IDEAS home Printed from https://ideas.repec.org/a/adr/anecst/y2018i129p1-32.html
   My bibliography  Save this article

Sorting Between and Within Industries: A Testable Model of Assortative Matching

Author

Listed:
  • John M. Abowd
  • Francis Kramarz
  • Sébastien Pérez-Duarte
  • Ian M. Schmutte

Abstract

We test Shimer's (2005) theory of the sorting of workers between and within industrial sectors based on directed search with coordination frictions, deliberately maintaining its static general equilibrium framework. We fit the model to sector-specific wage, vacancy and output data, including publicly-available statistics that characterize the distribution of worker and employer wage heterogeneity across sectors. Our empirical method is general and can be applied to a broad class of assignment models. The results indicate that industries are the loci of sorting-more productive workers are employed in more productive industries. The evidence confirms that strong assortative matching can be present even when worker and employer components of wage heterogeneity are weakly correlated.

Suggested Citation

  • 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.
  • Handle: RePEc:adr:anecst:y:2018:i:129:p:1-32
    DOI: 10.15609/annaeconstat2009.129.0001
    as

    Download full text from publisher

    File URL: http://www.jstor.org/stable/10.15609/annaeconstat2009.129.0001
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. John M. Abowd & Kevin McKinney & Ian M. Schmutte, 2015. "Modeling Endogenous Mobility in Wage Determiniation," Working Papers 15-18, Center for Economic Studies, U.S. Census Bureau.
    2. Lucia Foster & Cheryl Grim & John Haltiwanger, 2016. "Reallocation in the Great Recession: Cleansing or Not?," Journal of Labor Economics, University of Chicago Press, vol. 34(S1), pages 293-331.
    3. Jan Eeckhout & Philipp Kircher, 2011. "Identifying Sorting--In Theory," Review of Economic Studies, Oxford University Press, vol. 78(3), pages 872-906.
    4. David Card & Jörg Heining & Patrick Kline, 2013. "Workplace Heterogeneity and the Rise of West German Wage Inequality," The Quarterly Journal of Economics, Oxford University Press, vol. 128(3), pages 967-1015.
    5. Sakata, Shinichi & White, Halbert, 2001. "S-estimation of nonlinear regression models with dependent and heterogeneous observations," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 5-72, July.
    6. John M. Abowd & Robert H. Creecy & Francis Kramarz, 2002. "Computing Person and Firm Effects Using Linked Longitudinal Employer-Employee Data," Longitudinal Employer-Household Dynamics Technical Papers 2002-06, Center for Economic Studies, U.S. Census Bureau.
    7. Christina Gathmann & Uta Schönberg, 2010. "How General Is Human Capital? A Task-Based Approach," Journal of Labor Economics, University of Chicago Press, vol. 28(1), pages 1-49, January.
    8. Cristian Bartolucci & Francesco Devicienti, 2012. "Better Workers Move to Better Firms: A Simple Test to Identify Sorting," Carlo Alberto Notebooks 259, Collegio Carlo Alberto.
    9. Steven J. Davis & R. Jason Faberman & John C. Haltiwanger, 2013. "The Establishment-Level Behavior of Vacancies and Hiring," The Quarterly Journal of Economics, Oxford University Press, vol. 128(2), pages 581-622.
    10. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
    11. repec:wly:emetrp:v:85:y:2017:i::p:29-65 is not listed on IDEAS
    12. Susana Iranzo & Fabiano Schivardi & Elisa Tosetti, 2008. "Skill Dispersion and Firm Productivity: An Analysis with Employer-Employee Matched Data," Journal of Labor Economics, University of Chicago Press, vol. 26(2), pages 247-285, April.
    13. Ruud, Paul A., 2000. "An Introduction to Classical Econometric Theory," OUP Catalogue, Oxford University Press, number 9780195111644.
    14. 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.
    15. Andreas Hornstein & Per Krusell & Giovanni L. Violante, 2011. "Frictional Wage Dispersion in Search Models: A Quantitative Assessment," American Economic Review, American Economic Association, vol. 101(7), pages 2873-2898, December.
    16. David Card & Ana Rute Cardoso & Patrick Kline, 2016. "Bargaining, Sorting, and the Gender Wage Gap: Quantifying the Impact of Firms on the Relative Pay of Women," The Quarterly Journal of Economics, Oxford University Press, vol. 131(2), pages 633-686.
    17. Robert Shimer, 2005. "The Assignment of Workers to Jobs in an Economy with Coordination Frictions," Journal of Political Economy, University of Chicago Press, vol. 113(5), pages 996-1025, October.
    18. L. Ingber, 2012. "Adaptive simulated annealing," Lester Ingber Papers 12as, Lester Ingber.
    19. Marcus Hagedorn & Tzuo Hann Law & Iourii Manovskii, 2017. "Identifying Equilibrium Models of Labor Market Sorting," Econometrica, Econometric Society, vol. 85, pages 29-65, January.
    20. Becker, Gary S, 1973. "A Theory of Marriage: Part I," Journal of Political Economy, University of Chicago Press, vol. 81(4), pages 813-846, July-Aug..
    21. John Kennes & Daniel le Maire, 2013. "Job Heterogeneity and Coordination Frictions," Economics Working Papers 2013-09, Department of Economics and Business Economics, Aarhus University.
    22. John Abowd & Francis Kramarz & Paul Lengermann & Kevin McKinney & Sébastien Roux, 2012. "Persistent inter‐industry wage differences: rent sharing and opportunity costs," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 1(1), pages 1-25, December.
    23. John M. Abowd & Paul A. Lengermann & Kevin L. McKinney, 2002. "The Measurement of Human Capital in the U.S. Economy," Longitudinal Employer-Household Dynamics Technical Papers 2002-09, Center for Economic Studies, U.S. Census Bureau, revised Mar 2003.
    24. Thaler, Richard H, 1989. "Interindustry Wage Differentials," Journal of Economic Perspectives, American Economic Association, vol. 3(2), pages 181-193, Spring.
    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. Erling Barth & Alex Bryson & James C. Davis & Richard Freeman, 2016. "It's Where You Work: Increases in the Dispersion of Earnings across Establishments and Individuals in the United States," Journal of Labor Economics, University of Chicago Press, vol. 34(S2), pages 67-97.
    2. Erling Barth & James Davis & Richard B. Freeman, 2018. "Augmenting the Human Capital Earnings Equation with Measures of Where People Work," Journal of Labor Economics, University of Chicago Press, vol. 36(S1), pages 71-97.
    3. John Kennes & Daniel le Maire, 2016. "On the equivalence of buyer and seller proposals within canonical matching and pricing environments," Economics Working Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
    4. Kory Kantenga, 2016. "Sorting and Wage Inequality," 2016 Meeting Papers 660, Society for Economic Dynamics.

    More about this item

    Keywords

    Wage Differentials; Human Capital; Skills; Job Matching; Simulation Methods;

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity

    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:adr:anecst:y:2018:i:129:p:1-32. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Laurent Linnemer). General contact details of provider: http://edirc.repec.org/data/ensaefr.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.