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Taylor Rules and the Euro

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  • Tanya Molodtsova
  • Alex Nikolsko-Rzhevskyy
  • David H. Papell

Abstract

This paper uses real-time data to show that inflation and either the output gap or unemployment, the variables which normally enter central banks' Taylor rules for interest-rate-setting, can provide evidence of out-of-sample predictability and forecasting ability for the United States Dollar/Euro exchange rate from the inception of the Euro in 1999 to the end of 2007. 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. The strongest evidence is found for specifications that neither incorporate interest rate smoothing nor include the real exchange rate in the forecasting regression, and 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. The evidence is stronger with inflation forecasts than with inflation rates and with real-time data than with revised data. Bad news about inflation and good news about real economic activity both lead to out-of-sample predictability and forecasting ability through forecasted exchange rate appreciation.

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Paper provided by Department of Economics, Emory University (Atlanta) in its series Emory Economics with number 0903.

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Date of creation: Feb 2009
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Handle: RePEc:emo:wp2003:0903

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  1. 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.
  2. Gourinchas, Pierre-Olivier & Tornell, Aaron, 2004. "Exchange rate puzzles and distorted beliefs," Journal of International Economics, Elsevier, vol. 64(2), pages 303-333, December.
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Cited by:
  1. Christophe Amat & Tomasz Michalski & Gilles Stoltz, 2014. "Forecasting exchange rates better than the random walk thanks to machine learning techniques," Working Papers halshs-01003914, HAL.
  2. Kenneth Rogoff, 2009. "Exchange rates in the modern floating era: what do we really know?," Review of World Economics (Weltwirtschaftliches Archiv), Springer, vol. 145(1), pages 1-12, April.
  3. Barbara Rossi, 2012. "Comment on "Taylor Rule Exchange Rate Forecasting during the Financial Crisis"," NBER Chapters, in: NBER International Seminar on Macroeconomics 2012, pages 106-116 National Bureau of Economic Research, Inc.
  4. Nikolsko-Rzhevskyy, Alex & Prodan, Ruxandra, 2012. "Markov switching and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 28(2), pages 353-365.
  5. Hayo, Bernd & Neuenkirch, Matthias, 2010. "Do Federal Reserve communications help predict federal funds target rate decisions?," Journal of Macroeconomics, Elsevier, vol. 32(4), pages 1014-1024, December.
  6. Onur Ince, 2013. "Forecasting Exchange Rates Out-of-Sample with Panel Methods and Real-Time Data," Working Papers 13-04, Department of Economics, Appalachian State University.
  7. Adriana Z. Fernandez & Evan F. Koenig & Alex Nikolsko-Rzhevskyy, 2011. "A real-time historical database for the OECD," Globalization and Monetary Policy Institute Working Paper 96, Federal Reserve Bank of Dallas.
  8. Carlos Lenz & Marcel Savioz, 2009. "Monetary determinants of the Swiss franc," Working Papers 2009-16, Swiss National Bank.
  9. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
  10. Andrew Levin & John B. Taylor, 2010. "Falling Behind the Curve: A Positive Analysis of Stop-Start Monetary Policies and the Great Inflation," NBER Working Papers 15630, National Bureau of Economic Research, Inc.
  11. Charles Engel, 2013. "Exchange Rates and Interest Parity," NBER Working Papers 19336, National Bureau of Economic Research, Inc.

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