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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
Journal of Human Resources, January 2019, 54 (1) 255-265; 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, School of Economics and a research fellow at IZA
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Daniel S. Hamermesh
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, 2003–2015, 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.

JEL Classification
  • J22
  • C21
  • Received December 2016.
  • Accepted June 2017.
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Journal of Human Resources: 54 (1)
Journal of Human Resources
Vol. 54, Issue 1
1 Jan 2019
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Labor Supply Elasticities
Garry F. Barrett, Daniel S. Hamermesh
Journal of Human Resources Jan 2019, 54 (1) 255-265; DOI: 10.3368/jhr.54.1.1216.8407R1

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Labor Supply Elasticities
Garry F. Barrett, Daniel S. Hamermesh
Journal of Human Resources Jan 2019, 54 (1) 255-265; DOI: 10.3368/jhr.54.1.1216.8407R1
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  • Article
    • Abstract
    • I. Introduction
    • II. Time-Use Data in the Estimation of Labor Supply
    • III. Nonclassical Measurement Error
    • IV. Conclusion
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Keywords

  • J22
  • C21
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