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.
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Volume (Year): 74 (1992) Issue (Month): 1 (February) Pages: 146-53 Download reference. The following formats are available: HTML
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