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

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  • Garry 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. Employing hours of work in diaries collected by the American Time Use Survey, 2003-12, along with the same respondents’ recalled usual hours, we show that the latter yield elasticities that are positively biased. We argue that this bias arises from the salience on recalled hours of differences in wage rates.

Suggested Citation

  • Garry Barrett & Daniel S. Hamermesh, 2016. "Labor Supply Elasticities: Overcoming Nonclassical Measurement Error Using More Accurate Hours Data," NBER Working Papers 22920, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:22920
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    References listed on IDEAS

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    2. repec:hal:pseose:halshs-00943036 is not listed on IDEAS
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    Cited by:

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    2. 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.
    3. 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.
    4. 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).
    5. 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.
    6. 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).
    7. 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.
    8. Borjas, George J. & Hamermesh, Daniel S., 2023. "The Mismeasurement of Work Time: Implications for Wage Discrimination and Inequality," IZA Discussion Papers 16699, Institute of Labor Economics (IZA).
    9. Gibney, Victoria Hunter & West, Kristine L. & Gershenson, Seth, 2022. "Blurred Boundaries: A Day in the Life of a Teacher," IZA Discussion Papers 15548, Institute of Labor Economics (IZA).
    10. 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.
    11. 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.
    12. Gimenez-Nadal, José Ignacio & Sevilla, Almudena, 2022. "Work Effort in the UK: Trends and Explanations," IZA Discussion Papers 15329, Institute of Labor Economics (IZA).

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    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

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