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Better Workers Move to Better Firms: A Simple Test to Identify Sorting

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  • Francesco Devicienti

    (Università di Torino)

  • Cristian Bartolucci

    (Collegio Carlo Alberto)

Abstract

We propose a test that uses information on workers' mobility, wages and firms' profits to identify the sign and strength of assortative matching. The basic intuition underlying our empirical strategy is that, in the presence of positive (negative) assortative matching, good workers are more (less) likely to move to better firms than bad workers. Assuming that agents' payoffs are increasing in their own types allows us to use within-firm variation on wages to rank workers by their types and firm profits to rank firms. We exploit a panel data set that combines Social Security earnings records for workers in the Veneto region of Italy with detailed balance-sheet information for employers. We find robust evidence that positive assortative matching is a pervasive phenomenon in the labor market. This result is in contrast with what we find from correlating the worker and firm fixed effects in standard Mincerian wage equations.

Suggested Citation

  • Francesco Devicienti & Cristian Bartolucci, 2013. "Better Workers Move to Better Firms: A Simple Test to Identify Sorting," 2013 Meeting Papers 249, Society for Economic Dynamics.
  • Handle: RePEc:red:sed013:249
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    Cited by:

    1. Gaure, Simen, 2014. "Practical Correlation Bias Correction in Two-way Fixed Effects Linear Regression," Memorandum 21/2014, Oslo University, Department of Economics.
    2. Leland D. Crane, 2014. "Firm Dynamics and Assortative Matching," Working Papers 14-25, Center for Economic Studies, U.S. Census Bureau.
    3. Cristian Bartolucci, 2013. "Gender Wage Gaps Reconsidered: A Structural Approach Using Matched Employer-Employee Data," Journal of Human Resources, University of Wisconsin Press, vol. 48(4), pages 998-1034.
    4. John M. Abowd & Francis Kramarz & Sébastien Pérez-Duarte & Ian M. Schmutte, 2018. "Sorting Between and Within Industries: A Testable Model of Assortative Matching," Annals of Economics and Statistics, GENES, issue 129, pages 1-32.
    5. Bagger, Jesper & Sørensen, Kenneth L. & Vejlin, Rune, 2013. "Wage sorting trends," Economics Letters, Elsevier, vol. 118(1), pages 63-67.
    6. Ryan Michaels & Michele Battisti, 2013. "Coordinated labor Supply within the Firm: Evidence and Implications," 2013 Meeting Papers 1116, Society for Economic Dynamics.
    7. IKEUCHI Kenta & FUKAO Kyoji & Cristiano PERUGINI, 2021. "Establishment Size, Workforce Composition and the College Wage Gap in Japan," Discussion papers 21022, Research Institute of Economy, Trade and Industry (RIETI).
    8. Mori, Tomoya & Sakaguchi, Shosei, 2018. "Collaborative knowledge creation: Evidence from Japanese patent data," MPRA Paper 88716, University Library of Munich, Germany.
    9. Cristian Bartolucci & Ignacio Monzon, 2014. "Frictions Lead to Sorting: a Partnership Model with On-the-Match Search," Carlo Alberto Notebooks 385, Collegio Carlo Alberto.
    10. Hector Chade & Jan Eeckhout & Lones Smith, 2017. "Sorting through Search and Matching Models in Economics," Journal of Economic Literature, American Economic Association, vol. 55(2), pages 493-544, June.
    11. Rasmus Lentz & Jesper Bagger, 2009. "An Empirical Model of Wage Dispersion with Sorting," 2009 Meeting Papers 964, Society for Economic Dynamics.
    12. Marino, Marianna & Parrotta, Pierpaolo & Pozzoli, Dario, 2016. "Educational diversity and knowledge transfers via inter-firm labor mobility," Journal of Economic Behavior & Organization, Elsevier, vol. 123(C), pages 168-183.
    13. Jacob Schwartz, 2018. "Schooling Choice, Labour Market Matching, and Wages," Papers 1803.09020, arXiv.org, revised Aug 2019.
    14. Bastien Drut & Richard Duhautois, 2017. "Assortative Matching Using Soccer Data," Journal of Sports Economics, , vol. 18(5), pages 431-447, June.
    15. Battisti, Michele, 2017. "High wage workers and high wage peers," Labour Economics, Elsevier, vol. 46(C), pages 47-63.
    16. Luca Paolo Merlino & Pierpaolo Parrotta & Dario Pozzoli, 2012. "Assortative Matching Gender," Working Papers ECARES ECARES 2012-040, ULB -- Universite Libre de Bruxelles.
    17. Luca Paolo Merlino & Pierpaolo Parrotta & Dario Pozzoli, 2018. "Gender Differences in Sorting," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 57(4), pages 671-709, October.
    18. Gabriel Burdín, 2016. "Equality Under Threat by the Talented: Evidence from Worker‐Managed Firms," Economic Journal, Royal Economic Society, vol. 126(594), pages 1372-1403, August.
    19. Jesper Bagger & Rasmus Lentz, 2014. "An Empirical Model of Wage Dispersion with Sorting," Economics Working Papers 2014-11, Department of Economics and Business Economics, Aarhus University.
    20. Tomoya Mori & Shosei Sakaguchi, 2019. "Creation of knowledge through exchanges of knowledge: Evidence from Japanese patent data," Papers 1908.01256, arXiv.org, revised Aug 2020.
    21. Rasmus Lentz & Jesper Bagger, 2015. "An Empirical Model of Wage Dispersion with Sorting," 2015 Meeting Papers 1345, Society for Economic Dynamics.

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    More about this item

    JEL classification:

    • J6 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior

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