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Sibling Death Clustering in India: Genuine Scarring vs Unobserved Heterogeneity

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  • Wiji Arulampalam
  • Sonia Bhalotra

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Abstract

Data from a range of different environments indicate that the incidence of death is not randomly distributed across families but, rather, that there is a clustering of death amongst siblings. A natural explanation of this would be that there are (observed or unobserved) differences across families, for example in genetic frailty, education or living standards. Another hypothesis of considerable interest for both theory and policy is that there is a causal process whereby the death of a child influences the risk of death of the succeeding child in the family. Drawing language from the literature on the economics of unemployment, the causal effect is referred to here as scarring. This paper investigates the extent of scarring in India, distinguishing this from family-level risk factors common to siblings. It offers a number of methodological innovations upon previous research in the area. Estimates are obtained for each of three Indian states, which exhibit dramatic differences in socio-economic and demographic variables. The results suggest significant scarring in each of the three regions. Eliminating scarring, it is estimated, would reduce the infant mortality rate by 7% in the state of Uttar Pradesh, 3.1% in West Bengal and 2.9% in Kerala.

Suggested Citation

  • Wiji Arulampalam & Sonia Bhalotra, 2003. "Sibling Death Clustering in India: Genuine Scarring vs Unobserved Heterogeneity," Bristol Economics Discussion Papers 03/552, Department of Economics, University of Bristol, UK.
  • Handle: RePEc:bri:uobdis:03/552
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    File URL: http://www.efm.bris.ac.uk/economics/working_papers/pdffiles/dp03552.pdf
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    References listed on IDEAS

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    6. Dean R. Hyslop, 1999. "State Dependence, Serial Correlation and Heterogeneity in Intertemporal Labor Force Participation of Married Women," Econometrica, Econometric Society, vol. 67(6), pages 1255-1294, November.
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    Cited by:

    1. 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.
    2. Alok Bhargava & Sadia Chowdhury & K. K. Singh, 2006. "Healthcare infrastructure, contraceptive use and infant mortality in Uttar Pradesh, India," World Scientific Book Chapters,in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 23, pages 319-335 World Scientific Publishing Co. Pte. Ltd..
    3. Iyer, S. & Weeks, M., 2009. "Social Interactions, Ethnicity and Fertility in Kenya," Cambridge Working Papers in Economics 0903, Faculty of Economics, University of Cambridge.
    4. Wiji Arulampalam & Sonia Bhalotra, 2004. "Inequality in Infant Survival Rates in India: Identification of State-Dependence Effects," Bristol Economics Discussion Papers 04/558, Department of Economics, University of Bristol, UK.
    5. Bhalotra, Sonia, 2006. "Childhood Mortality and Economic Growth," WIDER Working Paper Series 079, World Institute for Development Economic Research (UNU-WIDER).
    6. Sonia Bhalotra & Arthur van Soest, 2004. "Birth Spacing and Neonatal Mortality in India: Dynamics, Frailty and Fecundity," Bristol Economics Discussion Papers 04/567, Department of Economics, University of Bristol, UK.
    7. Wiji Arulampalam & Mark B. Stewart, 2009. "Simplified Implementation of the Heckman Estimator of the Dynamic Probit Model and a Comparison with Alternative Estimators," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(5), pages 659-681, October.

    More about this item

    Keywords

    Death clustering; infant mortality; state dependence; scarring; unobserved heterogeneity; dynamic random effects logit (probit); India;

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • I1 - Health, Education, and Welfare - - Health
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development

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