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.

[img]
Preview
Text
es-324.pdf - Published Version
Available under License Creative Commons Attribution.

Download (736kB) | Preview
[img] Text
user_agreement_es324.pdf - Supplemental Material
Restricted to Repository staff only

Download (427kB)

Abstract or Table of Contents

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: 04 Jun 2023 06:00
ISSN: 1605-7996
URI: https://irihs.ihs.ac.at/id/eprint/4078

Actions (login required)

View Item View Item