Properties of Census Dual System Population Size Estimators

Abstract

We study parametric and non-parametric approaches for assessing the accuracy and coverage of a population census based on dual system surveys. The two parametric approaches being considered are post-stratification and logistic regression, which have been or will be implemented for the US Census dual system surveys. We show that the parametric model-based approaches are generally biased unless the model is correctly specified. We then study a local post-stratification approach based on a non-parametric kernel estimate of the Census enumeration functions. We illustrate that the non-parametric approach avoids the risk of model mis-specification and is consistent under relatively weak conditions. The performances of these estimators are evaluated numerically via simulation studies and an empirical analysis based on the 2000 US Census post-enumeration survey data. © 2011 The Authors. International Statistical Review © 2011 International Statistical Institute.