Decision Rules for Field Effort Reduction in the Decennial Census

Thomas M. Menino Convention & Exhibition Center 

The Decennial Census is the largest peacetime mobilization in the United States, including a field operation that requires hundreds of thousands of enumerators that knock on doors of housing units who have not self-responded to the Census. This nonresponse follow-up (NRFU) operation is very costly. In order to control NRFU-related data collection costs and reduce contact burden on the US population, the Census uses internally-held administrative data (AD) to identify housing units that can be enumerated with in-house data, reducing the need for repeated enumerator follow-ups.

A data quality-driven approach to using these AD to enumerate NRFU-eligible housing units could reduce the overall cost of the NRFU operation, while allowing enumerators to focus on cases with unavailable or poor quality AD. The 2026 Census Test will incorporate a decision rules framework to determine which housing units could accurately and sufficiently be enumerated using administrative records, reducing the need for NRFU contact attempts on these cases.

This talk will include a discussion of the overall decision rules framework, the component models, and select simulation results.

adaptive and responsive design

data quality

survey costs

predictive models

bayesian methods 

Survey Research Methods Section