The Human Development Index (HDI) is a widely used summary measure of the level of development of countries. It improves on a simple ranking of GDP per capita or income per capita, because it takes into account health and education. Specifically, it is made up of four indicators: (1) life expectancy at birth; (2) mean years of schooling of adults (aged 25 years and over); (3) expected years of schooling of children aged 6 (which is based on current age-specific enrolment rates at each level of schooling); and (4) gross national income per capita (adjusted for purchasing power parity).
However, one of the problems with the HDI is that it aggregates across each country as a whole. If you want to know anything about the relative levels of development in rural and urban areas of a country, or coastal and landlocked areas, or between different states, the HDI doesn't provide much assistance. However, help is at hand. There is now a Subnational Human Development Index (SHDI) available, and published by the Global Data Lab. The SHDI covers 1625 regions in 161 countries going from 1990 to 2019. Interestingly, for New Zealand it provides index values for all 16 regions, which might be useful for research (because there seems to be a reasonable amount of variation both between regions and over time).
I was alerted to the SHDI's existence by this 2020 article by Inaki Permanyer (Centre d'Estudis Demogràfics) and Jeroen Smits (Radboud University), published in the journal Population and Development Review (ungated version here, and useful summary here). Permanyer and Smits use the SHDI to characterise changes global human development inequality since 2000, which marks a change from considering inequality purely in terms of income (or wealth). Here's the 2018 distribution of the index (Figure 1 from the paper):
Permanyer and Smits note that:
...one can observe clear geographic patterns within countries (e.g., north–south divides in Belgium, Germany, Italy, and Spain). Some countries exhibit large regional variations (e.g., China, India, or Colombia) while others are quite homogeneous (e.g., Australia). Very often, the region where the capital city is located exhibits the highest human development levels and remote rural regions the lowest.
Not all of those are visible in the figure of course, due to the scale. Then, looking at inequality as measured by the Gini coefficient, they find that:
...inequality in the global SHDI distribution has monotonically decreased from 0.14 in 2000 to 0.11 fifteen years later.
That's consistent with the overall trend observed in income (see here, for example). There are similar trends in the components of the SHDI (health, education, and income). However:
...we observe substantial differences in the magnitudes and speed of the decline. According to the Gini index, differences in the life expectancy index across world regions are smaller than differences in the education index.
Countries are converging much quicker in terms of health than in terms of either education or income. Looking at whether global inequality is mostly within or between countries, they show:
...the very high contribution of within country inequality to total inequality in the groups of countries at low- and intermediate levels of development (where as much as 70 percent of the world population lives). In these groups of countries, about half of inequality in SHDI is within-country inequality.
That is quite a different result from the analysis of Branko Milanovic, who showed that only 10-20 percent of global income inequality was within-country inequality (see this post). Permanyer and Smits explore their results a little further, finding that for the least developed countries:
...within-country SHDI inequality is mostly due to variation in education... In the high developed countries, standard of living surpasses education as the most important explanatory factor for within country SHDI variation...
So, if you only consider variation in per capita income, as Milanovic does, you potentially miss a large contributor to within-country inequality in the least developed countries, which is the variation in education.
All of this helps to paint a more complete picture of global inequality in living standards. Looking forward, if we want greater equality in human development, there clearly needs to be a greater focus on education in developing countries.
Read more:
- The great Chinese inequality turnaround?
- Several research articles on inequality
- Chinese growth and global inequality
- More evidence of declining global inequality
- Changing global inequality, migration and open borders
- The last two centuries of global inequality
- Inequality was similar, or higher, in ancient times than it is today
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