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. We 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. We also provide 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.
| Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:6459 |
| Date | January 2018 |
| Creators | KC, Samir, Wurzer, Marcus, Speringer, Markus, Lutz, Wolfgang |
| Publisher | The National Academies of Sciences, Engineering, and Medicine |
| Source Sets | Wirtschaftsuniversität Wien |
| Language | English |
| Detected Language | English |
| Type | Article, PeerReviewed |
| Format | application/pdf, application/pdf |
| Rights | Creative Commons: Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) |
| Relation | https://doi.org/10.1073/pnas.1722359115, http://www.nasonline.org/, http://www.pnas.org/lookup/suppl/doi:10.1073/pnas.1722359115/-/DCSupplemental, http://www.pnas.org/, http://epub.wu.ac.at/6459/ |
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