Large Bayesian vector auto regressions

B-Tier
Journal: Journal of Applied Econometrics
Year: 2010
Volume: 25
Issue: 1
Pages: 71-92

Score contribution per author:

0.670 = (α=2.01 / 3 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:wly:japmet:v:25:y:2010:i:1:p:71-92
Journal Field
Econometrics
Author Count
3
Added to Database
2026-01-24