Human Development Reports - United Nations Development Programme (UNDP)

The 2013 Human Development Report examines the profound shift in global dynamics driven by the fast-rising new powers of the developing world, and its long-term implications for human development. China has overtaken Japan as the world’s second biggest economy, while lifting hundreds of millions of its people out of poverty. India is reshaping its future with new entrepreneurial creativity and social policy innovation. Brazil is raising its living standards through expanding international relationships and antipoverty programs that are emulated worldwide. But the “Rise of the South” analyzed in the Report is a much larger phenomenon: Turkey, Mexico, Thailand, South Africa, Indonesia and many other developing nations are also becoming leading actors on the world stage.

The Report shows how this growing diversity in voice and power is transforming global politics and economics and challenging assumptions that have guided the major post–Second World War international institutions.  Leaders of the South are asking for more representative international governance structures that better incorporate principles of democracy and equity. Countries of the South are increasingly driving global economic growth and broad-based social change.

The Report demonstrates that the rise of the South is the result not of adherence to a fixed set of policy prescriptions, but of pragmatic policies responding to local circumstances and opportunities—including a deepening of the developmental role of states, a dedication to improving human development (including through better education, health care and social welfare programs) through policy innovation, and an openness to engaging with the world economy through trade and investment.

Even so, future progress will require policymakers in the South as well as in the North to address such critical challenges issues as equity, accountability, environmental risks, changing demography and meaningful civic participation.

The report describes a global shift of power and resources on a historic scale that should continue well into the 21^st century. For the first time since the early 19^th century, the combined output of the developing world’s three leading economies—Brazil, China and India—is about equal to the combined GDP of the long-standing industrial powers of  Western Europe and North America—Canada, France, Germany, Italy, the United Kingdom and the United States. This represents a dramatic rebalancing of global economic strength. The Report shows the three biggest Southern economies overtaking those six traditional industrial powers by the end of the decade (calculating GDP in purchasing-power terms), and continuing to expand beyond 2020.

No, this is about much more than the BRICS countries. The Report shows clearly that the phenomenon of the ‘Rise of the South’ embraces more than 40 developing nations that have all notably accelerated their human development progress in recent years. Some of the largest countries have made especially rapid advances, notably Brazil, China, India, Indonesia, South Africa and Turkey. But there has also been impressive human development progress in smaller economies such as Bangladesh, Chile, Ghana, Rwanda, and Tunisia.

One way to identify high HDI achievers is to look at countries with positive income growth and good performance on measures of health and education relative to other countries at comparable levels of development. These include some of the largest countries— Brazil, China, India, and Indonesia— as well as smaller economies: Bangladesh, Chile, Ghana, Malaysia, Mauritius, Mexico, Thailand, Tunisia, Turkey, Uganda and Viet Nam. Another way of identifying high achievers in human development is to look for countries that have been more successful in closing the “human development gap,” as measured by the reduction in their HDI shortfall (the distance from the maximum HDI score). We also identify high HDI achievers by the positive and statistically significant “residuals” obtained from a regression of the change in log of HDI between 2012 and 1990 on the log of HDI in 1990 in a cross-country sample of 132 countries. This way, more than 40 developing countries are identified as having made rapid progress in HDI between 1990 and 2012, relative to countries at similar levels of HDI in 1990.

The term refers to a state with a proactive government that pursues economic growth as a pathway to human development. A developmental state is characterized by strategic interventions that shape a country’s future:   promoting targeted economic sectors; clearly articulating social and economic goals; and directing competent bureaucracies to achieve those goals. The developmental state ultimately derives its political legitimacy from delivering better social services and living standards to its people. 

The report analyses and reports on policies across a very wide range – health, education, social, economic, industrial – and in every region. Often, it is the combination of policies rather than one alone. Here are some examples:

Brazil’s industrial and trade policy: When Brazil’s inward-oriented economic strategy switched to an export focus, individual firms that benefited from large domestic markets could rely on capacities built up over decades. Embraer, for example, is now the world’s leading producer of regional jet commercial aircraft of up to 120 seats. The country’s steel industry has a similar story. Government intervention meant that agricultural technology has also been strength of Brazil. The System for Agricultural Research and Innovation has contributed to the nearly fourfold growth in agricultural efficiency per worker.

Chile’s support of agriculture and food: Chilean firms have had major success in expanding exports of processed agricultural food and beverages and forestry and fish products. Support from a nonprofit corporation, Fundación Chile, helped make the country’s commercial salmon cultivation one of the highest in the world.

Bangladesh’s industrial, social and education policy: Bangladesh took advantage of market distortions in world apparel trade, and learnt how to succeed in international markets, combining built-up competitiveness with trade preferences in favor of least developed countries (LDCs).  By 2010, its share of world apparel exports had increased to about 4.8%, from about 0.8% in 1990. More than 95% of women in the garment industry are migrants from rural areas. This unprecedented employment opportunity for young women has narrowed gender gaps in employment and income. At the same time, the higher participation of girls in formal education has been enhanced by nongovernmental organizations like BRAC. One result has been a halving of the infant mortality rate.

Indonesia’s technology policy: Indonesia used telecommunications technology to connect its large cluster of far-flung islands and to open the country to the outside world. This required extensive private and public investment and policy guidance. By 2010, an estimated 85% of adults owned phones, as state encouragement and market competition slashed the prices of handsets and phone service. In July 2012, there were 7.4 million registered Facebook users in greater Jakarta alone—the second most of any city in the world. 

India’s industrial and education policies: India’s state-led, import-substituting industrialization was accompanied by a deliberate effort to build human capabilities and invest in world-class tertiary education.  After the reforms of the 1990s, these investments paid off when India was unexpectedly able to capitalize on its stock of skilled workers in emergent information technology–enabled industries, which by 2011–2012 were generating $70 billion in export earnings. In pharmaceuticals there is a similar story.  

China’s trade policy: Rapid market opening in China would have shut down state enterprises without creating new industrial activities, so the state reformed gradually. To attract foreign direct investment, create jobs and promote exports, it established special economic zones. At the same time, it increased the competencies of its workers and firms by requiring foreign firms to enter into joint ventures, transfer technology or meet high requirements for domestic content. By 2011, China had completed 10 years of membership in the World Trade Organization and overtaken Germany as the largest exporter of goods and services. 

Social policy in Mexico and Brazil: Conditional cash transfer programmes in Mexico, Brazil and other countries are designed to increase beneficiaries’ incomes and their access to health and education by making transfers conditional on requirements such as visits to health clinics and school attendance. They target individuals from low-income or disadvantaged households and provide support in cash. Mexico’s Oportunidades, for example, is conditional on children’s school attendance and medical checkups and parents’ attendance at community meetings. It distributed about $3 billion to some 5 million beneficiary households in 2012. Brazil’s Bolsa Familia and Oportunidades, the two largest programmes in Latin America, cost less than 1% of GDP. 

Agricultural and economic policy in Ghana: In the 1970s and early 1980s, Ghana’s cocoa sector – the main pillar of the economy - faced near-collapse. Ghana restored its international competitiveness by devaluing the currency, increasing the capacity of the private sector, and giving farmers a much higher share of prices received. Between 1983 and 2006, the country doubled its production of cocoa per hectare, and today the sector supports 700,000 people. It has also invested in helping farmers connect to world markets: A recent survey found that around 61% of cocoa farmers owned mobile phones.

Health policy in Rwanda: Rwanda has introduced community-based health insurance to boost access to health services.  As a result, health care became more affordable in rural areas, and under-five mortality fell from 196 deaths per 1,000 live births in 2000 to 103 in 2007, and the maternal mortality ratio declined more than 12% a year over 2000–2008. Rwanda is on track to reach the Millennium Development Goal for maternal health.

The human development consequences of the rise of the South have been profound: the proportion of people living in extreme income poverty   was slashed from 43% in 1990 to 22% of the world’s population in 2008, with more than 500 million people lifted from poverty in China alone.   As a result, the world community achieved well ahead of schedule the poverty eradication target of the first of the eight Millennium Development Goals, which was to halve the proportion of people living on less than $1.25 a day between 1990 and 2015.

The number of countries with a Human Development Index (HDI) value below the 25th percentile in 1990 dropped from 33 to 30 between 1990 and 2000 and was halved from 30 to 15 between 2000 and 2012. Between 1990 and 2012, almost all countries greatly advanced in human development terms, as measured by the HDI.  Indeed, no country for which complete data was available had a lower HDI value in 2012 than it did in 2000.

Income inequality is on the rise in many countries. Between 1990 and 2005, the Inequality-adjusted HDI for 66 countries shows overall inequality falling only marginally, because declining inequality in health and education was offset by rising inequality in income.

Globally, there have been much greater reductions in inequality in health and education in the last two decades than in income. This is partly because of the measures used—life expectancy and mean years of schooling have upper bounds to which all countries eventually converge. But for income, there is no upper limit. Virtually all studies agree that global income inequality is high, though there is no consensus on recent trends. One study that integrated the income distribution of 138 countries over 1970–2000 found that although mean income per capita has risen, inequality has not. Other studies conclude the opposite. Still others find no change at all. Inequality is not just a feature of developing countries. The rising income inequality in the United States and some European countries highlights fairness in how incomes are distributed and who benefits from growth. 

Yet much can be done to narrow these gaps. In Latin America, long the region with the greatest inequality, the trend has begun to reverse due to poverty reduction initiatives and other government interventions, including public spending aided by high commodity prices internationally. Brazil and Mexico are leaders of this trend, using cash-transfer programs and other mechanisms to raise living standards in poor communities.

Education is “one of the most powerful instruments for advancing equity and human development,” says the Report. It “builds people’s capacities and expands their freedom of choice. Education boosts people’s self-confidence and makes it easier for them to find better jobs, engage in public debate and make demands on government for health care, social security and other entitlements. Education also has striking benefits for health and mortality.” Education is a common denominator in many national success stories, in the Republic of Korea, China, India, and Ghana, for example.

There is overwhelming evidence of the importance of education for women. Educated women contribute to society in multiple ways, as citizens, as highly productive members of the work force, and as mothers, sisters, and daughters. Educated mothers tend to have fewer, healthier and better educated children. Educated women have better access to contraception.  Mother’s education is more important to child survival than household income or wealth, data in the Report shows. A modeling exercise conducted for the Report projects the impact of differences in education levels on child mortality over 2010– 2050 under two scenarios. The “base case” scenario assumes current trends in educational attainment continue. The “fast track” scenario assumes much more ambitious education policy targets, similar to those achieved in recent decades by the Republic of Korea. The results from the fast track scenario show substantially fewer child deaths as mother’s level of schooling rises. Projection in the Report  estimate that  between 2045 and 2050 in India, six million  children are likely to die before the age of five projected to die under the base-case scenario, but  that would be reduced to three million  under the fast track scenario.

Between 1980 and 2010, developing countries increased their share of world merchandise trade from 25% to 47% and their share of world output from 33% to 45%.  One major contributor to this trend is that developing nations of the South are trading not just with the North but also increasingly with one another. Between 1980 and 2011, South–South trade increased from less than 8% of world merchandise trade to more than 26%, with growth particularly remarkable in the 2000s. Over the same period, the share of North–North trade declined from 46% to less than 30%. Projections show that trade between developing countries will soon surpass trade between developed countries.  

If foreign trade is managed well, with proceeds directed to the long-term benefit of the public, this engagement with the world economy can be a positive force for human development, the Report says.  Data show a correlation in developing countries between human development gains and a rising contribution of foreign trade to the national economy.

Even more important than being integrated with global markets are the terms of engagement with these markets. Without investment in people, returns from global markets can be limited and transitory. Success is more likely to be the result not of a sudden opening but of gradual and sequenced integration with the world economy, according to national circumstances, and accompanied by investment in people, institutions and infrastructure.  A number of smaller economies have successfully focused on niche products, whose success is often the fruit of years of state support built on existing competencies or the creation of new ones.

The Report shows that foreign direct investment (FDI), like foreign trade, can help contribute to human development if it is strategically managed to benefit a country’s specific needs and potential, including through greater education opportunities and other public services. Successful performance in trade, investment and international production ultimately depends on rising levels of human development, as illustrated by the association between high export earnings per capita and achievement in education and health. The more globally integrated economies also tend to offer better opportunities to women.

The capacity of people and institutions also affects the benefits from FDI. Host countries need to invest in the capacity of their people to identify, assimilate and develop the useful knowledge embedded in foreign capital and ideas. Indeed, an educated and healthy workforce is often a key factor in influencing the decision of foreign investors on where to locate. A positive correlation between FDI inflows and achievements in health and education was evident in a study of 137 countries carried out for the Report.

As their economies soared, many countries have piled up large amounts of foreign exchange reserves. This represents a change in global finances, but also in the global economic balance of power. Between 2000 and the third quarter of 2011, global foreign exchange reserves rose from $1.9 trillion to $10.1 trillion, with a dominant share of the increase accumulated by emerging and developing countries (including Brazil, China, India, Indonesia, the Republic of Korea, Malaysia, Mexico, Thailand and others) whose reserves totaled $6.8 trillion. China alone holds more than $3 trillion in foreign reserves.

Developing countries have also amassed sovereign wealth funds. According to data by the Sovereign Wealth Fund Institute, these had an estimated $4.3 trillion in assets at the end of 2010, with $3.5 trillion held by developing and emerging economies and $800 billion in East Asia alone.

The report argues that this mountain of money could be used better if invested in development. “The resources could be deployed in more productive ways to support the provision of public goods, to provide capital to projects that enhance productive capacities and economic and human development and to promote regional and subregional financial stability,” it argues. “Allocating just 3% of liquid international reserves of the nine G20 countries of the South would increase the share of public investment in these countries by 4.1%–11.7% of GDP, close to the average level of public investment for all developing countries.”

The Report strongly contends that all developing countries have a right to pursue and attain higher levels of human development – and that this can and indeed must be achieved without imperilling the environment. Fossil-fuelled growth is not a prerequisite for a better life, as defined in human development terms. Investments that improve equity—in access to renewable energy, water and sanitation, and reproductive health—can advance both sustainability and human development. Stronger accountability and democratic processes, including through active civil society engagement and independent media, can also improve policy outcomes. The 2011 Human Development Report analysed these questions in detail.

The Report argues that the formation of a new South Commission is one way to look at how countries in the South can develop new institutions and partnerships, and share knowledge, experiences and technology. In 1987, the first South Commission was organized under the leadership of Julius Nyerere, then president of Tanzania, and the renowned economist Manmohan Singh, who is now prime minister of India. Its 1990 report “The Challenge to the South” was a landmark document, urging countries of the South to act in solidarity in North-South negotiations, arguing for people-centred development, presciently identifying climate change as a long-term development issue, and identifying societal challenges such as endemic poverty, social exclusion and inequality.

Since then, the world and the South have been thoroughly transformed. The possibilities for co-operation are greater than ever, but the political context is very different. Decolonization is now a fading memory in most states; the Cold War, which helped shape the Non-Aligned Movement, is long finished; and many of the states of the South are themselves emerging as political and economic superpowers. “A new South Commission, building on the legacy of the first commission but reflecting the strengths and needs of the South today, could provide a fresh vision,” the Report argues, “based on recognition of how the diversity of the South can be a force for a new kind of solidarity, aimed at accelerating human development progress for decades to come.”

The dominant institutions of global governance - the UN, the IMF and the World Bank - were created in and reflect a very different era.    The South is under-represented. The rising countries of the South are now often finding alternative mechanisms for cooperation in trade, finance, development and assistance, including regional arrangements and bilateral partnerships.  Global governance is becoming a mosaic of new arrangements and old structures, which need to interact and cooperate more systematically and efficiently, in what the Report terms  “coherent pluralism.”

But some urgent issues such as climate change can be resolved only globally. Here, it matters that states from the South are given less representation than their population and economic size merit. For example, China, which is the world’s second largest economy and its largest cache of foreign reserves, has a smaller voting share in the World Bank than France or the United Kingdom.

Similarly, the United Nations Security Council makes decisions on global peace and security with a permanent membership that reflects the post-war geopolitical structure of 1945, excluding all of Africa and Latin America, as well as India, poised to soon surpass China as the world’s most populous country. “The major international institutions need to be more representative, transparent and accountable,” argues the Report. “The Bretton Woods institutions, the regional development banks and even the UN system all risk diminishing relevance if they fail to represent all member states and their people adequately.

The Human Development Reports have been commissioned and published by UNDP since 1990 as an intellectually independent, empirically grounded analysis of development issues, trends, progress and policies. The Report’s ultimate goal is to help advance human development. This means placing as much emphasis on health, education, and the expansion human freedoms and abilities as economic growth. As the first Human Development Report in 1990 asserted in its opening sentence, “The real wealth of a nation is its people.”

The Reports and related resources can be found at hdr.undp.org, including downloadable Reports or summaries in a dozen languages; eBooks; Human Development Research Papers; updated statistical indicators; data visualization tools; interactive maps; and data profiles of all UN member states.

The human development approach is anchored in a vision of development that was pioneered by Mahbub ul Haq, the lead author of the first Human Development Reports, and Amartya Sen, the Nobel Laureate economist who advised and assisted Haq in developing the report’s overall philosophical approach and its trademark Human Development Index. The 1990 Report said the goal of human development is “enlarging people’s choices,” including the ability to be healthy, to be educated, and to enjoy a decent standard of living. But the first Reports also stressed that human development and wellbeing go far beyond these dimensions to encompass a much broader range of capabilities, including political freedoms and human rights. Indeed, the “concept” of human development is much broader than the “measure” of human development (e.g., HDI). Its enthusiastic reception by governments, civil society, researchers and the media demonstrated the deep resonance of this innovative approach in the development community and beyond.

With its wealth of empirical data and innovative approach to measuring development, the Human Development Reports have had a deep impact on development thinking around the world. The Reports have prompted and informed discussions and debates, and have pioneered ideas that have since become widely accepted. For example, the concept of the Millennium Development Goals (MDGs) can be traced in part back to the 1991 Report on financing development. The concept of human security, the theme of the 1994 Report, has also strongly influenced subsequent development debates. The 1999 Report highlighted the diverse impacts of globalization on human wellbeing including the often neglected subject of care and caring labour. The Human Development Reports have also long stressed the importance of sustainability. The 1994 Report emphasized the centrality of sustainable development to the human development approach of putting people first, not economic growth as an end in itself.  The first Report, in 1990, warned presciently about ozone damage and urban pollution and other environmental hazards. The 2007/8 Report addressed the consequences of climate change for the world’s poor.  The 2011 Report, building on that legacy, identified policies that can advance sustainability and equality simultaneously, locally as well as globally.  The 2013 Report carries on that tradition, examining the human development impact to date and projected long-term human development implications of "the Rise of the South."

With its wealth of empirical data and innovative approach to measuring development, the Human Development Reports have had a deep impact on development thinking around the world. The Reports have prompted and informed discussions and debates, and have pioneered ideas that have since become widely accepted. For example, the concept of the Millennium Development Goals (MDGs) can be traced in part back to the 1991 Report on financing development. The concept of human security, the theme of the 1994 Report, has also strongly influenced subsequent development debates. The 1999 Report highlighted the diverse impacts of globalization on human wellbeing including the often neglected subject of care and caring labour. The Human Development Reports have also long stressed the importance of sustainability. The 1994 Report emphasized the centrality of sustainable development to the human development approach of putting people first, not economic growth as an end in itself.  The first Report, in 1990, warned presciently about ozone damage and urban pollution and other environmental hazards. The 2007/8 Report addressed the consequences of climate change for the world’s poor.  The 2011 Report, building on that legacy, identified policies that can advance sustainability and equality simultaneously, locally as well as globally.  The 2013 Report carries on that tradition, examining the human development impact to date and projected long-term human development implications of "the Rise of the South."

More than 40 editorially autonomous Human Development Reports with a regional focus have been produced in the past two decades with support from UNDP’s regional bureaus. With often 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 the Asia-Pacific region, treatment of the Roma and other minorities in Central Europe, and social inequalities in Latin America. These regional Reports reflect the global report’s traditions of intellectual autonomy and a human development perspective, putting people first.  In addition, local editorial teams with UNDP support have produced many national Reports - more than 650 in 140 countries to date. These reports bring a human development perspective to national policy concerns through locally managed consultations and research.  National Reports often focus on issues of gender, ethnicity, or rural/urban divides to help identify inequality, measure progress, and identify early warning signs of potential conflict. Because these reports are grounded in national needs and perspectives, many have had significant influence on national polices, including strategies for achieving the Millennium Development Goals and other human development priorities. For more information on national and regional Human Development Reports, see hdr.undp.org/en/nhdr/.

The Human Development Index (HDI) is a composite measure of human development. It measures average achievements in a country in three basic dimensions of human development: a long and healthy life (health), access to knowledge (education) and a decent standard of living (income). Data availability determines HDI country coverage. To enable comparisons among countries, the HDI calculated with the most recent available internationally comparable data from leading international data agencies and other credible data sources, rather than from national sources directly.

The Inequality-adjusted Human Development Index (IHDI) adjusts the Human Development Index (HDI) for inequality in distribution of each dimension across the population. 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 is less than the HDI as inequality rises. In this sense, the IHDI is the actual level of human development (accounting for this inequality), while the HDI can be viewed as an index of “potential” human development (or the maximum level of HDI) that could be achieved if there was no inequality. The “loss” in potential human development due to inequality is given by the difference between the HDI and the IHDI and can be expressed as a percentage.

The Gender Inequality Index (GII) reflects women’s 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 human development due to inequality between female and male achievements in these dimensions. It ranges from 0, which indicates that women and men fare equally, to 1, which indicates that women fare as poorly as possible in all measured dimensions.

The Multidimensional Poverty Index (MPI) identifies multiple deprivations at the individual level in health, education 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. Each person in a given household is classified as poor or not poor depending on the number of deprivations his or her household experiences. These data are then aggregated into the national measure of poverty.

The Human Development Report presents two types of statistical information: statistics in its indices and associated Statistical Tables, which provide a global assessment of country achievements in different areas of human development, and statistical evidence in the thematic analysis in the Report itself, which may be based on international, national or sub-national data. The online Human Development Report database contains a full-time series data set for all indicators included in the printed edition of the Report.

The Human Development Report Office is primarily a user, not a producer, of statistics. To allow comparisons across countries and over time in the Report, it relies on international data agencies with the mandate, resources and expertise to collect and compile data on specific indicators. For more information see the contact information of major data agencies. Sources for all data used in the indicator tables are given in short citations at the end of each table. When an agency provides data it has collected from another source, both sources are credited in the table notes. When an agency has drawn from other data contributors, only the ultimate source is provided. The Report provides the original data components used by the Human Development Report Office to ensure that its calculations can be easily replicated.  

The statistical evidence used in the thematic analysis in the Report is often drawn from the Statistical Tables. But other sources include commissioned papers, government documents, national human development reports, reports of non-governmental organizations, journal articles and other scholarly publications. Official statistics usually receive priority. But because of the cutting-edge nature of the issues discussed, relevant official statistics may not exist, so that nonofficial sources of information must be used. Nevertheless, the Human Development Report Office is committed to relying on data compiled through scholarly and scientific research and to ensuring impartiality in the sources of information and in its use in the analysis.  Where information from sources other than the Report’s indicator tables is used in boxes or tables in the text, the source is shown and the full citation is given in the bibliography. In each chapter, endnotes specify the sources of statistical information not drawn from the indicator tables.

The 2013 Report divides countries into four groups according to country HDI rankings: Very High, High, Medium and Low Human Development. The groups each represent one quartile of the annual HDI grouping, which in 2013 comprises 187 countries and territories. Developing countries are further classified by the Report into Arab States, Asia and the Pacific, Europe and Central Asia, Latin America and the Caribbean, and Sub-Saharan Africa, following UNDP Regional Bureau classifications. (Due to its size and diversity, the Asia-Pacific region is subdivided for the Report’s statistical purposes into two: South Asia, and East Asia & the Pacific.)

The Millennium Development Goals (MDGs) are a set of quantifiable, time-bound goals adapted from the Millennium Declaration, which was endorsed in March 2002 by the UN member states.  The Human Development Report incorporates some indicators used in Millennium Development Goals in its annual Statistical Tables, but does not report on the achievement of the MDGs as such.

The United Nations Statistics Division’s Millennium Indicators Database  (http://mdgs.un.org) is the chief UN source of data on the MDGs, providing updated statistics for the Secretary-General’s yearly report on progress towards the Millennium Development Goals, as well as for other annual reports, including the Human Development Reports and the World Bank’s World Development Indicators reports. The UN Statistics Division, the World Bank and other data providers - such as the Joint UN Programme on HIV/AIDS (UNAIDS), the UNESCO Institute for Statistics (UIS), the United Nations Children's Fund (UNICEF), and the World Health Organization (WHO) - enable the Report to include the most recent available MDGs figures. MDGs data can be found in:  

1)     MDG Monitor: Tracking the Millennium Development Goals http://www.globalgovernancewatch.org/resources/mdg-monitor--tracking-the-millennium-development-goals

2)     Global and national efforts

UNSD Millennium Indicators Database http://unstats.un.org/unsd/mdg/Default.aspx

The Human Development Index (HDI) is a composite measure of health, education and income that was introduced in the first Human Development Report in 1990 as an alternative to purely economic assessments of national progress, such as GDP growth.  It soon became the most widely accepted and cited measure of its kind, and has been adapted for national use by many countries. HDI values and rankings in the global Human Development Report are calculated using the latest internationally comparable data from mandated international data providers. Previous HDI values and rankings are retroactively recalculated using the same updated data sets and current methodologies, and are presented in Table 2 of the Statistical Annex of the 2013  Report. The HDI rankings and values in the 2013 Human Development Report cannot therefore be compared directly to HDI rankings and values published in previous Human Development Reports.

The 2012 HDI covers 187 countries, the same number as in 2011, while only 169 were included in the 2010 HDI. This major expansion of HDI coverage is the result of intensified efforts by the Human Development Report office to work with international data providers and national statistical agencies to obtain required development indicators for the HDI which had been unavailable for some countries in previous years.

Data constraints precluded HDI estimates for member states: Marshall Islands, Monaco, Nauru, the People’s Democratic Republic of Korea, San Marino, Somalia, South Sudan and Tuvalu.

The new HDI rankings introduce the concept of the statistical tie for the first time since the HDI was introduced in the first Human Development Report in 1990, for countries with HDI values that are identical to at least three decimal points. Ireland and Sweden, each with an HDI value of 0.916, are both ranked #7 in the new HDI, for example, though the two countries’ HDI values diverge when calculated to four or more decimal points.

After consultations with many leading experts in development measurement, we concluded that differences beyond a thousandth of a percent are statistically insignificant. When two countries are so close in their HDI values, sharing the same ranking is more accurate and fair. (For more information: Aguna and Kovacevic, 2011: http://hdr.undp.org/en/reports/global/hdr2010/papers/HDRP_2010_47.pdf)

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with such different human development outcomes. For example, the Bahamas’ GNI per capita is higher than New Zealand’s (by 17%) but life expectancy at birth is about 5 years shorter, mean years of schooling is 4 years shorter and expected years of schooling differ greatly between the two countries, resulting in New Zealand having a much higher HDI value than the Bahamas. These striking contrasts can stimulate debate about government policy priorities.

The HDI rankings did change for a significant number of countries. Since the ranking is relative, the better performance of other countries can explain some of the changes. However, the most significant factor was the revisions made to the data by data providers. It is for this reason that HDI ranks from two reports are not comparable. That is why users of the HDR are advised not to compare the results from different Reports, but to use Table 2 from the latest report, which is based on the latest data available. In this table, HDRO presents trends in HDI using comparable and consistent time series data. The true rank change is expressed in this table as the number of places a country has moved within the index. A change in rank of 0 indicates that a country has neither improved nor declined in HDI relative to other countries between 2011 and 2012.

Health (Life expectancy): The UN Population Division revised its life expectancy series biennially, which sometimes creates both increases and decreases for many countries. Just like in 2011, the life expectancy at birth data used for this year’s HDI and its trends are from the 2010 Revision of the World Population Prospects.

Education (“Expected years of schooling” and “Mean years of schooling”):  Because HDRO must rely on data from international organizations that provide data which are comparable across countries, the data contained in the 2013 Report may not match data from national surveys.  Data for mean years of schooling (for the current adult population 25 years and older) are similar to those used in the 2011 Report and they refer to year 2010, unless specified differently.

Gross national income: Gross national income per capita is expressed in constant purchasing-power-parity (PPP$) terms. These estimates are based on:  the reported GNI pc in current national units, the GDP deflator, the GNI pc in current PPP$, and the IMF estimates of the real GDP growth for 2011 and 2012.  Each of these indicator series is updated or revised every year. For example, in 2011 there were no reported values for GNI for several countries for the year 2010. IMF projections were used instead. Some of these 2010 values became available in 2012 in the UN SNA Main Aggregates and were used for estimation of the 2012 GNI pc, see: http://data.un.org/Explorer.aspx?d=SNAAMA .  Just as in 2011, GNI per capita estimates for 2012 is expressed in constant 2005 PPP$.

Yes, the HDI indicators can be adapted at the country level provided they meet other aspects of statistical quality. It can also be disaggregated at sub-national level to compare levels and disparities among different subpopulations within a country, provided that appropriate data at the level of disaggregation are available; or can be estimated using sound statistical methodology. The highlighting of internal disparities using HDI methodology has prompted constructive policy debates in many countries.

Life expectancy at birth is provided by the UN Department of Economic and Social Affairs; mean years of schooling are based  on UNESCO’s Institute for Statistics (UIS) educational attainment data and Barro and Lee methodology; expected years of schooling  are provided by UIS; and GNI per capita by the World Bank and the International Monetary Fund. For a few countries, mean years of schooling are estimated from nationally representative household surveys, and for few countries GNI was obtained from the UN SNA Main Aggregates database. Many data gaps still exist in even some very basic areas of human development indicators. While actively advocating for the improvement of human development data, as a principle and for practical reasons, the Human Development Report Office does not collect data directly from countries.

The HDI attempts to make an assessment of 187 diverse countries and areas, with very different price levels. To compare economic statistics across countries, the data must first be converted into a common currency. Unlike market exchange rates, PPP rates of exchange allow this conversion to take account of price differences between countries. In that way GNI per capita (PPP US$) better reflects people's living standards. In theory, 1 PPP dollar (or international dollar) has the same purchasing power in the domestic economy of a country as US$1 has in the US economy. The new PPP values have been used since 2008. The latest International Comparison Survey ICP, from which the PPPs are calculated, was done in 2005; 146 countries took part in the survey, which were 26 more than in the previous one. For further discussion on the PPP, see Human Development Indices – A statistical update 2008 (Section 2). For computation of the 2011 HDI, GNI is expressed in constant 2005 PPP$. This is a change from 2010 when GNI was expressed in constant 2008 PPP$. A reason was to fully comply with the World Bank’s and IMF’s standards for expressing the monetary variables in 2005 constant international (PPP) dollars. This change had a differential impact on countries but on average the change was minimal.

When one indicator is missing, the HDRO estimates the missing value using an alternative source or a cross-country regression model. The estimated values along with the method and/or model used are first communicated to the affected country before using it for the computation of the HDI. Mean years of schooling (MYS) for Andorra and Liechtenstein was based on the MYS of neighbouring countries Spain and Switzerland, respectively. For 20 countries, the MYS was estimated from nationally representative household surveys—UNICEF’s Multiple Indicator Cluster Surveys (MICS) Demographic and Health Surveys (DHS), and the World Bank’s Income International Distribution Database. For eight countries—Cape Verde, Eritrea, Grenada, Kiribati, St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines and Vanuatu—mean years of schooling was estimated by a cross-country regression model. Expected years of schooling were estimated by cross-country regression for eleven countries— Bahrain, Germany (tertiary education), Haiti, Liberia, Micronesia (Federated States of), Palau, Papua New Guinea, Sierra Leone, South Africa, Syrian Arab Republic, and Turkmenistan.

No. GNI per capita only reflects average national income. It tells nothing of how that income is spent, whether on universal health, education or military expenditure. Comparing rankings on GNI per capita and the HDI can reveal much about the results of national policy choices. For example, a country with a very high GNI per capita, such as Kuwait which has a relatively low mean years of schooling for its adult population, can have a lower HDI rank than, say, Barbados, which has less than 30% of the GNI per capita of Kuwait.

Prior to 2010, HDI cut-off points were set as absolute values, and were inevitably somewhat arbitrary. With the new classifications, the approach is explicitly relative -- based on quartiles. The new classification also reduces the amount of variation within each group: previously the medium human development group ranged from 0.500 to 0.799, whereas now the effective range is 0.536 to 0.710. It does however mean that the size of each group depends on the total number of ranked countries and that some countries may enter lower classification even if they continue to make progress In these cases we would stress focusing on the change in the HDI value over time (see Table 2), and underline that the classifications are relative, not absolute. The low group, as in 2011, is the bottom 46 countries.

No. The concept of human development is much broader than what can be captured in the HDI, or any other of the composite indices in the Human Development Report (Inequality-adjusted HDI, Gender Inequality Index and Multidimensional Poverty Index). The HDI, for example, does not reflect political participation or gender inequalities. The HDI and the other composite indices can only offer a broad proxy on some of the key issues of human development, gender disparity and human poverty. A fuller picture of a country's level of human development requires analysis of other indicators and information presented in the statistical annex of the report.

The HDI remains a composite index that measures progress in the three basic dimensions—health, knowledge and income. Under the previous HDI formula, health was measured by life expectancy at birth; education or “knowledge” by a combination of the adult literacy rate and school enrolment rates (for primary through university years); and income or standard of living by GDP per capita adjusted for purchasing-power parity (PPP US$).

Health is still measured by life expectancy at birth. But since 2010, in the knowledge component of the HDI is measured by combining the expected years of schooling for a school-age child in a country entering school today with the mean years of prior schooling for adults aged 25 and older. The income measurement, meanwhile, has changed from purchasing-power-adjusted per-capita Gross Domestic Product (GDP) to purchasing-power-adjusted per-capita Gross National Income (GNI); GNI includes some remittances, providing a more accurate economic picture of many developing countries.

The indicators were changed for several reasons. For example, adult literacy used in the old HDI (which is simply a binary variable, literate or illiterate, with no gradations) is an insufficient measure for knowledge achievement. By including average years of schooling and expected years of schooling, one can better capture the level of education and recent changes.

Gross Domestic Product (GDP) is the monetary value of goods and services produced in a country irrespective of how much is retained in the country. Gross National Income (GNI) expresses the income accrued to residents of a country, including some international flows, and excluding income generated in the country but repatriated abroad. Thus, GNI is a more accurate measure of a country’s economic welfare. As shown in the 2010 Report, significant differences could exist between the income of a country’s residents, measured by GNI or GDP.

Previously, the HDI had a form of the arithmetic mean of dimension indices obtained from the corresponding indicators by normalization using the fixed minima and maxima. The normalization refers to the transformation of indicators expressed in different units to the unit-less quantities taking values between 0 and 1. The 2010 introduced HDI has a form of geometric mean of dimension indices obtained from the indicators by normalization based on minima and maxima observed over the period for which the HDI has been computed and reported. Thus, the previous “cap” on the income component was replaced in the 2010 HDI by an “observed maximum” per-capita income level. Adopting the geometric mean produces lower index values, with the largest changes occurring in countries with uneven development across dimensions. The geometric mean has only a moderate impact on HDI rankings.

Unlike the old HDI, the new HDI based on the geometric mean takes into account differences in achievement across dimensions. Poor performance in any dimension is now directly reflected in the new HDI, which captures how well a country’s performance is across the three dimensions. That is to say, a low achievement in one dimension is not anymore linearly compensated for by high achievement in another dimension. The geometric mean reduces the level of substitutability between dimensions and at the same time ensures that a 1% decline in index of say life expectancy at birth has the same impact on the HDI as a 1% decline in education or income index. Thus, as a basis for comparisons of achievements, this method is also more respectful of the intrinsic differences across the dimensions than a simple average.

Income is instrumental to human development, but the contribution diminishes as incomes rise. GDP in the previous HDI was capped at $40,000 and was logarithmically transformed. The original HDI placed this cap on income to reflect the view that beyond some upper set amount, additional income does not expand human development opportunities. A further consideration was that while literacy rates and school enrolment and life expectancy have “natural” caps (100%, mortality limits, and so on forth), the highest incomes would continue rising, skewing the upper ranks of the HDI to increasingly income-driven values and rankings over time.

There are other reasons why the cap on income is lifted. First, countries were increasingly bunched at the cap. This meant that we could not distinguish among an increasing number of countries at the top of the distribution. In 2007, the GDP of 13 countries exceeded the cap. Thus, the discriminatory power of capped income has been weakened, especially for discrimination between the very high developed countries. Second, it was not originally intended to be binding in the sense of totally disregarding additional income beyond a particular level. For example, the income cap of PPP $40,000 was not binding on countries when it was introduced in the mid-1990s but rather was an upper bound used to normalize the income dimension index. Third, the use of geometric mean intensifies the diminishing returns of the logarithmic transformation of GNI compared to the arithmetic mean. Fourth, and very importantly, the use of real maximum values instead of caps allows the resulting dimensional indices to vary in similar ranges so that their implicit weights are more similar than had been the case under the previous method.

The new HDI uses the natural logarithm instead of the previously used logarithm with the base of 10. This minor change has no effect on the value of the income index and is motivated by the fact that most of the economic literature uses the natural logarithm of income. The caps in each dimension are lifted so one can say that they are equal to the observed maxima over the period (1980-2012) for which HDI trends are presented.

This is based on historical evidence (Maddison, 2010, and Riley, 2005), which indicates 20 years as the minimum. If a society or a subgroup of society has a life expectancy below the typical age of reproduction, that society would die out. Lower values have occurred during some crises, such as the Rwandan genocide, but these were exceptional cases that were not sustainable. See:

Maddison, A. 2010. Historical Statistics of World Economy: 1-2008 AD. Paris: Organization for Economic Cooperation and Development.

Riley, J.C. 2005. Poverty and Life Expectancy. Cambridge, UK: Cambridge University Press.

Noorkbakhsh (1998). The Human Development Index: Some Technical Issues and Alternative Indices. Journal of International Development 10, 589-605.

Generally, the minimum values are set to the values that a society needs to survive over time. For both education indicators, the minimum is set to 0 since societies can subsist without formal education. For income, it is set at $100 per capita GNI, which is lower than the lowest value attained by any country in recent history (Zimbabwe in 2008). The minimum values are essentially fixed. Should any country’s per capita GNI fall close to or below $100, the minimum will be changed accordingly.

The maximum values are observed over the period for which HDI trends are presented (from 1980), so while there might be year to year variation of the maximum values, the changes are not going to have any impact on ranks. This is because of the multiplicative form of the new HDI, which preserves the relative position of countries when maximum values change, although, the HDI values are affected by the choice of the normalizing parameters.

No, each year HDI trends are recalculated from 1980 based on consistent time series data and the new maximum values. In any case, the HDI is not meant to monitor progress in the short term—it takes time before policy interventions reflect on indicators such as mean years of schooling and life expectancy at birth. This is why HDI trends are provided in five-year intervals.

There are arguments for and against transforming the health and education variables to account for diminishing returns. It is true that health and education are not only of intrinsic value; they, like income, are instrumental to other dimensions of human development not included in the HDI (Sen, 1999). Thus, their ability to be converted into other ends may likewise incur diminishing returns. The approach is to value each year of age or education equally, and therefore the principle has been applied only to the income indicator.

The new HDI assigns equal weight to all three dimension indices; the two education sub-indices are also weighted equally. This is different from the previous HDI, which weighted them differentially. The choice of weights is based on the normative judgment that all three dimensions are equally important. Research papers that provide a statistical justification for this approach include Noorkbakhsh (1998) and Decanq and Lugo (2009). The new HDI has more equal ranges of variation of dimension indices than the previous one, implying that the effective weighting is more equal than it was before. See:

Decanq, K. and Lugo, M.A. 2009. Weights in Multidimensional Indices of Well-Being. OPHI working paper No. 18. (To appear in Economic Reviews)

As a simple summary index, the HDI is designed to reflect average achievements in three basic aspects of human development – leading a long and healthy life, being knowledgeable and enjoying a decent standard of living. The policy of the Human Development Report Office has always been to construct additional complementary composite indices for covering some of the “missing” dimensions in the HDI. Gender disparity, inequality and human deprivation are measured by other indices (see Gender Inequality Index, Multidimensional Poverty Index and Inequality-adjusted HDI). Participation and other aspects of well-being are measured using a range of objective and subjective indicators and are discussed in the Report. Measurement issues related to these aspects of human development demonstrate the conceptual and methodological challenges that need to be further addressed.

The changes in the indicators and method of aggregation have resulted in substantial changes for a number of countries. Adopting the geometric mean of aggregation produces lower index values for all countries because the extent to which a higher achievement in one dimension can compensate lower achievement in other dimensions is reduced. The average decline is about 7% with the largest changes occurring in countries with uneven achievement across dimensions.

The Human Development Report Office strives to include as many UN member countries as possible in the HDI. To include a country in the HDI we need recent, reliable and comparable data for all three dimensions of the Index. For a country to be included, statistics should ideally be available from the relevant international data agencies.

The HDI represents a national average of human development achievements in the three basic dimensions making up the HDI: health, education and income. Like all averages, it conceals disparities in human development across the population within the same country. Two countries with different distributions of achievements can have the same average HDI value. The IHDI takes into account not only the average achievements of a country on health, education and income, but also how those achievements are distributed among its citizens by “discounting” each dimension’s average value according to its level of inequality.

The average world loss in HDI due to inequality is about 23.3 %—ranging from 5.4% (Czech Republic) to 43.9% (Angola). People in sub-Saharan Africa suffer the largest losses due to inequality in all three dimensions, followed by South Asia and the Latin America and the Caribbean. Sub-Saharan Africa suffers the highest inequality in health (39%), while South Asia is impacted by unequal distribution in education (42%). Latin America and the Caribbean suffers the largest loss of any region due to inequality in income (38.5%).

Generally, countries in the low human development group also tend to have more multidimensional inequality and thus larger losses in human development due to inequality, while countries in the very high group experience the least inequality in human development. The East Asia and the Pacific Region performs well on the IHDI, particularly in access to healthcare and education, and former socialist countries in Europe and Central Asia have relatively egalitarian distributions across all three dimensions.

Although this is the third year that the IHDI has been calculated, the IHDI was not recalculated for previous years primarily due to the lack of time series data for inequality in education and income for a majority of countries.

The approach 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 the geometric mean of dimension indices adjusted for inequality. The inequality in each dimension is estimated by the Atkinson inequality measure, which is based on the assumption that a society has a certain level of aversion to inequality.

The IHDI relies on data on income/consumption and years of schooling from major publicly available databases, which contain national household surveys harmonized to common international standards: Eurostat’s EU Survey on Income and Living Conditions, Luxembourg Income Study, World Bank’s International Income Distribution Database, United Nations Children’s Fund’s Multiple Indicators Cluster Survey, US Agency for International Development’s Demographic and Health Survey, World Health Organization’s World Health Survey, and United Nations University’s World Income Inequality Database. For inequality in the health dimension, we used the abridged life tables from the United Nations Population Division.

The IHDI uses the HDI indicators that refer to 2012 and measures of inequality that are based on household surveys from 2002 to 2011 and life tables that refer to the 2010-2015 period. We therefore use the year to which the HDI indicators refer to, especially because we report the inequality-adjusted indicators/indices in tables.

The IHDI uses the HDI indicators that refer to 2012 and measures of inequality that are based on household surveys from 2002 to 2011 and life tables that refer to the 2010-2015 period. We therefore use the year to which the HDI indicators refer to, especially because we report the inequality-adjusted indicators/indices in tables.

The IHDI captures the inequality in distribution of the HDI dimensions. However, it is not association sensitive, meaning it does not account for overlapping inequalities—whether the same people experience the multiple deprivations. Also, the individual values of indicators such as income can be zero or even negative, so they have been adjusted to non-negative non-zero values uniformly across countries.

The IHDI allows a direct link to inequalities in dimensions of the HDI to the resulting loss in human development, and thus it can help inform policies towards inequality reduction and to evaluate the impact of various policy options aimed at inequality reduction.

The IHDI and its components can be useful as a guide to helping governments better understand the inequalities across populations and their contribution to the overall loss of inequality.

The IHDI in its current form was inspired by a similar index produced by Mexico’s National Human Development Report. The IHDI can be adapted to compare the inequalities in different subpopulations within a country, providing that the appropriate data is available. National teams can use proxy distributions for indicators, which may make more sense in their particular case.

The IHDI is one of three experimental indices introduced in 2010, alongside the Gender Inequality Index and the Multidimensional Poverty Index. It will evolve over time like all the other human development indices.

This is the most difficult aspect as life expectancy data are aggregate indicators. However, the inequality is estimated from the abridged life table (usually five-year age cohort) data and reflects the current inequality in mortality patterns—some people die under the age of one and others die at 75 or later. Undoubtedly, the quality of these estimates is no better than the data in the life table itself.

One of the key properties of the approach is that it is “subgroup consistent.” This means that if inequality declines in one subgroup and remains unchanged in the rest of population, then the overall inequality declines. The second important property is that the IHDI can be obtained by first computing inequality for each dimension and then across dimensions, which further implies that it can be computed by combining data from different sources.

The Gini index is commonly used as a measure of inequality of income, consumption or wealth. There was an attempt to apply the Gini index to measure multidimensional inequality (Hicks, 1998).

The choice of the Atkinson index was guided by three factors: (i) subgroup consistency, (ii) emphasis on the inequality in the lower end of distribution, and (iii) simplicity of computation and mathematical elegance of the resulting composite Inequality-adjusted Human Development Index.

(i)             Subgroup consistency means that if inequality declines in one subgroup (region, ethnic group, etc.) and remains unchanged in the rest of population, then the overall inequality declines. The Gini coefficient does not have this property.

(ii)            By its construction, the Gini coefficient puts equal weights to the entire distribution, while the Atkinson index puts more weight to the lower end, thus accounting better for child mortality, illiteracy, and income poverty.

Finally, the geometric form of the HDI in combination with the Atkinson index provides a simple and elegant path-independent composite IHDI, obtained by first computing inequality for each dimension and then across dimensions, which further implies that it can be computed by combining data from different sources (life tables and different surveys for education and income).

No. Due to data limitations, the IHDI does not capture all overlapping inequalities—whether the same person experiences one or multiple deprivations.

By their very nature, income and consumption yield different levels of inequalities, with income inequality being higher than inequality in consumption. Income seems to correspond more naturally to the notion of “command over resources.” Consumption data are arguably more accurate in developing countries, less skewed by high values, and directly reflect the conversion of resources. Income data also pose technical challenges because of the greater presence of zero and negative values. In an ideal world, one would be consistent in the use of either income or consumption data to estimate inequality. However, to obtain sufficient country coverage, it was necessary to use both. The final estimates are lightly influenced by whether the data are income or consumption.

Inequality in the education dimension is approximated only by inequality in years of schooling of the adult population. For simplicity, the estimate of inequality in education is based only on the distribution of years of schooling across the population, drawn from nationally representative household surveys.

Expected years of schooling is an aggregate measure and inequality in its distribution would be reflected in current school enrolment ratios. Certainly, there is a difference in inequalities in the two distributions, with the distribution of expected years of schooling across the school-age population being lower. Thus, one can speculate that overall inequality in the HDI distribution would be reduced if expected years of schooling were used.

Years of schooling of adults is mostly derived from the highest level of schooling achieved. Using UNESCO’s country information on the duration of schooling needed for each level, the highest level of schooling is converted into years. While the duration of primary, secondary and most of post-secondary education is more or less standardized, the very high levels—masters and doctoral studies—vary across countries. However, the Atkinson measure of inequality which is used to assess inequality in HDI education components is less sensitive to differences at the upper end of a distribution.

The Gender Inequality Index (GII) reflects women’s 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 human development due to inequality between female and male achievements in these dimensions. It ranges from 0, which indicates that women and men fare equally, to 1, which indicates that women fare as poorly as possible in all measured dimensions. The health dimension is measured by two indicators: maternal mortality ratio and the adolescent fertility rate. The empowerment dimension is also measured by two indicators: the share of parliamentary seats held by each sex and by secondary and higher education attainment levels. The labour dimension is measured by women’s participation in the work force. The Gender Inequality Index is designed to reveal the extent to which national achievements in these aspects of human development are eroded by gender inequality, and to provide empirical foundations for policy analysis and advocacy efforts.

There is no country with perfect gender equality – hence all countries suffer some loss in their HDI achievement when gender inequality is taken into account, through use of the GII metric. The Gender Inequality Index is similar in method to the Inequality-adjusted Human Development Index (IHDI). It can be interpreted as a percentage loss to potential human development due to shortfalls in the dimensions included. Since the Gender Inequality Index includes different dimensions than the HDI, it cannot be interpreted as a loss in HDI itself. Unlike the HDI, higher GII values indicate lower achievement.

The world average score on the GII is 0.463, reflecting a percentage loss in achievement across the three     dimensions due to gender inequality of 46.3%. Regional averages range from 28.0% in Europe and Central Asia, to nearly 58% in Sub-Saharan Africa. At the country level losses due to gender inequality range from 4.5% in the Netherlands, to 74.7% in Yemen. Sub-Saharan Africa, South Asia and the Arab States suffer the largest losses due to gender inequality (57.7%, 56.8% and 55.5% respectively).

The Gender Inequality Index faces major data limitations, which constrains the choice of indicators. For example, we use national parliamentary representation that excludes participation at the local government level and elsewhere in community and public life. The labour market dimension lacks information on incomes, employment and on unpaid work mostly done by women. The Index misses other important dimensions, such as time use – the fact that many women have the additional burden of care giving and housekeeping, which cut into leisure time and increase stress and physical exhaustion. Asset ownership, gender-based violence and participation in community decision-making are also not captured, mainly due to limited data availability.

The Gender Inequality Index relies on data from major publicly available databases, including the maternal mortality ratio from the United Nations Maternal Mortality Estimation Group (MMEIG), the WHO, UNICEF, UNFPA and the World Bank; adolescent fertility rates from the UN Department of Economic and Social Affair’s World Population Prospects; educational attainment statistics from the UNESCO Institute for Statistics educational attainment tables and the Barro-Lee data sets; parliamentary representation from the International Parliamentary Union; and labour market participation from the International Labour Organization’s Key Indicators of the Labour Market (KILM) 7^th Edition.

It is true that reproductive health indicators used in the Gender Inequality Index do not have equivalent indicators for men. So in this dimension, the reproductive health of girls and women is compared to what should be societal goals—no maternal death, and no adolescent pregnancy. The rationale is that safe motherhood reflects the importance society attaches to women’s reproductive role. Early childbearing, as measured by the adolescent fertility rate, is associated with greater health risks for mothers and infants; also, adolescent mothers often are forced out of school and into low-skilled jobs.

Only 3 out of 148 countries included in the GII have female shares of parliamentary seats equal to zero. We replaced the zero value with 0.1% to make the computation possible. The rationale is that while women may not be represented in parliament, they do have some political influence. The relative rank of these countries is sensitive to the choice of the replacement value. The lowest observed non-zero female parliamentary representation was 0.7% for Yemen.

No, there has been no change in calculation. As in 2011, maternal mortality ratio enters the Gender Inequality Index truncated at 10 which affects the range of Gender Inequality Index values which theoretically should be between 0 and 1. This is corrected by normalizing the maternal mortality ratio by 10. This intervention generally reduced the values of the Gender Inequality Index. To facilitate the comparison a trend of the Gender Inequality Index based on consistent time series data has been calculated.

The introduction in 1995 of the Gender-related Development Index (GDI) and the Gender Empowerment Measure (GEM) coincided with growing international recognition of the importance of monitoring progress in the elimination of gender gaps in all aspects of life. While the GDI and the GEM have contributed immensely to the gender debate, they have conceptual and methodological limitations. The Gender Inequality Index was introduced as an experimental index in 2010 as part of the 20^th anniversary edition of the Human Development Report. Just as the HDI continues to evolve, the Gender Inequality Index will also evolve as and when data becomes available.

The GDI was not a measure of gender inequality: it was the HDI adjusted for gender disparities in its basic components and cannot be interpreted independently of the HDI. The difference between the HDI and the GDI appears to be small because the differences captured in the three dimensions tend to be small, giving a misleading impression that gender gaps are irrelevant. In addition, gender-disaggregated incomes have to be estimated in a very crude way using not so realistic assumptions due to the lack of income data by gender for over three-fourths of countries.

Both the GDI and GEM combined relative and absolute achievements. The earned income component uses both—the income level and the gender-disaggregated income shares. However, income levels tend to dominate the indices, and as a result, countries with low income levels cannot achieve a high score even with perfect gender equality in the distribution of earnings and other components of the indices. Nearly all of the GEM indicators reflect an elite bias, making the measure more relevant for developed countries and urban areas in developing countries.

The Gender Inequality Index introduces methodological improvements and alternative indicators. It measures inequality between genders in three dimensions, with carefully chosen indicators to reflect women’s reproductive health status, their empowerment and labour market participation relative to men’s. The Gender Inequality Index combines elements of the GDI and the GEM. Income, the most controversial component of the GDI and GEM, is not a component of the Gender Inequality Index. Moreover, the new Index does not allow high achievement in one dimension to compensate for low achievement in another dimension.

The World Economic Forum’s Global Gender Gap Index (GGI), released on November 1, 2011, differs from the Human Development Report’s GII in many ways. First, the dimensions and indicators are different. Second, the GGI measures gender gaps without taking into consideration a country’s level of development. In contrast, the GII shows the loss to potential achievement in a country due to gender inequality across reproductive health, empowerment and labour market participation. The Economist Intelligence Unit’s Women’s Economic Opportunity Index (WEOI) is also different in that it focusses on laws and regulations about women’s participation in the labour market and social institutions that affect women’s economic participation. It has five dimensions – labour policies and practice, women’s economic opportunity, access to finance, education and training, women’s legal and social status, and general business environment. Each category or sub-category has four to five indicators. Like the OECD’s Social Institutions and Gender Index (SIGI), the WEOI complements the GII by helping us understand the underlying causes of gender inequalities in economic participation.

The Gender Inequality Index provides insights into gender disparities in health, empowerment and labour market in 148 countries. It can be useful to help governments and others understand the ramifications of gaps between women and men. The Gender Inequality Index, as any other global composite index, is constrained by the need for international comparability. But it could be readily adapted for use at the national or local level.

The Multidimensional Poverty Index (MPI) identifies multiple deprivations at the individual level in health, education 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. Each person in a given household is classified as poor or non-poor depending on the number of deprivations his or her household experiences. This data are then aggregated into the national measure of poverty.

The MPI reflects both the prevalence of multidimensional deprivation, and its intensity—how many deprivations people experience at the same time. It can be used to create a comprehensive picture of people living in poverty, and permits comparisons both across countries, regions and the world and within countries by ethnic group, urban or rural location, as well as other key household and community characteristics. The MPI builds on recent advances in theory and data to present the first global measure of its kind, and offers a valuable complement to income-based poverty measures. The 2013 Human Development Report (HDR) presents estimates for 104 countries with a combined population of 5.4 billion (76% of the world total). About 1.6 billion people in the countries covered—30% of their entire population—lived in multidimensional poverty between 2002 and 2011.

The MPI identifies overlapping deprivations at the household level across the same three dimensions as the Human Development Index (living standards, health, and education) and shows the average number of poor people and deprivations with which poor households contend. For details see Alkire and Santos (2010).

The MPI replaced the HPI, which was published from 1997 to 2009. Pioneering in its day, the HPI used country averages to reflect aggregate deprivations in health, education, and standard of living. It could not identify specific individuals, households or larger groups of people as jointly deprived. The MPI addresses this shortcoming by capturing how many people experience overlapping deprivations (prevalence) and how many deprivations they face on average (intensity). The MPI can be broken down by indicator to show how the composition of multidimensional poverty changes for different regions, ethnic groups and so on—with useful implications for policy.

One deprivation alone may not represent poverty. The MPI requires a household to be deprived in multiple indicators at the same time. A person is multidimensionally poor if the weighted indicators in which he or she is deprived add up to at least 33%.

We could not include income due to data constraints. Income poverty data come from different surveys, and these surveys often do not have information on health and nutrition. For most countries we are not able to identify whether the same people are income poor and also deprived in all the MPI indicators so could not include income.

We could not include empowerment due to data constraints. The Demographic and Health Surveys (DHS surveys) collect data on women’s’ empowerment for some countries, but not every DHS survey includes empowerment, and the other surveys do not have these data. Data on men’s empowerment or political freedom are missing.

The MPI relies on three main databases that are publicly available and comparable for most developing countries: the Demographic and Health Survey (DHS), the Multiple Indicators Cluster Survey (MICS), and the World Health Survey (WHS).  [See list of surveys included for the 2012 Estimation]

We could not include other countries due to data constraints. Comparable data on each of the indicators were not available for other developing nations. There was also a deliberate effort not to use data from surveys conducted earlier than 2002.

The MPI relies on the most recent and reliable data available since 2002. The difference in dates limits direct cross-country comparisons, as circumstances may have improved, or deteriorated, in the intervening years. This is the reason why we do not rank countries based on MPI value. This year we have grouped countries into two categories—those with estimates based in surveys conducted between 2007 and 2011 in one group and those 2002 to 2006 in another.

The MPI complements income poverty measures. It measures various deprivations directly. In practice, although there is a clear overall relationship between MPI and $1.25 per day poverty, the estimates do differ for many countries. This is a topic for further research, but some possibilities can include provision of public services, as well as different abilities to convert income into outcomes such as good nutrition.

The MPI, like the $1.25 per day line, is a globally comparable measure of poverty. It measures acute multidimensional poverty, and only includes indicators that are available for many countries. National poverty measures are typically monetary measures, and thus capture something different. The fact that there are differences does not mean that the national poverty number, or the MPI headcount is wrong—these simply measure different conceptions of poverty. At the same time, just as national poverty measures, in contrast, are designed to reflect the domestic situation more accurately and often differ in very useful ways from the $1.25 measure, some countries may wish to build a national multidimensional poverty index that is tailored to their context, to complement this international MPI.

No. The MPI is intended to complement monetary measures of poverty, including $1.25 per day estimates. The relationship between these measures, as well as their policy implications and methodological improvement, are priorities for further research.

The MPI methodology shows aspects in which the poor are deprived and help to reveal the interconnections among those deprivations. This enables policymakers to target resources and design policies more effectively. This is especially useful where the MPI reveals areas or groups characterized by severe deprivation. Examples where this has been done in practice include Mexico’s poverty-reduction program, as described in the 2011 Human Development Report.

The MPI reflects the severe deprivations that people face at the same time. Because it was designed to compare across developing nations, it is most relevant to lesser developed countries. We have described the MPI as a measure of “acute” poverty to avoid confusion with the World Bank’s measure of “extreme” poverty that captures those living on less than $1.25 a day.

The MPI constitutes a family or set of poverty measures. These measures can be unpacked to show the composition of poverty both across countries, regions and the world and within countries by ethnic group, urban/rural location, as well as other key household and community characteristics. This is why OPHI describes the MPI as a high resolution lens on poverty: it can be used as an analytical tool to identify the most prevailing deprivations. The MPI measures are explained below:

Incidence of poverty: the proportion of people who are poor according to the MPI (those who are deprived in at least 33.3% of the weighted indicators).

Average intensity of poverty: the average number of deprivations people experience at the same time.

MPI value: The MPI value summarizes information on multiple deprivations into a single number. It is calculated by multiplying the incidence of poverty by the average intensity of poverty.

The MPI indicators are drawn from the MDGs as far as the available internationally comparable data allow. The 10 indicators of the MPI are identical, or relate, to MDG indicators: nutrition (MDG 1), child mortality (MDG 4), access to drinking water (MDG 7), access to sanitation facility (MDG 7) and use of an improved source of cooking fuel (MDG 9). The overall MPI can be broken down into its constituent parts, revealing the overlapping needs of families and communities across a range of indicators which so often have been presented in isolation. This helps policymakers to see where challenges lie and what needs to be addressed.

The MPI has some drawbacks, due mainly to data constraints. First, the indicators include both outputs (such as years of schooling) and inputs (such as cooking fuel) as well as one stock indicator (child mortality, which could reflect a death that was recent or long ago), because data are not available for all dimensions. Second, the health data are relatively weak and overlook some groups’ deprivations especially for nutrition, though the patterns that emerge are plausible and familiar. Third, in some cases careful judgments were needed to address missing data. But to be considered multidimensionally poor, households must be deprived in at least six standard of living indicators or in three standard of living indicators and one health or education indicator. This requirement makes the MPI less sensitive to minor inaccuracies. Fourth, intra-household inequalities may be severe, but these could not be reflected. Fifth, while the MPI goes well beyond a headcount to include the intensity of poverty experienced, it does not measure inequality among the poor, although decompositions by group can be used to reveal group-based inequalities. Finally, the estimates presented here are based on publicly available data and cover various years between 2000 and 2010, which limits direct cross-country comparability.

The multidimensional poverty approach can be adapted using indicators and weights that make sense at the country level to create tailored national poverty measures. The MPI can be useful as a guide to helping governments tailor a poverty measure that reflects multiple local indicators and data. In 2009 Mexico, became the first country to adopt a multidimensional poverty measure reflecting multiple deprivations on the household level.

Yes. The global MPI estimates are constrained by need for comparability. National teams should use the indicators and weights that make sense. At the country level, however, the multidimensional poverty approach to assessing deprivations at the household level can be tailored using country-specific data and indicators to provide a richer picture of poverty at the country level.

Yes. The MPI methodology can and should be modified to generate national Multidimensional Poverty Measures that reflect local cultural, economic, climatic and other factors. The international MPI was devised as an analytical tool to compare acute poverty across nations.

We estimated the MPI over time and conducted trend analysis for a handful of countries for which suitable data are available for. For details see page 51 of Alkire and Santos (2010).

The effects of shocks are difficult to capture in any poverty measure. Because the standard survey data used to estimate the global measure are collected infrequently, the ability to detect changes is limited by the available data fed. The MPI will reflect the impacts of shocks as far as these cause children to leave primary education or to become malnourished, for example. If more frequent data are available at the country or local level, this can be used to seek to capture the effects of larger scale economic and other shocks.

The MPI is one of three new experimental series introduced in 2010, alongside the Inequality-adjusted Human Development Index and the Gender Inequality Index. It will evolve over time just like the other human development indices.

The GDI – Gender-related Development Index – is a composite indicator that measures the average achievement of a population in the same dimensions as the HDI while adjusting for gender inequalities in the level of achievement in the three basic aspects of human development. It uses the same variables as the HDI, disaggregated by gender. For details on how to calculate the GDI see  Technical note 1 HDR 2007/2008 [5 680 KB].

The GEM – Gender Empowerment Measure – is a composite indicator that captures gender inequality in three key areas:

• Political participation and decision-making, as measured by women’s and men’s percentage shares of parliamentary seats;
• Economic participation and decision-making power, as measured by two indicators – women’s and men’s percentage shares of positions as legislators, senior officials and managers and women’s and men’s percentage shares of professional and technical positions;
• Power over economic resources, as measured by women’s and men’s estimated earned income (PPP US$).

For details on how to calculate the GEM see  Technical note 1 HDR 2007/2008 [5 680 KB].

The GDI is not a measure of gender inequality. Rather, it is a measure of human development that adjusts the human development index (HDI) to penalize for disparities between women and men in the three dimensions of the HDI.
To illustrate the fact that gender empowerment does not depend on income, it is useful to compare relative rankings on the GEM and the relative level of national income. For example,

• In this year’s GEM, Slovakia ranks 32nd in the GEM, ahead of Japan, in 57th place, yet income per person in Slovakia is much lower than Japan's (20,076 PPP US$ vs. 33,632 PPP US$ for 2007).
• The Sweden and Canada have very similar income per person (36,712 PPP US$ and 35,812 PPP US$ for 2007) yet in the GEM Sweden ranks 1st and Canada 12th.

Both indicators can be disaggregated to highlight gender inequality within countries, which can vary widely across regions.

Poverty has traditionally been measured as a lack of income - but this is far too narrow a definition. Human poverty is a concept that captures the many dimensions of poverty that exist in both poor and rich countries—it is the denial of choices and opportunities for living a life one has reason to value. The HPI-1–Human Poverty Index for developing and transition countries – measures human deprivations in the same three aspects of human development as the HDI (long and healthy life, knowledge and a decent standard of living). HPI-2–Human Poverty Index for selected high-income OECD countries–includes, in addition to the three dimensions in HPI-1, social exclusion.

For HPI-1 (developing and transition countries), deprivation in health is measured by the probability at birth of not surviving to age 40; deprivation in knowledge is measured by the percentage of adults who are illiterate; deprivation in a decent standard of living is measured by two variables: the percentage of people not having sustainable access to an improved water source and the percentage of children below the age of five who are underweight. See:  Table I1 HDR 2009 [111 KB].

For HPI-2 (selected high-income OECD countries), deprivation in health is measured by the probability at birth of not surviving to age 60; deprivation in knowledge is measured by the percentage of adults lacking functional literacy skills; deprivation in a decent standard of living is measured by the percentage of people living below the income poverty line, set at 50% of the adjusted median household disposable income; and social exclusion is measured by the rate of long-term (12 months or more) unemployment of the labour force. See:  Table I1 HDR 2009 [111 KB].

For details on how to calculate the HPI-1 and HPI-2 see  Technical note 1 HDR 2007/2008 [5 680 KB].

To focus attention on the most deprived people and deprivations in basic human capabilities in a country, not on average national achievement. The human poverty indices focus directly on the number of people living in deprivation – presenting a very different picture from average national achievement. It also moves the focus of poverty debates away from concern about income poverty alone.

To highlight the presence of human poverty in both the rich and poor countries. High income per person is no guarantee of a poverty-free country. Even among the richest countries, there is human poverty. The latest human poverty index for OECD countries (HPI-2) shows that the human poverty levels of a country like the United States – where income per capita is amongst the top 5 in the category – is more than double that in Sweden, a country where income per capita represents only 80 percent of that of the United States.

To guide national planning for poverty alleviation. Many National Human Development Reports now break down the HPI by region or other socioeconomic groups to identify the areas or social groups within the country most deprived in terms of human poverty. The results can be dramatic, creating national debate and helping to reshape policies.

Lack of data is a particular constraint in monitoring gender disparity and poverty. Coverage of the GDI in HDR 2009 is limited to 155countries, GEM to 109 countries, and the HPI-1 to 135 developing and transition countries and HPI-2 to 25 high-income OECD countries (see also “Why isn’t HDI compiled for all UN member countries?”).