A Reconsideration of the Meese-Rogoff Puzzle – Alternative Approaches to Model Estimation and Forecast Evaluation
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This study revisits the Meese-Rogoff puzzle by estimating the traditional monetary models of exchange rate determination in state-space form and comparing the accuracy of these forecasts against the naïve random walk model using a wide range of conventional and alternative measures of forecasting accuracy. The results demonstrate that incorporating stochastic movements in the parameters of exchange rate models does not enable the Meese-Rogoff puzzle to be overturned. However, estimating these models in state-space form substantially improves forecasting accuracy to the extent that the model and random walk produce an equivalent magnitude of error. Furthermore, the results prove that the Meese-Rogoff puzzle can be overturned if the forecasts are evaluated by alternative criteria. These criteria include direction accuracy, profitability, and measures that jointly take into account both magnitude and direction accuracy.
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Moosa, I.; Burns, Kelly (2015)The Messe-Rogoff puzzle has been a debatable topic since 1983 when Richard Meese and Kenneth Rogoff demonstrated that no exchange rate model can outperform the random walk in out-of-sample forecasting. This finding been ...
Moosa, I.; Burns, Kelly (2015)For the past 30 years international monetary economists have believed that exchange rate models cannot outperform the random walk in out-of-sample forecasting as a result of the 1983 paper written by Richard Meese and ...
Moosa, I.; Burns, Kelly (2014)Several explanations have been put forward for the Meese–Rogoff puzzle that exchange rate models cannot outperform the random walk in out-of-sample forecasting. We suggest that a simple explanation for the puzzle is the ...