Uncovering Regimes in Out of Sample Forecast Errors from Predictive Regressions*
提出一组检验统计量，用于评估递归估计的线性预测回归产生的样本外预测误差中是否存在机制，该方法对高度持久预测变量和起始窗口大小具有稳健性，并应用于价值溢价的可预测性分析。
Abstract We introduce a set of test statistics for assessing the presence of regimes in out of sample forecast errors produced by recursively estimated linear predictive regressions that can accommodate multiple highly persistent predictors. Our test statistics are designed to be robust to the chosen starting window size and are shown to be both consistent and locally powerful. Their limiting null distributions are also free of nuisance parameters and hence robust to the degree of persistence of the predictors. Our methods are subsequently applied to the predictability of the value premium whose dynamics are shown to be characterized by state dependence.