Forecasting the Real Exchange Rate using a Long Span of Data. A Rematch: Linear vs Nonlinear

David A. Peel, Ivan Paya () and Efthymios G. Pavlidis

No 6075, Working Papers from Lancaster University Management School, Economics Department

Abstract: This paper deals with the nonlinear modeling and forecasting of the dollar-sterling real exchange rate using a long span 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 winner turns out to be the nonlinear model, against the odds.

Keywords: Real Exchange Rate; Nonlinearity; Robust Linearity Tests; Forecast Evaluation; Bootstrapping. (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-for, nep-ifn, nep-opm and nep-ore
Date: 2009
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Persistent link: http://EconPapers.repec.org/RePEc:lan:wpaper:006075

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