The Taylor Rule and Forecast Intervals for Exchange Rates

Abstract

In this paper, we examine the Meese-Rogoff puzzle from a different perspective: out-of-sample interval forecasting. While most studies in the literature focus on point forecasts, we apply semiparametric interval forecasting to a group of exchange rate models. Forecast intervals for 10 OECD exchange rates are generated and the performance of the empirical exchange rate models are compared with the random walk. Our contribution is twofold. First, we find that in general, exchange rate models generate tighter forecast intervals than the random walk, given that their intervals cover out-of-sample exchange rate realizations equally well. Our results suggest a connection between exchange rates and economic fundamentals: economic variables contain information useful in forecasting distributions of exchange rates. We also find that the benchmark Taylor rule model performs better than the monetary, PPP and forward premium models, and its advantages are more pronounced at longer horizons. Second, the bootstrap inference framework proposed in this paper for forecast interval evaluation can be applied in a broader context, such as inflation forecasting.JEL codes: C14, C53, F31 Keywords: Meese-Rogoff puzzle, exchange rate forecast, interval forecasting, Taylor rule model. Meese and Rogoff (1983) find that economic fundamentals-such as the money supply, trade balance and national incomeare of little use in forecasting out-of-sample exchange rates. This finding has been termed the Meese-Rogoff puzzle. In defense of fundamental-based exchange rate models, various combinations of economic variables and econometric methods haveWe are grateful to Editor Ken West and two anonymous referees for valuable comments and suggestions that greatly improved the paper. We also thank

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“…Moreover, empirical evidence in favor of predictive ability of macroeconomic fundamentals has been mainly found at longer horizons (Engel et al, 2007). Cheung et al (2005) conclude that models with macroeconomic fundamentals cannot outperform the random walk and only models with Taylor rule fundamentals can have some predictive merit (Molodtsova and Papell, 2009;Wang and Wu, 2012).…”

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“…They find evidence that an interest rate reaction function in the form of a Taylor rule works particularly well. Similarly, Wang and Wu (2012) report that in their analysis of a group of exchange rate models for 10 OECD countries, the Taylor rule performs best empirically as a monetary policy rule. Taylor (2001) generally discusses the role of the exchange rate in monetary policy rules.…”