English, Article, Journal or magazine article edition: Real-time conditional forecasts with Bayesian VARs: An application to New Zealand Chris Bloor; Troy Matheson

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Bookmark: http://trove.nla.gov.au/version/59604
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Real-time conditional forecasts with Bayesian VARs: An application to New Zealand
Author
  • Chris Bloor
  • Troy Matheson
Physical Description
  • preprint
Notes
  • We develop a large Bayesian VAR (BVAR) model of the New Zealand economy that incorporates the conditional forecasting estimation techniques of Waggoner and Zha (1999). We examine the real-time forecasting performance as the size of the model increases using an unbalanced data panel. In a realtime 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 8, 13, or 50 variable specifications for our dataset. Finally, we demonstrate techniques for imposing judgement and for forming a semi-structural interpretation of the BVAR forecasts.
  • RePEc:nzb:nzbdps:2009/​02
Language
  • English
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