Mean reversion in the US unemployment rate – evidence from bootstrapped out-of-sample forecasts

Abstract

This article investigates whether the US unemployment rate is best described as a unit-root or mean-reverting process. An out-of-sample forecast exercise is conducted in which the performance of an autoregressive (AR) model with an imposed unit root is compared with that of a mean-reverting AR model. A bootstrap distribution for the relative root mean square forecast error is generated and provides strong support for mean reversion in the US unemployment rate.