Quotation Frühwirth-Schnatter, Sylvia. 2002. Bayesian Clustering of Many Short Time Series. CORE (Center for Operations Research and Econometrics), Louvain-la-Neuve, Frankreich, 30.10.


RIS


BibTeX

Abstract

In the present paper we propose a method to infer on the different clusters potentially present in a panel data set that is data driven in the sense that the classification of each subject into a specific group is estimated along with the model parameters. The general model allows additionally for time-varying parameters, whereby the timing of the structural changes is also part of the model estimation. The presence of two latent variables, the group- and the state-identifying indicators, calls for Bayesian Markov chain Monte Carlo techniques. An application to individual bank lending data of the US banking sector illustrates the methodology. We obtain results that are broadly consistent with the bank lending view. Moreover, we infer a significant asymmetric effect of monetary policy over time which favors the evidence for models of credit cycles.

Tags

Press 'enter' for creating the tag

Publication's profile

Status of publication Published
Affiliation WU
Type of publication Paper presented at an academic conference or symposium
Language English
Title Bayesian Clustering of Many Short Time Series
Event CORE (Center for Operations Research and Econometrics)
Year 2002
Date 30.10
Country France
Location Louvain-la-Neuve

Associations

People
Frühwirth-Schnatter, Sylvia (Details)
Organization
Institute for Statistics and Mathematics IN (Details)
Google Scholar: Search