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A tale of Work from Home in the aftermath of the Great Recession: Learning from high-frequency diaries

Author

Listed:
  • Arie Kapteyn

    (USC - University of Southern California)

  • Elena Stancanelli

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

This study contributes to the growing literature on Work from Home (WfH), focusing on the responsiveness of the phenomenon to the business cycle. In particular, the Great Recession led many states to implement unprecedented and expansionary unemployment benefit measures (Extended Benefit, EB), which were often revoked when the recession resumed. EB measures differ widely in generosity and timing across states. We exploit this, for identification purposes, by linking the interview date of the respondents to the American Time Use Survey (ATUS) to the dates of implementation of EB programs, in the respondent's state of residence. ATUS provides unique cross-sectional information on WfH for a representative sample of Americans. Taking an approach inspired by a Regression Discontinuity Design, we find that recessions, as proxied by EB expansionary measures, significantly increase women's commuting. In contrast, women's remote work increases with economic recovery, as captured by EB contractionary measures. The evidence for men is less clear-cut.

Suggested Citation

  • Arie Kapteyn & Elena Stancanelli, 2024. "A tale of Work from Home in the aftermath of the Great Recession: Learning from high-frequency diaries," PSE-Ecole d'économie de Paris (Postprint) halshs-04746449, HAL.
  • Handle: RePEc:hal:pseptp:halshs-04746449
    DOI: 10.1007/s11150-024-09725-6
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-04746449v1
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    References listed on IDEAS

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    1. David Card & Andrew Johnston & Pauline Leung & Alexandre Mas & Zhuan Pei, 2015. "The Effect of Unemployment Benefits on the Duration of Unemployment Insurance Receipt: New Evidence from a Regression Kink Design in Missouri, 2003-2013," American Economic Review, American Economic Association, vol. 105(5), pages 126-130, May.
    2. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    3. Alan I. Barreca & Melanie Guldi & Jason M. Lindo & Glen R. Waddell, 2011. "Saving Babies? Revisiting the effect of very low birth weight classification," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(4), pages 2117-2123.
    4. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs," Econometrica, Econometric Society, vol. 82, pages 2295-2326, November.
    5. Edward P. Lazear & Kathryn L. Shaw & Christopher Stanton, 2016. "Making Do with Less: Working Harder during Recessions," Journal of Labor Economics, University of Chicago Press, vol. 34(S1), pages 333-360.
    6. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Roc ́ıo Titiunik, 2017. "rdrobust: Software for regression-discontinuity designs," Stata Journal, StataCorp LLC, vol. 17(2), pages 372-404, June.
    7. David S. Lee & Thomas Lemieux, 2010. "Regression Discontinuity Designs in Economics," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 281-355, June.
    8. McCrary, Justin, 2008. "Manipulation of the running variable in the regression discontinuity design: A density test," Journal of Econometrics, Elsevier, vol. 142(2), pages 698-714, February.
    9. Dingel, Jonathan I. & Neiman, Brent, 2020. "How many jobs can be done at home?," Journal of Public Economics, Elsevier, vol. 189(C).
    10. Casey B. Mulligan, 2011. "Rising Labor Productivity during the 2008-9 Recession," NBER Working Papers 17584, National Bureau of Economic Research, Inc.
    11. Barrero, Jose Maria & Bloom, Nick & Davis, Steven J., 2020. "Why Working From Home Will Stick," SocArXiv wfdbe, Center for Open Science.
    12. Henry S. Farber, 2017. "Employment, Hours, and Earnings Consequences of Job Loss: US Evidence from the Displaced Workers Survey," Journal of Labor Economics, University of Chicago Press, vol. 35(S1), pages 235-272.
    13. Sabrina Wulff Pabilonia & Victoria Vernon, 2022. "Telework, Wages, and Time Use in the United States," Review of Economics of the Household, Springer, vol. 20(3), pages 687-734, September.
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