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

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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.

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  • E Pavlidis & I Paya & D Peel, 2009. "Forecasting the Real Exchange Rate using a Long Span of Data. A Rematch: Linear vs Nonlinear," Working Papers 601190, Lancaster University Management School, Economics Department.
    • Handle: RePEc:lan:wpaper:601190
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    Cited by:

    1. Yoon, Gawon, 2010. "Do real exchange rates really follow threshold autoregressive or exponential smooth transition autoregressive models?," Economic Modelling, Elsevier, vol. 27(2), pages 605-612, March.

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