HDI

Areas of Relatively High Human Development in Greater South Asia

Today’s post continues the GeoCurrents series on the Human Development Index (HDI), focusing initially on greater South Asia. Here we look at areas with relatively high HDI figures.

For decades, the region’s highest human development levels have been found in the far south and southwest, specifically in the Indian states of Kerala and Goa and in Sri Lanka. All invested heavily in health and education, reaping substantial rewards. For decades, Kerala was well ahead of the rest of India, especially in female literacy. This patterns partly reflects the region’s social structure, which has long been less male dominated than most of the rest of India.

Sri Lanka has also long outpaced other parts of South Asia, but its edge has been steadily slipping. In 1990, Sri Lanka posted an HDI figure of .629, substantially ahead of Goa’s .552 and Kerala’s .544, and well ahead of Tamil Nadu’s .471. By 2019, Sri Lanka has advanced to .782, but it was now behind Kerala’s .790 and just ahead of Goa’s .761. At the time, Tamil Nadu’s HDI figure had surged to .708. Give Sri Lanka’s current political crisis and economic meltdown, it would not be surprising to see Tamil Nadu and several other Indian states overtake it in the next few years.

 

 

In northern India, the adjacent states of Punjab and Haryana, along with the National Capital Territory of New Delhi, exhibit relatively high HDI numbers, and have done so for decades. These two states are at the center of India’s agricultural “green revolution,” and are the site of substantial agro-industrial economic growth. Although neither Punjab nor Haryana top of the list agricultural production by Indian state, their relative productivity becomes apparent when population is factored in (see the chart posted here). These two states were also the hub of the massive 2020-2021 farmer protest movement that roiled India and caused its government to backtrack on planned prom-market agricultural reforms.

 

 

The neighboring state of Himachal Pradesh also exhibits a relatively high HDI figure, but the factors behind its development are distinctive. Whereas Punjab and Haryana are lowland states with fertile soils, Himachal Pradesh is a land of rugged topography, located in the Himalayan mountains and foothills. Its developmental ascent, moreover, has been much more recent. Through the 1960s, its indicators remained relatively low. A World Bank report credits its transformation on effective and non-corrupt political leadership, female empowerment, and mass electrification based on hydropower. Intriguingly, the population of Himachal Pradesh is overwhelmingly rural, with the state posting one of India’s lowest urbanization rates. In general, both in India and the world at large, low urbanization correlates with low social and economic development. This seeming paradox has received relatively little attention, and as a result it will be the subject of a future GeoCurrents post.

 

 

Higher than average HDI figures are posted across greater southwestern India. This large region has been the site of most of India’s recent industrial and financial expansion. As the next map shows, it is also contains almost all of India’s major tech hubs.

 

 

 

 

 

A far different situation is found in India’s far northeastern periphery. This is another rugged area that was long noted for its relative isolation, poorly developed infrastructure, and numerous ethnic insurgencies. Yet its human development indicators are now well above the average for the country. Many of the so-called tribal peoples of this region converted from animism to Christianity under the influence of missionaries during the colonial period, and three of its states (Nagaland, Mizoram, and Meghalaya) now have solid Christian (mostly Protestant) majorities. Missionaries stressed education, resulting in mass literacy. Women also have a relatively high social position in these societies, which are more culturally related to those of Southeast Asia than they are to those of South Asia. Recent infrastructural initiatives by the Indian and local governments, especially in electrification and road construction, have significantly improved economic conditions.

 

In neighboring Burma, several rugged and so-called tribal regions with Christian majorities or large minorities also post higher than expected HDI figures.

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The Human Development Index (HDI) in the State-Based and Demic Frameworks

World Map of Human Development Index, Demic FrameworkThe Human Development Index (HDI) is the most widely used method of assessing the overall level of human wellbeing across the planet. Today’s post examines HDI rankings in the demic and state-based frameworks. As is the case in regard to GDP measurements, the demic map portrays broad regional patterns of development relatively well, while missing a number of local particularities captured by the conventional map. But the state-based framework also misses local distinctions, those found at the sub-national level.

State-based Map of the Human Development Index The HDI is composite statistic that takes into account longevity, educational attainment, and standard of living. The calculations used to construct the index are involved, as several separate measurements and sub-indexes are employed.* Whether the results adequately reflect “human development” is an open issue; like all other social indexes, the HDI has notable limitations and omissions. It treats “standard of living,” for example, as reducible to per capita GDP (PPP), which is simply not the case. The HDI also ignores gender equity and environmental cleanliness, which many observers regard as significant aspects of wellbeing. But all told, the HDI is still the most comprehensive and widely used measurement of human development, and therefore deserves extended consideration.

Map Comparing HDI and GDP, State-Based Framework In general, global HDI maps track GDP maps relatively closely, as can be seen in the pair of state-based maps to the left. Wealthy countries, not surprisingly, tend to have high HDI numbers, whereas poor countries generally post low numbers.  Exception to this general rule can be instructive. On the quantile-based maps posted here, some oil-rich countries (Qatar, Equatorial Guinea) end up in significantly lower color categories in regard to HDI than they do in regard to GDP, reflecting the unbalanced nature of their development. A number of other countries, ranging from Kenya to Cambodia to Cuba to North Korea, on the other hand, fall into higher categories on the HDI map, reflecting in part successful educational programs. North Korea’s elevated HDI position, however, may point to statistical shortcomings and perhaps governmental manipulation of the data; certainly if a “malnutrition and food insecurity” component were added to the index, the position of North Korea would drop sharply.

As the demic HDI map posted above shows, exceptional areas also appear at the sub-national level. The most strikingly of such distinctions is found in southern South Asia. The region composed of Sri Lanka, the Maldives, and the Indian states of Tamil Nadu and Kerala ranks much higher in terms of human development than it does in regard to GDP. Sri Lanka and Kerala have long been noted for near universal literacy and impressive levels of public health, achievements realized despite meager economic resources. More recently, Tamil Nadu has made rapid progress in these same areas. Whereas in strictly economic terms, western India has the advantage, in terms of overall social development, southern India comes out ahead. North-central India, in contrast, lags well back in both domains.

In terms of human development, China appears much better off on the demic map than on the state-based map. As expected, coastal China scores higher than the rest of the country, but even the poorest interior regions come out relatively well.  Note that the region composed of Shanghai and Jiangsu falls into the highest color category on this map. But the position of China on the two HDI maps also reveals a problem with the underlying data. All regions of China fall into higher color categories on the demic map than China as a whole does on the state-based map. As the two maps apply the same numerical ranges to the same color categories, such results are a statistically impossible.** What this seeming error indicates is that data collected at the state and the sub-state levels are not necessarily comparable.

In global terms, the most important take-home message from the demic HDI map is the low standing of tropical Africa. Whereas virtually all parts of tropical Africa fall into the bottom two color categories, only one region outside of Africa does the same, that composed of Nepal and the Indian state of Bihar. The state-based map also captures the low level of human development in tropical Africa, but not so clearly. In terms of health and education, much of tropical Africa posts figures lower than what might be expected on the basis of per capita GDP. The HIV epidemic plays a significant role here, as does under-investment in education.

Finally, the demic HDI map reveals an unexpected pattern in Latin America. In the GDP maps, the region composed of Colombia, Venezuela, Panama, Costa Rica and Ecuador comes out ahead of its neighbor to the south, the region composed largely of northern Brazil, Peru, Bolivia, and Paraguay. On the HDI map, the positions are reversed. As the state-based map shows, the relatively high position of Peru in human development is a significant factor here. Intriguingly, Peru’s new government is emphasizing human development, arguing that the previous administration put economic growth above broader developmental considerations.

* In 2010, the UN revised its method of calculating HDI, broadening the educational sub-index. The current post uses the earlier for of the index, as new figures for most sub-national entities are not yet available.

** If anything, the average HDI figures for the demic regions of China should be slightly lower than the figure for China as a whole, as the Chinese provincial data used to make the demic map are from 2008 (the most recent we could find), whereas the figure for China as a whole is from 2009. As China posts slight developmental improvement annually, the overall figure for 2009 should be slightly higher than that from 2008.

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