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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.

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Bibliographic Info

Paper provided by Department of Economics, University of Bristol, UK in its series Bristol Economics Discussion Papers with number 03/552.

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Length: 41 pages
Date of creation: 19 Jun 2003
Date of revision:
Handle: RePEc:bri:uobdis:03/552

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

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References

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  1. Bolstad W. M & Manda S. O, 2001. "Investigating Child Mortality in Malawi Using Family and Community Random Effects: A Bayesian Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 12-19, March.
  2. Bhargava, Alok, 2003. "Family planning, gender differences and infant mortality: evidence from Uttar Pradesh, India," Journal of Econometrics, Elsevier, vol. 112(1), pages 225-240, January.
  3. Williamson, Jeffrey G., 1988. "Migration and urbanization," Handbook of Development Economics, in: Hollis Chenery & T.N. Srinivasan (ed.), Handbook of Development Economics, edition 1, volume 1, chapter 11, pages 425-465 Elsevier.
  4. Jane Miller & James Trussell & Anne Pebley & Barbara Vaughan, 1992. "Birth spacing and child mortality in bangladesh and the Philippines," Demography, Springer, vol. 29(2), pages 305-318, May.
  5. Narendranathan, W. & Elias, P., 1990. "Influences of Past History on the Incidence of Youth Unemployment: Empirical Finding for the U.K," The Warwick Economics Research Paper Series (TWERPS) 369, University of Warwick, Department of Economics.
  6. Bob Baulch & John Hoddinott, 2000. "Economic mobility and poverty dynamics in developing countries," Journal of Development Studies, Taylor & Francis Journals, vol. 36(6), pages 1-24.
  7. DaVanzo, J. & Pebley, A.R., 1993. "Maternal Depletion and Child Survival in Guatemala and Malaysia," Papers 93-18, RAND - Labor and Population Program.
  8. 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.
  9. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
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Cited by:
  1. Bhalotra, Sonia, 2006. "Childhood Mortality and Economic Growth," Working Paper Series RP2006/79, World Institute for Development Economic Research (UNU-WIDER).
  2. 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.
  3. 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.
  4. Arulampalam, Wiji & Stewart, Mark, 2007. "Simplified Implementation of the Heckman Estimator of the Dynamic Probit Model and a Comparison with Alternative Estimators," IZA Discussion Papers 3039, Institute for the Study of Labor (IZA).
  5. Sonia Bhalotra & Arthur van Soest, 2007. "Birth Spacing, Fertility and Neonatal Mortality in India:Dynamics, Frailty and Fecundity," The Centre for Market and Public Organisation 07/168, Department of Economics, University of Bristol, UK.
  6. Bhargava, Alok & Chowdhury, Sadia & Singh, K.K., 2005. "Healthcare infrastructure, contraceptive use and infant mortality in Uttar Pradesh, India," Economics & Human Biology, Elsevier, vol. 3(3), pages 388-404, December.
  7. Iyer, S. & Weeks, M., 2009. "Social Interactions, Ethnicity and Fertility in Kenya," Cambridge Working Papers in Economics 0903, Faculty of Economics, University of Cambridge.

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