A Modeling Approach for Administrative Record Enumeration in the Decennial Census

Abstract

The use of administrative records-data collected by governmental agencies or commercial businesses in the course of administering a program or service-for household enumeration may be one way to significantly reduce Decennial Census costs, particularly in nonresponse follow-up (NRFU). Administrative records suffer the complications of big data in that they are collected for purposes not related to Census enumeration, yet contain a wealth of information relevant to Census enumeration. This paper describes a modeling approach to determine which administrative data are sufficiently reliable to proxy for a field response in a way that reduces costs and balances quality. Specifically, the approach is to (1) develop and assess models to determine characteristics of good-quality administrative records via a retrospective study of linked field and administrative data; and (2) choose a quality threshold, in a statistically defensible way, at which administrative records take the place of field responses. This paper presents empirical results illustrating the cost-quality trade-off of this approach applied to Census enumeration. We assess three classification techniques to further detail the cost-quality trade-off and allow flexibility in balancing predictive power and implementation complexity.