A Bayesian Analysis of Female Wage Dynamics Using Markov Chain Clustering
AbstractIn this work, we analyze wage careers of women in Austria. We identify groups of female employees with similar patterns in their earnings development. Covariates such as e.g. the age of entry, the number of children or maternity leave help to detect these groups. We find three different types of female employees: (1) “high-wage mums”, women with high income and one or two children, (2) “low-wage mums”, women with low income and ‘many’ children and (3) “childless careers”, women who climb up the career ladder and do not have children. We use a Markov chain clustering approach to find groups in the discretevalued time series of income states. Additional covariates are included when modeling group membership via a multinomial logit model.
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Bibliographic InfoPaper provided by The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria in its series NRN working papers with number 2011-04.
Length: 16 pages
Date of creation: Jul 2011
Date of revision:
Contact details of provider:
Postal: NRN Labor Economics and the Welfare State, c/o Rudolf Winter-Ebmer, Altenbergerstr. 69, 4040 Linz
Web page: http://www.labornrn.at/
More information through EDIRC
Income Career; Transition Data; Multinomial Logit; Auxiliary Mixture Sampler; Markov Chain Monte Carlo;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-11-01 (All new papers)
- NEP-ECM-2011-11-01 (Econometrics)
- NEP-HME-2011-11-01 (Heterodox Microeconomics)
- NEP-LAB-2011-11-01 (Labour Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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"State Dependence and Wage Dynamics: A Heterogeneous Markov Chain Model for Wage Mobility in Austria,"
114, Institute for Advanced Studies.
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IEW - Working Papers
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