A few days back I wrote a post claiming that “for all the work that goes into the Human Development Index, it just doesn’t tell you much that you wouldn’t learn from simple comparisons of G.D.P. per capita.” Subsequently, Francisco Rodriguez, who heads research at the UN Human Development Report Office, touched base to tell me that he thought I hadn’t told the whole story. Francisco is a terrific macroeconomist (in fact, he was the TA when I took my graduate macro classes at Harvard), and so he kindly agreed to write a guest post filling in the missing pieces.
What Does the Human Development Index Really Measure?
By Francisco Rodriguez
A Guest Post
Last week, Justin Wolfers presented a simple yet apparently powerful critique of the Human Development Index (H.D.I.) — a summary index of per-capita income, health, and education indicators published by the United Nations Development Programme. The correlation between the rank of H.D.I. and that given by G.D.P. is 0.95, and a scatterplot of one against the other looks like a 45 degree line plus measurement error. Justin’s critique is not new, and neither is my response. Indeed, the literature on the links between human development and per-capita income is quite vast, including the entire 1996 Human Development Report.
The criticism that Justin levies at the H.D.I. is based on the high correlation between the rank of the H.D.I. and the rank of G.D.P. If you think that development economics is purely about ranking countries, then Justin is right; both indicators do give similar comparisons.
But we care about human development not just because we want to know how to rank countries. Rankings may be a good way to compare NCAA teams or American Idol contestants, but are not necessarily the best way to think about differences in living standards across countries. For example, a cross-sectional rank correlation cannot tell you much about two key issues that have been the focus of much of the cross-country macro development literature: understanding what drives improvements over time in well-being and understanding how inequality across countries has evolved.
On both of these questions, the H.D.I. and G.D.P. give considerably different answers.
Consider first changes over time. Improvements over time in human development differ significantly from growth rates of per-capita income. The figure below shows the relationship between the growth rate of per-capita income and the change in H.D.I.; the correlation is 0.43. The correlation between changes in the non-income components of H.D.I. and the growth rate of G.D.P. is 0.03. That is, the information contained in changes in health and education appears to be very different from that contained in changes in income.
These differences between the H.D.I. and G.D.P. suggest some very different priorities.
For example, suppose we run two regressions: one to try to explain changes over time in per-capita income, and another to explain changes in H.D.I. Let’s use the same exact set of independent variables, which come from the list of usual suspects from the growth literature: initial values of income, schooling and life expectancy, and current values of openness, inflation, and the rule of law.
Here’s what we find: inflation is negatively and significantly related to changes in H.D.I. but not to growth. Trade openness and the rule of law are positively and significantly related to G.D.P. growth but not with H.D.I.; in fact, openness gets a negative though insignificant coefficient in the H.D.I. regression. In other words, the implications of cross-country regressions for development policy depend crucially on whether you are interested in raising G.D.P. growth or in increasing the H.D.I.
Alternatively, let’s think about international disparities in living standards. Researchers have tried to sort out whether inequality across countries is increasing or decreasing. As the figure below illustrates, while cross-country dispersion in (log) income per capita has been increasing, dispersion in H.D.I.’s has been declining. Again, looking at H.D.I. and looking at per-capita income gives substantively different answers.
Research carried out at the Human Development Report Office over the past 20 years has been devoted to understanding how different national and sub-national policies can make a difference to the expansion of individuals’ substantive freedoms to lead the lives they value. Covering topics as diverse as gender inequality, cultural liberty, and climate change, our reports have often found that the best policies for enlarging people’s choices are not necessarily the best ones for raising per-capita incomes. These results are of course contestable and should be debated. But this is a discussion that we could not even begin to have were it not for the concept of human development.