Kastner, Gregor, Huber, Forian. 2020. Sparse Bayesian Vector Autoregressions in Huge Dimensions. Journal of Forecasting. 39 1142-1165.
BibTeX
Abstract
We develop a Bayesian vector autoregressive (VAR) model with multivariate stochastic volatility that is capable of handling vast dimensional information sets. Three features are introduced to permit reliable estimation of the model. First, we assume that the reduced‐form errors in the VAR feature a factor stochastic volatility structure, allowing for conditional equation‐by‐equation estimation. Second, we apply recently developed global‐local shrinkage priors to the VAR coefficients to cure the curse of dimensionality. Third, we utilize recent innovations to efficiently sample from high‐dimensional multivariate Gaussian distributions. This makes simulation‐based fully Bayesian inference feasible when the dimensionality is large but the time series length is moderate. We demonstrate the merits of our approach in an extensive simulation study and apply the model to US macroeconomic data to evaluate its forecasting capabilities.
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Status of publication | Published |
---|---|
Affiliation | WU |
Type of publication | Journal article |
Journal | Journal of Forecasting |
Citation Index | SSCI |
WU Journalrating 2009 | A |
WU-Journal-Rating new | FIN-A, INF-A, MAR-B, STRAT-B, VW-D, WH-B |
Language | English |
Title | Sparse Bayesian Vector Autoregressions in Huge Dimensions |
Volume | 39 |
Year | 2020 |
Page from | 1142 |
Page to | 1165 |
Reviewed? | Y |
URL | https://onlinelibrary.wiley.com/doi/abs/10.1002/for.2680 |
DOI | https://doi.org/10.1002/for.2680 |
Open Access | Y |
Open Access Link | https://onlinelibrary.wiley.com/doi/abs/10.1002/for.2680 |
Associations
- Projects
- High-dimensional statistical learning: New methods to advance economic and sustainability policies
- People
- Kastner, Gregor (Details)
- External
- Huber, Forian (University of Salzburg, Austria)
- Organization
- Institute for Statistics and Mathematics IN (Details)
- Research areas (ÖSTAT Classification 'Statistik Austria')
- 1162 Statistics (Details)
- 5323 Econometrics (Details)
- 5701 Applied statistics (Details)
- 5707 Time series analysis (Details)