Granger Causal Priority and Choice of Variables in Vector Autoregressions

• 成果类型: Article
• 署名作者: Jarocinski, Marek; Mackowiak, Bartosz
• 署名单位: European Central Bank; Centre for Economic Policy Research - UK
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/REST_a_00601
• 发表日期: 2017-05
• 页码: 319-329
• 关键词: long-run causality; time-series; INFORMATION; models; ratio

摘要

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.