How Low Can You Go? Validating Administrative Union Records for Substate Estimates of US Union Membership
Abstract
Unions are important economic and political actors at the local level, but the primary source on US union membership, the Current Population Survey (CPS), is unreliable below the state level. Researchers have therefore turned to union-reported membership in federal "LM" filings, geolocating unions and aggregating their reported membership to estimate union density for counties, commuting zones, and congressional districts. We ask whether this practice is sound. We develop and defend multilevel regression with poststratification (MrP) on the CPS as a benchmark, then validate LM-based estimates against it from the state level down. LM, CPS, and MrP are highly correlated at the state level, but this correlation is roughly halved at the congressional-district, commuting-zone, and county levels. The breakdown is driven in part by reporting "lumpiness," which produces improbable values, including union densities exceeding 100%. Missing public sector union members explains only a small part of this divergence. These issues are substantively consequential: in a standard commuting-zone "China shock" regression, swapping density measures changes the import-exposure coefficient enough to alter its magnitude, significance, and sign. We conclude that LM records remain a rich resource for studying unions as organizations, but aggregating LM-reported membership is not a reliable way to measure union density at fine geographic resolution.
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BibTeX
@misc{ahlquist2026validating,
title = {{How Low Can You Go? Validating Administrative Union Records for Substate Estimates of US Union Membership}},
author = {John S. Ahlquist and Eric Thai},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.06774},
eprint = {2610.06774},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.06774},
}
RIS
TY - UNPB
TI - How Low Can You Go? Validating Administrative Union Records for Substate Estimates of US Union Membership
AU - John S. Ahlquist
AU - Eric Thai
PY - 2026
DA - 2026/10/05
PB - arXiv
DO - 10.48550/arxiv.2610.06774
UR - https://arxiv.org/abs/2610.06774
AB - Unions are important economic and political actors at the local level, but the primary source on US union membership, the Current Population Survey (CPS), is unreliable below the state level. Researchers have therefore turned to union-reported membership in federal "LM" filings, geolocating unions and aggregating their reported membership to estimate union density for counties, commuting zones, and congressional districts. We ask whether this practice is sound. We develop and defend multilevel regression with poststratification (MrP) on the CPS as a benchmark, then validate LM-based estimates against it from the state level down. LM, CPS, and MrP are highly correlated at the state level, but this correlation is roughly halved at the congressional-district, commuting-zone, and county levels. The breakdown is driven in part by reporting "lumpiness," which produces improbable values, including union densities exceeding 100%. Missing public sector union members explains only a small part of this divergence. These issues are substantively consequential: in a standard commuting-zone "China shock" regression, swapping density measures changes the import-exposure coefficient enough to alter its magnitude, significance, and sign. We conclude that LM records remain a rich resource for studying unions as organizations, but aggregating LM-reported membership is not a reliable way to measure union density at fine geographic resolution.
ER -