Taylor Rules and the Euro
This paper uses real-time data to analyze whether the variables that normally enter central banks’ interest-rate-setting rules, which we call Taylor rule fundamentals, can provide evidence of out-of-sample predictability for the United States Dollar/Euro exchange rate from the inception of the Euro in 1999 to the end of 2007. The major result of the paper is that the null hypothesis of no predictability can be rejected against an alternative hypothesis of predictability with Taylor rule fundamentals for a wide variety of specifications that include inflation and a measure of real economic activity in the forecasting regression. We also present less formal evidence that, with real-time data, the Taylor rule provides a better description of ECB than of Fed policy during this period. While the evidence of predictability is only found for specifications that do not include the real exchange rate in the forecasting regression, the results are robust to whether or not the coefficients on inflation and the real economic activity measure are constrained to be the same for the U.S. and the Euro Area and to whether or not there is interest rate smoothing. The evidence of predictability is stronger for real-time than for revised data, about the same with inflation forecasts as with inflation rates, and weakens if output gap growth is included in the forecasting regression. Bad news about inflation and good news about real economic activity both lead to out-of-sample predictability through forecasted exchange rate appreciation.
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Volume (Year): 43 (2011)
Issue (Month): (03)
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References listed on IDEAS
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- Gourinchas, Pierre-Olivier & Tornell, Aaron, 2004. "Exchange rate puzzles and distorted beliefs," Journal of International Economics, Elsevier, vol. 64(2), pages 303-333, December.
- Francis X. Diebold & Robert S. Mariano, 1994.
"Comparing Predictive Accuracy,"
NBER Technical Working Papers
0169, National Bureau of Economic Research, Inc.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
- Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
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