Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
997668 | International Journal of Forecasting | 2010 | 22 Pages |
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.
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Authors
Markus Jochmann, Gary Koop, Rodney W. Strachan,