AN INVESTIGATION OF GENERALIZED RAKINGIN THE SYNTHETIC ESTIMATION OFPOPULATION SIZE

The problem of counting a population that is cross-classified with respect to demographic and geographic attributes is considered. A census is conducted in which individuals are “captured” with probabilities that are believed to be relatively constant within demographic categories. The census is followed by a random sample in which individuals are “recaptured” independently of the census. Using the two counts, capture-recapture estimates of the demographic category populations are obtained. A synthetic estimate of population size for a geographic entity is obtained by summing the corresponding adjustment factors (capture-recapture estimates divided by census counts) across all individuals captured by the census in the entity. The use of generalized raking is considered as a method for smoothing adjustment factors. It is found that generalized raking differs little from a class of weighted least squares regression models. This suggests that generalized raking does not offer an improvement over regression for smoothing adjustment factors. The efficiency loss of generalized raking relative to the best regression-based procedures can be substantial.