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Forecast Evaluation of Nonlinear Models: The Case of Long‐Span Real Exchange Rates
Author(s) -
Pavlidis Efthymios G.,
Paya Ivan,
Peel David A.
Publication year - 2012
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.1247
Subject(s) - autoregressive model , econometrics , nonlinear system , us dollar , random walk , exchange rate , liberian dollar , economics , series (stratigraphy) , linear model , computer science , mathematics , statistics , macroeconomics , finance , paleontology , physics , quantum mechanics , biology
This paper deals with the nonlinear modeling and forecasting of the dollar–sterling and franc–sterling real exchange rates using long spans of data. Our contribution is threefold. First, we provide significant evidence of smooth transition dynamics in the series by employing a battery of recently developed in‐sample statistical tests. Second, we investigate the small‐sample properties of several evaluation measures for comparing recursive forecasts when one of the competing models is nonlinear. Finally, we run a forecasting race for the post‐Bretton Woods era between the nonlinear real exchange rate model, the random walk, and the linear autoregressive model. The nonlinear model outperforms all rival models in the dollar–sterling case but cannot beat the linear autoregressive in the franc–sterling. Copyright © 2011 John Wiley & Sons, Ltd.