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Density forecasting with BVAR models under macroeconomic data uncertainty

Clements, M. ORCID: https://orcid.org/0000-0001-6329-1341 and Galvão, A. B. (2022) Density forecasting with BVAR models under macroeconomic data uncertainty. Journal of Applied Econometrics. ISSN 1099-1255 (In Press)

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Abstract/Summary

Macroeconomic data are subject to data revisions. Yet, the usual way of generating real-time density forecasts from BVAR models makes no allowance for data uncertainty from future data revisions. We develop methods of allowing for data uncertainty when forecasting with BVAR models with stochastic volatility. Firstly, the BVAR forecasting model is estimated on real-time vintages. Secondly, the BVAR model is jointly estimated with a model of data revisions such that forecasts are conditioned on estimates of the 'true' values. We find that this second method generally improves upon conventional practice for density forecasting, for the US.

Item Type:Article
Refereed:Yes
Divisions:Henley Business School > ICMA Centre
ID Code:106195
Publisher:Wiley

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