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Addressing COVID-19 outliers in BVARs with stochastic volatility
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| Authors and Corporations: | , , , |
|---|---|
| Other Authors: | Clark, Todd E. 1963- [Author] • Marcellino, Massimiliano 1970- [Author] • Mertens, Elmar [Author] |
| Type of Resource: | E-Book |
| Language: | English |
| published: |
Frankfurt am Main
Deutsche Bundesbank
[2022]
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| Series: |
Deutsche Bundesbank: Discussion paper ; no 2022, 13
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| Subjects: | |
| Source: | Verbunddaten SWB Lizenzfreie Online-Ressourcen |
| ISBN: |
9783957298812
3957298814 |
| Summary: | The COVID-19 pandemic has led to enormous data movements that strongly affect parameters and forecasts from standard VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine transitory and persistent changes in volatility. The resulting density forecasts are much less sensitive to outliers in the data than standard VARs. Predictive Bayes factors indicate that our outlier-augmented SV model provides the best data fit for the pandemic period, as well as for earlier subsamples of relatively high volatility. In historical forecasting, outlier-augmented SV schemes fare at least as well as a conventional SV model. |
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| Physical Description: | 1 Online-Ressource (circa 39 Seiten); Illustrationen |
| ISBN: |
9783957298812
3957298814 |