Arbeitspapier
Bayesian Clustering of Categorical Time Series Using Finite Mixtures of Markov Chain Models
Two approaches for model-based clustering of categorical time series based on time- homogeneous first-order Markov chains are discussed. For Markov chain clustering the in- dividual transition probabilities are fixed to a group-specific transition matrix. In a new approach called Dirichlet multinomial clustering the rows of the individual transition matri- ces deviate from the group mean and follow a Dirichlet distribution with unknown group- specific hyperparameters. Estimation is carried out through Markov chain Monte Carlo. Various well-known clustering criteria are applied to select the number of groups. An appli- cation to a panel of Austrian wage mobility data leads to an interesting segmentation of the Austrian labor market.
- Sprache
-
Englisch
- Erschienen in
-
Series: NRN Working Paper, NRN: The Austrian Center for Labor Economics and the Analysis of the Welfare State ; No. 0907
- Klassifikation
-
Wirtschaft
- Thema
-
Markov chain Monte Carlo
model-based clustering
panel data
transition matrices
labor market
wage mobility
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Frühwirth-Schnatter, Sylvia
Pamminger, Christoph
- Ereignis
-
Veröffentlichung
- (wer)
-
Johannes Kepler University Linz, NRN - The Austrian Center for Labor Economics and the Analysis of the Welfare State
- (wo)
-
Linz
- (wann)
-
2009
- Handle
- Letzte Aktualisierung
- 10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Frühwirth-Schnatter, Sylvia
- Pamminger, Christoph
- Johannes Kepler University Linz, NRN - The Austrian Center for Labor Economics and the Analysis of the Welfare State
Entstanden
- 2009
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