DP2008/Preliminary Draft Real-time conditional forecasts with Bayesian VARs: An application to New Zealand

We examine the real-time forecasting performance of Bayesian VARs (BVARs) of different sizes using an unbalanced data panel. In a real-time out-of-sample forecasting exercise, we find that our BVAR methodology outperforms univariate and VAR benchmarks, and produces comparable forecast accuracy to the judgementally-adjusted forecasts produced internally at the Reserve Bank of New Zealand. We analyse forecast performance and find that, while there are trade offs across different variables, a 35 variable BVAR generally performs better than smaller or larger specifications. Finally, we demonstrate some techniques for imposing judgement and for forming a semi-structural interpretation of the BVAR forecasts. ∗ The views expressed in this paper are those of the author(s) and do not necessarily reflect the views of the Reserve Bank of New Zealand. All errors and omissions are ours and the views expressed are not necessarily those of the Reserve Bank of New Zealand. † Address: Economics Department, Reserve Bank of New Zealand, 2 The Terrace, PO Box 2498, Wellington, New Zealand. email address: [email protected]. ISSN 1177-7567 c ©Reserve Bank of New Zealand