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 (http://dx.doi.org/10.1016/j.ijforecast.2009.11.002)

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Abstract

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.

ORCID iDs

Jochmann, Markus, Koop, Gary ORCID logoORCID: https://orcid.org/0000-0002-6091-378X and Strachan, Rodney W.;
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