Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks
Jochmann, Markus and Koop, Gary and Strachan, Rodney W. (2010) Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks. International Journal of Forecasting, 26 (2). pp. 326-347. ISSN 0169-2070
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This paper builds a model which has two extensions over a standard VAR. The first of these is stochastic search variable selection, which is an automatic model selection device that allows coefficients in a possibly over-parameterized VAR to be set to zero. The second extension allows for an unknown number of structural breaks in the VAR parameters. We investigate the in-sample and forecasting performance of our model in an application involving a commonly-used US macroeconomic data set. In a recursive forecasting exercise, we find moderate improvements over a standard VAR, although most of these improvements are due to the use of stochastic search variable selection rather than to the inclusion of breaks.
Creators(s): |
Jochmann, Markus, Koop, Gary ![]() | Item type: | Article |
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ID code: | 14555 |
Notes: | Also available as a working paper (2008): http://personal.strath.ac.uk/gary.koop/jochmann_koop_strachan.pdf |
Keywords: | vector autoregressive model, predictive density, over-parameterization, structural break, shrinkage, Commerce, Business and International Management |
Subjects: | Social Sciences > Commerce |
Department: | Strathclyde Business School > Economics |
Depositing user: | Strathprints Administrator |
Date deposited: | 01 Apr 2010 14:13 |
Last modified: | 20 Jan 2021 18:19 |
Related URLs: | |
URI: | https://strathprints.strath.ac.uk/id/eprint/14555 |
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