Adaptive Minnesota Prior for High-Dimensional Vector Autoregressions
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Cited by:
- Gregor Kastner & Florian Huber, 2020.
"Sparse Bayesian vector autoregressions in huge dimensions,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
- Gregor Kastner & Florian Huber, 2017. "Sparse Bayesian vector autoregressions in huge dimensions," Papers 1704.03239, arXiv.org, revised Dec 2019.
- Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019.
"Mind the gap: A multi-country BVAR benchmark for the Eurosystem projections,"
International Journal of Forecasting, Elsevier, vol. 35(4), pages 1658-1668.
- Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: a multi-country BVAR benchmark for the Eurosystem projections," Working Paper Series 2227, European Central Bank.
- Martin Feldkircher & Luis Gruber & Florian Huber & Gregor Kastner, 2017.
"Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?,"
Papers
1711.00564, arXiv.org, revised Mar 2024.
- Martin Feldkircher & Florian Huber & Gregor Kastner, 2018. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Papers wuwp260, Vienna University of Economics and Business, Department of Economics.
- Feldkircher, Martin & Kastner, Gregor & Huber, Florian, 2018. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Paper Series 260, WU Vienna University of Economics and Business.
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Keywords
Bayesian VARs; Minnesota prior; Large datasets; Macroeconomic forecasting;All these keywords.
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2017-01-01 (Econometrics)
- NEP-ETS-2017-01-01 (Econometric Time Series)
- NEP-MAC-2017-01-01 (Macroeconomics)
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