IDEAS home Printed from
   My bibliography  Save this article

Modeling Endogenous Mobility in Earnings Determination


  • John M. Abowd
  • Kevin L. McKinney
  • Ian M. Schmutte


We evaluate the bias from endogenous job mobility in fixed-effects estimates of worker- and firm-specific earnings heterogeneity using longitudinally linked employer–employee data from the LEHD infrastructure file system of the U.S. Census Bureau. First, we propose two new residual diagnostic tests of the assumption that mobility is exogenous to unmodeled determinants of earnings. Both tests reject exogenous mobility. We relax exogenous mobility by modeling the matched data as an evolving bipartite graph using a Bayesian latent-type framework. Our results suggest that allowing endogenous mobility increases the variation in earnings explained by individual heterogeneity and reduces the proportion due to employer and match effects. To assess external validity, we match our estimates of the wage components to out-of-sample estimates of revenue per worker. The mobility-bias-corrected estimates attribute much more of the variation in revenue per worker to variation in match quality and worker quality than the uncorrected estimates. Supplementary materials for this article are available online.

Suggested Citation

  • John M. Abowd & Kevin L. McKinney & Ian M. Schmutte, 2019. "Modeling Endogenous Mobility in Earnings Determination," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 405-418, July.
  • Handle: RePEc:taf:jnlbes:v:37:y:2019:i:3:p:405-418
    DOI: 10.1080/07350015.2017.1356727

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Kevin L. McKinney & John M. Abowd & John Sabelhaus, 2021. "United States Earnings Dynamics: Inequality, Mobility, and Volatility," NBER Chapters, in: Measuring Distribution and Mobility of Income and Wealth, National Bureau of Economic Research, Inc.
    2. Cornwell, Christopher & Schmutte, Ian M. & Scur, Daniela, 2019. "Building a productive workforce: the role of structured management practices," LSE Research Online Documents on Economics 103404, London School of Economics and Political Science, LSE Library.
    3. Stéphane Bonhomme & Kerstin Holzheu & Thibaut Lamadon & Elena Manresa & Magne Mogstad & Bradley Setzler, 2020. "How Much Should we Trust Estimates of Firm Effects and Worker Sorting?," Working Papers 2020-77, Becker Friedman Institute for Research In Economics.
    4. Jinkins, David & Morin, Annaïg, 2018. "Job-to-job transitions, sorting, and wage growth," Labour Economics, Elsevier, vol. 55(C), pages 300-327.
    5. Eliason, Marcus & Hensvik, Lena & Kramarz, Francis & Nordstrom Skans, Oskar, 2019. "Social Connections and the Sorting of Workers to Firms," CEPR Discussion Papers 13672, C.E.P.R. Discussion Papers.
    6. Kenichi Nagasawa, 2018. "Identification and Estimation of Partial Effects with Proxy Variables," Papers 1811.00667,, revised Oct 2020.
    7. Nagasawa, Kenichi, 2020. "Identification and Estimation of Group-Level Partial Effects," The Warwick Economics Research Paper Series (TWERPS) 1243, University of Warwick, Department of Economics.

    More about this item


    Access and download statistics


    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:taf:jnlbes:v:37:y:2019:i:3:p:405-418. 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: . General contact details of provider: .

    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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: .

    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.