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PNAS Paper-Future Ppulation and Hman Cpital in Hterogeneous India

Samir KC (first author), distinguished professor of Asian Demographic Research Institute (ADRI) in Shanghai University and the academician Wolfgang Lutz (common corresponding author), distinguished part-time professor of ADRI jointly published the paper Future population and human capital in heterogeneous India with Shanghai University as the first unit in PNAS.


As the journal of United States National Academy of Sciences, PNAS is one of the most famous scientific journals recognized by the world (such as Nature, Science and Cell). Its impact factor was 9.423 in 2015 and 10.285 in the last five years. Since founded in 1914, PNAS has published a large number of high-level scientific papers, academic reviews, review and prospect of discipline and reports on academic trends of United States National Academy of Sciences.


This paper focused on how the demography heterogeneity and population educational level affect the population dynamic in future India. It suggests that the dominant model of considering only the age and sex structures at the national level should be complemented by multidimensional models depending on the importance of heterogeneity and substantive user interest in the additional dimensions.


Within the next decade India is expected to surpass China as the world’s most populous country due to still higher fertility and a younger population. Around 2025 each country will be home to around 1.5 billion people. India is demographically very heterogeneous with some rural illiterate populations still having more than four children on average while educated urban women have fewer than 1.5 children and with great differences between states. Professor Samir KC et al. show that the population outlook greatly depends on the degree to which this heterogeneity is explicitly incorporated into the population projection model used. The conventional projection model, considering only the age and sex structures of the population at the national level, results in a lower projected population than the same model applied at the level of states because over time the high-fertility states gain more weight, thus applying the higher rates to more people. The opposite outcome results from an explicit consideration of education differentials because over time the proportion of more educated women with lower fertility increases, thus leading to lower predicted growth than in the conventional model. To comprehensively address this issue, we develop a five-dimensional model of India’s population by state, rural/urban place of residence, age, sex, and level of education and show the impacts of different degrees of aggregation. This paper also provides human capital scenarios for all Indian states that suggest that India will rapidly catch up with other more developed countries in Asia if the recent pace of education expansion is maintained.