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An Estimation Of Worker And Firm Effects With Censored Data

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  • Ainara González de San Román
  • Yolanda F. Rebollo‐Sanz

Abstract

In this paper, we develop a new estimation method that is suitable for censored models with two high dimensional fixed effects and that is based on a sequence of least squares regressions, yielding significant savings in computing time and hence making it applicable to frameworks in which standard estimation techniques become unfeasible. We propose to apply this estimation method to investigate the role of firms in individual wage variation. Using a longitudinal match employer‐employee dataset from Spain, we show that the analysis of wage determination can be misleading when wages are censored. In particular, the role of firm wage policies in wage dispersion is overestimated by more than ten percentage points, while the role of time‐invariant individual characteristics is underestimated by fifteen percentage points. Hence, controlling for censored wages appears to reinforce the idea that when explaining individual wage dispersion, what workers ‘are’ is more important than what workers ‘do’.

Suggested Citation

  • Ainara González de San Román & Yolanda F. Rebollo‐Sanz, 2018. "An Estimation Of Worker And Firm Effects With Censored Data," Bulletin of Economic Research, Wiley Blackwell, vol. 70(4), pages 459-482, October.
  • Handle: RePEc:bla:buecrs:v:70:y:2018:i:4:p:459-482
    DOI: 10.1111/boer.12112
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    1. 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.
    2. Thomas Cornelissen, 2008. "The Stata command felsdvreg to fit a linear model with two high-dimensional fixed effects," Stata Journal, StataCorp LP, vol. 8(2), pages 170-189, June.
    3. Powell, James L, 1986. "Symmetrically Trimmed Least Squares Estimation for Tobit Models," Econometrica, Econometric Society, vol. 54(6), pages 1435-1460, November.
    4. 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.
    5. Gruetter, Max & Lalive, Rafael, 2009. "The importance of firms in wage determination," Labour Economics, Elsevier, vol. 16(2), pages 149-160, April.
    6. Abowd, John M. & Kramarz, Francis, 1999. "The analysis of labor markets using matched employer-employee data," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 40, pages 2629-2710, Elsevier.
    7. Torres, Sónia & Portugal, Pedro & Addison, John T. & Guimaraes, Paulo, 2013. "The Sources of Wage Variation: A Three-Way High-Dimensional Fixed Effects Regression Model," IZA Discussion Papers 7276, Institute of Labor Economics (IZA).
    8. 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.
    9. Amemiya, Takeshi, 1973. "Regression Analysis when the Dependent Variable is Truncated Normal," Econometrica, Econometric Society, vol. 41(6), pages 997-1016, November.
    10. Paulo Guimarães & Pedro Portugal & Anabela Carneiro, 2009. "Real Wages and the Business Cycle: Accounting for Worker and Firm Heterogeneity," Working Papers w200910, Banco de Portugal, Economics and Research Department.
    11. Kenneth L. Sørensen & Rune Vejlin, 2014. "Return To Experience And Initial Wage Level: Do Low Wage Workers Catch Up?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(6), pages 984-1006, September.
    12. 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.
    13. M. J. Andrews & L. Gill & T. Schank & R. Upward, 2008. "High wage workers and low wage firms: negative assortative matching or limited mobility bias?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(3), pages 673-697, June.
    14. Guimaraes, Paulo & Portugal, Pedro, 2009. "A Simple Feasible Alternative Procedure to Estimate Models with High-Dimensional Fixed Effects," IZA Discussion Papers 3935, Institute of Labor Economics (IZA).
    15. Goldberger, Arthur S, 1970. "Unbiased Prediction by Recursive Least Squares," Econometrica, Econometric Society, vol. 38(2), pages 367-367, March.
    16. John M. Abowd (corresponding) & Francis Kramarz, 2004. "Are Good Workers Employed by Good Firms? A Simple Test of Positive Assortative Matching Models," Econometric Society 2004 North American Winter Meetings 385, Econometric Society.
    17. Olsen, Randall J, 1978. "Note on the Uniqueness of the Maximum Likelihood Estimator for the Tobit Model," Econometrica, Econometric Society, vol. 46(5), pages 1211-1215, September.
    18. James Tobin, 1956. "Estimation of Relationships for Limited Dependent Variables," Cowles Foundation Discussion Papers 3R, Cowles Foundation for Research in Economics, Yale University.
    19. Paulo Guimaraes & Pedro Portugal, 2009. "Estimating high-dimensional fixed-effects models," DC09 Stata Conference 2, Stata Users Group.
    20. John M. Abowd & Simon D. Woodcock, 2004. "Multiply-Imputing Confidential Characteristics and File Links in Longitudinal Linked Data," Longitudinal Employer-Household Dynamics Technical Papers 2004-04, Center for Economic Studies, U.S. Census Bureau.
    21. Abowd, John M. & Kramarz, Francis, 1999. "Econometric analyses of linked employer-employee data," Labour Economics, Elsevier, vol. 6(1), pages 53-74, March.
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    Cited by:

    1. Anna Zaharieva, 2014. "On-the-Job Search and Optimal Schooling under Uncertainty and Irreversibility," Politica economica, Società editrice il Mulino, issue 2-3, pages 299-339.
    2. Yolanda F. Rebollo-Sanz, 2017. "Decomposing the structure of wages into firm and worker effects: some insights from a high unemployment economy," Working Papers 17.10, Universidad Pablo de Olavide, Department of Economics.

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    More about this item

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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