Abstract
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 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 to be applied to the issue of causality between the live cattle futures market and a major slaughter cattle cash market. Copyright 1992 by MIT Press.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
