Balanced predictive regressions

In a predictive regression, a less persistent return series is regressed on the first lag of some highly persistent predictors. Therefore, predictability could often be missed due to the persistence imbalance. The aim of this paper is to balance the predictive regression by augmenting it with an additional lag of the predictors. This second lag generally reduces the persistence level on the right-hand side of the equation to achieve balance. We then propose a simple test procedure for univariate and multivariate predictive regressions, based on least squares estimation. Empirically, we reexamine the popular predictors in the literature and find quite different results.