1 Forecasting the Real Exchange Rates Behavior: An Investigation of Nonlinear Competing Models

Abstract: There is a large amount of literature which finds that real exchange rates appear to be characterized by several non-linear specifications. While each of these nonlinear models “fits ” some particular real exchange rates series especially well, leading to good in-sample properties, the recent studies have not come to any consensus whether the nonlinear models provide a better specification than the linear model and/or the random walk model according to their out of sample forecasting performance. Our goal is to examine two important nonlinear methods (Band-TAR and ESTAR models) concerning their ability to generate out of sample forecasts, when estimating real exchange rate series for 20 OECD countries. We find strong evidence that the ESTAR model outperforms the random walk model and that neither the linear model nor the Band-TAR model significantly outperforms the random walk model, when forecasting out of sample. On the other hand, a comparison between the nonlinear models and the linear models would not be conclusive due to the low power of tests for predictive ability when bootstrapping critical values