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Job Durations with Worker and Firm Specific Effects: MCMC Estimation with Longitudinal Employer-Employee Data

  • Horny, Guillaume

    ()

    (Bank of France)

  • Mendes, Rute

    ()

    (University of Turin)

  • van den Berg, Gerard J.

    ()

    (University of Mannheim)

We study job durations using a multivariate hazard model allowing for worker-specific and firm-specific unobserved determinants. The latter are captured by unobserved heterogeneity terms or random effects, one at the firm level and another at the worker level. This enables us to decompose the variation in job durations into the relative contribution of the worker and the firm. We also allow the unobserved terms to be correlated. For the empirical analysis we use a Portuguese longitudinal matched employer-employee data set. The model is estimated with a Bayesian Markov Chain Monte Carlo (MCMC) estimation method. The results imply that firm characteristics explain around 30% of the variation in log job durations. In addition, we find a positive correlation between unobserved worker and firm characteristics.

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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 3992.

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Length: 30 pages
Date of creation: Feb 2009
Date of revision:
Handle: RePEc:iza:izadps:dp3992
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  1. Van den Berg, Gerard J., 2000. "Duration Models: Specification, Identification, and Multiple Durations," MPRA Paper 9446, University Library of Munich, Germany.
  2. Bernhard Boockmann. & Dragana Djurdjevic. & Guillaume Horny. & François Laisney., 2009. "Bayesian estimation of Cox models with non-nested random effects: an application to the ratification of ILO conventions by developing countries," Working papers 249, Banque de France.
  3. Rute Mendes & Gerard J. van den Berg & Maarten Lindeboom, 2007. "An Empirical Assessment of Assortative Matching in the Labor Market," Carlo Alberto Notebooks 62, Collegio Carlo Alberto.
  4. Daniela Del Boca & Robert M. Sauer, 2006. "Life Cycle Employment and Fertility Across Institutional Environments," Carlo Alberto Notebooks 20, Collegio Carlo Alberto.
  5. José Vieira & Ana Cardoso & Miguel Portela, 2005. "Gender segregation and the wage gap in Portugal: an analysis at the establishment level," Journal of Economic Inequality, Springer, vol. 3(2), pages 145-168, August.
  6. Benoit Dostie, 2004. "Job Turnover and the Returns to Seniority," Econometric Society 2004 North American Winter Meetings 127, Econometric Society.
  7. Miguel Portela & Ana Rute Cardoso, 2005. "The provision of wage insurance by the firm: evidence from a longitudinal matched employer-employee dataset," NIPE Working Papers 17/2005, NIPE - Universidade do Minho.
  8. L. Randall Wray & Stephanie Bell, 2004. "Introduction," Chapters, in: Credit and State Theories of Money, chapter 1 Edward Elgar.
  9. Light, Audrey & Ureta, Manuelita, 1992. "Panel Estimates of Male and Female Job Turnover Behavior: Can Female Nonquitters Be Identified?," Journal of Labor Economics, University of Chicago Press, vol. 10(2), pages 156-81, April.
  10. Jean-Marc Robin & Costas Meghir & Jeremy Lise, 2009. "Matching, Sorting and Wages," 2009 Meeting Papers 180, Society for Economic Dynamics.
  11. Farber, Henry S., 1999. "Mobility and stability: The dynamics of job change in labor markets," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 37, pages 2439-2483 Elsevier.
  12. Samuel Manda & Renate Meyer, 2005. "Age at first marriage in Malawi: a Bayesian multilevel analysis using a discrete time-to-event model," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 439-455.
  13. Johnson, William R, 1978. "A Theory of Job Shopping," The Quarterly Journal of Economics, MIT Press, vol. 92(2), pages 261-78, May.
  14. Leonardo Grilli, 2005. "The random-effects proportional hazards model with grouped survival data: a comparison between the grouped continuous and continuation ratio versions," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(1), pages 83-94.
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