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Research ArticleArticle

Labor Supply Elasticities: Overcoming Nonclassical Measurement Error Using More Accurate Hours Data

Garry F. Barrett and Daniel S. Hamermesh
Published online before print July 07, 2017, 1216-8407R1; DOI: https://doi.org/10.3368/jhr.54.1.1216.8407R1
Garry F. Barrett
*Garry Barrett is a professor of economics at the University of Sydney and a research fellow at IZA. Daniel Hamermesh is Distinguished Scholar at Barnard College, professor emeritus at the University of Texas at Austin and Royal Holloway, University of London, and research associate, IZA and NBER.
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Daniel S. Hamermesh
*Garry Barrett is a professor of economics at the University of Sydney and a research fellow at IZA. Daniel Hamermesh is Distinguished Scholar at Barnard College, professor emeritus at the University of Texas at Austin and Royal Holloway, University of London, and research associate, IZA and NBER.
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Abstract

We measure the impact of measurement error in labor-supply elasticities estimated over recalled usual work hours, as is ubiquitous in the literature. We employ data on hours of work in diaries collected by the American Time Use Survey, 2003-15, along with the same respondents’ recalled usual work hours. Estimates using the latter yield elasticities that are positively biased. We argue that this bias arises from the salient effects of differences in wage rates on recalled hours.

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Journal of Human Resources: 60 (3)
Journal of Human Resources
Vol. 60, Issue 3
1 May 2025
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Labor Supply Elasticities: Overcoming Nonclassical Measurement Error Using More Accurate Hours Data
Garry F. Barrett, Daniel S. Hamermesh
Journal of Human Resources Jul 2017, 1216-8407R1; DOI: 10.3368/jhr.54.1.1216.8407R1

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Labor Supply Elasticities: Overcoming Nonclassical Measurement Error Using More Accurate Hours Data
Garry F. Barrett, Daniel S. Hamermesh
Journal of Human Resources Jul 2017, 1216-8407R1; DOI: 10.3368/jhr.54.1.1216.8407R1
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