Model-based Clustering of Multiple Time Series

Sylvia Kaufmann and Frühwirth-Schnatter, Sylvia

No 4650, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: We propose to use the attractiveness of pooling relatively short time series that display similar dynamics, but without restricting to pooling all into one group. We suggest estimating the appropriate grouping of time series simultaneously along with the group-specific model parameters. We cast estimation into the Bayesian framework and use Markov chain Monte Carlo simulation methods. We discuss model identification and base model selection on marginal likelihoods. A simulation study documents the efficiency gains in estimation and forecasting that are realized when appropriately grouping the time series of a panel. Two economic applications illustrate the usefulness of the method in analysing also extensions to Markov switching within clusters and heterogeneity within clusters, respectively.

Keywords: Panel data; Clustering; Mixture modelling; Markov switching; Markov chain monte carlo (search for similar items in EconPapers)
JEL-codes: C11 C33 E32 (search for similar items in EconPapers)
Date: 2004-09
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mac
References: Add references at CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
https://cepr.org/publications/DP4650 (application/pdf)
CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org

Related works:
Journal Article: Model-Based Clustering of Multiple Time Series (2008)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:4650

Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP4650

Access Statistics for this paper

More papers in CEPR Discussion Papers from C.E.P.R. Discussion Papers Centre for Economic Policy Research, 33 Great Sutton Street, London EC1V 0DX.
Bibliographic data for series maintained by ().