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Evaluating the use of real-time data in forecasting output levels and recessionary events in the US

Aristidou, Chrystalleni; Lee, Kevin; Shields, Kalvinder

Authors

Chrystalleni Aristidou

Kevin Lee kevin.lee@nottingham.ac.uk

Kalvinder Shields k.shields@unimelb.edu.au



Abstract

The paper proposes a modelling framework and evaluation procedure to judge the usefulness of real-time datasets incorporating past data vintages and survey expectations in forecasting. The analysis is based on `meta models' obtained using model-averaging techniques and judged by various statistical and economic criteria, including a novel criterion based on a fair bet. Analysing US output data over 1968q4-2015q1, we find both elements of the real-time data are useful with their contributions varying over time. Revisions data are particularly valuable for point and density forecasts of growth but survey expectations are important in forecasting rare recessionary events.

Journal Article Type Article
Publication Date Jan 1, 2019
Journal Journal of the Royal Statistical Society: Series A (Statistics in Society)
Print ISSN 0964-1998
Electronic ISSN 1467-985X
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 182
Issue 1
Pages 131-163
APA6 Citation Aristidou, C., Lee, K., & Shields, K. (2019). Evaluating the use of real-time data in forecasting output levels and recessionary events in the US. Journal of the Royal Statistical Society: Series A, 182(1), 131-163. doi:10.1111/rssa.12366
DOI https://doi.org/10.1111/rssa.12366
Keywords Real-time data; Revision; Survey; Forecasting; Model averaging; Output; Recession
Publisher URL https://rss.onlinelibrary.wiley.com/doi/abs/10.1111/rssa.12366
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf
Additional Information This is the peer reviewed version of the following article, which has been published in final form at https://rss.onlinelibra...abs/10.1111/rssa.12366. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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