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

Guillaume Horny, Rute Mendes and Gerard van den Berg

No 3992, IZA Discussion Papers from Institute of Labor Economics (IZA)

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.

Keywords: dynamic models; frailties; Gibbs sampling; assortative matching; job transitions; matched employer-employee data (search for similar items in EconPapers)
JEL-codes: C11 C15 C41 J20 J41 J62 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2009-02
New Economics Papers: this item is included in nep-bec and nep-lab
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Published - published in: Journal of Business and Economic Statisticsc, 30(3) 2012, 468-480

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Related works:
Journal Article: Job Durations With Worker- and Firm-Specific Effects: MCMC Estimation With Longitudinal Employer--Employee Data (2012)
Working Paper: Job durations with worker and firm specific effects: MCMC estimation with longitudinal employer-employee data (2009)
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