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Bayesian VAR Forecasts, Survey Information and Structural Change in the Euro Area

Gergely Ganics and Florens Odendahl ()

Working papers from Banque de France

Abstract: We incorporate external information extracted from the European Central Bank's Survey of Professional Forecasters into the predictions of a Bayesian VAR, using entropic tilting and soft conditioning. The resulting conditional forecasts significantly improve the plain BVAR point and density forecasts. Importantly, we do not restrict the forecasts at a specific quarterly horizon, but their possible paths over several horizons jointly, as the survey information comes in the form of one- and two-year-ahead expectations. Besides improving the accuracy of the variable that we target, the spillover effects to ``other-than-targeted'' variables are relevant in size and statistically significant. We document that the baseline BVAR exhibits an upward bias for GDP growth after the financial crisis and our results provide evidence that survey forecasts can help mitigate the effects of structural breaks on the forecasting performance of a popular macroeconometric model.

Keywords: : Survey of Professional Forecasters; Density forecasts; Entropic tilting; Soft conditioning. (search for similar items in EconPapers)
JEL-codes: C53 C32 E37 (search for similar items in EconPapers)
Pages: 65 pages
Date: 2019
New Economics Papers: this item is included in nep-eec, nep-ets, nep-for and nep-mac
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Working Paper: Bayesian VAR forecasts, survey information and structural change in the euro area (2019) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:bfr:banfra:733

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