• Medientyp: Bericht; E-Book
  • Titel: Analysing plant closure effects using time-varying mixture-of-experts Markov chain clustering
  • Beteiligte: Frühwirth-Schnatter, Sylvia [Verfasser:in]; Pittner, Stefan [Verfasser:in]; Weber, Andrea [Verfasser:in]; Winter-Ebmer, Rudolf [Verfasser:in]
  • Erschienen: Vienna: Institute for Advanced Studies (IHS), 2016
  • Sprache: Englisch
  • Schlagwörter: Inhomogeneous Markov chains ; Multinomial Logit ; Transition data ; Markov Chain Monte Carlo ; Panel data
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  • Beschreibung: In this paper, we study data on discrete labor market transitions from Austria. In particular, we follow the careers of workers who experience a job displacement due to plant closure and observe - over a period of forty quarters - whether these workers manage to return to a steady career path. To analyse these discrete-valued panel data, we develop and apply a new method of Bayesian Markov chain clustering analysis based on inhomogeneous first order Markov transition processes with time-varying transition matrices. In addition, a mixture-of-experts approach allows us to model the prior probability to belong to a certain cluster in dependence of a set of covariates via a multinomial logit model. Our cluster analysis identifies five career patterns after plant closure and reveals that some workers cope quite easily with a job loss whereas others suffer large losses over extended periods of time.
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