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

Author

Listed:
  • Garry F. Barrett
  • Daniel S. Hamermesh

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.

Suggested Citation

  • Garry F. Barrett & Daniel S. Hamermesh, 2019. "Labor Supply Elasticities: Overcoming Nonclassical Measurement Error Using More Accurate Hours Data," Journal of Human Resources, University of Wisconsin Press, vol. 54(1), pages 255-265.
    • Handle: RePEc:uwp:jhriss:v:54:y:2019:i:1:p:255-265
    Note: DOI: 10.3368/jhr.54.1.1216.8407R1
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    File URL: http://jhr.uwpress.org/cgi/reprint/54/1/255
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    Cited by:

    1. Borjas, George J. & Edo, Anthony, 2021. "Gender, Selection into Employment, and the Wage Impact of Immigration," IZA Discussion Papers 14261, IZA Network @ LISER.
    2. Daniel S. Hamermesh & Katie R. Genadek & Michael C. Burda, 2021. "Racial/Ethnic Differences in Non-Work at Work," ILR Review, Cornell University, ILR School, vol. 74(2), pages 272-292, March.
    3. Cheng Chou & Ruoyao Shi, 2020. "Utilizing Two Types of Survey Data to Enhance the Accuracy of Labor Supply Elasticity Estimation," Working Papers 202018, University of California at Riverside, Department of Economics.
    4. Loukas Karabarbounis & Jeremy Lise & Anusha Nath, 2022. "Minimum Wages and Labor Markets in the Twin Cities," NBER Working Papers 30239, National Bureau of Economic Research, Inc.
    5. Song, Jia & Cheng, Terence C., 2020. "How do gender differences in family responsibilities affect doctors' labour supply? Evidence from Australian panel data," Social Science & Medicine, Elsevier, vol. 265(C).
    6. Cheng Chou & Ruoyao Shi, 2021. "What time use surveys can (and cannot) tell us about labor supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 917-937, November.
    7. Coniglio, Nicola D. & Hoxhaj, Rezart & Jayet, Hubert, 2019. "On the road to integration? Immigrant’s demand for informal (& formal) education," GLO Discussion Paper Series 389, Global Labor Organization (GLO).
    8. Lusi Liao & Sasiwimon Warunsiri Paweenawat, 2021. "The inversion of married women's labour supply and wage: Evidence from Thailand," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 35(1), pages 82-98, May.
    9. Borjas, George J. & Hamermesh, Daniel S., 2023. "The Mismeasurement of Work Time: Implications for Wage Discrimination and Inequality," IZA Discussion Papers 16699, IZA Network @ LISER.
    10. Gibney, Victoria Hunter & West, Kristine L. & Gershenson, Seth, 2022. "Blurred Boundaries: A Day in the Life of a Teacher," IZA Discussion Papers 15548, IZA Network @ LISER.
    11. Heath,Rachel & Mansuri,Ghazala & Rijkers,Bob & Seitz,William Hutchins & Sharma,Dhiraj, 2020. "Measuring Employment : Experimental Evidence from Urban Ghana," Policy Research Working Paper Series 9263, The World Bank.
    12. Lusi Liao & Sasiwimon Warunsiri Paweenawat, 2018. "Labour Supply of Married Women in Thailand: 1985–2016," PIER Discussion Papers 88, Puey Ungphakorn Institute for Economic Research.
    13. Gimenez-Nadal, José Ignacio & Sevilla, Almudena, 2022. "Work Effort in the UK: Trends and Explanations," IZA Discussion Papers 15329, IZA Network @ LISER.

    More about this item

    JEL classification:

    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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