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at 4-digit at district level from Census of India for the years 2001 and 2011, which was also a period of high economic
growth. We derive motivation from the literature on localization, industrialization, and urbanization economies
which are deemed as drivers of employment growth. Occupational concentration is calculated with locational Gini
whose value varies from 0.08 to 0.50 across occupations. We model locational Gini as a function of requirement of
specialized knowledge, knowledge spillover, input sharing, interaction with public, and other occupation level
correlates. The first four variables are constructed using specific modules of O-NET database. We find that
specialized knowledge, a measure of labour market pooling, is positively associated with occupational
concentration. As robustness exercise, concerns over omitted variables and endogeneity are addressed by
instrumenting the variable specialized knowledge requirement. This paper contributes to the nascent literature by
studying concentration across occupations in a developing country. Apart from that, we establish the importance
of labour pooling as an important factor in explaining concentration of occupations.

1116 Growth, determinants and spatial distribution of Health Insurance/Schemes in
India (2005-2016)

Mohit Pandey, R. Nagrajan

International Institute for Population Science, Mumbai, India

Categories

11. Population and Economy: Demographic Dividend, Labor Market and Population Policies

Abstract

Health is an essential constituent of human resource development. Good health is the real wealth of society. Health
insurance is a method to finance healthcare; health insurance can help to reduce OOPE and CHE. We divided health
insurance into four parts Social health insurance, Private health insurance, Community health insurance,
Government-initiated health insurance schemes. This paper objective to assess the coverage of health
insurance/scheme in India according to NFHS-3 and NFHS-4 by Socio-economic and demographic characteristics,
also we want to analyze essential determinants of health insurance and we want to see spatial distribution. So as
mentioned this study has used NFHS-3 and NFHS-4; for this study, bivariate and multivariate analyses (binary logistic
regression) have been done. So in this study, we found that the Coverage of health insurance has increased from
NFHS-3(4.9) to NFHS-4(28.7); we found that in rural areas have a significant increase in health insurance in
comparison to urban. In some state like Andra Pradesh(3.4 to 70.5), Tamil Nadu(2.1 to 75.6) have significantly
increased due to state health insurance. When we analyze determinants of health insurance then we found that
residence, region, education, caste and wealth quantile are essential determinants.

349 Do Drivers of Labor Force Participation Differ according to Gender in the Rural
and Urban in India?

Wonbin Park, Amaresh Dubey
Jawaharlal Nehru University, Delhi, India