Analysing Plant Closure Effects Using Time-Varying Mixture-of-Experts Markov Chain Clustering

Frühwirth-Schnatter, Sylvia; Pittner, Stefan; Weber, Andrea and Winter-Ebmer, RudolfORCID: https://orcid.org/0000-0001-8157-6631 (October 2016) Analysing Plant Closure Effects Using Time-Varying Mixture-of-Experts Markov Chain Clustering. Former Series > Working Paper Series > IHS Economics Series 324, 28 p.

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Abstract

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.

Item Type:	IHS Series
Keywords:	Transition data, Markov Chain Monte Carlo, Multinomial Logit, Panel data, Inhomogeneous Markov chains
Research Units:	Former Research Units (until 2020) > Labor Market and Social Policy
Date Deposited:	05 Oct 2016 12:55
Last Modified:	25 Sep 2023 06:01
ISSN:	1605-7996
URI:	https://irihs.ihs.ac.at/id/eprint/4078

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