IDEAS home Printed from https://ideas.repec.org/p/ucr/wpaper/202017.html
   My bibliography  Save this paper

What Time Use Surveys Can (And Cannot) Tell Us About Labor Supply

Author

Listed:
  • Cheng Chou

    (University of Leicester)

  • Ruoyao Shi

    (Department of Economics, University of California Riverside)

Abstract

The American Time Use Survey (ATUS) accurately measures hours worked on a single day. Employing the potential outcome framework, we show that weekly labor supply parameters can be consistently estimated using the ATUS daily hours, but recovering weekly hours or their distribution is impossible due to the time specificity problem. We propose and carefully examine the properties of several new estimators. We recommend the impute estimator, a simple modification of the 2SLS estimator by imputing the dependent variable using daily subsamples. We apply it to the ATUS and find substantially different elasticity estimates from the CPS, especially for married women.

Suggested Citation

  • Cheng Chou & Ruoyao Shi, 2019. "What Time Use Surveys Can (And Cannot) Tell Us About Labor Supply," Working Papers 202017, University of California at Riverside, Department of Economics, revised Jul 2020.
    • Handle: RePEc:ucr:wpaper:202017
    as

    Download full text from publisher

    File URL: https://economics.ucr.edu/repec/ucr/wpaper/202017.pdf
    File Function: First version, 2019
    Download Restriction: no
    File URL: https://economics.ucr.edu/repec/ucr/wpaper/202017R.pdf
    File Function: Revised version, 2020
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Francine D. Blau & Lawrence M. Kahn, 2007. "Changes in the Labor Supply Behavior of Married Women: 1980–2000," Journal of Labor Economics, University of Chicago Press, vol. 25(3), pages 393-438.
    2. John Bound & Charles Brown & Greg J. Duncan & Willard L. Rodgers, 1989. "Measurement Error In Cross-Sectional and Longitudinal Labor Market Surveys: Results From Two Validation Studies," NBER Working Papers 2884, National Bureau of Economic Research, Inc.
    3. Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, January.
    4. Harley Frazis & Jay Stewart, 2012. "How to Think about Time-Use Data: What Inferences Can We Make about Long- and Short-Run Time Use from Time Diaries?," Annals of Economics and Statistics, GENES, issue 105-106, pages 231-245.
    5. Blundell, Richard & Macurdy, Thomas, 1999. "Labor supply: A review of alternative approaches," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 27, pages 1559-1695, Elsevier.
    6. 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.
    7. Paul J. Devereux, 2004. "Changes in Relative Wages and Family Labor Supply," Journal of Human Resources, University of Wisconsin Press, vol. 39(3).
    8. Mark Aguiar & Mark Bils & Kerwin Kofi Charles & Erik Hurst, 2021. "Leisure Luxuries and the Labor Supply of Young Men," Journal of Political Economy, University of Chicago Press, vol. 129(2), pages 337-382.
    9. Angrist, Joshua D., 1991. "Grouped-data estimation and testing in simple labor-supply models," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 243-266, February.
    10. Brzozowski, Matthew & Crossley, Thomas F. & Winter, Joachim K., 2017. "A comparison of recall and diary food expenditure data," Food Policy, Elsevier, vol. 72(C), pages 53-61.
    11. Xiaohong Chen & Han Hong & Elie Tamer, 2005. "Measurement Error Models with Auxiliary Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(2), pages 343-366.
    12. Duncan, Greg J & Hill, Daniel H, 1985. "An Investigation of the Extent and Consequences of Measurement Error in Labor-Economic Survey Data," Journal of Labor Economics, University of Chicago Press, vol. 3(4), pages 508-532, October.
    13. Mark Aguiar & Erik Hurst, 2007. "Measuring Trends in Leisure: The Allocation of Time Over Five Decades," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(3), pages 969-1006.
    14. repec:adr:anecst:y:1999:i:55-56:p:09 is not listed on IDEAS
    15. repec:adr:anecst:y:2012:i:105-106:p:11 is not listed on IDEAS
    16. Jason Abrevaya & Jerry A. Hausman, 1999. "Semiparametric Estimation with Mismeasured Dependent Variables: An Application to Duration Models for Unemployment Spells," Annals of Economics and Statistics, GENES, issue 55-56, pages 243-275.
    17. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    18. Cheng Chou & Ruoyao Shi, 2019. "What Time Use Surveys Can (And Cannot) Tell Us About Labor Supply," Working Papers 202017, University of California at Riverside, Department of Economics, revised Jul 2020.
    19. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    20. Mark Aguiar & Erik Hurst & Loukas Karabarbounis, 2012. "Recent Developments in the Economics of Time Use," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 373-397, July.
    21. Jonathan Guryan & Erik Hurst & Melissa Kearney, 2008. "Parental Education and Parental Time with Children," Journal of Economic Perspectives, American Economic Association, vol. 22(3), pages 23-46, Summer.
    22. Claudia Goldin, 2014. "A Grand Gender Convergence: Its Last Chapter," American Economic Review, American Economic Association, vol. 104(4), pages 1091-1119, April.
    23. 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.
    24. Juhn, Chinhui & Murphy, Kevin M, 1997. "Wage Inequality and Family Labor Supply," Journal of Labor Economics, University of Chicago Press, vol. 15(1), pages 72-97, January.
    25. Hu, Yingyao & Sasaki, Yuya, 2017. "Identification Of Paired Nonseparable Measurement Error Models," Econometric Theory, Cambridge University Press, vol. 33(4), pages 955-979, August.
    26. Heckman, James J, 1993. "What Has Been Learned about Labor Supply in the Past Twenty Years?," American Economic Review, American Economic Association, vol. 83(2), pages 116-121, May.
    27. Daniel S. Hamermesh & Harley Frazis & Jay Stewart, 2005. "Data Watch: The American Time Use Survey," Journal of Economic Perspectives, American Economic Association, vol. 19(1), pages 221-232, Winter.
    28. Naeem Ahmed & Matthew Brzozowski & Thomas Crossley, 2006. "Measurement errors in recall food consumption data," IFS Working Papers W06/21, Institute for Fiscal Studies.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Thomas Le Barbanchon & Johannes F. Schmieder & Andrea Weber, 2024. "Job Search, Unemployment Insurance, and Active Labor Market Policies," NBER Working Papers 32720, National Bureau of Economic Research, Inc.
    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. Cheng Chou & Ruoyao Shi, 2019. "What Time Use Surveys Can (And Cannot) Tell Us About Labor Supply," Working Papers 202017, University of California at Riverside, Department of Economics, revised Jul 2020.
    4. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. 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.
    4. Francine D. Blau & Lawrence M. Kahn, 2007. "Changes in the Labor Supply Behavior of Married Women: 1980–2000," Journal of Labor Economics, University of Chicago Press, vol. 25(3), pages 393-438.
    5. René Morissette & Feng Hou, 2008. "Does the labour supply of wives respond to husbands' wages? Canadian evidence from micro data and grouped data," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(4), pages 1185-1210, November.
    6. Anil Kumar, 2016. "Lifecycle-consistent female labor supply with nonlinear taxes: evidence from unobserved effects panel data models with censoring, selection and endogeneity," Review of Economics of the Household, Springer, vol. 14(1), pages 207-229, March.
    7. Stevenson, Adam, 2012. "The Labor Supply and Tax Revenue Consequences of Federal Same-Sex Marriage Legalization," National Tax Journal, National Tax Association;National Tax Journal, vol. 65(4), pages 783-806, December.
    8. Aguiar, M. & Hurst, E., 2016. "The Macroeconomics of Time Allocation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 203-253, Elsevier.
    9. Claudia Olivetti & Barbara Petrongolo, 2016. "The Evolution of Gender Gaps in Industrialized Countries," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 405-434, October.
    10. Juliane Hennecke, 2020. "Locus of Control and Female Labor Force Participation," Working Papers 2020-03, Auckland University of Technology, Department of Economics.
    11. Gutknecht, Daniel, 2011. "Nonclassical Measurement Error in a Nonlinear (Duration) Model," Economic Research Papers 270763, University of Warwick - Department of Economics.
    12. Zhu, Mengbing & Xing, Chunbing & Li, Yi, 2023. "Husbands' wages and married women's labor supply in urban China," China Economic Review, Elsevier, vol. 82(C).
    13. Hu, Yingyao, 2017. "The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics," Journal of Econometrics, Elsevier, vol. 200(2), pages 154-168.
    14. Jorge Gonz�lez, 2015. "Estimating income elasticities of leisure activities using cross-sectional categorized data," Documentos de Trabajo dt2015-02, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
    15. González Chapela, Jorge, 2014. "Some estimates for income elasticities of leisure activities in the United States," MPRA Paper 57303, University Library of Munich, Germany.
    16. Lin, Zhongjian & Hu, Yingyao, 2024. "Binary choice with misclassification and social interactions, with an application to peer effects in attitude," Journal of Econometrics, Elsevier, vol. 238(1).
    17. J. Ignacio Gimenez-Nadal & José Alberto Molina & Yu Zhu, 2018. "Intergenerational mobility of housework time in the United Kingdom," Review of Economics of the Household, Springer, vol. 16(4), pages 911-937, December.
    18. Olivier Bargain & Andreas Peichl, 2016. "Own-wage labor supply elasticities: variation across time and estimation methods," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-31, December.
    19. Raj Chetty & Adam Guren & Day Manoli & Andrea Weber, 2013. "Does Indivisible Labor Explain the Difference between Micro and Macro Elasticities? A Meta-Analysis of Extensive Margin Elasticities," NBER Macroeconomics Annual, University of Chicago Press, vol. 27(1), pages 1-56.

    More about this item

    Keywords

    labor supply; time specificity; impute estimator; relative asymptotic efficiency; survey methods;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ucr:wpaper:202017. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Kelvin Mac (email available below). General contact details of provider: https://edirc.repec.org/data/deucrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.