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Estimation of worker and firm effects with censored data

Author

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  • Yolanda F. Rebollo-Sanz

    () (Department of Economics, Universidad Pablo de Olavide)

  • Ainara González de San Román

    () (Instituto de Empresa)

Abstract

The main contribution of this paper is to provide researchers with a new estimation method suitable for censored models with two high dimensional fixed effects. This new estimation method is based on a sequence of least squares regressions. In practice, use of this method can result in significant savings in computing time, and it is applicable to datasets where the number of fixed effects makes standard estimation techniques unfeasible. In addition, the paper both analyses the theoretical properties of the procedure and evaluates its practical performance by means of a Monte Carlo simulation study. Finally, it describes an application to the Spanish economy using a Spanish longitudinal match employer-employee dataset which provides wage information on the working population over a 13-year period. In particular, this paper contributes to the empirical literature on wage determination by providing the first decomposition of individual wages for Spain that takes into account both worker and firm effects after adjusting for censoring. This empirical exercise shows that the biases encountered when censored issues are not taken into account can be of sufficient magnitude as to overestimate the role of firm effects in wage dispersion. In our empirical research, individual heterogeneity explains more than 60% of wage dispersion.

Suggested Citation

  • Yolanda F. Rebollo-Sanz & Ainara González de San Román, 2013. "Estimation of worker and firm effects with censored data," Working Papers 13.05, Universidad Pablo de Olavide, Department of Economics, revised May 2014.
  • Handle: RePEc:pab:wpaper:13.05
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    References listed on IDEAS

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    1. 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.
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    3. 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.
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    5. 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).
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    9. 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.
    10. Anabela Carneiro & Paulo Guimaraes & Pedro Portugal, 2009. "Real Wages and the Business Cycle: Accounting for Worker and Firm Heterogeneity," CEF.UP Working Papers 0903, Universidade do Porto, Faculdade de Economia do Porto.
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    Citations

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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," International Journal of Manpower, Emerald Group Publishing, vol. 38(5), pages 765-787, August.

    More about this item

    Keywords

    fixed effects; algorithm; wage decomposition; censoring; simulation; assortative matching;

    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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