Predictive Consequences of Using Conditioning or Causal Variables
研究了基于两个信息集的预测，其中一个包含另一个及额外的因果变量，在一般成本函数下，包含因果变量的信息集预期成本更小。
Forecasts based on two information sets, one of which includes the other plus additional causal variables are considered. Given a general cost function of forecast errors, it is shown that the expected cost is smaller for the information set that includes the causal variables.