The first Human Development Report introduced a new way of measuring development by combining indicators of life expectancy, educational attainment and income into a composite human development index, the HDI. The breakthrough for the HDI was the creation of a single statistic which was to serve as a frame of reference for both social and economic development. The HDI sets a minimum and a maximum for each dimension, called goalposts, and then shows where each country stands in relation to these goalposts, expressed as a value between 0 and 1.

The education component of the HDI is now measured by mean of years of schooling for adults aged 25 years and expected years of schooling for children of school entering age. Mean years of schooling is estimated based on educational attainment data from censuses and surveys available in the UNESCO Institute for Statistics database and Barro and Lee (2010) methodology). Expected years of schooling estimates are based on enrolment by age at all levels of education and population of official school age for each level of education. Expected years of schooling is capped at 18 years. The indicators are normalized using a minimum value of zero and maximum values are set to the actual observed maximum value of mean years of schooling from the countries in the time series, 1980–2010, that is 13.1 years estimated for Czech Republic in 2005. Expected years of schooling is maximized by its cap at 18 years. The education index is the geometric mean of two indices.
The life expectancy at birth component of the HDI is calculated using a minimum value of 20 years and maximum value of 83.4 years. This is the observed maximum value of the indicators from the countries in the time series, 1980–2010. Thus, the longevity component for a country where life expectancy birth is 55 years would be 0.552.
For the wealth component, the goalpost for minimum income is $100 (PPP) and the maximum is $107,721 (PPP), both estimated during the same period, 1980-2011.
The decent standard of living component is measured by GNI per capita (PPP$) instead of GDP per capita (PPP$) The HDI uses the logarithm of income, to reflect the diminishing importance of income with increasing GNI. The scores for the three HDI dimension indices are then aggregated into a composite index using geometric mean. Refer to the Human Development Report 2011
Technical notes [388 KB] for more details.
The HDI facilitates instructive comparisons of the experiences within and between different countries.
To learn more:
One way the use of the human development index has been improved is through disaggregation. A country's overall index can conceal the fact that different groups within the country have very different levels of human development. Disaggregated HDIs are arrived at by using the data for the HDI components pertaining to each of the separate groups; treating each group as if it was a separate country. Such groups may be defined relative to income, geographical or administrative regions, urban/rural residence, gender and ethnicity. Using disaggregated HDIs at the national and sub-national levels helps highlight the significant disparities and gaps: among regions, between the sexes, between urban and rural areas and among ethnic groups. The analysis made possible by the use of the disaggregated HDIs should help guide policy and action to address gaps and inequalities.
Disparities may already be well known, but the HDI can reveal them even more starkly. Disaggregation by social group or region can also enable local community groups to press for more resources as well as to force accountability on local representatives, making the HDI a tool for participatory development.
Disaggregated HDIs have been used extensively for analysis since their inception, including: Brazil, Colombia, Egypt, Gabon, Germany, India, Kazakhstan, Malaysia, Mexico, Nigeria, Papua New Guinea, Poland, South Africa, Trinidad and Tobago, Turkey, Ukraine and USA. Recent National Human Development Reports in China and Kenya found wide provincial and urban/rural disparities while a similar study in Guatemala has shown that those disparities apply to ethnic groups as well.
For the Human Development Report 2006, an HDI
disaggregated by income groups was calculated for 13 developing countries along
with the United States and Finland. The
study highlights the differences in human development between different income
groups within the same country. Among the results, it was found that the
richest 20% of the population in Bolivia had an HDI rank 97
positions higher than the poorest 20%. Likewise, in South Africa the top quintile ranks
101 positions above the lowest. Furthermore, the top quintile in the United States
has an HDI value that exceeds all other countries for which the statistic was
computed, while the poorest quintile ranks 49 positions lower. For more details
on the methodology and a complete set of results see the 2006 Report technical note 2
HDI by income group HDR 2006 [88 KB] and Grimm and others 2006
A Human development index by income groups HDR 2006 [326 KB].
To reflect country-specific priorities and problems and to be more sensitive to a country's level of development, the HDI appearing in the global HDRs can be tailored so that additional components are included in the calculation. HDI adjustments should utilize the methods of weighting and normalization as the original HDI, making use of maximum and minimum values to create an index for the added component. In addition, indicator-specific weights can be tailored such that they reflect national policy priorities.
Additional adjustments to the HDI could involve expanding the breadth of existing component indices. For example, the life expectancy category could be adjusted to reflect under-five or maternal mortality rates; the income component could be adjusted to reflect unemployment, incidence of income poverty or the Gini-corrected mean national income; and finally the educational component can be adjusted to include the number of students enrolled in particularly important fields of study, such as the mathematics and sciences.
It is difficult to use the HDI to monitor changes in human development in the short-term because two of its components, namely life expectancy and mean years of schooling change slowly. To address this limitation, components that are more sensitive to short-term changes could be added to the national HDI. For example, the rate of employment, the percent of population with access to health services, or the daily caloric intake as a percentage of recommended intake could be used in place of the traditional indicators of the HDI.
Thus, the usefulness and versatility of the HDI as an analytical tool for HD at the national and sub-national levels would be enhanced if countries choose components that reflect their priorities and problems and are sensitive to their development levels, rather than rigidly using the three components presented in the HDI of the global HDRs.
As previously mentioned, when adjusting the HDI to reflect additional concerns, a commitment to data integrity and rigorous attention to statistical protocol should always be a concern of paramount importance.
National wealth has the potential to expand people's choices. However, it may not. The manner in which countries spend their wealth, not the wealth itself, is decisive. Moreover, an excessive obsession with the creation of material wealth can obscure the ultimate objective of enriching human lives. In many instances, countries with higher average incomes have higher average life expectancies, lower rates of infant and child mortality and higher educational attainment and school enrollment, and consequently a higher human development index (HDI). But these associations are far from perfect. In inter-country comparisons, income variations tend to explain not much more than half the variation in life expectancy, or in infant and child mortality. And they explain an even smaller part of the differences in adult educational attainment.
Although there is a definite correlation between material wealth and human well-being, it breaks down in far too many societies. Many countries have high GNI per capita, but low human development indicators and vice versa. While some countries at similar levels of GNI per capita have vastly different levels of human development. See the State of Human Development in HDR 2006 for a discussion
State of Human Development HDR 2006 [557 KB].
Given the imperfect nature of wealth as gauge of human development, the HDI offers a powerful alternative to GNI for measuring the relative socio-economic progress at national and sub-national levels. Comparing HDI and per capita income ranks of countries, regions or ethnic groups within countries highlights the relationship between their material wealth on the one hand and their human development on the other. A negative gap implies the potential of redirecting resources to Human Development.
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 | ||
| Palau | 49 | |
| Cuba | 51 | |
| Seychelles | 52 | |
| Antigua and Barbuda | 60 | |
| Grenada | 67 | |
| Lebanon | 71 | |
| Saint Kitts and Nevis | 72 | |
| Dominica | 81 | |
| Saint Lucia | 82 | |
| Saint Vincent and the Grenadines | 85 | |
| Oman | 89 | |
| Samoa | 99 | |
| Occupied Palestinian Territory | 114 | |
| Kiribati | 122 | |
| Vanuatu | 125 | |
| Iraq | 132 | |
| Bhutan | 141 | |
| Eritrea | 177 |
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)