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Estimation of worker and firm effects with censored data

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Author Info

  • 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.

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Bibliographic Info

Paper provided by Universidad Pablo de Olavide, Department of Economics in its series Working Papers with number 13.05.

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Length: 42 pages
Date of creation: Sep 2013
Date of revision: May 2014
Handle: RePEc:pab:wpaper:13.05

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

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References

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  1. Abowd, John M. & Kramarz, Francis, 1999. "Econometric analyses of linked employer-employee data," Labour Economics, Elsevier, Elsevier, vol. 6(1), pages 53-74, March.
  2. John M. Abowd & Francis Kramarz & David N. Margolis, 1999. "High Wage Workers and High Wage Firms," Econometrica, Econometric Society, Econometric Society, vol. 67(2), pages 251-334, March.
  3. Thomas Cornelissen, 2008. "The Stata command felsdvreg to fit a linear model with two high-dimensional fixed effects," Stata Journal, StataCorp LP, StataCorp LP, vol. 8(2), pages 170-189, June.
  4. Gruetter, Max & Lalive, Rafael, 2004. "The Importance of Firms in Wage Determination," IZA Discussion Papers 1367, Institute for the Study of Labor (IZA).
  5. John M. Abowd & Simon D. Woodcock, 2004. "Multiply-Imputing Confidential Characteristics and File Links in Longitudinal Linked Data," Longitudinal Employer-Household Dynamics Technical Papers, Center for Economic Studies, U.S. Census Bureau 2004-04, Center for Economic Studies, U.S. Census Bureau.
  6. Sónia Torres & Pedro Portugal & John T. Addison & Paulo Guimarães, 2013. "The sources of wage variation: a three-way high-dimensional fixed effects regression model," Working Papers, Banco de Portugal, Economics and Research Department w201309, Banco de Portugal, Economics and Research Department.
  7. Olsen, Randall J, 1978. "Note on the Uniqueness of the Maximum Likelihood Estimator for the Tobit Model," Econometrica, Econometric Society, Econometric Society, vol. 46(5), pages 1211-15, September.
  8. Amemiya, Takeshi, 1973. "Regression Analysis when the Dependent Variable is Truncated Normal," Econometrica, Econometric Society, Econometric Society, vol. 41(6), pages 997-1016, November.
  9. Abowd, John M. & Kramarz, Francis, 1999. "The analysis of labor markets using matched employer-employee data," Handbook of Labor Economics, Elsevier, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 40, pages 2629-2710 Elsevier.
  10. James Tobin, 1956. "Estimation of Relationships for Limited Dependent Variables," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University 3R, Cowles Foundation for Research in Economics, Yale University.
  11. Powell, James L, 1986. "Symmetrically Trimmed Least Squares Estimation for Tobit Models," Econometrica, Econometric Society, Econometric Society, vol. 54(6), pages 1435-60, November.
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Cited by:
  1. Anna Zaharieva, 2013. "On-the-job search and optimal schooling under uncertainty and irreversibility," Working Papers, Bielefeld University, Center for Mathematical Economics 492, Bielefeld University, Center for Mathematical Economics.

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