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 state dependence (or scarring). This paper investigates the extent of state dependence in India, distinguishing this from family-level risk factors common to siblings. It offers a number of methodological innovations upon previous research. Estimates are obtained for each of three Indian states, which exhibit dramatic differences in socio-economic and demographic variables. The results suggest a significant degree of state dependence in each of the three regions. Eliminating scarring, it is estimated, would reduce the incidence of infant mortality (among children born after the first child) by 9.8% in the state of Uttar Pradesh, 6.0% in West Bengal and 5.9% in Kerala.
death clustering infant mortality state dependence scarring unobserved heterogeneity dynamic random effects logit multi-level model India