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The time-varying evolution of inflation risks
The time-varying evolution of inflation risks
Publication metadata
This paper develops a Bayesian quantile regression model with time-varying parameters (TVPs) for forecasting inflation risks. The proposed parametric methodology bridges the empirically established benefits of TVP regressions for forecasting inflation with the ability of quantile regression to model flexibly the whole distribution of inflation. In order to make our approach accessible and empirically efficient Gibbs sampler by transforming the state-space form of the TVP quantile regression into an equivalent high-dimensional regression form. An application of this methodology points to a good forecasting performance of quantile regressions with TVPs augmented with specific credit and money-based indicators for the prediction of the conditional distribution of inflation in the euro area, both in the short and longer run, and specifically for tail risks.
- Published:
- Corporate author(s): European Central Bank
- Personal author(s): Musso, Alberto ; Landau, Bettina ; Korobilis, Dimitris ; Phella, Anthoulla
- Themes: Economy — Finance
- Subject: economic cycle , economic forecasting , economic indicator , economic model , euro area , financial risk , inflation
ISSN
1725-2806
ISBN
978-92-899-4853-1
DOI
10.2866/861413
Catalogue number
QB-AR-21-091-EN-N
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| ISSN 1725-2806 | ISBN 978-92-899-4853-1 | DOI 10.2866/861413 | Catalogue number QB-AR-21-091-EN-N |
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