Combining forward and backward mortality estimation

Demographers often form estimates by combining information from two data sources-a challenging problem when one or both data sources are incomplete. A classic example entails the construction of death probabilities, which requires death counts for the subpopulations under study and corresponding base population estimates. Approaches typically entail 'back projection', as in Wrigley and Schofield's seminal analysis of historical English data, or 'inverse' or 'forward projection' as used by Lee in his important reanalysis of that work, both published in the 1980s. Our paper shows how forward and backward approaches can be optimally combined, using a generalized method of moments (GMM) framework. We apply the method to the estimation of death probabilities for relatively small subpopulations within the United States (men born 1930-39 by state of birth by birth cohort by race), combining data from vital statistics records and census samples

Algorithm · Census · Econometrics · Economics · Estimation · Population · Population projection · Projection (relational algebra) · Research methodology · Sociology · Statistics · Birth, Development, and Health · Computer Science · Demography · Health disparities and outcomes · Insurance, Mortality, Demography, Risk Management · Mathematics

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