TY - JOUR
T1 - Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks
AU - Jochmann, Markus
AU - Koop, Gary
AU - Strachan, Rodney W.
N1 - Also available as a working paper (2008): http://personal.strath.ac.uk/gary.koop/jochmann_koop_strachan.pdf
PY - 2010/4
Y1 - 2010/4
N2 - 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.
AB - 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.
KW - vector autoregressive model
KW - predictive density
KW - over-parameterization
KW - structural break
KW - shrinkage
UR - http://www.scopus.com/inward/record.url?scp=77649272473&partnerID=8YFLogxK
UR - http://dx.doi.org/10.1016/j.ijforecast.2009.11.002
U2 - 10.1016/j.ijforecast.2009.11.002
DO - 10.1016/j.ijforecast.2009.11.002
M3 - Article
VL - 26
SP - 326
EP - 347
JO - International Journal of Forecasting
JF - International Journal of Forecasting
SN - 0169-2070
IS - 2
ER -