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

Author

Listed:
  • Horny, Guillaume

    (Bank of France)

  • Mendes, Rute

    (University of Turin)

  • van den Berg, Gerard J.

    (University of Groningen)

Abstract

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.

Suggested Citation

  • Horny, Guillaume & Mendes, Rute & van den Berg, Gerard J., 2009. "Job Durations with Worker and Firm Specific Effects: MCMC Estimation with Longitudinal Employer-Employee Data," IZA Discussion Papers 3992, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp3992
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    1. Mendes, Rute & van den Berg, Gerard J. & Lindeboom, Maarten, 2010. "An empirical assessment of assortative matching in the labor market," Labour Economics, Elsevier, vol. 17(6), pages 919-929, December.
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    9. Guillaume Horny & Dragana Djurdjevic & Bernhard Boockmann & François Laisney, 2008. "Bayesian Estimation of Cox Models with Non-nested Random Effects: an Application to the Ratification Of ILO Conventions by Developing Countries," Annals of Economics and Statistics, GENES, issue 89, pages 193-214.
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    Cited by:

    1. Ferreira, Priscila, 2009. "The determinants of promotions and firm separations," ISER Working Paper Series 2009-11, Institute for Social and Economic Research.
    2. Giuseppe Tattara & Marco Valentini, 2010. "Turnover and Excess Worker Reallocation. The Veneto Labour Market between 1982 and 1996," LABOUR, CEIS, vol. 24(4), pages 474-500, December.
    3. Katharina Dengler & Katrin Hohmeyer & Cordula Zabel, 2021. "Welfare recipients’ transition into employment and employment stability in Germany," LABOUR, CEIS, vol. 35(4), pages 450-484, December.
    4. Paul, Marie & Fernandez-Kranz, Daniel & Rodriguez-Planas, Nuria, 2014. "The Wage Effects of Fixed-term Contract Employment Revisited: an Investigation Based on Social Security Records," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100324, Verein für Socialpolitik / German Economic Association.
    5. Mendes, Rute & van den Berg, Gerard J. & Lindeboom, Maarten, 2010. "An empirical assessment of assortative matching in the labor market," Labour Economics, Elsevier, vol. 17(6), pages 919-929, December.
    6. Raul Caruso & Ilaria Petrarca & Roberto Ricciuti, 2014. "Spatial Concentration of Military Dictatorships in Sub-Saharan Africa (1977-2007)," CESifo Working Paper Series 4802, CESifo.
    7. Daniel Fernández-Kranz & Marie Paul & Núria Rodríguez-Planas, 2015. "Part-Time Work, Fixed-Term Contracts, and the Returns to Experience," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(4), pages 512-541, August.
    8. Robert Hill & Kezia Lilenstein & Amy Thornton, 2020. "Job spells in an emerging market: Evidence from apartheid and post-apartheid South Africa," WIDER Working Paper Series wp-2020-27, World Institute for Development Economic Research (UNU-WIDER).
    9. Castro Silva, Hugo & Lima, Francisco, 2017. "Technology, employment and skills: A look into job duration," Research Policy, Elsevier, vol. 46(8), pages 1519-1530.
    10. Rémi Piatek & Pia Pinger, 2016. "Maintaining (Locus of) Control? Data Combination for the Identification and Inference of Factor Structure Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(4), pages 734-755, June.

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    More about this item

    Keywords

    dynamic models; frailties; Gibbs sampling; assortative matching; job transitions; matched employer-employee data;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • J20 - Labor and Demographic Economics - - Demand and Supply of Labor - - - General
    • J41 - Labor and Demographic Economics - - Particular Labor Markets - - - Labor Contracts
    • J62 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Job, Occupational and Intergenerational Mobility; Promotion

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