Hard to count: How survey and administrative records modeling can enhance census nonresponse followup 1

Abstract

Previous studies have shown that modeling based on administrative records can be predictive of Nonresponse Followup (NRFU) enumeration outcomes in U.S. Census Bureau Decennial data collection operations. We compare model predictive power when varying training data sources and evaluate the extent to which survey data can be used to reduce enumerator workload when combined with available administrative data. We perform the evaluation using the 2010 Census and the 2014 American Community Survey. Our main finding is that a large survey-based training dataset, such as the American Community Survey, can provide results comparable to Census data. Robustness checks then illustrate that even small sample survey-based training datasets can also yield comparable predictions. We also discuss a broader role for use of existing survey data in NRFU operations of statistical agencies outside of the United States when national Census or administrative data sources have only incomplete coverage of the population.