The Human Development Index (HDI) is a summary measure of human development. It measures the average achievements in a country in three basic dimensions of human development: a long and healthy life (health), access to knowledge (education) and a decent standard of living (income). Data availability determines HDI country coverage. To enable cross-country comparisons, the HDI is, to the extent possible, calculated based on data from leading international data agencies and other credible data sources available at the time of writing.
The 2011 HDI covers a record 187 countries and territories, 18 more than the 169 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. (For a full explanation of the results and methodology of the 2011 HDI and other indexes in the 2011 Human Development Report, please see the accompanying FAQs sheets on the 2011 HDI, IHDI, GII, and MPI.)
This year we have 18 more countries in the HDI table than were included in 2010, which accounts for a significant portion of changes in rank. A better performance of other competitors can explain some of the changes too. However, the most significant factor is the revisions to the indicators that were done by data providers this year that affected the HDI of many countries.
Because of the change in the number of countries with the HDI this year and because of data revisions done in 2010 and 2011, the HDI ranks from two reports are not comparable. That is why we advise users of the HDR 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. It is important to refer to Table 2 of the report when comparing rank and HDI value changes from one year to the next. The table is where HDRO presents trends in HDI using comparable 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 2010 and 2011.
|2011 HDI Rank|
|Antigua and Barbuda||60|
|Saint Kitts and Nevis||72|
|Saint Vincent and the Grenadines||85|
|Occupied Palestinian Territory||114|
Health (Life expectancy): The UN population division revised its life expectancy series in 2011, creating both increases and decreases for many countries.
Education (“Expected years of schooling” and “Mean years of schooling”): Because HDRO must rely on data from international institutions that provide data which are comparable across countries, the data contained in the 2011 Report may not match data from national surveys. Data for mean years of schooling (for the current adult population over 25) in the 2010 and 2011 HDI are based on national-level World Bank surveys over the past decade.
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 2010 and 2011. Each of these indicator series is updated or revised every year. For example, in 2010 there were no reported values for GNI for several countries for the year 2009. IMF projections were used instead. Some of these 2009 values became available in 2011 in the UN SNA Main Aggregates and were used for estimation of the 2011 GNI pc, see: http://data.un.org/Explorer.aspx?d=SNAAMA . Also in 2011 GNI is expressed in constant 2005 PPP$ while in 2010 it was expressed in constant 2008 PPP$. The different base years make these values incomparable directly.
The HDI remains a composite index that measures progress in the three basic dimensions—health, knowledge and income. Under the previous HDI formula, health was measured by life expectancy at birth; education or “knowledge” by a combination of the adult literacy rate and school enrolment rates (for primary through university years); and income or standard of living by GDP per capita adjusted for purchasing-power parity (PPP US$).
Health is still measured by life expectancy at birth. But the 2010 HDI measured achievement in knowledge 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.
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 (1980-2011) 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.
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 judgement 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)
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). However, the resulting index was not consistent for all subgroups. Moreover, the Gini index does not emphasize the lower part of the distribution, but instead places the same weight throughout the distribution.
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) – see Technical Note 3 for details. 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 0.492, reflecting a percentage loss in achievement across the three dimensions due to gender inequality of 49.2%. Regional averages range from 31% in Europe and Central Asia, to 61% in Sub-Saharan Africa. At the country level losses due to gender inequality range from 4.9% in Sweden, to 76.9% in Yemen. Sub-Saharan Africa, South Asia and the Arab States suffer the largest losses due to gender inequality (61%, 60.1% and 56.3% respectively). Regional patterns reveal that reproductive health is the largest contributor to gender inequality around the world – women in Sub-Saharan Africa, with a massive 73% loss, suffer the most in this dimension, followed by South Asia (65.9%) and the Arab States and Latin America and the Caribbean (each with 62.5% loss). The Arab States and South Asia are both also characterized by relatively weak female empowerment.
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 20th anniversary edition of the Human Development Report. Just as the HDI continues to evolve, the Gender Inequality Index will also be refined.
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 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 nonpoor depending on the number of deprivations his or her household experiences. These data are then aggregated into the national measure of poverty.
The MPI reflects both the incidence 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 2011 Human Development Report (HDR) presents estimates for 109 countries with a combined population of 5.5 billion (79% of the world total). About 1.7 billion people in the countries covered—a third of their entire population—lived in multidimensional poverty between 2000 and 2010.
As the 2011 Human Development Report states, 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 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.