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Child mortality in rural India

Author

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  • Van der Klaauw, Bas
  • Limin Wang

Abstract

The authors focus on infant and child mortality in rural areas of India. They construct a flexible duration model framework that allows for frailty at multiple levels and interactions between the child's age and individual socioeconomic, and environmental characteristics. The model is estimated using the 1998-99 wave of the Indian National Family and Health Survey. The estimated results show that socioeconomic and environmental characteristics have significantly different effects on mortality rates at different ages. These are particularly important immediately after birth. The authors use the estimated model for policy experiments. These indicate that child mortality can be reduced substantially, particularly by improving the education of women and reducing indoor air pollution caused by cooking fuels. In addition, providing access to electricity and sanitation facilities can reduce under-five-years mortality rates significantly.

Suggested Citation

  • Van der Klaauw, Bas & Limin Wang, 2004. "Child mortality in rural India," Policy Research Working Paper Series 3281, The World Bank.
  • Handle: RePEc:wbk:wbrwps:3281
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    References listed on IDEAS

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    14. Bhalotra, Sonia & Soest, Arthur van, 2008. "Birth-spacing, fertility and neonatal mortality in India: Dynamics, frailty, and fecundity," Journal of Econometrics, Elsevier, vol. 143(2), pages 274-290, April.
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    Citations

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    Cited by:

    1. World Bank, 2007. "India - Achieving the Millennium Development Goals (MDG) in India's Poor States : Reducing Child Mortality in Orissa," World Bank Publications - Reports 7728, The World Bank Group.
    2. World Bank, 2004. "Stabilization and Fiscal Empowerment : The Twin Challenges Facing India's States, Volume 2. Detailed Report," World Bank Publications - Reports 16775, The World Bank Group.
    3. Kenneth Harttgen, 2007. "The Impact of HIV on Children´s Welfare," Ibero America Institute for Econ. Research (IAI) Discussion Papers 157, Ibero-America Institute for Economic Research.
    4. Pérez-Moreno, Salvador & Blanco-Arana, María C. & Bárcena-Martín, Elena, 2016. "Economic cycles and child mortality: A cross-national study of the least developed countries," Economics & Human Biology, Elsevier, vol. 22(C), pages 14-23.
    5. Federico Ciani & Gianna C. Giannelli, 2011. "Surviving the genocide: the impact of the Rwandan genocide on child mortality," Working Papers - Economics wp2011_19.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    6. G. Naline & Brinda Viswanathan, 2017. "Predictors of Age-Specific Childhood Mortality in India," Working Papers 2017-167, Madras School of Economics,Chennai,India.
    7. Thong Pham & Peter Kooreman & Ruud Koning & Doede Wiersma, 2013. "Gender patterns in Vietnam’s child mortality," Journal of Population Economics, Springer;European Society for Population Economics, vol. 26(1), pages 303-322, January.
    8. Kazuya Wada, 2011. "What Effect Does Female Autonomy Have on Child Health? Microeconometric Evidence from Rural India," Global COE Hi-Stat Discussion Paper Series gd11-202, Institute of Economic Research, Hitotsubashi University.
    9. Gebrehiwot , Tagel & Hassen, Sied, 2022. "Impact of Energy Access on Food Security and Child Nutrition: Panel Data Evidence from Rural Ethiopia," EfD Discussion Paper 22-11, Environment for Development, University of Gothenburg.
    10. Srivastava, Shobhit & Rashmi, & Paul, Ronak, 2021. "Urban-rural differential in neonatal and post-neonatal mortality clustering among Indian siblings: Evidence from National Family Health Survey 2015–16," Children and Youth Services Review, Elsevier, vol. 121(C).
    11. Marie-Claude Martin, 2008. "Individual and Collective Resources and Health in Morocco," WIDER Working Paper Series RP2008-21, World Institute for Development Economic Research (UNU-WIDER).

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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