Job durations with worker- and firm-specific effects: MCMC estimation with longitudinal employer-employee data

Guillaume Horny*, Rute Mendes, Gerard J. van den Berg

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

5 Citations (Scopus)

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 in a model that is primarily relevant for markets with small firms. For the empirical analysis, we use a Portuguese longitudinal matched employer-employee dataset. The model is estimated with a Bayesian Markov chain Monte Carlo (MCMC) estimation method. The results imply that unobserved firm characteristics explain almost 40% of the systematic variation in log job durations. In addition, we find a positive correlation between unobserved worker and firm characteristics.

Original languageEnglish
Pages (from-to)468-480
Number of pages13
JournalJournal of business & economic statistics
Volume30
Issue number3
DOIs
Publication statusPublished - 2012

Keywords

  • Assortative matching
  • Dynamic models
  • Frailties
  • Gibbs sampling
  • Job transitions
  • Matched employer-employee data

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