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Match Effects

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Abstract

We present an empirical model of earnings that controls for observable and unobservable characteristics of workers (person effects), unmeasured characteristics of their employers (firm effects), and unmeasured characteristics of worker-firm matches (match effects). The distinction between these components is important, because they have different implications for the persistence of individual earnings and the returns to employment mobility. We find that match effects, which have been ignored in previous work, are an important determinant of log earnings. They explain about 16 percent of observed variation, and much of the change in earnings when workers change employer. Specifications that omit match effects over-estimate the returns to experience by as much as 30 percent, attribute too much variation to person effects and little to firm effects, and underestimate the correlation between person and firm effects. Overall, our results suggest that some of the returns previously attributed to general human capital actually reflect the returns to sorting into higher-paying firms and better worker-firm matches.

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  • Simon D. Woodcock, 2007. "Match Effects," Discussion Papers dp07-13, Department of Economics, Simon Fraser University.
  • Handle: RePEc:sfu:sfudps:dp07-13
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    Cited by:

    1. Davidson, Carl & Heyman, Fredrik & Matusz, Steven & Sjöholm, Fredrik & Zhu, Susan Chun, 2014. "Globalization and imperfect labor market sorting," Journal of International Economics, Elsevier, vol. 94(2), pages 177-194.
    2. Klein, Michael W. & Moser, Christoph & Urban, Dieter M., 2013. "Exporting, skills and wage inequality," Labour Economics, Elsevier, vol. 25(C), pages 76-85.
    3. Marinescu, Ioana E. & Wolthoff, Ronald P., 2015. "Opening the Black Box of the Matching Function: The Power of Words," IZA Discussion Papers 9071, Institute for the Study of Labor (IZA).
    4. Beatriz Muriel, 2011. "Rethinking Earnings Determinants in the Urban Areas of Bolivia," Development Research Working Paper Series 06/2011, Institute for Advanced Development Studies.
    5. Castellucci, Fabrizio & Padula, Mario & Pica, Giovanni, 2011. "The age-productivity gradient: Evidence from a sample of F1 drivers," Labour Economics, Elsevier, vol. 18(4), pages 464-473, August.
    6. Krishna, Pravin & Poole, Jennifer P. & Senses, Mine Zeynep, 2014. "Wage Effects of Trade Reform with Endogenous Worker Mobility," Journal of International Economics, Elsevier, vol. 93(2), pages 239-252.
    7. Nikolas Mittag, 2015. "A Simple Method to Estimate Large Fixed Effects Models Applied to Wage Determinants and Matching," CERGE-EI Working Papers wp532, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    8. Mittag, Nikolas, 2016. "A Simple Method to Estimate Large Fixed Effects Models Applied to Wage Determinants and Matching," IZA Discussion Papers 10447, Institute for the Study of Labor (IZA).
    9. Woodcock, Simon D., 2008. "Wage differentials in the presence of unobserved worker, firm, and match heterogeneity," Labour Economics, Elsevier, vol. 15(4), pages 771-793, August.
    10. Torben Sørensen & Rune Vejlin, 2013. "The importance of worker, firm and match effects in the formation of wages," Empirical Economics, Springer, vol. 45(1), pages 435-464, August.
    11. Kramarz, Francis & Machin, Stephen & Ouazad, Amine, 2008. "What Makes a Test Score? The Respective Contributions of Pupils, Schools, and Peers in Achievement in English Primary Education," IZA Discussion Papers 3866, Institute for the Study of Labor (IZA).
    12. Edward P. Lazear & Paul Oyer, 2012. "Personnel Economics," Introductory Chapters,in: Robert Gibbons & John Roberts (ed.), The Handbook of Organizational Economics Princeton University Press.
    13. Edward P. Lazear, 1995. "Personnel Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262121883, March.
    14. Mittag, Nikolas, 2012. "New methods to estimate models with large sets of fixed effects with an application to matched employer-employee data from Germany," FDZ Methodenreport 201201_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    15. Andrews, M.J. & Gill, L. & Schank, T. & Upward, R., 2012. "High wage workers match with high wage firms: Clear evidence of the effects of limited mobility bias," Economics Letters, Elsevier, vol. 117(3), pages 824-827.
    16. repec:spr:empeco:v:53:y:2017:i:4:d:10.1007_s00181-016-1179-0 is not listed on IDEAS
    17. Thomas Cornelißen & Olaf Hübler, 2011. "Unobserved Individual and Firm Heterogeneity in Wage and Job‐Duration Functions: Evidence from German Linked Employer–Employee Data," German Economic Review, Verein für Socialpolitik, vol. 12(4), pages 469-489, November.
    18. Mark Bils & Yongsung Chang & Sun-Bin Kim, 2011. "Worker Heterogeneity and Endogenous Separations in a Matching Model of Unemployment Fluctuations," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(1), pages 128-154, January.
    19. Almeida, Rita K. & Poole, Jennifer P., 2017. "Trade and labor reallocation with heterogeneous enforcement of labor regulations," Journal of Development Economics, Elsevier, vol. 126(C), pages 154-166.
    20. Laurent Gobillon & François-Charles Wolff & Patrice Guillotreau, 2013. "The anatomy of prices on the French fish market," PSE Working Papers halshs-00839147, HAL.
    21. Laurent Gobillon & François-Charles Wolff & Patrice Guillotreau, 2013. "The anatomy of prices on the French fish market," Working Papers halshs-00839147, HAL.
    22. Failla, Virgilio & Melillo, Francesca & Reichstein, Toke, 2017. "Entrepreneurship and employment stability — Job matching, labour market value, and personal commitment," Journal of Business Venturing, Elsevier, vol. 32(2), pages 162-177.

    More about this item

    Keywords

    linked employer-employee data; earnings dispersion; person and firm effects; fixed effects; random effects; labor market sorting; human capital;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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