Uncovering Regimes in Out of Sample Forecast Errors from Predictive Regressions*

We introduce a set of test statistics for assessing the presence regimes in out sample forecast errors produced by recursively estimated linear predictive regressions that can accommodate multiple highly persistent predictors. Our are designed to be robust chosen starting window size and shown both consistent locally powerful. Their limiting null distributions also free nuisance parameters hence degree persistence methods subsequently applied predictability value premium whose dynamics characterized state dependence.