Granger Causal Priority and Choice of Variables in Vector Autoregressions

A-Tier
Journal: Review of Economics and Statistics
Year: 2017
Volume: 99
Issue: 2
Pages: 319-329

Score contribution per author:

2.011 = (α=2.01 / 2 authors) × 2.0x A-tier

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

Abstract

We derive a closed-form expression for the posterior probability of Granger noncausality in a gaussian vector autoregression with a conjugate prior. We also express in closed form the posterior probability of Granger causal priority, a more general relation that accounts for indirect effects between variables and therefore is suitable in a multivariate context. One can use these results to answer the classic question, “Is variable z relevant for variable x?” and to choose variables for a vector autoregression.

Technical Details

RePEc Handle
repec:tpr:restat:v:99:y:2017:i:2:p:319-329
Journal Field
General
Author Count
2
Added to Database
2026-01-25