Tests for Forecast Encompassing
针对同一变量的两个预测，提出检验一个预测是否包含另一个预测信息的方法，发现传统最小二乘检验对非正态误差不稳健，并给出稳健替代检验。
We consider the situation in which two forecasts of the same variable are available. The possibility exists of forming a combined forecast as a weighted average of the individual ones and estimating the weights that should be optimally attached to each forecast. If the entire weight should optimally be associated with one forecast, that forecast is said to encompass the other. A natural test for forecast encompassing is based on least squares regression. We find, however, that the null distribution of this test statistic is not robust to nonnormality in the forecast errors. We discuss several alternative tests that are robust.