Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables

Joshua C.C. Chan, Gary Koop

Research output: Working paperDiscussion paper

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 fiv-variate steady-state VAR.
LanguageEnglish
Place of PublicationGlasgow
PublisherUniversity of Strathclyde
Pages1-16
Number of pages17
Volume2011
Publication statusPublished - Jan 2011

Fingerprint

Modeling
Macroeconomic variables
Econometric methodology
Clustering
Multivariate models
Uncertainty

Keywords

  • multivariate modelling
  • bayesian
  • bayesian clustering
  • econometrics
  • steady-state VAR

Cite this

Chan, J. C. C., & Koop, G. (2011). Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables. (11 ed.) (pp. 1-16). Glasgow: University of Strathclyde.
Chan, Joshua C.C. ; Koop, Gary. / Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables. 11. ed. Glasgow : University of Strathclyde, 2011. pp. 1-16
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Chan, JCC & Koop, G 2011 'Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables' 11 edn, University of Strathclyde, Glasgow, pp. 1-16.

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

11. ed. Glasgow : University of Strathclyde, 2011. p. 1-16.

Research output: Working paperDiscussion paper

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N2 - 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 fiv-variate steady-state VAR.

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Chan JCC, Koop G. Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables. 11 ed. Glasgow: University of Strathclyde. 2011 Jan, p. 1-16.