An Empirical Evaluation of the Use of Administrative Records to Predict Census Day Residency

Administrative records (AR) databases offer the prospect of reduced respondent burden and substantial cost savings in census taking and are promising for identifying people missed in the census. However, available AR databases have not yet been shown to be sufficient for strict enumeration purposes, mainly because of the lack of synchronicity between census day and the dates that data enter into the AR files. An important unsolved problem in using AR data is determining which correspond to people actually resident on census day. This paper uses a hierarchical model developed by Stuart and Zaslavsky (2001, 2002) to predict census day residency by modeling migration and observation in the record systems. There are two innovative features to the model: it is at an individual level, and uses all data available, including record dates and covariate information. In this application, we use data from the Statistical Administrative Records System, a simulated “administrative records census,” to make block-level total population estimates. We illustrate by comparing estimates to Census 2000.