Fischer, Manfred M., Hauzenberger, Niko, Huber, Florian, Pfarrhofer, Michael. 2022. General Bayesian time-varying parameter VARs for predicting government bond yields. Journal of Applied Econometrics.
BibTeX
Abstract
US yield curve dynamics are subject to time-variation, but there is ambiguity about its precise form. This paper develops a vector autoregressive (VAR) model with time-varying parameters and stochastic volatility which treats the nature of parameter dynamics as unknown. Coefficients can evolve according to a random walk, a Markov switching process, observed predictors, or depend on a mixture of these. To decide which form is supported by the data and to carry out model selection, we adopt Bayesian shrinkage priors. Our framework is applied to model the US yield curve. We show that the model forecasts well, and focus on selected in-sample features to analyze determinants of structural breaks in US yield curve dynamics.
Tags
Press 'enter' for creating the tagPublication's profile
Status of publication | Published |
---|---|
Affiliation | WU |
Type of publication | Journal article |
Journal | Journal of Applied Econometrics |
Citation Index | SSCI |
WU Journalrating 2009 | A |
WU-Journal-Rating new | FIN-A, VW-B, WH-B |
Language | English |
Title | General Bayesian time-varying parameter VARs for predicting government bond yields |
Year | 2022 |
Reviewed? | Y |
DOI | na |
Open Access | N |
JEL | C11, C32, E43, E47 |
Associations
- People
- Fischer, Manfred M. (Details)
- Hauzenberger, Niko (Former researcher)
- Huber, Florian (Former researcher)
- Pfarrhofer, Michael (Former researcher)
- Organization
- Institute for Economic Geography and GIScience IN (Details)
- Research areas (Ă–STAT Classification 'Statistik Austria')
- 1162 Statistics (Details)
- 5371 Macroeconomics (Details)