IDEAS home Printed from https://ideas.repec.org/p/tem/wpaper/1901.html
   My bibliography  Save this paper

Heterogeneous Effects of Job Displacement on Earnings

Author

Listed:
  • Afrouz Azadikhah Jahromi

    (Department of Economics, Temple University)

  • Brantly Callaway

    (Department of Economics, Temple University)

Abstract

This paper considers how the effect of job displacement varies across different individuals. In particular, our interest centers on features of the distribution of the individual-level effect of job displacement. Identifying features of this distribution is particularly challenging - e.g., even if we could randomly assign workers to be displaced or not, many of the parameters that we consider would not be point identified. We exploit our access to panel data, and our approach relies on comparing outcomes of displaced workers to outcomes the same workers would have experienced if they had not been displaced and if they maintained the same rank in the distribution of earnings as they had before they were displaced. Using data from the Displaced Workers Survey, we find that displaced workers earn about $157 per week less than they would have earned if they had not been displaced. We also find that there is substantial heterogeneity. We estimate that 42% of workers have higher earnings than they would have had if they had not been displaced and that a large fraction of workers have substantially lower earnings than the average effect of displacement. Finally, we also document major differences in the distribution of the effect of job displacement across education levels, sex, age, and counterfactual earnings levels. Throughout the paper, we rely heavily on quantile regression. First, we use quantile regression as a flexible (yet feasible) first step estimator of conditional distributions and quantile functions that our main results build on. We also use quantile regression to study how covariates affect the distribution of the individual-level effect of job displacement.

Suggested Citation

  • Afrouz Azadikhah Jahromi & Brantly Callaway, 2019. "Heterogeneous Effects of Job Displacement on Earnings," DETU Working Papers 1901, Department of Economics, Temple University.
  • Handle: RePEc:tem:wpaper:1901
    as

    Download full text from publisher

    File URL: http://www.cla.temple.edu/RePEc/documents/DETU_19_01.pdf
    File Function: First version, 2019
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Callaway, Brantly, 2021. "Bounds on distributional treatment effect parameters using panel data with an application on job displacement," Journal of Econometrics, Elsevier, vol. 222(2), pages 861-881.
    2. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, January.
    3. Jacobson, Louis S & LaLonde, Robert J & Sullivan, Daniel G, 1993. "Earnings Losses of Displaced Workers," American Economic Review, American Economic Association, vol. 83(4), pages 685-709, September.
    4. Christoph Rothe & Dominik Wied, 2013. "Misspecification Testing in a Class of Conditional Distributional Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(501), pages 314-324, March.
    5. Kenneth A. Couch & Dana W. Placzek, 2010. "Earnings Losses of Displaced Workers Revisited," American Economic Review, American Economic Association, vol. 100(1), pages 572-589, March.
    6. Markus Frölich & Blaise Melly, 2013. "Unconditional Quantile Treatment Effects Under Endogeneity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 346-357, July.
    7. Louis S. Jacobson & Robert J. LaLonde & Daniel G. Sullivan, 1993. "Long-term earnings losses of high-seniority displaced workers," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 17(Nov), pages 2-20.
    8. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 487-535.
    9. John M. Abowd & Francis Kramarz & David N. Margolis, 1999. "High Wage Workers and High Wage Firms," Econometrica, Econometric Society, vol. 67(2), pages 251-334, March.
    10. Neal, Derek, 1995. "Industry-Specific Human Capital: Evidence from Displaced Workers," Journal of Labor Economics, University of Chicago Press, vol. 13(4), pages 653-677, October.
    11. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
    12. Susan Athey & Guido W. Imbens, 2006. "Identification and Inference in Nonlinear Difference-in-Differences Models," Econometrica, Econometric Society, vol. 74(2), pages 431-497, March.
    13. Stéphane Bonhomme & Ulrich Sauder, 2011. "Recovering Distributions in Difference-in-Differences Models: A Comparison of Selective and Comprehensive Schooling," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 479-494, May.
    14. Abadie, Alberto, 2003. "Semiparametric instrumental variable estimation of treatment response models," Journal of Econometrics, Elsevier, vol. 113(2), pages 231-263, April.
    15. Brantly Callaway & Tong Li, 2019. "Quantile treatment effects in difference in differences models with panel data," Quantitative Economics, Econometric Society, vol. 10(4), pages 1579-1618, November.
    16. Henry S. Farber, 2005. "What do we know about job loss in the United States? evidence from the displaced workers survey, 1984-2004," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 29(Q II), pages 13-28.
    17. Marianne P. Bitler & Jonah B. Gelbach & Hilary W. Hoynes, 2017. "Can Variation in Subgroups' Average Treatment Effects Explain Treatment Effect Heterogeneity? Evidence from a Social Experiment," The Review of Economics and Statistics, MIT Press, vol. 99(4), pages 683-697, July.
    18. Sen, Amartya, 1997. "On Economic Inequality," OUP Catalogue, Oxford University Press, number 9780198292975.
    19. Fan, Yanqin & Park, Sang Soo, 2010. "Sharp Bounds On The Distribution Of Treatment Effects And Their Statistical Inference," Econometric Theory, Cambridge University Press, vol. 26(3), pages 931-951, June.
    20. 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.
    21. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    22. Ruhm, Christopher J, 1991. "Are Workers Permanently Scarred by Job Displacements?," American Economic Review, American Economic Association, vol. 81(1), pages 319-324, March.
    23. Henry S. Farber, 2005. "What do we know about Job Loss in the United States? Evidence from the Displaced Workers Survey, 1984-2004," Working Papers 877, Princeton University, Department of Economics, Industrial Relations Section..
    24. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    25. Lori G. Kletzer & Robert W. Fairlie, 2003. "The Long-Term Costs of Job Displacement for Young Adult Workers," ILR Review, Cornell University, ILR School, vol. 56(4), pages 682-698, July.
    26. Jovanovic, Boyan, 1979. "Job Matching and the Theory of Turnover," Journal of Political Economy, University of Chicago Press, vol. 87(5), pages 972-990, October.
    27. Henry S. Farber, 2005. "What do we know about Job Loss in the United States? Evidence from the Displaced Workers Survey, 1984-2004," Working Papers 877, Princeton University, Department of Economics, Industrial Relations Section..
    28. Topel, Robert H, 1991. "Specific Capital, Mobility, and Wages: Wages Rise with Job Seniority," Journal of Political Economy, University of Chicago Press, vol. 99(1), pages 145-176, February.
    29. William J. Carrington & Bruce Fallick, 2017. "Why Do Earnings Fall with Job Displacement?," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 56(4), pages 688-722, October.
    30. Stevens, Ann Huff, 1997. "Persistent Effects of Job Displacement: The Importance of Multiple Job Losses," Journal of Labor Economics, University of Chicago Press, vol. 15(1), pages 165-188, January.
    31. Fan, Yanqin & Guerre, Emmanuel & Zhu, Dongming, 2017. "Partial identification of functionals of the joint distribution of “potential outcomes”," Journal of Econometrics, Elsevier, vol. 197(1), pages 42-59.
    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. Bernd Fitzenberger & Roger Koenker & José Machado & Blaise Melly, 2022. "Economic applications of quantile regression 2.0," Empirical Economics, Springer, vol. 62(1), pages 1-6, January.
    2. Dan A. Black & Lars Skipper & Jeffrey A. Smith & Jeffrey Andrew Smith, 2023. "Firm Training," CESifo Working Paper Series 10268, CESifo.

    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. Callaway, Brantly, 2021. "Bounds on distributional treatment effect parameters using panel data with an application on job displacement," Journal of Econometrics, Elsevier, vol. 222(2), pages 861-881.
    2. Fackler, Daniel & Müller, Steffen & Stegmaier, Jens, 2017. "Explaining wage losses after job displacement: Employer size and lost firm rents," IWH Discussion Papers 32/2017, Halle Institute for Economic Research (IWH).
    3. Fujita, Shigeru, 2018. "Declining labor turnover and turbulence," Journal of Monetary Economics, Elsevier, vol. 99(C), pages 1-19.
    4. Cozzi, Marco & Fella, Giulio, 2016. "Job displacement risk and severance pay," Journal of Monetary Economics, Elsevier, vol. 84(C), pages 166-181.
    5. Fujii, Mayu & Shiraishi, Kousuke & Takayama, Noriyuki, 2018. "The effects of early job separation on later life outcomes," Journal of the Japanese and International Economies, Elsevier, vol. 48(C), pages 68-84.
    6. Simone Balestra & Uschi Backes-Gellner, 2017. "When a Door Closes, a Window Opens? Long-Term Labor Market Effects of Involuntary Separations," German Economic Review, Verein für Socialpolitik, vol. 18(1), pages 1-21, February.
    7. Jon Ellingsen & Caroline Espegren, 2022. "Lost in transition? Earnings losses of displaced petroleum workers," Working Papers No 06/2022, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    8. Philip Jung & Moritz Kuhn, 2019. "Earnings Losses and Labor Mobility Over the Life Cycle," Journal of the European Economic Association, European Economic Association, vol. 17(3), pages 678-724.
    9. Dickens William T. & Triest Robert K., 2012. "Potential Effects of the Great Recession on the U.S. Labor Market," The B.E. Journal of Macroeconomics, De Gruyter, vol. 12(3), pages 1-41, October.
    10. Ortego-Marti, Victor, 2017. "Loss of skill during unemployment and TFP differences across countries," European Economic Review, Elsevier, vol. 100(C), pages 215-235.
    11. Kevin F. Hallock, 2009. "Job Loss and the Fraying of the Implicit Employment Contract," Journal of Economic Perspectives, American Economic Association, vol. 23(4), pages 69-93, Fall.
    12. René Morissette & Hanqing Qiu & Ping Ching Winnie Chan, 2013. "The risk and cost of job loss in Canada, 1978–2008," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 46(4), pages 1480-1509, November.
    13. Krebs, Tom & Scheffel, Martin, 2019. "Optimal Social Insurance and Rising Labor Market Risk," IZA Discussion Papers 12128, Institute of Labor Economics (IZA).
    14. Andreas Gulyas & Krzysztof Pytka, 2019. "Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach," CRC TR 224 Discussion Paper Series crctr224_2019_131, University of Bonn and University of Mannheim, Germany.
    15. Cozzi, Marco & Fella, Giulio, 2016. "Job displacement risk and severance pay," Journal of Monetary Economics, Elsevier, vol. 84(C), pages 166-181.
    16. William J. Carrington & Bruce Fallick, 2017. "Why Do Earnings Fall with Job Displacement?," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 56(4), pages 688-722, October.
    17. Philip Ball, 2011. "Mixed Signals: to what extent does male wage scarring vary with the characteristics of the local labour market in which unemployment was experienced?," Discussion Papers 11/13, University of Nottingham, School of Economics.
    18. Ichino, Andrea & Schwerdt, Guido & Winter-Ebmer, Rudolf & Zweimüller, Josef, 2017. "Too old to work, too young to retire?," The Journal of the Economics of Ageing, Elsevier, vol. 9(C), pages 14-29.
    19. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    20. David H. Autor & David Dorn & Gordon H. Hanson & Jae Song, 2014. "Trade Adjustment: Worker-Level Evidence," The Quarterly Journal of Economics, Oxford University Press, vol. 129(4), pages 1799-1860.

    More about this item

    Keywords

    Job Displacement; Joint Distribution of Potential Outcomes; Distribution of the Treatment Effect; Quantile Regression; Heterogeneous Effects; Rank Invariance;
    All these keywords.

    JEL classification:

    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    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:tem:wpaper:1901. 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: Dimitrios Diamantaras (email available below). General contact details of provider: https://edirc.repec.org/data/edtemus.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.