The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Large Bayesian vector auto regressions
Abstract
This paper shows that vector auto regression (VAR) with Bayesian shrinkage is an appropriate tool for large dynamic models. We build on the results of De Mol and co‐workers (2008) and show that, when the degree of shrinkage is set in relation to the cross‐sectional dimension, the forecasting performance of small monetary VARs can be improved by adding additional macroeconomic variables and sectoral information. In addition, we show that large VARs with shrinkage produce credible impulse responses and are suitable for structural analysis. Copyright © 2009 John Wiley & Sons, Ltd.
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Citations
Cites
Does Information Help Recovering Structural Shocks from past Observations?
Giannone, D., & Reichlin, L. (2006) · Journal of the European Economic Association · doi:10.1162/jeea.2006.4.2-3.455 · Cited by 133
Self-citation
Cited by
Prior Selection for Vector Autoregressions
Giannone, D., Lenza, M., & Primiceri, G. E. (2015) · Review of Economics and Statistics · doi:10.1162/rest_a_00483 · Cited by 710
Self-citationUS Monetary Policy and the Global Financial Cycle
Miranda-Agrippino, S., & Rey, H. (2015) · National Bureau of Economic Research · doi:10.3386/w21722 · Cited by 490
Now-Casting and the Real-Time Data Flow
Bańbura, M., Giannone, D., Modugno, M., & Reichlin, L. (2013) · Handbook of Economic Forecasting · doi:10.1016/b978-0-444-53683-9.00004-9 · Cited by 448
Self-citationRegularized estimation in sparse high-dimensional time series models
Basu, S., & Michailidis, G. (2015) · The Annals of Statistics · doi:10.1214/15-aos1315 · Cited by 345
Forecasting stock returns under economic constraints
Pettenuzzo, D., Timmermann, A., & Valkanov, R. (2014) · Journal of Financial Economics · doi:10.1016/j.jfineco.2014.07.015 · Cited by 293
Metadata
- Authors
- Bańbura, M., Giannone, D., & Reichlin, L.
- Venue
- Journal of Applied Econometrics
- Publisher
- Wiley
- Published
- 2010-01
- Volume
- 25
- Issue
- 1
- Pages
- 71-92
- ISSN
- 0883-7252 (ISSN-L)
- 1099-1255
- OpenAlex
- W2056186894
- Cited by
- 1,151
- References
- 1
- FWCI
- 58.55
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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