Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks

Markus Jochmann, Gary Koop, Rodney W. Strachan

Research output: Working paper

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Abstract

This paper builds a model which has two extensions over a standard VAR. The …rst of these is stochastic search variable selection, which is an automatic model selection device which allows for coefficients in a possibly over-parameterized VAR to be set to zero. The second allows for an unknown number of structual breaks in the VAR parameters. We investigate the in-sample and forecasting performance of our model in an application involving a commonly-used US macro-economic data set. We …nd that, in-sample, these extensions clearly are warranted. In a recursive forecasting exercise, we …nd moderate improvements over a standard VAR, although most of these improvements are due to the use of stochastic search variable selection rather than the inclusion of breaks.
Original languageEnglish
Place of PublicationGlasgow
PublisherUniversity of Strathclyde
Number of pages34
Publication statusUnpublished - Jun 2008

Keywords

  • Bayesian forecasting
  • forecasting
  • stochastic search
  • variable selection
  • economic theory

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  • Research Output

    Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks

    Jochmann, M., Koop, G. & Strachan, R. W., Apr 2010, In : International Journal of Forecasting. 26, 2, p. 326-347 21 p.

    Research output: Contribution to journalArticle

  • 18 Citations (Scopus)

    Cite this

    Jochmann, M., Koop, G., & Strachan, R. W. (2008). Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks. University of Strathclyde.