Labor Market Entry and Earnings Dynamics: Bayesian Inference Using Mixtures-of-Experts Markov Chain Clustering

Arbeitspapier

This paper analyzes patterns in the earnings development of young labor market en- trants over their life cycle. We identify four distinctly di®erent types of transition patterns between discrete earnings states in a large administrative data set. Further, we investigate the e®ects of labor market conditions at the time of entry on the probability of belonging to each transition type. To estimate our statistical model we use a model-based clustering approach. The statistical challenge in our application comes from the di±culty in extending distance-based clustering approaches to the problem of identify groups of similar time series in a panel of discrete-valued time series. We use Markov chain clustering, proposed by Pam- minger and FrÄuhwirth-Schnatter (2010), which is an approach for clustering discrete-valued time series obtained by observing a categorical variable with several states. This method is based on ¯nite mixtures of ¯rst-order time-homogeneous Markov chain models. In order to analyze group membership we present an extension to this approach by formulating a prob- abilistic model for the latent group indicators within the Bayesian classi¯cation rule using a multinomial logit model.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Working Paper ; No. 1011

Classification and Topics

• Classification: Wirtschaft
• Subject: Labor Market Entry Conditions ; Transition Data ; Markov Chain Monte Carlo ; Multinomial Logit ; Panel Data ; Auxiliary Mixture Sampler ; Bayesian Statistics ; Lohn ; Junge Arbeitskräfte ; Berufseinstieg ; Erwerbsverlauf ; Markovscher Prozess ; Monte-Carlo-Methode ; Bayes-Statistik ; Schätzung ; Österreich

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Frühwirth-Schnatter, Sylvia ; Weber, Andrea ; Winter-Ebmer, Rudolf
• Event: Veröffentlichung
• (who): Johannes Kepler University of Linz, Department of Economics
• (where): Linz
• (when): 2010

Further information

• Handle: http://hdl.handle.net/10419/73582
• Last update: 10.03.2025, 11:42 AM CET