..
11 0 2 0 0 0 0 0 3 1 0 2 1 2 0 0 5 0 .. .. .. 2 .. 8 7 2 14 1 9 13 3 2 1 20 16 6
9,799 78,319 35,049 11,678 12,575 32,492 3,355 1,696 361 2,723 924 33,141 25,059 29,916 96,596 325 7,513 1,110 .. .. .. 69,471 .. 2,331 4,890 54,444 19,221 4,529 69,648 2,357 8,741 36,336 16,966 23,357 25,300 32,575
15 48 34 78 149 46 67 0b 141 87 32 84 44 43 80 72 242 .. .. .. .. 36 .. 150 159 156 91 146 .. 240 103 109 70 63 .. 145
1.0 1.1 13.8 156.3 248.6 4.5 60.0 154.5 302.1 499.4 444.7 20.2 163.9 87.4 144.2 329.7 0.0 .. .. .. .. 4.9 .. .. .. 1.8 92.5 .. .. .. 0.2 0.7 143.7 99.0 .. ..
.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0 .. .. .. .. .. .. .. .. .. .. .. .. 0 0 .. .. .. ..
11.0 29.4 72.3 59.5 1.0 58.8 0.8 .. .. 73.2 .. 45.4 1.9 18.5 25.0 0.1 b 2.9 .. .. .. .. 26.3 .. 3.2 7.4 10.0 18.8 24.9 .. 8.6 5.3 9.9 22.1 23.3 .. 10.1
table
OTHER COUNTRIES OR TERRITORIES Korea, Democratic People’s Rep. of Marshall Islands Monaco Nauru San Marino Somalia Tuvalu Human Development Index groups Very high human development High human development Medium human development Low human development Regions Arab States East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean South Asia Sub-Saharan Africa Least developed countries Small island developing states World
191 .. .. .. .. 2,068 .. .. .. 212 1,035 .. 84 .. 104 443 1,286 1,151 .. ..
.. .. .. .. .. 1,383 .. .. .. 357 696 .. .. .. .. 424 798 794 .. ..
7
NOTES a. Data refer to the most recent year available during the period specified. b. Less than 1. c. Less than 0.05. DEFINITIONS Population under age 5 suffering from stunting: Percentage of children under age 5 falling two standard deviations or more below the median height-for-age of the reference population. Population under age 5 suffering from wasting: Percentage of children under age 5 falling two standard deviations or more below the median weight-for-height of the reference population. Number of deaths due to natural disasters: People confirmed as dead, or missing and presumed dead, as a result of natural disasters, which include drought, extreme temperature, flood, mass movement, wet storm and wildfire. Population affected by natural disasters: People requiring immediate assistance during a period of emergency as a result of a natural disaster (as defined above), including displaced, evacuated, homeless and injured people. Deaths due to water pollution: Deaths due to diarrhoea attributable to poor water, sanitation or hygiene. Deaths due to indoor air pollution: Deaths due to acute respiratory infections (children under age 5), chronic obstructive pulmonary disease (adults over age 30) and lung cancer (adults over age 30) attributable to indoor smoke from solid fuels.
Deaths due to outdoor air pollution: Deaths due to respiratory infections and diseases, lung cancer and selected cardiovascular diseases attributable to outdoor air pollution. Deaths due to malaria: Deaths due to malaria. Deaths due to dengue: Deaths due to dengue fever, dengue haemorrhagic fever and dengue shock syndrome. Population living on degraded land: Percentage of the population living on severely and very severely degraded land. Land degradation estimates consider biomass, soil health, water quantity and biodiversity, and range in severity. MAIN DATA SOURCES Columns 1 and 2: WHO (2010b). Columns 3 and 4: WHO Collaborating Centre for Research on the Epidemiology of Disasters (2011) and UNDESA (2011). Columns 5–7: HDRO calculations based on WHO (2009) and UNDESA (2011). Column 8: WHO (2010c). Column 9: HDRO calculations based on WHO (2011) and UNDESA (2011). Column 10: FAO (2011b).
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table
Perceptions about well-being and the environment
WELL-BEING Overall life Humans satisfaction cause Global warming threat (0, least satisfied; global warming 10, most satisfied) (% yes) (% seriousa) 2006–2010b 2006–2010b 2006–2010b ENVIRONMENT Satisfaction Satisfaction Active in with government with actions environmental to reduce to preserve group emissions the environment (% yes) (% satisfied) (% satisfied) 2006–2010b 2006–2010b 2006–2010b Satisfaction with air quality (% satisfied) 2006–2010b Satisfaction with water quality (% satisfied) 2006–2010b
HDI rank
VERY HIGH HUMAN DEVELOPMENT 1 Norway 2 Australia 3 Netherlands 4 United States 5 New Zealand 6 Canada 7 Ireland 8 Liechtenstein 9 Germany 10 Sweden 11 Switzerland 12 Japan 13 Hong Kong, China (SAR) 14 Iceland 15 Korea, Republic of 16 Denmark 17 Israel 18 Belgium 19 Austria 20 France 21 Slovenia 22 Finland 23 Spain 24 Italy 25 Luxembourg 26 Singapore 27 Czech Republic 28 United Kingdom 29 Greece 30 United Arab Emirates 31 Cyprus 32 Andorra 33 Brunei Darussalam 34 Estonia 35 Slovakia 36 Malta 37 Qatar 38 Hungary 39 Poland 40 Lithuania 41 Portugal 42 Bahrain 43 Latvia 44 Chile 45 Argentina 46 Croatia 47 Barbados HIGH HUMAN DEVELOPMENT 48 Uruguay 49 Palau 50 Romania 51 Cuba 52 Seychelles 53 Bahamas 54 Montenegro 55 Bulgaria
7.6 7.5 7.5 7.2 7.2 7.7 7.3 .. 6.7 7.5 7.5 6.1 5.6 6.9 6.1 7.8 7.4 6.9 7.3 6.8 6.1 7.4 6.2 6.4 7.1 6.5 6.2 7.0 5.8 7.1 6.4 .. .. 5.1 6.1 5.8 6.8 4.7 5.8 5.1 4.9 5.9 4.7 6.6 6.4 5.6 .. 6.1 .. 4.9 5.4 .. .. 5.5 4.2
46.8 45.1 43.6 35.9 41.1 55.8 47.6 .. 59.7 50.1 .. 83.7 80.0 37.9 85.3 45.3 40.9 42.6 52.7 58.6 65.1 55.1 63.2 57.0 53.7 57.2 45.2 38.5 81.3 29.2 79.4 .. .. 44.3 56.9 66.8 39.3 51.0 43.2 51.4 61.5 35.4 49.2 68.5 80.4 61.5 .. 72.9 .. 44.9 .. .. .. 59.9 49.3
43.7 70.5 52.6 54.7 59.0 73.9 58.7 .. 60.4 48.6 .. 77.3 68.6 34.4 82.8 32.8 67.4 63.1 60.4 65.5 69.2 41.7 70.9 87.0 62.1 72.7 35.5 58.8 95.5 71.0 89.4 .. .. 36.0 54.7 85.8 67.4 74.5 55.1 49.7 90.7 74.3 39.6 93.1 97.4 .. .. 85.6 .. 74.3 .. .. .. .. 66.0
11.6 19.5 15.5 17.6 24.6 19.3 .. .. 12.8 11.4 .. 14.1 .. 12.5 9.4 18.1 14.3 21.4 .. 10.0 .. .. 10.4 14.6 15.5 19.8 13.0 17.2 6.0 .. .. .. .. 6.8 .. 13.0 .. 6.1 6.2 4.3 10.0 .. 3.9 7.6 4.2 .. .. 4.1 .. 3.5 .. .. .. .. ..
.. .. .. 43.9 .. 34.0 .. .. 49.1 47.6 54.4 33.0 21.6 .. 29.3 33.5 .. .. 41.3 .. .. .. .. .. .. 69.8 26.6 .. 16.0 .. .. .. .. 16.8 .. .. .. .. 17.5 11.0 28.5 .. 21.2 26.8 7.0 .. .. 32.7 .. 17.4 .. .. .. .. 10.9
51.5 63.8 66.1 57.8 74.8 61.7 58.9 .. 61.8 62.9 63.9 46.8 41.4 56.0 36.4 64.3 37.7 56.0 63.9 57.5 55.9 57.3 46.0 29.7 76.8 80.5 56.6 66.8 19.8 89.7 45.7 .. .. 45.2 42.8 53.8 87.1 32.7 43.6 29.9 37.2 65.3 38.9 42.1 33.9 38.1 .. 70.5 .. 14.3 54.5 .. .. 50.1 19.4
89.3 93.1 81.5 87.8 93.0 84.5 94.8 .. 86.3 89.3 83.7 78.2 27.8 85.2 72.0 91.6 58.4 74.0 88.0 76.6 80.2 89.7 82.0 69.8 85.7 91.1 69.0 88.8 68.7 81.5 63.0 .. .. 75.0 70.4 44.4 80.6 83.5 80.3 70.2 85.7 85.6 75.1 69.5 75.0 75.0 .. 85.6 .. 71.4 52.8 .. .. 66.2 69.3
95.3 93.4 94.2 89.5 89.0 91.3 90.6 .. 95.0 96.7 96.1 87.8 78.4 96.9 81.6 97.4 55.7 84.7 97.1 83.9 90.0 95.0 83.6 80.6 92.3 92.9 89.2 94.8 64.7 84.4 67.4 .. .. 66.8 86.0 64.0 79.6 86.2 79.6 69.7 90.0 85.0 65.3 84.5 73.8 81.2 .. 92.9 .. 69.5 59.3 .. .. 78.2 60.8
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perceptions about well-being and the environment
WELL-BEING Overall life Humans satisfaction cause Global warming threat (0, least satisfied; global warming 10, most satisfied) (% yes) (% seriousa) 2006–2010b 2006–2010b 2006–2010b ENVIRONMENT Satisfaction Satisfaction Active in with government with actions environmental to reduce to preserve group emissions the environment (% yes) (% satisfied) (% satisfied) 2006–2010b 2006–2010b 2006–2010b Satisfaction with air quality (% satisfied) 2006–2010b Satisfaction with water quality (% satisfied) 2006–2010b
HDI rank
56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94
Saudi Arabia Mexico Panama Serbia Antigua and Barbuda Malaysia Trinidad and Tobago Kuwait Libya Belarus Russian Federation Grenada Kazakhstan Costa Rica Albania Lebanon Saint Kitts and Nevis Venezuela, Bolivarian Republic of Bosnia and Herzegovina Georgia Ukraine Mauritius Former Yugoslav Republic of Macedonia Jamaica Peru Dominica Saint Lucia Ecuador Brazil Saint Vincent and the Grenadines Armenia Colombia Iran, Islamic Republic of Oman Tonga Azerbaijan Turkey Belize Tunisia
6.3 6.8 7.3 4.5 .. 5.6 6.7 6.8 4.9 5.5 5.4 .. 5.5 7.3 5.3 5.0 .. 7.5 4.7 4.1 5.1 .. 4.2 6.2 5.6 .. .. 5.8 6.8 .. 4.4 6.4 5.1 .. .. 4.2 5.5 6.5 5.1 5.6 5.3 4.0 4.7 .. .. 4.7 6.6 6.2 .. 6.7 .. 5.8 5.8 .. 4.6 5.6 4.9 4.7 4.7 5.1 ..
34.6 70.9 66.6 64.1 .. 65.5 75.8 33.3 22.8 48.7 48.0 .. 43.8 80.5 30.7 68.2 .. 61.4 66.4 40.8 60.9 .. 54.8 .. 66.5 .. .. 58.6 81.3 .. 31.6 73.1 61.7 .. .. 37.3 55.1 59.0 33.0 60.2 39.4 56.5 54.6 .. .. 47.5 29.4 74.9 .. 72.0 .. 72.4 72.5 .. 58.6 48.6 76.2 45.1 47.4 16.9 ..
78.6 94.5 97.0 .. .. 71.1 98.2 58.8 64.3 48.6 48.9 .. 57.2 92.2 .. 79.7 .. 97.9 .. 78.2 68.2 .. .. .. 96.0 .. .. 97.7 94.9 .. 80.0 96.1 77.6 .. .. 85.2 86.0 85.7 58.6 68.7 59.6 76.3 92.0 .. .. 31.7 .. 66.7 .. 92.8 .. 95.2 95.6 .. 65.5 83.2 92.9 66.7 58.0 67.0 ..
10.6 6.1 9.2 .. .. 27.3 6.2 .. .. 5.0 5.7 .. 8.7 13.0 .. .. .. 5.8 .. 3.6 5.1 .. .. .. 10.7 .. .. 9.1 7.2 .. 9.8 12.5 9.2 .. .. 13.0 12.4 20.3 .. 2.9 .. 10.0 15.8 .. .. 11.6 .. 43.8 .. 12.9 .. 8.6 11.6 .. 11.4 11.3 30.4 4.1 11.8 6.2 ..
.. 22.7 16.5 .. .. 17.1 .. .. .. 20.0 9.4 .. 14.3 33.2 .. .. .. 27.2 .. 15.2 3.2 .. .. .. 15.5 .. .. 33.0 29.6 .. 12.4 30.6 .. .. .. 21.1 12.9 .. .. .. .. 40.1 14.7 .. .. 33.4 .. 28.7 .. 23.3 .. 13.5 20.1 .. .. 4.5 26.8 .. .. 44.5 ..
53.3 46.8 44.1 28.1 .. 64.2 26.3 69.2 .. 50.6 18.3 .. 37.4 59.6 27.4 23.7 .. 59.8 22.1 38.0 8.8 .. 39.8 32.9 35.5 .. .. 39.1 48.2 .. 27.8 53.5 55.2 .. .. 28.1 41.9 30.3 66.7 59.4 42.4 61.7 53.1 .. .. 73.0 .. 75.5 .. 39.7 .. 45.5 45.5 .. 16.7 15.5 86.2 25.7 28.4 71.4 ..
55.5 78.0 85.2 61.9 .. 82.3 75.8 55.7 65.0 65.1 57.6 .. 61.6 86.3 54.5 50.5 .. 77.1 71.2 67.4 55.4 .. 73.0 85.8 64.7 .. .. 60.7 68.2 .. 58.9 73.7 66.6 .. .. 65.4 72.3 70.7 66.7 71.1 57.1 91.7 69.2 .. .. 75.1 80.8 83.0 .. 74.0 .. 87.7 72.8 .. 55.4 62.8 82.4 83.2 62.3 86.5 ..
60.4 67.7 75.9 60.2 .. 82.9 74.0 67.8 69.9 62.6 52.8 .. 55.7 88.7 50.2 47.3 .. 67.9 71.7 66.4 51.0 .. 69.7 88.8 67.8 .. .. 62.4 83.1 .. 61.3 80.2 58.4 .. .. 51.0 64.1 63.3 50.3 59.0 60.7 88.0 69.7 .. .. 73.3 71.2 82.8 .. 70.4 .. 83.9 74.4 .. 59.7 60.1 83.4 76.1 58.4 82.1 ..
table
8
MEDIUM HUMAN DEVELOPMENT 95 Jordan 96 Algeria 97 Sri Lanka 98 Dominican Republic 99 Samoa 100 Fiji 101 China 102 Turkmenistan 103 Thailand 104 Suriname 105 El Salvador 106 Gabon 107 Paraguay 108 Bolivia, Plurinational State of 109 Maldives 110 Mongolia 111 Moldova, Republic of 112 Philippines 113 Egypt 114 Occupied Palestinian Territory 115 Uzbekistan 116 Micronesia, Federated States of
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perceptions about well-being and the environment
WELL-BEING Overall life Humans satisfaction cause Global warming threat (0, least satisfied; global warming 10, most satisfied) (% yes) (% seriousa) 2006–2010b 2006–2010b 2006–2010b ENVIRONMENT Satisfaction Satisfaction Active in with government with actions environmental to reduce to preserve group emissions the environment (% yes) (% satisfied) (% satisfied) 2006–2010b 2006–2010b 2006–2010b Satisfaction with air quality (% satisfied) 2006–2010b Satisfaction with water quality (% satisfied) 2006–2010b
HDI rank
table
8
117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141
Guyana Botswana Syrian Arab Republic Namibia Honduras Kiribati South Africa Indonesia Vanuatu Kyrgyzstan Tajikistan Viet Nam Nicaragua Morocco Guatemala Iraq Cape Verde India Ghana Equatorial Guinea Congo Lao People’s Democratic Republic Cambodia Swaziland Bhutan
6.0 3.6 4.5 4.9 5.9 .. 4.7 5.5 .. 5.0 4.4 5.3 5.7 4.7 6.3 5.1 .. 5.0 4.6 .. 3.8 5.0 4.1 .. .. .. 4.3 .. 5.8 4.9 .. 4.2 5.3 4.6 4.6 3.2 .. 4.4 4.4 4.8 4.3 3.8 4.8 .. 4.2 2.8 3.8 5.3 5.0 4.0 3.7 .. 4.4 4.2 5.1 4.8 4.7 4.4 3.8 .. ..
36.2 25.6 53.2 48.6 54.1 .. 37.2 75.5 .. 46.4 16.7 71.3 70.6 67.4 74.9 40.1 .. 49.4 58.6 .. 58.3 71.6 41.4 .. .. .. 62.8 .. 32.4 66.7 .. 70.0 .. 57.2 66.8 52.9 .. 65.7 41.0 37.5 59.7 12.6 51.2 .. 52.8 43.1 34.4 63.0 51.9 48.1 45.7 .. 58.5 79.8 46.9 31.2 36.5 .. 64.6 .. ..
83.3 79.9 50.0 75.4 88.9 .. 70.4 88.1 .. 68.9 66.7 68.8 94.8 89.0 94.6 62.3 .. 83.4 69.0 .. 75.4 63.3 89.6 .. .. .. 82.9 .. 71.6 92.1 .. 89.2 .. 68.2 94.0 83.5 .. 65.8 72.0 67.5 88.6 79.6 74.2 .. 73.1 77.3 82.1 66.5 82.4 74.4 71.3 .. 80.1 .. .. 75.6 53.5 .. 93.9 .. ..
27.8 26.1 .. 17.6 25.3 .. 26.8 18.9 .. 15.5 24.9 16.8 14.7 3.2 16.9 .. .. 11.6 27.8 .. 12.9 47.9 8.6 .. .. .. 23.7 .. 10.1 11.9 .. 32.0 .. 14.6 6.4 47.1 .. .. 17.3 39.6 24.9 32.6 15.9 .. 25.6 16.7 .. 31.4 55.4 31.2 12.0 .. 19.0 .. .. 12.2 .. .. 21.4 .. ..
.. .. .. .. 12.2 .. 34.5 28.7 .. 5.7 31.4 14.9 21.5 .. 14.7 .. .. 41.6 33.9 .. .. .. 42.8 .. .. .. 17.9 .. 24.9 45.2 .. .. .. 15.7 .. 30.6 .. .. 15.3 10.9 19.3 .. .. .. 33.7 .. .. 22.1 .. 76.8 .. .. .. 5.8 60.8 14.2 10.2 .. 26.2 .. ..
34.1 76.1 50.4 57.9 39.3 .. 55.7 48.2 .. 27.7 42.8 67.6 56.2 32.6 39.1 15.8 .. 45.4 59.9 .. 27.8 72.5 85.5 .. .. .. 63.2 .. 21.1 47.3 .. 69.9 .. 44.2 43.8 51.3 .. 30.1 30.8 32.2 42.4 24.9 32.1 .. 47.9 23.4 36.6 45.0 54.0 90.3 34.6 .. 38.9 32.1 82.3 45.5 50.1 36.6 44.7 .. ..
78.7 70.1 55.7 76.4 74.4 .. 85.7 82.1 .. 87.3 84.0 62.9 82.4 57.9 82.4 61.5 .. 79.1 89.1 .. 65.5 88.6 83.1 .. .. .. 86.0 .. 77.6 83.1 .. 59.9 88.4 82.9 81.0 61.7 .. 80.0 77.9 73.9 87.9 38.8 64.2 .. 81.4 52.4 76.7 82.4 69.0 78.5 78.1 .. 80.3 74.8 91.1 67.1 73.1 72.0 79.5 .. ..
53.8 72.4 49.8 81.6 69.7 .. 53.4 86.9 .. 82.9 65.0 62.3 68.5 63.9 66.8 44.4 .. 62.7 72.0 .. 33.5 82.7 73.0 .. .. .. 51.8 .. 55.0 69.5 .. 47.4 .. 51.4 52.6 34.7 .. 56.4 67.3 46.8 81.8 26.0 57.4 .. 59.6 33.8 55.8 53.9 63.5 54.5 55.6 .. 62.4 52.1 61.8 60.7 62.3 29.2 57.0 .. ..
LOW HUMAN DEVELOPMENT 142 Solomon Islands 143 Kenya 144 São Tomé and Príncipe 145 Pakistan 146 Bangladesh 147 Timor-Leste 148 Angola 149 Myanmar 150 Cameroon 151 Madagascar 152 Tanzania, United Republic of 153 Papua New Guinea 154 Yemen 155 Senegal 156 Nigeria 157 Nepal 158 Haiti 159 Mauritania 160 Lesotho 161 Uganda 162 Togo 163 Comoros 164 Zambia 165 Djibouti 166 Rwanda 167 Benin 168 Gambia 169 Sudan 170 Côte d'Ivoire 171 Malawi 172 Afghanistan 173 Zimbabwe 174 Ethiopia 175 Mali 176 Guinea-Bissau 177 Eritrea
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perceptions about well-being and the environment
WELL-BEING Overall life Humans satisfaction cause Global warming threat (0, least satisfied; global warming 10, most satisfied) (% yes) (% seriousa) 2006–2010b 2006–2010b 2006–2010b ENVIRONMENT Satisfaction Satisfaction Active in with government with actions environmental to reduce to preserve group emissions the environment (% yes) (% satisfied) (% satisfied) 2006–2010b 2006–2010b 2006–2010b Satisfaction with air quality (% satisfied) 2006–2010b Satisfaction with water quality (% satisfied) 2006–2010b
HDI rank
178 179 180 181 182 183 184 185 186 187
Guinea Central African Republic Sierra Leone Burkina Faso Liberia Chad Mozambique Burundi Niger Congo, Democratic Republic of the
4.3 3.6 4.1 4.0 4.2 3.7 4.7 3.8 4.1 4.0 6.7 5.9 4.9 4.7 5.0 .. 5.3 6.5 5.0 4.4 4.4 .. 5.3
39.8 67.2 52.1 52.5 32.1 55.0 53.0 45.8 .. 47.7 54.4 62.3 52.1 49.6 48.2 .. 47.6 72.8 49.7 49.5 .. .. 53.5
78.4 77.3 74.0 96.3 71.8 96.0 87.8 91.6 .. .. 66.3 .. 62.2 78.4 69.1 .. 62.8 94.8 82.6 .. .. .. 67.9
30.8 .. 50.8 14.3 43.2 29.9 8.4 16.1 14.4 .. .. .. .. .. .. .. .. 8.8 11.6 .. .. .. ..
.. .. .. .. .. 12.9 .. 28.1 25.9 16.3 .. .. .. .. .. .. .. .. 39.2 .. .. .. ..
22.7 63.5 29.8 48.5 34.4 56.8 53.6 55.7 58.3 31.0 52.4 40.9 58.2 39.9 37.3 .. 30.8 46.3 43.6 44.5 45.5 .. 51.6
54.9 87.0 72.7 73.8 79.4 57.1 79.1 84.9 90.9 70.5 81.7 67.5 77.2 76.7 69.7 .. 67.1 71.8 78.8 75.7 76.8 .. 76.5
38.3 41.2 36.6 39.4 50.7 34.9 71.4 52.1 63.0 22.1 87.2 67.0 69.8 51.8 62.8 .. 63.2 74.6 62.9 46.6 52.6 .. 69.2
Human Development Index groups Very high human development High human development Medium human development Low human development Regions Arab States East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean South Asia Sub-Saharan Africa Least developed countries Small island developing states World
table
8
NOTES The typical World Poll survey includes at least 1,000 surveys of randomly selected individuals. In some countries oversamples are collected in major cities or areas of special interest. Additionally, in some large countries, such as China and the Russian Federation, sample sizes of at least 2,000 are collected. Although rare, in some instances the sample size is between 500 and 1,000. Quality control procedures are used to validate that correct samples are selected and that the correct person is randomly selected in each household. Gallup’s methodology ensures that the reported data are representative of 95 percent of the world’s adult population (ages 15 and older). For further information, see https://worldview.gallup. com/content/methodology.aspx. a. Very serious and somewhat serious. b. Data refer to the most recent year available during the period specified. SURVEY QUESTIONS Overall life satisfaction: Please imagine a ladder, with steps numbered from zero at the bottom to ten at the top. Suppose we say that the top of the ladder represents the best possible life for you, and the bottom of the ladder represents the worst possible life for you. On which step of the ladder would you say you personally feel you stand at this time, assuming that the higher the step the better you feel about your life, and the lower the step the worse you feel about it? Which step comes closest to the way you feel?
Humans cause global warming: Temperature rise is a part of global warming or climate change. Do you think rising temperatures are a result of human activities? (Asked of those who said they know something or a great deal about global warming and climate change.) Global warming threat: How serious of a threat is global warming to you and your family? (Asked of those who said they know something or a great deal about global warming and climate change.) Active in environmental group: Which of these, if any, have you done in the past year? Been active in a group or organization that works to protect the environment. Satisfaction with government to reduce emissions: Do you think the government of this country is doing enough to reduce emissions of gases released by motor vehicles and factories, or not? Satisfaction with actions to preserve the environment: In this country, are you satisfied or dissatisfied with the efforts to preserve the environment? Satisfaction with air quality: In the city or area where you live, are you satisfied or dissatisfied with the quality of air? Satisfaction with water quality: In the city or area where you live, are you satisfied or dissatisfied with the quality of water? MAIN DATA SOURCE Columns 1–8: Gallup (2011).
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education and health
EDUCATION Gross enrolment ratio Adult literacy rate (% ages 15 and older) Primary education resources Pupil– School teacher teachers ratio trained (pupils per to teach teacher) (%) One-year-olds lacking immunization against HEALTH Mortality HIV Under prevalence Adult Healthfive Youth (per 1,000 (per (% ages 15–24) adjusted life people) expectancya Measles 1,000 live (%) births) Female Male Female Male (years) 2009 2009 2009 2009 2009 2009 2007
HDI rank
Primary Secondary Tertiary (%) (%) (%)
DTP (%) 2009
2005–2010b 2001–2010b 2001–2010b 2001–2010b 2005–2010b 2005–2010b
VERY HIGH HUMAN DEVELOPMENT 1 Norway 2 Australia 3 Netherlands 4 United States 5 New Zealand 6 Canada 7 Ireland 8 Liechtenstein 9 Germany 10 Sweden 11 Switzerland 12 Japan 13 Hong Kong, China (SAR) 14 Iceland 15 Korea, Republic of 16 Denmark 17 Israel 18 Belgium 19 Austria 20 France 21 Slovenia 22 Finland 23 Spain 24 Italy 25 Luxembourg 26 Singapore 27 Czech Republic 28 United Kingdom 29 Greece 30 United Arab Emirates 31 Cyprus 32 Andorra 33 Brunei Darussalam 34 Estonia 35 Slovakia 36 Malta 37 Qatar 38 Hungary 39 Poland 40 Lithuania 41 Portugal 42 Bahrain 43 Latvia 44 Chile 45 Argentina 46 Croatia 47 Barbados HIGH HUMAN DEVELOPMENT 48 Uruguay 49 Palau 50 Romania 51 Cuba 52 Seychelles 53 Bahamas
.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 99.7 .. 97.7 98.9 .. 94.7 .. .. 97.2 90.0 97.9 .. 95.3 99.8 .. 92.4 94.7 99.4 99.5 99.7 94.9 91.4 99.8 98.6 97.7 98.8 .. 98.3 .. 97.7 99.8 91.8 ..
98.7 106.4 106.9 98.2 101.2 98.4 104.6 108.9 103.6 96.2 103.4 102.3 104.0 98.3 104.3 98.6 111.1 103.4 98.7 108.7 98.4 97.4 107.2 103.3 100.4 .. 103.5 106.4 101.2 105.4 105.4 89.0 106.5 100.2 102.1 98.6 105.9 99.7 97.1 97.2 112.3 106.6 98.7 106.4 116.7 95.3 .. 113.6 101.4 99.3 103.6 106.2 103.4
110.4 132.7 120.8 93.6 126.3 102.2 118.1 105.0 101.7 102.6 96.0 101.0 82.1 108.3 97.2 118.4 89.1 107.5 100.4 113.0 96.8 109.0 120.8 100.5 96.0 .. 95.1 99.0 101.8 95.2 98.4 80.8 98.2 99.3 92.0 100.3 85.2 98.8 98.9 99.2 106.8 96.4 92.7 90.4 85.9 95.2 .. 87.9 95.7 93.5 89.6 105.0 93.3
73.5 82.3 61.6 85.9 83.5 62.3 60.6 34.7 .. 71.5 51.2 58.6 56.6 74.3 100.0 77.0 62.5 66.3 59.3 55.3 87.6 90.9 73.4 67.2 10.0 .. 60.9 59.0 90.8 30.4 52.0 10.3 17.1 63.7 55.8 32.2 10.2 62.5 71.4 79.5 61.2 51.2 67.3 54.8 69.4 48.9 .. 64.9 37.9 67.1 117.8 .. ..
.. .. .. 13.9 14.6 .. 15.8 6.5 13.0 9.3 .. 18.1 15.9 .. 22.4 .. 13.1 11.1 11.4 18.7 17.2 13.6 12.6 10.3 11.9 17.4 18.5 18.3 10.3 15.6 14.2 10.3 11.9 12.2 15.7 10.5 11.2 10.5 9.6 12.8 11.2 .. 10.4 24.6 16.3 14.8 14.1 15.0 12.5 15.8 9.4 13.8 15.8
.. .. .. .. .. .. .. .. .. .. .. .. 95.1 .. .. .. .. .. .. .. .. .. .. .. .. 94.3 .. .. .. 100.0 .. 100.0 84.1 .. .. .. 48.9 .. .. .. .. .. .. .. .. .. 58.1 .. .. .. 100.0 99.4 91.1
8 8 3 5 8 20 7 .. 7 2 5 2 .. 4 6 11 7 1 17 1 4 1 4 4 1 3 1 7 1 8 1 1 1 5 1 27 1 1 1 2 4 2 5 3 6 4 7 5 51 3 4 1 4
8 6 4 8 11 7 11 .. 4 3 10 6 .. 8 7 16 4 6 17 10 5 2 2 9 4 5 2 14 1 8 13 2 1 5 1 18 1 1 2 4 5 1 4 4 1 2 6 6 25 3 4 3 2
3 5 4 8 6 6 4 2 4 3 4 3 .. 3 5 4 4 5 4 4 3 3 4 4 3 3 4 6 3 7 4 4 7 6 7 7 11 6 7 6 4 12 8 9 14 5 11 13 15 12 6 12 12
50 45 56 78 57 53 57 .. 53 47 43 42 .. 43 46 65 45 59 50 54 54 56 43 41 57 42 63 58 44 66 41 44 82 77 74 44 48 99 76 95 54 87 105 59 88 60 80 84 110 90 78 108 126
83 79 75 134 86 87 97 .. 99 74 74 86 .. 65 109 107 78 105 102 117 131 124 94 77 95 76 138 95 106 84 81 94 105 234 184 76 69 229 197 274 123 127 284 116 160 153 136 156 229 219 120 227 202
<0.1 0.1 <0.1 0.2 <0.1 0.1 0.1 .. <0.1 <0.1 0.1 <0.1 .. 0.1 <0.1 0.1 <0.1 <0.1 0.2 0.1 <0.1 <0.1 0.1 <0.1 0.1 <0.1 <0.1 0.1 0.1 .. .. .. .. 0.2 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 0.2 .. 0.1 0.1 0.2 <0.1 1.1 0.2 .. <0.1 0.1 .. 3.1
<0.1 0.1 0.1 0.3 <0.1 0.1 0.1 .. 0.1 <0.1 0.2 <0.1 .. 0.1 <0.1 0.1 0.1 <0.1 0.3 0.2 <0.1 0.1 0.2 <0.1 0.1 <0.1 <0.1 0.2 0.1 .. .. .. .. 0.3 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 0.3 .. 0.2 0.2 0.3 <0.1 0.9 0.3 .. 0.1 0.1 .. 1.4
73 74 73 70 73 73 73 .. 73 74 75 76 .. 74 71 72 73 72 72 73 71 72 74 74 73 73 70 72 72 68 70 74 66 66 67 72 67 66 67 63 71 66 64 70 67 68 67 67 64 65 69 63 65
158
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education and health
EDUCATION Gross enrolment ratio Adult literacy rate (% ages 15 and older) Primary education resources Pupil– School teacher teachers ratio trained (pupils per to teach teacher) (%) One-year-olds lacking immunization against HEALTH Mortality HIV Under prevalence Adult Healthfive Youth (per 1,000 (per (% ages 15–24) adjusted life people) expectancya Measles 1,000 live (%) births) Female Male Female Male (years) 2009 2009 2009 2009 2009 2009 2007
HDI rank
Primary Secondary Tertiary (%) (%) (%)
DTP (%) 2009
2005–2010b 2001–2010b 2001–2010b 2001–2010b 2005–2010b 2005–2010b
54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94
Montenegro Bulgaria Saudi Arabia Mexico Panama Serbia Antigua and Barbuda Malaysia Trinidad and Tobago Kuwait Libya Belarus Russian Federation Grenada Kazakhstan Costa Rica Albania Lebanon Saint Kitts and Nevis Venezuela, Bolivarian Republic of Bosnia and Herzegovina Georgia Ukraine Mauritius Former Yugoslav Republic of Macedonia Jamaica Peru Dominica Saint Lucia Ecuador Brazil Saint Vincent and the Grenadines Armenia Colombia Iran, Islamic Republic of Oman Tonga Azerbaijan Turkey Belize Tunisia
.. 98.3 86.1 93.4 93.6 97.8 99.0 92.5 98.7 93.9 88.9 99.7 99.6 .. 99.7 96.1 95.9 89.6 .. 95.2 97.8 99.7 99.7 87.9 97.1 86.4 89.6 .. .. 84.2 90.0 .. 99.5 93.2 85.0 86.6 99.0 99.5 90.8 .. 77.6 92.2 72.6 90.6 88.2 98.8 .. 94.0 99.6 93.5 94.6 84.1 87.7 94.6 90.7 98.4 97.5 98.5 95.4
106.1 101.5 98.9 116.6 109.0 97.7 99.8 94.6 104.2 94.8 110.3 99.0 96.8 107.2 108.8 109.9 118.9 103.2 95.7 103.2 108.9 107.8 97.5 100.0 88.9 93.3 109.1 112.3 96.7 117.5 127.5 106.9 98.5 120.2 102.8 83.9 111.8 95.1 99.3 121.9 108.2 96.8 107.7 96.9 106.2 100.3 94.2 112.7 .. 91.1 113.8 115.0 134.3 99.4 107.2 111.0 110.1 93.6 110.1
102.1 87.6 96.8 90.2 72.7 91.5 110.5 68.7 88.8 89.9 93.5 90.1 84.8 99.1 98.5 96.1 72.4 82.1 96.3 82.1 91.2 87.5 94.5 87.2 83.2 91.2 89.1 105.5 95.8 75.4 100.8 109.1 93.1 94.6 83.1 91.3 102.7 99.4 82.0 75.6 90.2 88.2 96.5 87.0 76.8 76.1 80.9 78.2 .. 77.0 75.4 63.6 53.1 66.8 81.3 83.7 92.2 88.6 82.5
.. 53.6 32.8 27.9 45.1 49.8 14.7 36.5 11.6 18.9 55.7 77.0 77.2 53.5 39.5 25.3 19.3 52.5 18.4 78.2 37.0 25.8 81.1 25.9 40.6 24.2 34.5 3.5 16.0 42.4 34.4 .. 50.1 37.0 36.5 26.4 6.4 19.1 38.4 11.2 34.4 40.7 30.6 .. 33.3 7.4 15.4 24.5 .. 45.0 12.3 24.6 .. 36.5 38.3 — 52.7 38.3 28.7
.. 17.3 11.4 28.1 23.6 16.2 16.2 14.6 17.6 8.6 .. 15.0 17.4 17.1 16.2 18.4 20.2 13.9 14.3 14.5 .. 8.9 15.6 21.6 16.4 27.7 20.9 16.1 20.0 19.2 23.0 17.0 19.3 29.3 20.3 11.8 22.3 11.1 .. 22.6 17.0 .. 23.0 23.1 25.2 31.7 26.0 17.2 .. 16.0 16.0 32.6 .. 26.5 24.2 12.7 30.4 15.7 33.7
.. .. 91.5 95.6 91.5 94.2 57.1 .. 88.0 100.0 .. 99.9 .. 68.8 .. 87.6 .. .. 61.6 86.3 .. 94.6 99.9 100.0 .. .. .. 57.8 87.6 77.9 .. 79.6 77.5 100.0 98.4 100.0 .. 99.9 .. 42.5 .. .. 99.3 .. 83.6 .. 97.8 .. .. .. 100.0 93.2 .. .. .. 74.1 100.0 .. ..
8 6 2 11 16 5 1 5 10 2 2 4 2 1 2 14 2 26 1 17 10 12 10 1 4 10 7 1 5 25 1 1 7 8 1 2 1 27 4 3 1 2 7 3 18 28 1 3 4 1 13 9 55 8 15 2 5 15 13
14 4 2 5 15 5 1 5 6 3 2 1 2 1 1 19 3 47 1 17 7 17 6 1 4 12 9 1 1 34 1 1 4 5 1 3 1 33 3 3 2 5 12 4 21 51 6 6 1 2 12 5 45 9 14 2 6 10 12
9 10 21 17 23 7 12 6 35 10 19 12 12 15 29 11 15 12 15 18 14 29 15 17 11 31 21 10 20 24 21 12 22 19 31 12 19 34 20 18 21 25 32 15 32 25 18 19 45 14 26 17 69 23 51 13 29 17 33
85 86 102 88 82 90 158 95 120 50 101 117 144 143 185 69 88 85 90 92 67 97 148 99 79 131 96 103 90 96 102 110 103 80 90 85 233 134 73 129 70 111 105 82 149 167 157 87 212 139 124 128 262 98 132 70 141 134 130
161 205 186 157 145 184 197 175 225 66 175 324 391 248 432 115 126 166 185 196 145 235 395 219 144 224 123 192 188 173 205 204 246 166 144 157 135 221 134 202 129 195 135 275 172 198 263 142 380 270 217 281 321 168 203 97 305 309 240
.. <0.1 .. 0.1 0.3 0.1 .. <0.1 0.7 .. .. 0.1 0.3 .. 0.2 0.1 .. <0.1 .. .. .. <0.1 0.3 0.2 .. 0.7 0.1 .. .. 0.2 .. .. <0.1 0.1 <0.1 <0.1 .. 0.1 <0.1 1.8 <0.1 .. <0.1 <0.1 0.7 .. 0.1 .. .. .. 0.4 0.3 3.5 0.1 0.1 <0.1 <0.1 0.1 <0.1
.. <0.1 .. 0.2 0.4 0.1 .. 0.1 1 .. .. <0.1 0.2 .. 0.1 0.2 .. 0.1 .. .. .. <0.1 0.2 0.3 .. 1 0.2 .. .. 0.2 .. .. <0.1 0.2 <0.1 <0.1 .. <0.1 <0.1 0.7 <0.1 .. 0.1 <0.1 0.3 .. 0.1 .. .. .. 0.6 0.4 1.4 0.2 0.1 <0.1 <0.1 0.1 <0.1
65 66 62 67 67 65 66 64 62 69 64 62 60 61 56 69 64 62 64 66 67 64 60 63 66 64 67 66 66 64 64 63 61 66 61 65 63 59 66 60 66 63 62 63 63 61 62 66 55 62 61 61 52 64 58 64 58 61 62
table
9
MEDIUM HUMAN DEVELOPMENT 95 Jordan 96 Algeria 97 Sri Lanka 98 Dominican Republic 99 Samoa 100 Fiji 101 China 102 Turkmenistan 103 Thailand 104 Suriname 105 El Salvador 106 Gabon 107 Paraguay 108 Bolivia, Plurinational State of 109 Maldives 110 Mongolia 111 Moldova, Republic of 112 Philippines
STATISTICAL TAbLeS
159
education and health
EDUCATION Gross enrolment ratio Adult literacy rate (% ages 15 and older) Primary education resources Pupil– School teacher teachers ratio trained (pupils per to teach teacher) (%) One-year-olds lacking immunization against HEALTH Mortality HIV Under prevalence Adult Healthfive Youth (per 1,000 (per (% ages 15–24) adjusted life people) expectancya Measles 1,000 live (%) births) Female Male Female Male (years) 2009 2009 2009 2009
HDI rank
Primary Secondary Tertiary (%) (%) (%)
DTP (%) 2009
2005–2010b 2001–2010b 2001–2010b 2001–2010b 2005–2010b 2005–2010b
table
9
113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141
Egypt Occupied Palestinian Territory Uzbekistan Micronesia, Federated States of Guyana Botswana Syrian Arab Republic Namibia Honduras Kiribati South Africa Indonesia Vanuatu Kyrgyzstan Tajikistan Viet Nam Nicaragua Morocco Guatemala Iraq Cape Verde India Ghana Equatorial Guinea Congo Lao People’s Democratic Republic Cambodia Swaziland Bhutan
66.4 94.6 99.3 .. .. 84.1 84.2 88.5 83.6 .. 88.7 92.2 82.0 99.2 99.7 92.8 78.0 56.1 74.5 78.1 84.8 62.8 66.6 93.3 .. 72.7 77.6 86.9 52.8 .. 87.0 88.8 55.5 55.9 50.6 70.0 92.0 70.7 64.5 72.9 60.1 62.4 49.7 60.8 59.1 48.7 57.5 89.7 73.2 56.9 74.2 70.9 .. 70.7 41.7 46.5 70.2 55.3 73.7
101.1 78.9 91.8 110.3 103.0 109.4 122.2 112.1 116.0 116.5 101.2 120.8 108.1 95.2 102.2 104.1 116.9 107.4 113.6 102.5 98.1 116.9 105.2 83.2 119.5 111.8 116.5 107.9 109.1 107.3 112.7 130.4 85.1 95.1 112.5 127.7 115.8 113.8 160.4 104.9 54.9 85.4 83.7 89.5 114.9 .. 104.4 104.4 121.6 115.2 119.4 112.9 54.5 150.7 121.9 84.7 74.0 73.6 119.3
67.2 87.1 103.5 90.5 103.4 81.5 74.7 64.7 64.5 84.8 93.9 79.5 47.3 84.1 84.4 66.9 67.9 55.8 56.6 51.5 81.5 60.0 57.2 26.2 43.1 43.9 40.4 53.3 61.7 34.8 59.5 51.0 33.1 42.3 51.2 23.0 53.1 41.5 31.5 27.4 .. 45.7 30.1 30.5 43.5 .. 24.5 45.0 27.4 41.3 45.8 .. 30.5 26.7 36.3 55.7 38.0 26.3 29.5
28.5 45.7 9.8 .. 11.2 7.6 .. 8.9 18.7 .. .. 23.5 4.8 50.8 19.8 9.7 18.0 12.9 17.7 15.5 14.9 13.5 8.6 .. 6.4 13.4 7.0 4.4 6.6 .. 4.1 4.4 5.2 7.9 15.2 2.8 10.7 9.0 3.6 1.4 .. 10.2 8.0 10.1 5.6 .. 3.8 3.6 4.1 5.3 5.2 .. 3.5 4.8 5.8 4.6 .. 8.4 —
27.2 28.0 17.1 16.6 25.6 25.2 17.8 30.1 33.3 25.0 30.7 16.6 23.8 24.0 22.7 19.5 29.2 26.6 29.4 17.0 23.9 .. 33.1 27.2 64.4 30.5 49.1 32.4 27.7 .. 46.8 26.2 39.7 45.8 29.1 .. 28.4 46.3 47.9 53.7 35.8 .. 34.7 46.3 31.9 .. 39.1 33.8 49.3 41.3 30.2 60.5 34.1 68.3 44.9 36.6 38.4 42.1 ..
.. 100.0 100.0 .. 63.7 97.4 .. 95.6 36.4 85.4 87.4 .. 100.0 65.7 88.3 99.6 72.7 100.0 .. .. 86.5 .. 47.6 45.3 89.0 96.9 99.5 94.0 91.5 .. 96.8 48.1 85.2 58.4 .. .. 98.9 61.8 .. 100.0 .. .. .. 51.2 73.7 .. 100.0 57.6 89.4 14.6 57.4 .. 100.0 93.9 71.8 .. 59.7 100.0 ..
3 .. 2 9 2 4 20 17 2 14 31 18 32 5 7 4 2 1 8 35 1 34 6 67 9 43 6 5 4 19 25 2 15 6 28 27 10 20 22 15 36 34 14 58 18 41 36 17 36 11 17 19 11 3 17 2 16 19 7
5 .. 5 14 3 6 19 24 1 18 38 18 48 1 11 3 1 2 8 31 4 29 7 49 24 41 8 5 2 40 26 10 20 11 30 23 13 26 36 9 42 42 21 59 21 41 41 15 32 16 21 15 27 8 28 4 18 33 8
21 30 36 39 35 57 16 48 30 46 62 39 16 37 61 24 26 38 40 44 28 66 69 145 128 59 88 73 79 36 84 78 87 52 56 161 71 154 58 108 68 66 93 138 48 87 117 84 128 98 104 141 94 111 118 103 108 119 110
130 .. 139 161 224 324 95 357 134 173 479 143 159 162 160 107 122 87 151 145 111 169 253 355 320 251 190 560 194 119 282 104 189 222 154 353 188 409 198 311 221 180 218 365 159 227 262 573 348 278 229 477 271 258 246 246 275 456 496
215 .. 220 183 286 372 159 540 237 325 521 234 200 327 183 173 210 126 280 292 272 250 402 373 409 289 350 674 256 170 358 161 225 246 233 377 275 420 273 456 274 237 266 377 234 278 315 676 539 338 284 580 326 304 385 296 291 528 691
2009 <0.1 .. <0.1 .. 0.8 11.8 .. 5.8 0.2 .. 13.6 <0.1 .. 0.1 <0.1 0.1 0.1 0.1 0.3 .. .. 0.1 1.3 5 2.6 0.2 0.1 15.6 <0.1
2009 <0.1 .. <0.1 .. 0.6 5.2 .. 2.3 0.3 .. 4.5 0.1 .. 0.1 <0.1 0.1 0.1 0.1 0.5 .. .. 0.1 0.5 1.9 1.2 0.1 0.1 6.5 0.1
2007
60 .. 59 62 53 49 63 52 62 58 48 60 61 57 57 64 64 62 60 54 61 56 50 46 48 54 53 42 55 59 48 53 55 56 53 45 50 45 52 45 56 54 51 42 55 54 51 40 42 51 56 40 48 43 50 51 50 47 44
LOW HUMAN DEVELOPMENT 142 Solomon Islands 143 Kenya 144 São Tomé and Príncipe 145 Pakistan 146 Bangladesh 147 Timor-Leste 148 Angola 149 Myanmar 150 Cameroon 151 Madagascar 152 Tanzania, United Republic of 153 Papua New Guinea 154 Yemen 155 Senegal 156 Nigeria 157 Nepal 158 Haiti 159 Mauritania 160 Lesotho 161 Uganda 162 Togo 163 Comoros 164 Zambia 165 Djibouti 166 Rwanda 167 Benin 168 Gambia 169 Sudan 170 Côte d'Ivoire 171 Malawi
.. 4.1 .. <0.1 <0.1 .. 1.6 0.3 3.9 0.1 3.9 0.8 .. 0.7 2.9 0.1 1.3 0.3 14.2 4.8 2.2 <0.1 8.9 1.9 1.9 0.7 2.4 1.3 1.5 6.8
.. 1.8 .. 0.1 <0.1 .. 0.6 0.3 1.6 0.1 1.7 0.3 .. 0.3 1.2 0.2 0.6 0.4 5.4 2.3 0.9 <0.1 4.2 0.8 1.3 0.3 0.9 0.5 0.7 3.1
160
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education and health
EDUCATION Gross enrolment ratio Adult literacy rate (% ages 15 and older) Primary education resources Pupil– School teacher teachers ratio trained (pupils per to teach teacher) (%) One-year-olds lacking immunization against HEALTH Mortality HIV Under prevalence Adult Healthfive Youth (per 1,000 (per (% ages 15–24) adjusted life people) expectancya Measles 1,000 live (%) births) Female Male Female Male (years) 2009 2009 2009 2009 2009 2009 2007
HDI rank
Primary Secondary Tertiary (%) (%) (%)
DTP (%) 2009
2005–2010b 2001–2010b 2001–2010b 2001–2010b 2005–2010b 2005–2010b
172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187
Afghanistan Zimbabwe Ethiopia Mali Guinea-Bissau Eritrea Guinea Central African Republic Sierra Leone Burkina Faso Liberia Chad Mozambique Burundi Niger Congo, Democratic Republic of the
.. 91.9 29.8 26.2 52.2 66.6 39.5 55.2 40.9 28.7 59.1 33.6 55.1 66.6 28.7 66.8 100.0 .. .. .. .. .. .. .. 93.2 81.9 59.8 72.9 93.5 98.0 91.0 62.8 61.6 59.2 .. 80.9
103.9 .. 102.5 97.2 119.7 48.3 89.8 91.3 85.1 79.2 90.6 89.7 115.7 146.6 66.6 90.3 .. 90.3 127.7 93.0 92.9 32.6 100.1 102.7 110.3 113.3 96.5 95.0 112.3 98.5 116.8 109.8 100.2 99.6 95.1 106.9
43.8 .. 34.4 41.6 35.9 31.8 37.0 12.4 26.5 21.4 .. 24.1 25.5 21.2 13.3 36.7 .. 78.2 153.4 62.9 95.6 7.7 79.5 99.7 90.4 69.7 35.0 66.5 76.9 90.7 90.7 55.9 35.3 35.6 76.9 68.4
3.6 .. 3.6 6.0 2.9 2.0 9.2 2.5 2.0 3.4 .. 2.0 1.5 2.7 1.4 6.0 .. 15.9 .. .. .. — .. 72.9 49.3 20.5 6.2 25.8 24.9 57.1 42.7 13.1 5.9 5.7 51.6 27.6
42.8 .. 57.9 50.1 62.2 38.5 43.7 84.3 .. 47.8 24.3 60.9 58.5 51.4 38.6 37.3 .. .. .. 22.4 6.2 35.5 .. 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
.. .. 84.6 50.0 .. 92.2 73.1 .. .. 86.1 40.2 34.6 75.9 91.2 96.7 93.4 .. .. .. 74.2 .. .. .. .. .. .. .. .. .. .. 91.7 77.1 76.0 .. .. ..
17 27 21 26 32 1 43 46 25 18 36 77 24 8 30 23 7 7 1 1 8 69 11 5 6 19 26 16 7 4 8 27 30 21 24 18
24 24 25 29 24 5 49 38 29 25 36 77 23 9 27 24 2 6 1 1 8 76 10 7 5 18 28 18 9 4 7 25 32 23 26 18
199 90 104 191 193 55 142 171 192 166 112 209 142 166 160 199 33 35 4 44 2 180 35 6 19 44 117 49 26 19 22 69 129 120 57 58
352 574 379 218 369 179 337 470 363 262 337 384 434 407 224 331 126 386 51 303 48 350 280 60 106 131 287 139 103 118 99 173 355 282 155 137
440 672 445 357 431 249 474 461 414 443 389 412 557 424 229 442 207 429 112 448 57 382 255 114 223 204 346 198 168 281 181 245 430 357 207 211
.. 6.9 .. 0.5 2 0.4 0.9 2.2 1.5 0.8 0.7 2.5 8.6 2.1 0.5 .. .. .. .. .. .. 0.6 .. .. .. .. .. .. .. .. .. .. .. .. .. ..
.. 3.3 .. 0.2 0.8 0.2 0.4 1 0.6 0.5 0.3 1 3.1 1 0.2 .. .. .. .. .. .. 0.4 .. .. .. .. .. .. .. .. .. .. .. .. .. ..
36 39 50 42 42 55 47 42 35 43 48 40 42 43 44 45 59 52 73 55 75 45 58
table
OTHER COUNTRIES OR TERRITORIES Korea, Democratic People’s Rep. of Marshall Islands Monaco Nauru San Marino Somalia Tuvalu Human Development Index groups Very high human development High human development Medium human development Low human development Regions Arab States East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean South Asia Sub-Saharan Africa Least developed countries Small island developing states World
72 64 61 48 59 64 62 65 56 45 49 61 61
9
NOTES a. Based on methods described in the statistical annex of WHO (2007). Estimates for 2007 have been revised to take into account the Global Burden of Disease estimates for 2004 and may not be entirely comparable with those for 2002 published in WHO (2004). b. Data refer to the most recent year available during the period specified. DEFINITIONS Adult literacy rate: Percentage of the population ages 15 and older who can, with understanding, both read and write a short simple statement on their everyday life. Gross enrolment ratio: Total enrolment in a given level of education (primary, secondary or tertiary), regardless of age, expressed as a percentage of the official school-age population for the same level of education. Pupil–teacher ratio: Average number of pupils (students) per teacher in primary education in a given school year. School teachers trained to teach: Percentage of primary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching at the primary level of education.
One-year-olds lacking immunization against DTP: Percentage of one-year-olds who have not received three doses of the combined diphtheria, tetanus toxoid and pertussis (DTP) vaccine. One-year-olds lacking immunization against measles: Percentage of one-year-olds who have not received at least one dose of a measles vaccine. Under-five mortality: Probability of dying between birth and exactly age 5, expressed per 1,000 live births. Adult mortality: Probability that a 15-year-old person will die before reaching age 60, expressed per 1,000 adults. HIV prevalence: Percentage of the population ages 15–24 who are infected with HIV. Health-adjusted life expectancy at birth: Average number of years that a person can expect to live in “full health” taking into account years lived in less than full health due to disease and injury. MAIN DATA SOURCES Columns 1–6: UNESCO Institute for Statistics (2011). Columns 7, 8, 10, 11 and 14: WHO (2010a). Columns 9, 12 and 13: UNICEF (2011).
STATISTICAL TAbLeS
161
10
table
Population and economy
POPULATION Average annual growth (%) 1990/1995 2010/2015 Urbana (% of total) 2011 ECONOMY Foreign Net official Public GDP direct development expenditure Total Median Dependency per investment assistance Remittance on expenditure age ratio capita net inflows received inflows education on health (years) (%) (PPP $) (% of GDP) (% of GDP) (% of GDP) (% of GDP) (% of GDP) 2010 2011 2009 2009 2009 2009 2006–2009b 2009
HDI rank
Total (millions) 2011 2030
VERY HIGH HUMAN DEVELOPMENT 1 Norway 2 Australia 3 Netherlands 4 United States 5 New Zealand 6 Canada 7 Ireland 8 Liechtenstein 9 Germany 10 Sweden 11 Switzerland 12 Japan 13 Hong Kong, China (SAR) 14 Iceland 15 Korea, Republic of 16 Denmark 17 Israel 18 Belgium 19 Austria 20 France 21 Slovenia 22 Finland 23 Spain 24 Italy 25 Luxembourg 26 Singapore 27 Czech Republic 28 United Kingdom 29 Greece 30 United Arab Emirates 31 Cyprus 32 Andorra 33 Brunei Darussalam 34 Estonia 35 Slovakia 36 Malta 37 Qatar 38 Hungary 39 Poland 40 Lithuania 41 Portugal 42 Bahrain 43 Latvia 44 Chile 45 Argentina 46 Croatia 47 Barbados HIGH HUMAN DEVELOPMENT 48 Uruguay 49 Palau 50 Romania 51 Cuba 52 Seychelles 53 Bahamas 54 Montenegro 55 Bulgaria
4.9 c 5.6 c 22.6 d 27.8 d 16.7 17.3 313.1 361.7 4.4 5.2 34.3 39.8 4.5 5.4 0.0 0.0 82.2 79.5 9.4 10.4 7.7 8.1 126.5 120.2 7.1 8.5 0.3 0.4 48.4 50.3 5.6 5.9 7.6 9.8 10.8 11.2 8.4 8.6 63.1 68.5 2.0 2.1 5.4 5.6 46.5 50.0 60.8 60.9 0.5 0.6 5.2 6.0 10.5 10.8 62.4 69.3 11.4 11.6 7.9 10.5 1.1 1.3 0.1 0.1 0.4 0.5 1.3 1.3 5.5 5.5 0.4 0.4 1.9 2.4 10.0 9.6 38.3 37.8 3.3 3.1 10.7 10.3 1.3 1.7 2.2 2.1 17.3 19.5 40.8 46.8 4.4 4.2 0.3 0.3 3.4 0.0 21.4 11.3 0.1 0.3 0.6 7.4 3.6 0.0 20.3 11.0 0.1 0.4 0.6 6.5
0.5 c 1.2 d 0.7 1.0 1.6 1.1 0.4 1.3 0.7 0.6 1.0 0.4 1.2 1.0 0.8 0.4 3.4 0.3 0.7 0.4 0.4 0.5 0.3 0.0 1.3 2.9 0.0 0.3 1.0 5.2 2.2 4.1 2.8 –1.7 0.4 1.0 1.1 –0.1 0.2 –0.4 0.4 2.5 –1.3 1.8 1.3 0.7 0.3 0.7 2.7 –0.5 0.6 1.0 1.8 1.1 –1.1
0.7 c 1.3 d 0.3 0.9 1.0 0.9 1.1 0.8 –0.2 0.6 0.4 –0.1 1.0 1.2 0.4 0.3 1.7 0.3 0.2 0.5 0.2 0.3 0.6 0.2 1.4 1.1 0.3 0.6 0.2 2.2 1.1 1.5 1.7 –0.1 0.2 0.3 2.9 –0.2 0.0 –0.4 0.0 2.1 –0.4 0.9 0.9 –0.2 0.2 0.3 0.8 –0.2 0.0 0.3 1.1 0.1 –0.7
79.8 c 89.3 d 83.3 82.6 86.2 80.7 62.3 14.3 74.0 84.8 73.7 67.0 100.0 93.5 83.3 87.1 91.9 97.4 67.8 85.9 49.5 85.4 e 77.6 68.6 85.4 100.0 73.6 79.8 61.7 84.4 70.5 87.6 76.1 69.5 54.9 94.8 95.9 68.5 60.9 67.1 61.3 88.7 67.7 89.2 92.6 58.0 45.1 92.6 84.3 58.0 75.2 55.9 84.3 61.5 71.7
38.7 36.9 40.7 36.9 36.6 39.9 34.7 .. 44.3 40.7 41.4 44.7 41.8 34.8 37.9 40.6 30.1 41.2 41.8 39.9 41.7 42.0 40.1 43.2 38.9 37.6 39.4 39.8 41.4 30.1 34.2 .. 28.9 39.7 36.9 39.5 31.6 39.8 38.0 39.3 41.0 30.1 40.2 32.1 30.4 41.5 37.5 33.7 .. 38.5 38.4 .. 30.9 35.9 41.6
50.7 48.6 49.8 50.1 50.9 44.5 50.0 .. 51.5 54.2 47.4 57.9 32.1 49.2 38.1 53.3 61.0 52.7 47.9 54.9 44.3 52.1 47.6 53.1 46.1 35.6 41.6 52.0 50.1 21.0 41.4 .. 41.9 49.1 37.6 41.4 17.7 45.8 40.0 44.9 49.6 28.8 46.8 45.4 54.7 47.6 40.2 56.6 .. 43.3 42.0 .. 41.3 46.4 46.3
56,214 39,539 40,676 45,989 28,993 37,808 40,697 .. 36,338 37,377 45,224 32,418 43,229 36,795 27,100 37,720 27,656 36,313 38,818 33,674 27,133 35,265 32,150 32,430 83,820 50,633 25,581 35,155 29,617 57,744 30,848 .. .. 19,693 22,882 24,814 91,379 20,312 18,905 17,308 24,920 .. 16,437 14,311 14,538 19,986 .. 13,189 .. 14,278 .. 19,587 .. 13,086 13,870
3.0 2.4 4.2 1.0 –1.0 1.5 11.1 .. 1.2 2.8 5.6 0.2 24.9 0.5 0.2 0.9 2.0 –8.2 2.3 2.3 –1.2 0.0 0.4 1.4 372.6 9.2 1.4 3.4 0.7 .. 23.6 .. .. 9.2 0.0 11.2 .. 2.2 3.2 0.6 1.2 1.2 0.4 7.8 1.3 4.7 8.3 4.0 .. 3.9 .. 32.5 .. 32.0 9.4
.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.3 f .. .. .. .. .. 0.5 f .. 0.1 0.0 0.3 –0.1 0.2 27.9 .. 0.2 f 3.5 .. 1.8 ..
0.2 0.4 0.5 0.0 0.5 .. 0.3 .. 0.3 0.2 0.5 0.0 0.2 0.2 0.3 0.3 0.6 2.2 0.9 0.6 0.6 0.4 0.7 0.1 3.0 .. 0.6 0.3 0.6 .. 0.6 .. .. 1.7 1.9 0.6 .. 1.7 1.9 3.1 1.5 .. 2.3 0.0 0.2 2.3 3.2 0.3 .. 3.1 .. 1.6 .. .. 3.2
9.7 8.5 10.8 16.2 9.7 10.9 9.7 .. 11.3 9.9 11.3 8.3 .. 8.2 6.5 11.2 7.6 11.8 11.0 11.7 9.1 9.7 9.7 9.5 7.8 3.9 7.6 9.3 10.6 2.8 6.0 7.5 3.0 7.0 8.5 7.5 2.5 7.3 7.1 6.6 11.3 4.5 6.5 8.2 9.5 7.8 6.8 7.4 11.2 5.4 11.8 4.0 7.2 9.3 7.4
9.7 8.5 10.8 16.2 9.7 10.9 9.7 .. 11.3 9.9 11.3 8.3 .. 8.2 6.5 11.2 7.6 11.8 11.0 11.7 9.1 9.7 9.7 9.5 7.8 3.9 7.6 9.3 10.6 2.8 6.0 7.5 3.0 7.0 8.5 7.5 2.5 7.3 7.1 6.6 11.3 4.5 6.5 8.2 9.5 7.8 6.8 7.4 11.2 5.4 11.8 4.0 7.2 9.3 7.4
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population and economy
POPULATION Average annual growth (%) 1990/1995 2010/2015 Urbana (% of total) 2011 82.3 78.1 75.5 56.4 30.4 73.0 14.2 98.4 78.1 75.2 73.2 39.7 58.8 64.9 52.9 87.4 32.6 93.6 49.2 52.8 69.1 41.9 g 59.4 52.1 77.3 67.4 28.1 67.6 86.9 49.8 64.3 75.4 71.3 73.3 23.5 52.1 70.1 52.7 67.7 ECONOMY Foreign Net official Public GDP direct development expenditure Total Median Dependency per investment assistance Remittance on expenditure age ratio capita net inflows received inflows education on health (years) (%) (PPP $) (% of GDP) (% of GDP) (% of GDP) (% of GDP) (% of GDP) 2010 2011
HDI rank
Total (millions) 2030
56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94
2011 Saudi Arabia 28.1 Mexico 114.8 Panama 3.6 Serbia 9.9 Antigua and Barbuda 0.1 Malaysia 28.9 Trinidad and Tobago 1.3 Kuwait 2.8 Libya 6.4 Belarus 9.6 Russian Federation 142.8 Grenada 0.1 16.2 Kazakhstan Costa Rica 4.7 Albania 3.2 Lebanon 4.3 Saint Kitts and Nevis 0.1 Venezuela, Bolivarian Republic of 29.4 Bosnia and Herzegovina 3.8 4.3 Georgia 45.2 Ukraine 1.3 Mauritius Former Yugoslav Republic of Macedonia 2.1 Jamaica 2.8 Peru 29.4 Dominica 0.1 Saint Lucia 0.2 Ecuador 14.7 Brazil 196.7 Saint Vincent and the Grenadines 0.1 Armenia 3.1 Colombia 46.9 Iran, Islamic Republic of 74.8 Oman 2.8 Tonga 0.1 Azerbaijan 9.3 Turkey 73.6 Belize 0.3 Tunisia 10.6
38.5 135.4 4.5 9.5 0.1 37.3 1.4 4.0 7.8 8.9 136.4 0.1 18.9 5.7 3.3 4.7 0.1 37.0 3.5 3.8 40.5 1.4 2.0 2.8 35.5 0.1 0.2 17.9 220.5 0.1 3.1 56.9 84.4 3.6 0.1 10.8 86.7 0.4 12.2
2.7 1.8 2.1 1.3 2.0 2.6 0.7 –5.0 1.9 0.0 0.1 0.8 –0.7 2.4 –0.9 3.2 1.1 2.3 –5.1 –1.5 –0.2 1.4 0.6 0.8 1.9 0.1 1.3 2.1 1.6 0.1 –1.9 1.9 1.7 3.6 0.2 1.5 1.7 2.9 1.7 5.0 2.2 1.0 1.9 0.8 1.3 1.2 h 2.7 0.9 1.4 1.4 3.1 2.4 2.3 2.5 1.0 –0.1 2.3 1.8 4.4 2.2 2.1
2.1 1.1 1.5 –0.1 1.0 1.6 0.3 2.4 0.8 –0.3 –0.1 0.4 1.0 1.4 0.3 0.7 1.2 1.5 –0.2 –0.6 –0.5 0.5 0.1 0.4 1.1 0.0 1.0 1.3 0.8 0.0 0.3 1.3 1.0 1.9 0.4 1.2 1.1 2.0 1.0 1.9 1.4 0.8 1.2 0.5 0.8 0.4 h 1.2 0.5 0.9 0.6 1.9 1.7 1.6 1.3 1.5 –0.7 1.7 1.7 2.8 1.1 0.5
25.9 26.6 27.3 37.6 .. 26.0 30.8 28.2 25.9 38.3 37.9 25.0 29.0 28.4 30.0 29.1 .. 26.1 39.4 37.3 39.3 32.4 35.9 27.0 25.6 .. 27.4 25.5 29.1 27.9 32.1 26.8 27.1 25.3 21.3 29.5 28.3 21.8 28.9 20.7 26.2 30.7 25.1 20.9 26.4 34.5 24.5 34.2 27.6 23.2 21.6 23.1 21.7 24.6 25.4 35.2 22.2 24.4 18.1 24.2 20.8
49.5 54.1 54.7 46.7 .. 53.4 38.3 41.3 54.1 40.2 39.1 52.6 46.4 45.1 46.9 46.3 .. 53.6 40.8 44.6 42.5 39.8 41.4 57.4 55.7 .. 47.7 57.0 47.3 49.1 45.2 51.9 38.9 42.4 76.4 38.0 47.3 62.3 43.4 69.0 45.8 49.9 58.8 73.8 51.5 37.9 49.0 41.3 53.1 62.4 64.9 62.1 67.7 45.0 46.8 38.7 63.2 57.4 81.0 49.8 66.2
2009 23,480 14,258 13,057 11,893 18,778 14,012 25,572 .. 16,502 13,040 18,932 8,362 11,510 11,106 8,716 13,070 14,527 12,323 8,578 4,774 6,318 12,838 11,159 7,633 8,629 8,883 9,605 8,268 10,367 9,154 5,279 8,959 11,558 .. 4,466 9,638 13,668 6,628 8,273
2009
2009
2009
2006–2009b
2009
2.8 1.7 7.2 4.5 11.4 0.7 3.3 .. 2.7 3.8 3.0 14.5 11.8 4.6 8.1 13.9 24.5 –1.0 1.4 6.1 4.2 3.0 2.7 4.5 3.7 13.3 16.5 0.6 1.6 18.9 8.9 3.1 0.9 4.8 4.7 1.1 1.4 7.0 4.0 9.5 2.0 1.0 4.4 0.6 2.0 1.6 6.8 1.9 .. 2.0 0.3 1.4 2.4 7.6 14.8 2.4 1.2 3.6 .. 2.3 ..
0.0 f 0.0 0.3 1.4 0.6 0.1 0.0 .. 0.1 0.2 .. 8.3 0.3 0.4 3.0 1.8 1.1 0.0 2.4 8.6 0.6 1.8 2.2 1.3 0.4 10.1 4.7 0.4 0.0 5.5 5.9 0.5 0.0 0.1 f 12.4 0.6 0.2 2.0 f 1.3 3.0 0.2 1.7 0.3 16.1 2.5 0.0 0.2 0.0 3.7 f 1.4 0.8 1.1 4.4 2.4 9.4 4.3 0.2 0.5 25.3 f 0.6 42.0
0.1 2.5 0.7 12.6 2.2 0.6 0.5 .. 0.0 0.7 0.4 8.6 0.1 1.8 11.0 21.9 7.4 0.0 12.2 6.6 4.5 2.5 4.1 15.8 1.8 6.1 2.9 4.4 0.3 5.1 8.8 1.8 0.3 0.1 f 27.9 3.0 0.2 5.9 5.0 14.3 1.5 8.0 7.4 25.1 5.4 1.0 .. 0.6 0.1 16.5 0.1 4.3 6.2 0.3 4.8 22.4 12.3 3.8 17.6 .. ..
5.0 6.5 8.3 9.9 5.1 4.8 5.7 3.3 3.9 5.8 5.4 7.4 4.5 10.5 6.9 8.1 6.0 6.0 10.9 10.1 7.0 5.7 6.9 5.1 4.6 6.4 8.1 6.1 9.0 5.6 4.7 6.4 5.5 3.0 6.2 5.8 6.7 4.9 6.2 9.3 5.8 4.0 5.9 7.0 3.4 4.6 2.3 4.3 7.6 6.4 3.5 7.1 5.0 8.0 4.7 11.9 3.8 5.0 .. 5.2 13.8
5.0 6.5 8.3 9.9 5.1 4.8 5.7 3.3 3.9 5.8 5.4 7.4 4.5 10.5 6.9 8.1 6.0 6.0 10.9 10.1 7.0 5.7 6.9 5.1 4.6 6.4 8.1 6.1 9.0 5.6 4.7 6.4 5.5 3.0 6.2 5.8 6.7 4.9 6.2 9.3 5.8 4.0 5.9 7.0 3.4 4.6 2.3 4.3 7.6 6.4 3.5 7.1 5.0 8.0 4.7 11.9 3.8 5.0 .. 5.2 13.8
table
10
MEDIUM HUMAN DEVELOPMENT 95 Jordan 96 Algeria 97 Sri Lanka 98 Dominican Republic 99 Samoa 100 Fiji 101 China 102 Turkmenistan 103 Thailand 104 Suriname 105 El Salvador 106 Gabon 107 Paraguay 108 Bolivia, Plurinational State of 109 Maldives 110 Mongolia 111 Moldova, Republic of 112 Philippines 113 Egypt 114 Occupied Palestinian Territory 115 Uzbekistan 116 Micronesia, Federated States of
6.3 8.4 36.0 43.5 21.0 23.1 10.1 12.1 0.2 0.2 0.9 1.0 1,347.6 h 1,393.1 h 5.1 6.2 69.5 73.3 0.5 0.6 6.2 7.1 1.5 2.1 6.6 8.7 10.1 13.4 0.3 0.4 2.8 3.5 3.5 3.1 94.9 126.3 82.5 106.5 4.2 6.8 27.8 33.4 0.1 0.1
78.6 67.1 14.3 69.8 20.1 52.3 47.8 h 50.0 34.4 69.8 64.8 86.4 62.1 67.0 41.3 62.5 47.7 49.1 43.5 74.4 36.3 22.8
5,597 8,172 4,772 8,433 4,405 4,526 6,828 7,242 7,995 .. 6,629 14,419 4,523 4,419 5,476 3,522 2,854 3,542 5,673 .. 2,875 3,088
STATISTICAL TAbLeS
163
population and economy
POPULATION Average annual growth (%) Urbana (% of total) 2011 ECONOMY Foreign Net official Public GDP direct development expenditure Total Median Dependency per investment assistance Remittance on expenditure age ratio capita net inflows received inflows education on health (years) (%) (PPP $) (% of GDP) (% of GDP) (% of GDP) (% of GDP) (% of GDP) 2010 2011
HDI rank
Total (millions) 2011
117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141
Guyana Botswana Syrian Arab Republic Namibia Honduras Kiribati South Africa Indonesia Vanuatu Kyrgyzstan Tajikistan Viet Nam Nicaragua Morocco Guatemala Iraq Cape Verde India Ghana Equatorial Guinea Congo Lao People’s Democratic Republic Cambodia Swaziland Bhutan
2030 1990/1995 2010/2015 0.8 0.8 0.1 0.2 2.0 2.3 2.7 1.1 20.8 27.9 2.8 1.7 2.3 3.0 3.1 1.7 7.8 10.7 2.6 2.0 0.1 0.1 1.5 1.5 50.5 54.7 2.4 0.5 242.3 279.7 1.6 1.0 0.2 0.4 2.8 2.4 5.4 6.7 0.9 1.1 7.0 9.0 1.7 1.5 88.8 101.5 2.0 1.0 5.9 7.2 2.4 1.4 32.3 37.5 1.7 1.0 14.8 22.7 2.3 2.5 32.7 55.3 3.1 3.1 0.5 0.6 2.5 0.9 1,241.5 1,523.5 2.0 1.3 25.0 36.5 2.8 2.3 0.7 1.1 3.4 2.7 4.1 6.2 2.7 2.2 6.3 7.8 2.7 1.3 14.3 17.4 3.2 1.2 1.2 1.5 2.2 1.4 0.7 0.9 –1.5 1.5
28.7 61.8 56.2 38.6 52.2 44.0 62.2 44.6 26.0 34.5 26.4 31.0 57.6 58.8 49.9 66.1 61.8 30.3 52.2 39.9 62.5 34.3 20.4 21.3 35.5 18.9 22.5 63.0 36.2 28.6 28.6 59.4 34.3 59.2 30.6 26.9 12.6 32.4 42.7 50.5 19.2 53.6 41.7 27.6 13.5 44.1 28.3 35.9 76.3 19.2 42.5 58.9 40.8 51.3 20.3 22.9 38.8 16.8 36.6 30.2
23.8 22.9 21.1 21.2 21.0 .. 24.9 27.8 20.6 23.8 20.4 28.2 22.1 26.3 18.9 18.3 22.8 25.1 20.5 20.3 19.6 21.5 22.9 19.5 24.6 19.9 18.5 19.3 21.7 24.2 16.6 16.6 28.2 19.3 18.2 17.5 20.4 17.4 17.8 18.5 21.4 21.5 19.8 20.3 15.7 19.7 18.9 16.7 21.4 18.7 17.9 17.8 19.7 19.2 16.9 16.6 19.3 18.7 16.3 19.0
58.2 57.2 67.1 65.9 68.3 .. 53.0 47.8 70.8 52.3 66.6 41.3 62.7 49.8 83.4 85.6 58.1 54.4 73.3 72.5 79.4 60.3 54.3 70.5 50.7 74.7 82.1 77.4 64.7 54.4 95.3 95.1 43.8 78.6 84.9 92.2 71.3 87.1 85.0 86.1 65.8 66.6 73.7 70.3 103.5 74.6 83.0 98.4 63.5 83.6 87.4 84.8 76.7 80.1 96.0 93.9 73.6 79.2 97.6 80.2
2009 3,240 13,384 4,730 6,410 3,842 2,432 10,278 4,199 4,438 2,283 1,972 2,953 2,641 4,494 4,720 3,548 3,644 3,296 1,552 31,779 4,238 2,255 1,915 4,998 5,113
2009
2009
7.1 2.1 2.7 5.3 3.5 1.7 1.9 0.9 5.3 4.1 0.3 8.4 7.1 2.2 1.6 1.6 7.7 2.5 6.4 15.7 21.7 5.4 5.4 2.2 2.9 17.9 0.5 3.9 1.5 0.8 .. 2.9 .. 1.5 6.3 1.9 5.4 0.5 1.6 3.3 0.3 0.6 –1.3 4.0 3.8 1.8 1.7 5.5 9.2 2.3 1.4 5.4 4.9 1.6 1.3 1.3 1.1 0.8 1.2 1.7
8.5 2.5 0.5 3.6 3.3 15.6 0.4 0.2 16.5 7.1 8.3 4.4 13.1 1.0 1.0 4.5 13.1 0.2 6.1 0.5 4.1 7.2 7.7 2.0 9.6 42.9 6.1 15.8 1.7 1.3 9.5 0.4 .. 2.9 5.2 13.7 5.3 2.0 8.0 1.0 6.7 .. 9.4 6.4 11.4 17.5 9.5 11.1 14.5 18.0 10.3 18.5 4.6 10.6 16.6 45.7 f 14.1 13.4 11.0 17.6
2009 12.5 0.7 2.6 0.1 17.6 6.4 0.3 1.3 1.0 21.7 35.1 7.4 12.5 6.9 10.8 0.1 f 9.4 3.6 0.4 .. 0.1 0.6 3.4 3.1 ..
2006–2009b
2009
8.1 10.3 2.9 5.9 6.0 12.2 8.5 2.4 4.0 6.8 5.3 7.2 9.5 5.5 7.1 3.9 3.9 4.2 6.9 3.9 3.0 4.1 5.9 6.3 5.5 5.4 4.3 7.1 2.6 3.4 12.3 4.6 2.0 5.6 4.1 5.1 3.1 5.6 5.7 5.8 5.8 6.1 2.5 8.2 8.2 5.9 3.4 4.8 7.0 9.0 4.2 6.0 7.3 5.1 6.2 7.4 .. 4.3 5.6 6.1
8.1 10.3 2.9 5.9 6.0 12.2 8.5 2.4 4.0 6.8 5.3 7.2 9.5 5.5 7.1 3.9 3.9 4.2 6.9 3.9 3.0 4.1 5.9 6.3 5.5 5.4 4.3 7.1 2.6 3.4 12.3 4.6 2.0 5.6 4.1 5.1 3.1 5.6 5.7 5.8 5.8 6.1 2.5 8.2 8.2 5.9 3.4 4.8 7.0 9.0 4.2 6.0 7.3 5.1 6.2 7.4 .. 4.3 5.6 6.1
table
10
LOW HUMAN DEVELOPMENT 142 Solomon Islands 143 Kenya 144 São Tomé and Príncipe 145 Pakistan 146 Bangladesh 147 Timor-Leste 148 Angola 149 Myanmar 150 Cameroon 151 Madagascar 152 Tanzania, United Republic of 153 Papua New Guinea 154 Yemen 155 Senegal 156 Nigeria 157 Nepal 158 Haiti 159 Mauritania 160 Lesotho 161 Uganda 162 Togo 163 Comoros 164 Zambia 165 Djibouti 166 Rwanda 167 Benin 168 Gambia 169 Sudan 170 Côte d'Ivoire 171 Malawi 172 Afghanistan 173 Zimbabwe 174 Ethiopia 175 Mali 176 Guinea-Bissau
0.6 41.6 0.2 176.7 150.5 1.2 19.6 48.3 20.0 21.3 46.2 7.0 24.8 12.8 162.5 30.5 10.1 3.5 2.2 34.5 6.2 0.8 13.5 0.9 10.9 9.1 1.8 44.6 20.2 15.4 32.4 12.8 84.7 15.8 1.5
0.8 65.9 0.2 234.4 181.9 2.0 30.8 54.3 28.8 35.3 81.9 10.2 41.3 20.0 257.8 39.9 12.5 5.2 2.6 59.8 8.7 1.2 24.5 1.3 17.6 14.6 2.8 66.9 29.8 28.2 53.3 17.6 118.5 26.8 2.3
2.8 3.1 1.9 2.6 2.2 2.8 3.2 1.4 2.7 3.0 3.2 2.5 4.7 2.9 2.4 2.5 2.0 2.8 1.8 3.3 2.2 2.4 2.5 2.2 –4.9 3.4 3.1 2.6 3.2 1.0 8.4 2.2 3.3 2.5 2.0
2.5 2.7 2.0 1.8 1.3 2.9 2.7 0.8 2.1 2.8 3.1 2.2 3.0 2.6 2.5 1.7 1.3 2.2 1.0 3.1 2.0 2.5 3.0 1.9 2.9 2.7 2.7 2.4 2.2 3.2 3.1 2.2 2.1 3.0 2.1
2,547 1,573 1,820 2,609 1,416 805 5,812 .. 2,205 1,004 1,362 2,281 2,470 1,817 2,203 1,155 1,151 1,929 1,468 1,217 850 1,183 1,430 2,319 1,136 1,508 1,415 2,210 1,701 794 1,321 .. 934 1,185 1,071
0.4 5.7 1.0 f 5.4 11.8 .. 0.1 f .. 0.7 0.1 0.1 0.2 4.4 10.6 5.5 23.8 21.2 0.1 26.2 4.7 10.7 2.1 0.3 3.1 1.8 3.6 10.9 5.5 0.8 0.0 .. .. 0.9 4.5 5.6
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population and economy
POPULATION Average annual growth (%) 1990/1995 2010/2015 Urbana (% of total) 2011 ECONOMY Foreign Net official Public GDP direct development expenditure Total Median Dependency per investment assistance Remittance on expenditure age ratio capita net inflows received inflows education on health (years) (%) (PPP $) (% of GDP) (% of GDP) (% of GDP) (% of GDP) (% of GDP) 2010 2011 2009 2009 2009 2009 2006–2009b 2009
HDI rank
Total (millions) 2011 2030
177 178 179 180 181 182 183 184 185 186 187
Eritrea Guinea Central African Republic Sierra Leone Burkina Faso Liberia Chad Mozambique Burundi Niger Congo, Democratic Republic of the
5.4 10.2 4.5 6.0 17.0 4.1 11.5 23.9 8.6 16.1 67.8 24.5 0.1 0.0 0.0 0.0 9.6 0.0 1,129.5 972.9 3,545.5 1,259.7
8.4 15.9 6.4 8.5 29.1 6.5 18.4 35.9 11.4 30.8 106.0 26.2 0.1 0.0 0.0 0.0 16.4 0.0 1,218.5 1,082.5 4,087.6 1,857.2
0.3 5.5 2.5 –0.4 2.7 –0.3 3.0 3.2 1.7 3.3 3.8 1.6 1.5 1.3 1.7 1.2 –0.2 0.5 0.7 1.1 1.6 2.8 2.4 1.3 0.3 1.7 2.1 2.7 T 2.7 T 1.5 1.5 T
2.9 2.5 2.0 2.1 3.0 2.6 2.6 2.2 1.9 3.5 2.6 0.4 1.6 0.0 0.6 0.6 2.6 0.2 0.5 0.8 1.0 2.2 2.0 0.6 0.2 1.1 1.4 2.4 T 2.2 T 1.1 1.1 T
22.1 35.9 39.2 38.8 26.5 48.2 28.2 39.2 11.3 17.2 35.9 60.3 72.1 100.0 100.0 94.1 37.9 50.9 78.3 75.7 41.3 33.9 56.7 46.1 64.6 79.8 32.0 37.7 T 29.7 T 52.0 50.8 T
19.0 18.3 19.4 18.4 17.1 18.2 17.1 17.8 20.2 15.5 16.7 32.9 .. .. .. .. 17.5 .. 39.3 30.5 28.9 19.8 23.2 32.3 34.9 27.5 24.6 18.6 T 19.7 T 26.6 29.2 T
78.9 85.6 78.9 81.4 90.6 86.2 93.1 89.5 68.2 104.9 95.0 47.4 .. .. .. .. 91.2 .. 49.9 46.7 48.1 77.7 61.9 41.5 43.3 53.0 55.7 83.5 T 76.3 T 59.0 52.2 T
581 1,048 757 808 1,187 396 1,300 885 392 690 319 .. .. .. .. .. .. .. 35,768 12,861 5,077 1,671 8,256 6,227 14,244 10,739 3,368 2,181 1,379 5,241 10,715
0.0 1.2 2.1 3.8 2.1 24.9 6.8 9.0 0.0 13.7 9.0 .. .. .. .. .. .. .. 1.8 2.5 2.2 2.7 3.2 1.9 3.4 2.1 2.1 3.7 3.2 3.9 2.3
7.8 5.8 11.9 23.0 13.5 78.3 9.2 20.8 41.2 8.9 23.9 .. 32.1 .. .. .. .. .. .. 0.3 0.5 8.7 1.9 0.4 .. 0.4 1.4 9.9 12.0 3.7 2.2
.. 1.6 .. 2.4 1.2 6.2 .. 1.1 2.1 1.7 .. .. .. .. .. .. .. .. 0.3 1.2 2.2 5.1 2.7 1.4 1.4 1.5 4.5 2.2 5.2 6.7 0.7
2.2 5.7 4.3 13.1 6.4 13.2 7.0 5.7 13.1 6.1 9.5 .. 16.5 3.9 .. 7.1 .. 9.9 11.9 6.5 4.6 5.0 5.0 4.4 6.4 7.7 4.0 6.4 5.4 5.6 10.2
2.2 5.7 4.3 13.1 6.4 13.2 7.0 5.7 13.1 6.1 9.5 .. 16.5 3.9 .. 7.1 .. 9.9 11.2 6.7 4.5 5.1 5.3 4.3 6.3 7.6 4.1 6.2 5.6 7.0 6.0
OTHER COUNTRIES OR TERRITORIES Korea, Democratic People’s Rep. of Marshall Islands Monaco Nauru San Marino Somalia Tuvalu Human Development Index groups Very high human development High human development Medium human development Low human development Regions Arab States East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean South Asia Sub-Saharan Africa Least developed countries Small island developing states World
360.7 496.9 1,978.5 2,135.3 480.5 491.3 591.2 696.0 1,728.5 2,141.8 877.6 T 1,353.8 T 851.1 T 1,256.8 T 53.2 63.8 6,974.0 T 8,321.4 T
table
10
NOTES a. Because data are based on national definitions of what constitutes a city or metropolitan area, crosscountry comparison should be made with caution. b. Data refer to the most recent year available during the period specified. c. Includes Svalbard and Jan Mayen Islands. d. Includes Christmas Island, Cocos (Keeling) Islands and Norfolk Island. e. Includes Åland Islands. f. Refers to an earlier year than that specified. g. Includes Agalega, Rodrigues and Saint Brandon. h. Includes Taiwan Province of China and excludes Hong Kong Special Administrative Region and Macao Special Administrative Region. DEFINITIONS Total population: De facto population in a country, area or region as of 1 July. Average annual population growth: Average annual exponential growth rate for the period indicated. Urban population: De facto population living in areas classified as urban according to the criteria used by each area or country as of 1 July. Median age: Age that divides the population distribution into two equal parts—that is, 50 percent of the population is above that age and 50 percent is below it. Dependency ratio: Ratio of the sum of the population ages 0–14 and that ages 65 and older to the population ages 15–64.
GDP per capita: Gross domestic product (GDP) expressed in purchasing power parity international dollar terms, divided by midyear population. Foreign direct investment net inflows: Sum of equity capital, reinvestment of earnings, other long-term capital and short-term capital, expressed as a percentage of gross domestic product (GDP). Net official development assistance received: Disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies to promote economic development and welfare in countries and territories in part I of the Development Assistance Committee list of aid recipients, expressed as a percentage of the recipient country’s gross national income (GNI). Remittance inflows: Earnings and material resources transferred by international migrants or refugees to recipients in their country of origin or countries in which the migrant formerly resided, expressed as a percentage of the receiving country’s GDP. Public expenditure on education: Total public expenditure (current and capital) on education, expressed as a percentage of gross domestic product (GDP). Total expenditure on health: The sum of public and private health expenditure. It includes the provision of health services (preventive and curative), family planning activities, nutrition activities and emergency aid designated for health but does not include provision of water and sanitation. MAIN DATA SOURCES Columns 1–4, 6 and 7: UNDESA (2011). Column 5: UNDESA (2010). Columns 8–13: World Bank (2011a).
STATISTICAL TAbLeS
165
Technical notes
calculating the human development indices—graphical presentation
Human Development Index (HDI)
DIMENSIONS INDICATORS
Long and healthy life
Life expectancy at birth
Knowledge
Mean years of schooling Expected years of schooling
A decent standard of living
GNI per capita (PPP $)
DIMENSION INDEX
Life expectancy index
Education index
GNI index
Human Development Index (HDI) Inequality-adjusted Human Development Index (IHDI)
DIMENSIONS INDICATORS
Long and healthy life
Life expectancy at birth
Knowledge
Mean years of schooling Expected years of schooling
A decent standard of living
GNI per capita (PPP $)
DIMENSION INDEX
Life expectancy
Years of schooling
Income/consumption
INEQUALITYADJUSTED INDEX
Inequality-adjusted life expectancy index
Inequality-adjusted education index
Inequality-adjusted income index
Inequality-adjusted Human Development Index (IHDI) Gender Inequality Index (GII)
DIMENSIONS INDICATORS
Health
Maternal mortality ratio Adolescent fertility rate
Empowerment
Female and male population with at least secondary education Female and male shares of parliamentary seats
Labour market
Female and male labour force participation rates
DIMENSION INDEX
Female reproductive health index
Female empowerment index
Female labour market index
Male empowerment index
Male labour market index
Female gender index
Male gender index
Gender Inequality Index (GII) Multidimensional Poverty Index (MPI)
DIMENSIONS INDICATORS
Health
Nutrition Child mortality
Education
Years of schooling Children enrolled
Standard of living
Cooking fuel Toilet Water Electricity Floor Assets
POVERTY MEASURES
Intensity of poverty
Headcount ratio
Multidimensional Poverty Index (MPI)
167
Technical noTes
Technical note 1. calculating the human Development index The Human Development Index (HDI) is a summary measure of human development. It measures the average achievements in a country in three basic dimensions of human development: a long and healthy life, access to knowledge and a decent standard of living. The HDI is the geometric mean of normalized indices measuring achievements in each dimension. For a full elaboration of the method and its rationale, see Klugman, Rodriguez and Choi (2011). This technical note describes the steps to create the HDI, data sources and the methodology used to express income. steps to estimate the human Development index There are two steps to calculating the HDI.
Step 1. Creating the dimension indices Minimum and maximum values (goalposts) are set in order to transform the indicators into indices between 0 and 1. The maximums are the highest observed values in the time series (1980–2011). The minimum values can be appropriately conceived of as subsistence values. The minimum values are set at 20 years for life expectancy, at 0 years for both education variables and at $100 for per capita gross national income (GNI). The low value for income can be justified by the considerable amount of unmeasured subsistence and nonmarket production in economies close to the minimum, not captured in the official data. Goalposts for the Human Development Index in this Report
Dimension Life expectancy Observed maximum Minimum
the maximum. This is equivalent to applying equation 1 directly to the geometric mean of the two subcomponents. Because each dimension index is a proxy for capabilities in the corresponding dimension, the transformation function from income to capabilities is likely to be concave (Anand and Sen 2000). Thus, for income the natural logarithm of the actual minimum and maximum values is used.
Step 2. Aggregating the subindices to produce the Human Development Index The HDI is the geometric mean of the three dimension indices:
(ILife 1/3 . IEducation 1/3 . IIncome 1/3).
Example: Viet Nam
Indicator Value
(2)
Life expectancy at birth (years) Mean years of schooling (years) Expected years of schooling (years) GNI per capita (PPP $)
Note: Values are rounded.
75.2 5.5 10.4 2,805
Life expectancy index =
75.2 – 20 = 0.870 83.4 – 20 5.5 – 0 = 0.478 13.1 – 0 10.4 – 0 = 0.576 18 – 0 = 0.503
Mean years of schooling index =
Expected years of schooling index =
Mean years of schooling Expected years of schooling Combined education index Per capita income (PPP $)
83.4 (Japan, 2011) 13.1 (Czech Republic, 2005) 18.0 (capped at) 0.978 (New Zealand, 2010) 107,721 (Qatar, 2011)
20.0 0 0 0 100
Education index =
0.478 . 0.576 – 0 0.978 – 0
ln(2,805) – ln(100) Income index = ln(107,721) – ln(100) = 0.478 Human Development Index = 3 0.870 . 0.503 . 0.478 = 0.593 Data sources • Life expectancy at birth: UNDESA (2011) • Mean years of schooling: HDRO updates (http://hdr. undp.org/en/statistics/) based on UNESCO data on education attainment (http://stats.uis.unesco.org/unesco) using the methodology outlined in Barro and Lee (2010a) • Expected years of schooling: UNESCO Institute for Statistics (2011) • GNI per capita: World Bank (2011a), IMF (2011), UNSD (2011) and UNDESA (2011)
Having defined the minimum and maximum values, the subindices are calculated as follows: Dimension index = actual value – minimum value . maximum value – minimum value (1)
For education, equation 1 is applied to each of the two subcomponents, then a geometric mean of the resulting indices is created and finally, equation 1 is reapplied to the geometric mean of the indices using 0 as the minimum and the highest geometric mean of the resulting indices for the time period under consideration as
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Methodology used to express income GNI is traditionally expressed in current terms. To make GNI comparable across time, GNI is converted from current to constant terms by taking the value of nominal GNI per capita in purchasing power parity (PPP) terms for the base year (2005) and building a time series using the growth rate of real GNI per capita, as implied by the ratio of current GNI per capita in local currency terms to the GDP deflator. Official PPPs are produced by the International Comparison Program (ICP), which periodically collects thousands of prices of matched goods and services in many countries. The last round of this exercise refers to 2005 and covers 146 countries. The World Bank produces estimates for years other than the ICP benchmark based on inflation relative to the United States. Because other international organizations—such as the World Bank and the International Monetary Fund (IMF)— quote the base year in terms of the ICP benchmark, the HDRO does the same. To obtain the income value for 2011, IMF-projected GDP growth rates (based on constant terms) are applied to the most
recent GNI values. The IMF-projected growth rates are calculated in local currency terms and constant prices rather than in PPP terms. This avoids mixing the effects of the PPP conversion with those of real growth of the economy. estimating missing values For a small number of countries that were missing one out of four indicators, the HDRO filled the gap by estimating the missing value using cross-country regression models. The details of the models used are available at http://hdr.undp.org/ en/statistics/understanding/issues/. In this Report, the PPP conversion rates were estimated for three countries (Cuba, Occupied Palestinian Territory and Palau), expected years of schooling were estimated for five countries (Barbados, Haiti, Montenegro, Singapore and Turkmenistan) and mean years of schooling were estimated for eight countries (Antigua and Barbuda, Eritrea, Grenada, Kiribati, St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines, and Vanuatu). This brought the total number of countries in the HDI in 2011 up to 187, from 169 in 2010.
Technical note 2. calculating the inequality-adjusted human Development index The Inequality-adjusted Human Development Index (IHDI) adjusts the Human Development Index (HDI) for inequality in the distribution of each dimension across the population. It is based on a distribution-sensitive class of composite indices proposed by Foster, Lopez-Calva, and Szekely (2005), which draws on the Atkinson (1970) family of inequality measures. It is computed as a geometric mean of geometric means, calculated across the population for each dimension separately (for details, see Alkire and Foster 2010). The IHDI accounts for inequalities in HDI dimensions by “discounting” each dimension’s average value according to its level of inequality. The IHDI equals the HDI when there is no inequality across people but falls further below the HDI as inequality rises. In this sense, the IHDI is the actual level of human development (taking into account inequality), while the HDI can be viewed as an index of the “potential” human development that could be achieved if there was no inequality. The “loss” in potential human development due to inequality is the difference between the HDI and the IHDI and can be expressed as a percentage. Data sources Since the HDI relies on country-level aggregates such as national accounts for income, the IHDI must draw on alternative sources of data to obtain insights into the distribution. The distributions have different units—life expectancy is distributed across a hypothetical cohort, while years of schooling and income are distributed across individuals. Inequality in the distribution of HDI dimensions is estimated for: • Life expectancy, using data from abridged life tables provided by UNDESA (2011). This distribution is grouped in age intervals (0–1, 1–5, 5–10, ... , 85+), with the mortality rates and average age at death specified for each interval. • Mean years of schooling, using household survey data harmonized in international databases, including the Luxembourg Income Study, EUROSTAT’s European Union Survey of Income and Living Conditions, the World Bank’s International Income Distribution Database, the United Nations Children’s Fund’s Multiple Indicators Cluster Survey, ICF Macro’s Demographic and Health Survey, the World Health Organization’s World Health Survey and the United Nations University’s World Income Inequality Database. • Disposable household income or consumption per capita using the above listed databases and household surveys—or for a few countries, income imputed based on an asset index matching methodology using household survey asset indices (Harttgen and Vollmer 2011). A full account of data sources used for estimating inequality in 2011 is given at http://hdr.undp.org/en/ statistics/ihdi/.
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169
computing the inequality-adjusted human Development index There are three steps to computing the IHDI.
Step 1. Measuring inequality in the dimensions of the Human Development Index The IHDI draws on the Atkinson (1970) family of inequality measures and sets the aversion parameter ε equal to 1.1 In this case the inequality measure is A = 1 – g/µ, where g is the geometric mean and µ is the arithmetic mean of the distribution. This can be written as:
n
Step 3. Combining the dimension indices to calculate the Inequality-adjusted Human Development Index The IHDI is the geometric mean of the three dimension indices adjusted for inequality. First, the IHDI that includes the unlogged income index (IHDI*) is calculated:
IHDI* =
3
3
* * * ILife . IEducation . IIncome =
(1– ALife) . ILife . (1– AEducation) . IEducation . (1– AIncome) . IIncome* .
Ax = 1 –
X1 …Xn – X
The HDI based on unlogged income index (HDI*) is then calculated: (1) HDI* =
3
ILife . IEducation . IIncome* .
where {X1 …, Xn} denotes the underlying distribution in the dimensions of interest. A x is obtained for each variable (life expectancy, mean years of schooling and disposable income or consumption per capita).2 The geometric mean in equation 1 does not allow zero values. For mean years of schooling one year is added to all valid observations to compute the inequality. Income per capita outliers—extremely high incomes as well as negative and zero incomes—were dealt with by truncating the top 0.5 percentile of the distribution to reduce the influence of extremely high incomes and by replacing the negative and zero incomes with the minimum value of the bottom 0.5 percentile of the distribution of positive incomes. Sensitivity analysis of the IHDI is given in Kovacevic (2010).
Step 2. Adjusting the dimension indices for inequality – The mean achievement in an HDI dimension, X , is adjusted for inequality as follows:
The percentage loss to the HDI* due to inequalities in each dimension is calculated as: Loss = 1 –
3 IHDI* = 1 – (1–ALife) . (1–AEducation) . (1–AIncome) . HDI*
Assuming that the percentage loss due to inequality in income distribution is the same for both average income and its logarithm, the IHDI is then calculated as: IHDI = IHDI* . HDI = 3 (1–ALife) . (1–AEducation) . (1–AIncome) . HDI . HDI*
– X . (1 – Ax) = n X1 …Xn . Thus the geometric mean represents the arithmetic mean reduced by the inequality in distribution. The inequality-adjusted dimension indices are obtained from the HDI dimension indices, Ix, by multiplying them by (1 – Ax), where Ax , defined by equation 1, is the corresponding Atkinson measure:
* I x = (1 – Ax) . Ix . * The inequality-adjusted income index, I Income, is based on the unlogged GNI index, IIncome*. This enables the IHDI to account for the full effect of income inequality.
notes on methodology and caveats The IHDI is based on an index that satisfies subgroup consistency. This ensures that improvements or deteriorations in the distribution of human development within a certain group of society (while human development remains constant in the other groups) will be reflected in changes in the overall measure of human development. This index is also path independent, which means that the order in which data are aggregated across individuals, or groups of individuals, and across dimensions yields the same result—so there is no need to rely on a particular sequence or a single data source. This allows estimation for a large number of countries. The main disadvantage is that the IHDI is not association sensitive, so it does not capture overlapping inequalities. To make the measure association-sensitive, all the data for each individual must be available from a single survey source, which is not currently possible for a large number of countries.
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Example: Peru
Indicator Dimension index Inequality measure (A1) Inequality-adjusted index Human Development Index Inequality-adjusted Human Development Index
3
Loss %
Life expectancy Mean years of schooling Expected years of schooling Education index Logarithm of gross national income Gross national income
74.0 8.7 12.9
0.852 0.662 0.717 0.704
0.148
(1–0.148) ∙ 0.852 = 0.728
HDI with unlogged income HDI
3
0.852 . 0.704 . 0.077 = 0.359
0.728 . 0.535 . 0.054 = 0.275 1 – 0.275 / 0.359 = 0.232
3
0.852 . 0.704 . 0.634 = 0.725 (0.275 / 0.359) . 0.725 = 0.557
Note: Values are rounded.
0.240
(1–0.240) ∙ 0.704 = 0.535
9.03 8,389
0.634 0.077 0.300 (1–0.300) ∙ 0.077 = 0.054
Technical note 3. calculating the Gender inequality index The Gender Inequality Index (GII) reflects gender-based disadvantage in three dimensions—reproductive health, empowerment and the labour market—for as many countries as data of reasonable quality allow. The index shows the loss in potential human development due to inequality between female and male achievements in these dimensions. It varies between 0—when women and men fare equally—and 1, where one gender fares as poorly as possible in all measured dimensions. It is computed using the association-sensitive inequality measure suggested by Seth (2009). The index is based on the general mean of general means of different orders—the first aggregation is by the geometric mean across dimensions; these means, calculated separately for women and men, are then aggregated using a harmonic mean across genders. Data sources • Maternal mortality ratio (MMR): WHO, UNICEF, UNFPA and World Bank (2010) • Adolescent fertility rate (AFR): UNDESA (2011) • Share of parliamentary seats held by each sex (PR): Interparliamentary Union’s Parline database (2011) • Attainment at secondary and higher education (SE) levels: HDRO (2011) updates of Barro and Lee (2010b) estimates based on UNESCO Institute for Statistics data on education attainment (http://stats.uis.unesco.org/unesco/) • Labour market participation rate (LFPR): ILO (2011) computing the Gender inequality index There are five steps to computing the GII.
Step 1. Treating zeros and extreme values Because a geometric mean cannot have a zero value, a minimum value must be set for all component indicators. The minimum is set at 0.1 percent for adolescent fertility rate, share of
parliamentary seats held by women, attainment at secondary and higher education levels, and labour market participation rate. Female parliamentary representation of countries reporting zero is coded as 0.1 percent because even in countries without female members of the national parliaments, women have some political influence. Because higher maternal mortality suggests poorer maternal health, for the maternal mortality ratio the maximum value is truncated at 1,000 deaths per 100,000 births and the minimum value is truncated at 10. It is assumed that countries where maternal mortality ratios exceed 1,000 do not differ in their inability to create conditions and support for maternal health and that countries with 1–10 deaths per 100,000 births are performing at essentially the same level and that differences are random. Sensitivity analysis of the GII is given in Gaye et al. (2010).
Step 2. Aggregating across dimensions within each gender group, using geometric means Aggregating across dimensions for each gender group by the geometric mean makes the GII association sensitive (see Seth 2009). For women and girls, the aggregation formula is
GF =
3
10 . 1 MMR AFR
1/2
. (PRF . SEF) 1/2 . LFPRF ,
and for men and boys the formula is GM = 3 1 . (PRM . SEM) 1/2 . LFPRM . The rescaling by 0.1 of the maternal mortality ratio in the aggregation formula for women and girls is needed to account for the truncation of the maternal mortality ratio minimum at 10. This is a new adjustment introduced in Human Development Report 2011.3
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171
Step 3. Aggregating across gender groups, using a harmonic mean The female and male indices are aggregated by the harmonic mean to create the equally distributed gender index
Step 5. Calculating the Gender Inequality Index Comparing the equally distributed gender index to the reference standard yields the GII,
(G )–1 + (GM)–1 HARM (GF , GM) = F 2
–1
.
Example: Lesotho
Health Maternal mortality ratio
1–
HARM (GF , GM ) . –– GF, M
Empowerment Labour market
Using the harmonic mean of geometric means within groups captures the inequality between women and men and adjusts for association between dimensions.
Step 4. Calculating the geometric mean of the arithmetic means for each indicator The reference standard for computing inequality is obtained by aggregating female and male indices using equal weights (thus treating the genders equally) and then aggregating the indices across dimensions:
Female Male F + M 2
Adolescent fertility rate
Attainment at secondary Labour market Parliamentary and higher participation representation education rate
530 na
73.5 na 1 +1 73.5
0.229 0.771
0.243 0.203
0.719 0.787 0.719 + 0.787 2 = 0.743
( )( )
10 530 2
= 0.508
0.229 . 0.243 + 0.771 . 0.203 2 = 0.316
na is not applicable.
GF, M =
3
Health . Empowerment . LFPR 10 . 1 + 1 /2, MMR AFR
F
Using the above formulas, it is straightforward to obtain: GF 0.134 = 3
3
where Health = Empowerment =
10 . 1 530 73.5
0.229 . 0.243 . 0.719
( PR
. SEF + PRM . SEM /2, and
)
LFPRF + LFPRM . LFPR = 2 Health should not be interpreted as an average of corresponding female and male indices but as half the distance from the norms established for the reproductive health indicators—fewer maternal deaths and fewer adolescent pregnancies.
GM 0.675 =
1 . 0.771 . 0.203 . 0.787
3
–– GF, M 0.492 = 0.508 . 0.316 . 0.743 HARM (GF , GM ) 0.230= GII 1 1 1 + 2 0.134 0.675
–1
1 – (0.230/0.492) = 0.532.
Technical note 4. calculating the Multidimensional Poverty index The Multidimensional Poverty Index (MPI) identifies multiple deprivations at the individual level in education, health and standard of living. It uses micro data from household surveys, and—unlike the Inequality-adjusted Human Development Index—all the indicators needed to construct the measure must come from the same survey. More details can be found in Alkire and Santos (2010). Methodology Each person is assigned a deprivation score according to his or her household’s deprivations in each of the 10 component indicators. The maximum score is 100 percent, with each dimension equally weighted (thus the maximum score in each dimension is 33.3  percent). The education and health dimensions
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Human development report 2011
have two indicators each, so each component is worth 5/3 (or 16.7 percent). The standard of living dimension has six indicators, so each component is worth 5/9 (or 5.6 percent). The thresholds are as follows: • Education: having no household member who has completed five years of schooling and having at least one school-age child (up to grade 8) who is not attending school. • Health: having at least one household member who is malnourished and having had one or more children die. • Standard of living: not having electricity, not having access to clean drinking water, not having access to adequate sanitation, using “dirty” cooking fuel (dung, wood or charcoal), having a home with a dirt floor, and owning no car, truck
or similar motorized vehicle while owning at most one of these assets: bicycle, motorcycle, radio, refrigerator, telephone or television. To identify the multidimensionally poor, the deprivation scores for each household are summed to obtain the household deprivation, c. A cut-off of 33.3 percent, which is the equivalent of one-third of the weighted indicators, is used to distinguish between the poor and nonpoor. If c is 33.3 percent or greater, that household (and everyone in it) is multidimensionally poor. Households with a deprivation score greater than or equal to 20 percent but less than 33.3 percent are vulnerable to or at risk of becoming multidimensionally poor. Households with a deprivation score of 50 percent or higher are severely multidimensionally poor. The MPI value is the product of two measures: the multidimensional headcount ratio and the intensity (or breadth) of poverty. The headcount ratio, H, is the proportion of the population who are multidimensionally poor: q H= n where q is the number of people who are multidimensionally poor and n is the total population. The intensity of poverty, A, reflects the proportion of the weighted component indicators in which, on average, poor people are deprived. For poor households only, the deprivation scores are summed and divided by the total number of poor persons: ∑1c , A= q where c is the deprivation score that the poor experience. Weighted count of deprivations in household 1: 1. 5 5 = 2.22, + 1. 3 9
q
example using hypothetical data
Household Indicators 1 2 3 4 Weights
Household size Education No one has completed five years of schooling At least one school-age child not enrolled in school Health At least one member is malnourished One or more children have died Living conditions No electricity No access to clean drinking water No access to adequate sanitation House has dirt floor Household uses “dirty” cooking fuel (dung, firewood or charcoal) Household has no car and owns at most one of: bicycle, motorcycle, radio, refrigerator, telephone or television Results Household deprivation score, c (sum of each deprivation multiplied by its weight) Is the household poor (c > 33.3%)?
4 0 0 0 1 0 0 0 0 1
7 1 1 0 1 1 0 1 0 1
5 0 0 1 0 1 1 1 0 1
4 1 0 0 1 1 0 0 0 1 5/3 or 16.7% 5/3 or 16.7% 5/3 or 16.7% 5/3 or 16.7% 5/9 or 5.6% 5/9 or 5.6% 5/9 or 5.6% 5/9 or 5.6% 5/9 or 5.6%
0
1
0
1
5/9 or 5.6%
22.2% 72.2% 38.9% 50.0% No Yes Yes Yes
Note: 1 indicates deprivation in the indicator; 0 indicates nondeprivation.
Headcount ratio (H) = 7+5+4 = 0.800 4+7+5+4 (80 percent of people live in poor households) Intensity of poverty (A) = (7.22/10 . 7) + (3.89/10 . 5) + (5.00/10 . 4) = 0.5625 (7+5+4) (the average poor person is deprived in 56  percent of the weighted indicators). MPI = H . A = 0.450
which is equal to a deprivation score of 2.22/10 = 0.222, or 22.2 percent.
NOTES
1 The inequality aversion parameter affects the degree to which lower achievements are emphasized and higher achievements are de-emphasized. 2 Ax is estimated from survey data using the survey weights, Âx = 1 –
w X 1 … X nw n , where ∑1 wi = 1. ∑1n wi Xi
1 n
3 The GII trends calculated at five-year intervals for 1995–2011 using consistent data and methodology are available at http://hdr.undp.org/en/statistics/gii.
However, for simplicity and without loss of generality, equation 1 is referred to as the Atkinson measure.
Technical noTes
173
Regions
Arab States (20 countries or areas)
Algeria, Bahrain, Djibouti, Egypt, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Occupied Palestinian Territory, Oman, Qatar, Saudi Arabia, Somalia, Sudan, Syrian Arab Republic, Tunisia, United Arab Emirates, Yemen
East Asia and the Pacific (24 countries)
Cambodia, China, Fiji, Indonesia, Kiribati, Democratic People’s Rep. of Korea, Lao People’s Democratic Republic, Malaysia, Marshall Islands, Federated States of Micronesia, Mongolia, Myanmar, Nauru, Palau, Papua New Guinea, Philippines, Samoa, Solomon Islands, Thailand, Timor-Leste, Tonga, Tuvalu, Vanuatu, Viet Nam
Europe and Central Asia1 (30 countries)
Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic, Estonia, Georgia, Hungary, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Republic of Moldova, Montenegro, Poland, Romania, Russian Federation, Serbia, Slovakia, Slovenia, Tajikistan, The former Yugoslav Republic of Macedonia, Turkey, Turkmenistan, Ukraine, Uzbekistan
Latin America and the Caribbean (33 countries)
Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Plurinational State of Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Bolivarian Republic of Venezuela
South Asia (9 countries)
Afghanistan, Bangladesh, Bhutan, India, Islamic Republic of Iran, Maldives, Nepal, Pakistan, Sri Lanka
Sub-Saharan Africa (45 countries)
Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Comoros, Congo, Democratic Republic of the Congo, Côte d’Ivoire, Equatorial Guinea, Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mozambique, Namibia, Niger, Nigeria, Rwanda, São Tomé and Príncipe, Senegal, Seychelles, Sierra Leone, South Africa, Swaziland, United Republic of Tanzania, Togo, Uganda, Zambia, Zimbabwe
Note: Countries included in aggregates for Least Developed Countries and Small Island Developing States follow UN classifications, which are available at http://www.unohrlls.org/. HDRO does not include Bahrain, Barbados or Singapore in the aggregates for Small Island Developing States. 1. The former socialist countries of Europe and Central Asia that have undergone a political and economic transformation since 1989–1991 as well as Cyprus and Turkey.
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statistical references
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Global, Regional and National Human Development reports Human Development Reports: e annual global Human Development Reports (HDRs) have been published by UNDP since 1990 as intellectually independent and empirically grounded analyses of development issues, trends, progress and policies. Resources related to the 2011 Report and earlier HDRs are available free of charge at hdr.undp.org, including full texts and summaries in major UN languages, summaries of consultations and network discussions, the Human Development Research Paper Series and HDR news bulletins and other public information materials. Also available are statistical indicators, other data tools, interactive maps, country fact sheets and additional information associated with the HDRs. Regional Human Development Reports: More than 40 editorially autonomous HDRs with a regional focus have been produced in the past two decades with support from UNDP’s regional bureaus. With o en provocative analyses and policy advocacy, these reports have examined such critical issues as civil liberties and the empowerment of women in the Arab States, corruption in Asia and the Paci c, treatment of the Roma and other minorities in Central Europe and the inequitable distribution of wealth in Latin America and the Caribbean. National Human Development Reports: Since the release of the rst National HDR in 1992, National HDRs have been produced in 140 countries by local editorial teams with UNDP support. ese reports—more than 650 have been published to date—bring a human development perspective to national policy concerns through locally managed consultations and research. National HDRs o en focus on issues of gender, ethnicity or rural-urban divides to help identify inequality, measure progress and detect early warning signs of potential con ict. Because these reports are grounded in national needs and perspectives, many have had substantial in uence on national policies, including strategies for achieving the Millennium Development Goals and other human development priorities. For more information on National and Regional HDRs, including related training and reference resources, see hdr.undp.org/en/nhdr/. Human Development Reports 1990–2010 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007/2008 2009 2010 Concept and Measurement of Human Development Financing Human Development Global Dimensions of Human Development People’s Participation New Dimensions of Human Security Gender and Human Development Economic Growth and Human Development Human Development to Eradicate Poverty Consumption for Human Development Globalization with a Human Face Human Rights and Human Development Making New Technologies Work for Human Development Deepening Democracy in a Fragmented World Millennium Development Goals: A Compact among Nations to End Human Poverty Cultural Liberty in Today’s Diverse World International Cooperation at a Crossroads: Aid, Trade and Security in an Unequal World Beyond Scarcity: Power, Poverty and the Global Water Crisis Fighting Climate Change: Human Solidarity in a Divided World Overcoming Barriers: Human Mobility and Development e Real Wealth of Nations: Pathways to Human Development
For more information visit: http://hdr.undp.org
KEY TO COUNTRIES
2011 HDI rank and change in rank from 2010 to 2011
Afghanistan Albania Algeria Andorra Angola Antigua and Barbuda Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bhutan Bolivia, Plurinational State of Bosnia and Herzegovina Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Central African Republic Chad Chile China Colombia Comoros Congo Congo, Democratic Republic of the Costa Rica Côte d’Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Fiji Finland Former Yugoslav Republic of Macedonia France Gabon Gambia 172 70 96 32 148 60 45 86 2 19 91 53 42 146 47 65 18 93 167 141 108 74 118 84 33 55 181 185 139 150 6 133 179 183 44 101 87 163 137 187 69 170 46 51 31 27 16 165 81 98 83 113 105 136 177 34 174 100 22 78 20 106 168 Georgia Germany Ghana Greece Grenada Guatemala Guinea Guinea-Bissau Guyana Haiti Honduras Hong Kong, China (SAR) Hungary Iceland India Indonesia Iran, Islamic Republic of Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Kiribati Korea, Republic of Kuwait Kyrgyzstan Lao People’s Democratic Republic Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Madagascar Malawi Malaysia Maldives Mali Malta Mauritania Mauritius Mexico Micronesia, Federated States of Moldova, Republic of Mongolia Montenegro Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway 75 9 135 29 67 131 178 176 117 158 121 13 38 14 134 124 88 132 7 17 24 79 12 95 68 143 122 15 63 126 138 43 71 160 182 64 8 40 25 151 171 61 109 175 36 159 77 57 116 111 110 54 130 184 149 120 157 3 5 129 186 156 1 Occupied Palestinian Territory Oman Pakistan Palau Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Qatar Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Samoa São Tomé and Príncipe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands South Africa Spain Sri Lanka Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania, United Republic of Thailand Timor-Leste Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Vanuatu Venezuela, Bolivarian Republic of Viet Nam Yemen Zambia Zimbabwe 114 89 145 49 58 153 107 80 112 39 41 37 50 66 166 72 82 85 99 144 56 155 59 52 180 26 35 21 142 123 23 97 169 104 140 10 11 119 127 152 103 147 162 90 62 94 92 102 161 76 30 28 4 48 115 125 73 128 154 164 173
1
1
1 1
1 –1 1 1 –1
2 1 –1 1 –1 1 –1
–1 –1
–1 –1 2 1
–1 –1 1 1
–1 1 1
2 1
–1 1 –1 1 –10 1 –2 3
1 1
–1
–2
1
–1 1
–1 –1
–1
1 –1 3
–1 –1 2 –1 –1
3
1
1 1 –1
–2
–3 –2
1
1
NOTE Arrows indicate upward or downward movement in the country’s ranking over 2010–2011 using consistent data and methodology; a blank indicates no change.
The great development challenge of the 21st century is to safeguard the right of generations today and in the future to live healthy and fulfilling lives. The 2011 Human Development Report offers important new contributions to the global dialogue on this challenge, showing how sustainability is inextricably linked to equity—to questions of fairness and social justice and of greater access to a better quality of life. Forecasts suggest that continuing failure to reduce the grave environmental risks and deepening inequalities threatens to slow decades of sustained progress by the world’s poor majority—and even to reverse the global convergence in human development. Our remarkable progress in human development cannot continue without bold global steps to reduce both environmental risks and inequality. This Report identifies pathways for people, local communities, countries and the international community to promote environmental sustainability and equity in mutually reinforcing ways. New analysis shows how power imbalances and gender inequalities at the national level are linked to reduced access to clean water and improved sanitation, land degradation and illness and death due to air pollution, amplifying the effects associated with income disparities. Gender inequalities also interact with environmental outcomes and make them worse. At the global level governance arrangements often weaken the voices of developing countries and exclude marginalized groups. But there are alternatives to inequality and unsustainability. Investments that improve equity—for example, in access to renewable energy, water and sanitation, and reproductive healthcare—could advance both sustainability and human development. Stronger accountability and democratic processes can also improve outcomes. Successful approaches rely on community management, broadly inclusive institutions and attention to disadvantaged groups. Beyond the Millennium Development Goals, the world needs a development framework that reflects equity and sustainability. This Report shows that approaches that integrate equity into policies and programmes and that empower people to bring about change in the legal and political arenas hold enormous promise. The financing needed for development are many times greater than current official development assistance. Today’s spending on low-carbon energy sources, for example, is less than 2 percent of even the lowest estimate of need. Financing flows need to be channeled towards the critical challenges of unsustainability and inequity. While market mechanisms and private funding will be vital, they must be supported and leveraged by proactive public investment. Closing the financing gap requires innovative thinking, which this Report provides. The Report also advocates reforms to promote equity and voice. We have a collective responsibility towards the least privileged among us today and in the future around the world—and a moral imperative to ensure that the present is not the enemy of the future. This Report can help us see the ways forward.
ISBN 978-0-230-36331-1
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