The out-of-sample performance of an exact median-unbiased estimator for the near-unity AR(1) model

We analyse the forecasting performance of several strategies when estimating the near-unity AR(1) model. We focus on the Andrews' (1993) exact median-unbiased estimator (BC), the OLS estimator and the driftless random walk (RW). We also explore two pairwise combinations between these strategies. We do this to investigate whether BC helps in reducing forecast errors. Via simulations, we find that BC forecasts typically outperform OLS forecasts. When BC is compared to the RW we obtain mixed results, favouring the latter while the persistence of the true process increases. Interestingly, we find that the combination of BC-RW performs well in a near-unity scheme.