The effects of training incidence and planned training duration on labor market transitions

Bernd Fitzenberger, Aderonke Osikominu and Marie Paul

Journal of Econometrics, 2023, vol. 235, issue 1, 256-279

Abstract: This paper uses a dynamic model for employment and training transitions in discrete time to estimate average employment effects of training incidence and planned training duration for the treated. We account for the dynamics of program start and continuation while treatment and outcome transitions are linked through correlated individual-specific effects. Identification relies on a consistency condition, conditional sequential randomization, time-varying covariates, and exclusion restrictions. We implement our framework applying MCMC methods to rich administrative data for a large training program in Germany. In addition to finding a positive training effect on employment between 6 and 12 percentage points 2.5 years after program start, we demonstrate that a longer planned training duration typically results in higher medium- to long-term employment gains.

Keywords: Dynamic treatment effects; Dynamic nonlinear panel data models; MCMC; Training; Active labor market programs (search for similar items in EconPapers)
JEL-codes: C11 C33 J68 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:235:y:2023:i:1:p:256-279

DOI: 10.1016/j.jeconom.2022.03.004

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