TESTING FOR GRANGER FULL CAUSALITY

• 成果类型: Article
• 署名作者: COVEY, T; BESSLER, DA
• 署名单位: Texas A&M University System; Texas A&M University College Station
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.2307/2109552
• 发表日期: 1992-02
• 页码: 146-153
• 关键词: prequential analysis; futures prices; cattle prices; INFORMATION; MARKETS; money; spot; cash

摘要

A procedure is proposed to test for the existence of a fully causal relationship between two variables. The method involves contrasting the probabilistic forecasting performance of a univariate and bivariate specification for the same variable Y. If there exists some theory or belief that X causes Y, and the addition of a variable X to the information set of a prequential forecasting system for a variable Y reduces miscalibration and/or the level of forecast uncertainty with respect to Y's distribution for the next period, then a fully causal effect running from X to Y may be inferred. Vector autoregression allows testing for feedback. The method is applied to the issue of causality between the live cattle futures market and a major slaughter cattle cash market.