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Public Goods Access And Juvenile Sex Ratios In Rural India: Evidence From The 1991 And 2001 Village Census Data

Author

Listed:
  • Anil B. Deolalikar

    (Department of Economics, University of California Riverside)

  • Rana Hasan

    (Economics and Research Department, Asian Development Bank)

  • Rohini Somanathan

    (Delhi School of Economics, University of Delhi)

Abstract

We use village level data from the 1991 and 2001 Indian Censuses to examine how the availability of health facilities and safe drinking water at the village level affect juvenile sex ratios. In addition to controlling for village fixed effects in our estimating equation of the juvenile sex ratio, we also allow villages to be heterogeneous in terms of how their juvenile sex ratios respond to the availability of health facilities and safe drinking water. A key result we obtain is that although the presence of public health facilities does not exert a positive, significant effect on juvenile sex ratios on average, they do so in villages where the problem of discrimination against girls is most acute, i.e., in villages at the 0.10 and 0.25 quantiles of the conditional juvenile sex ratio distribution. Thus public policy can be an effective tool in improving gender balance in cases where it is most needed.  Â

Suggested Citation

  • Anil B. Deolalikar & Rana Hasan & Rohini Somanathan, 2009. "Public Goods Access And Juvenile Sex Ratios In Rural India: Evidence From The 1991 And 2001 Village Census Data," Working Papers 200911, University of California at Riverside, Department of Economics, revised Sep 2009.
  • Handle: RePEc:ucr:wpaper:200911
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    References listed on IDEAS

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    1. Becker, Gary S & Tomes, Nigel, 1976. "Child Endowments and the Quantity and Quality of Children," Journal of Political Economy, University of Chicago Press, vol. 84(4), pages 143-162, August.
    2. Rosenzweig, Mark R & Evenson, Robert E, 1977. "Fertility, Schooling, and the Economic Contribution of Children in Rural India: An Econometric Analysis," Econometrica, Econometric Society, vol. 45(5), pages 1065-1079, July.
    3. Alaka Malwade Basu, 1999. "Fertility Decline and Increasing Gender Imbalance in India, Including a Possible South Indian Turnaround," Development and Change, International Institute of Social Studies, vol. 30(2), pages 237-263, April.
    4. Buchinsky, Moshe, 1994. "Changes in the U.S. Wage Structure 1963-1987: Application of Quantile Regression," Econometrica, Econometric Society, vol. 62(2), pages 405-458, March.
    5. Eric R. Eide & Mark H. Showalter, 1999. "Factors Affecting the Transmission of Earnings across Generations: A Quantile Regression Approach," Journal of Human Resources, University of Wisconsin Press, vol. 34(2), pages 253-267.
    6. Buchinsky, Moshe, 1995. "Quantile regression, Box-Cox transformation model, and the U.S. wage structure, 1963-1987," Journal of Econometrics, Elsevier, vol. 65(1), pages 109-154, January.
    7. Chai Park, 1983. "Preference for Sons, Family Size, and Sex Ratio: An Empirical Study in Korea," Demography, Springer;Population Association of America (PAA), vol. 20(3), pages 333-352, August.
    8. Rosenzweig, Mark R & Wolpin, Kenneth I, 1986. "Evaluating the Effects of Optimally Distributed Public Programs: ChildHealth and Family Planning Interventions," American Economic Review, American Economic Association, vol. 76(3), pages 470-482, June.
    9. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    10. Jean Drèze & Mamta Murthi, 2001. "Fertility, Education, and Development: Evidence from India," Population and Development Review, The Population Council, Inc., vol. 27(1), pages 33-63, March.
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    Cited by:

    1. Nandi, Arindam & Deolalikar, Anil B., 2013. "Does a legal ban on sex-selective abortions improve child sex ratios? Evidence from a policy change in India," Journal of Development Economics, Elsevier, vol. 103(C), pages 216-228.

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    More about this item

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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