Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables

Joshua C.C. Chan, Gary Koop

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Macroeconomists working with multivariate models typically face uncertainty over which (if any) of their variables have long run steady states which are subject to breaks. Furthermore, the nature of the break process is often unknown. In this paper, we draw on methods from the Bayesian clustering literature to develop an econometric methodology which: i) finds groups of variables which have the same number of breaks; and ii) determines the nature of the break process within each group. We present an application involving a five-variate steady-state VAR.
LanguageEnglish
Pages186-193
Number of pages8
JournalComputational Statistics and Data Analysis
Volume76
Early online date18 May 2013
DOIs
Publication statusPublished - 1 Aug 2014

Fingerprint

Macroeconomics
Multivariate Models
Econometrics
Long-run
Modeling
Clustering
Uncertainty
Unknown
Methodology

Keywords

  • clustering
  • structural breaks
  • VAR
  • Bayesian

Cite this

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Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables. / Chan, Joshua C.C.; Koop, Gary.

In: Computational Statistics and Data Analysis, Vol. 76, 01.08.2014, p. 186-193.

Research output: Contribution to journalArticle

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