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 40 quarters -
whether these workers manage to return to a steady career path. To analyse
these discrete-valued panel data, we 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 mixtureof-
experts approach allows us to model the probability of belonging to a certain
cluster as depending on 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.
| Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:6541 |
| Date | January 2018 |
| Creators | Frühwirth-Schnatter, Sylvia, Pittner, Stefan, Weber, Andrea, Winter-Ebmer, Rudolf |
| Publisher | Institute of Mathematical Statistics |
| Source Sets | Wirtschaftsuniversität Wien |
| Language | English |
| Detected Language | English |
| Type | Article, PeerReviewed |
| Format | application/pdf |
| Relation | http://dx.doi.org/10.1214/17-AOAS1132, https://www.imstat.org/, https://www.imstat.org/wp-content/uploads/import/copyrightTA.pdf, http://epub.wu.ac.at/6541/ |
Page generated in 0.0022 seconds