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Density forecasting with BVAR models under macroeconomic data uncertainty
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Clements, Michael P. and Galvão, Ana B. (2023) Density forecasting with BVAR models under macroeconomic data uncertainty. Journal of Applied Econometrics, 38 (2). pp. 164-185. doi:10.1002/jae.2944 ISSN 0883-7252.
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Official URL: https://doi.org/10.1002/jae.2944
Abstract
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, especially for the US.
Item Type: | Journal Article | ||||||||
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Subjects: | H Social Sciences > HB Economic Theory H Social Sciences > HG Finance Q Science > QA Mathematics |
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Divisions: | Faculty of Social Sciences > Warwick Business School | ||||||||
Library of Congress Subject Headings (LCSH): | Macroeconomics -- Econometric models, Economic forecasting, Stochastic processes , Inflation (Finance) | ||||||||
Journal or Publication Title: | Journal of Applied Econometrics | ||||||||
Publisher: | Wiley-Blackwell Publishing, Inc | ||||||||
ISSN: | 0883-7252 | ||||||||
Official Date: | March 2023 | ||||||||
Dates: |
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Volume: | 38 | ||||||||
Number: | 2 | ||||||||
Page Range: | pp. 164-185 | ||||||||
DOI: | 10.1002/jae.2944 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Date of first compliant deposit: | 3 October 2022 | ||||||||
Date of first compliant Open Access: | 27 January 2023 | ||||||||
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