Developing a Residence Candidate File for Use With Employer-Employee Matched Data
January 2017
Working Paper Number:
CES-17-40
Abstract
This paper describes the Longitudinal Employer-Household Dynamics (LEHD) program's ongoing efforts to use administrative records in a predictive model that describes residence locations for workers. This project was motivated by the discontinuation of a residence file produced elsewhere at the U.S. Census Bureau. The goal of the Residence Candidate File (RCF) process is to provide the LEHD Infrastructure Files with residence information that maintains currency with the changing state of administrative sources and represents uncertainty in location as a probability distribution. The discontinued file provided only a single residence per person/year, even when contributing administrative data may have contained multiple residences. This paper describes the motivation for the project, our methodology, the administrative data sources, the model estimation and validation results, and the file specifications. We find that the best prediction of the person-place model provides similar, but superior, accuracy compared with previous methods and performs well for workers in the LEHD jobs frame. We outline possibilities for further improvement in sources and modeling as well as recommendations on how to use the preference weights in downstream processing.
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:
estimating,
data,
employee,
employed,
job,
consolidated,
imputation,
department,
workforce,
worker,
housing,
residential,
employer household,
residence,
datasets,
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Center for Economic Studies,
Decennial Census,
Housing and Urban Development,
Postal Service,
Department of Housing and Urban Development,
American Community Survey,
Longitudinal Employer Household Dynamics,
Protected Identification Key,
Employment History File,
Employer Characteristics File,
Individual Characteristics File,
Department of Health and Human Services,
Quarterly Workforce Indicators,
NUMIDENT,
Composite Person Record,
Master Address File,
2010 Census,
Probability Density Function,
Indian Health Service,
PIKed,
MAFID,
Center for Administrative Records Research and Applications,
MAF-ARF,
HHS
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