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The Taylor Rule and Forecast Intervals for Exchange Rates

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  • JIAN WANG
  • JASON J. WU

Abstract

This paper attacks the Meese-Rogoff (exchange rate disconnect) puzzle from a different perspective: out-of-sample interval forecasting. Most studies in the literature focus on point forecasts. In this paper, we apply Robust Semi-parametric (RS) interval forecasting to a group of Taylor rule models. Forecast intervals for twelve OECD exchange rates are generated and modified tests of Giacomini and White (2006) are conducted to compare the performance of Taylor rule models and the random walk. Our contribution is twofold. First, we find that in general, Taylor rule models generate tighter forecast intervals than the random walk, given that their intervals cover out-of-sample exchange rate realizations equally well. This result is more pronounced at longer horizons. Our results suggest a connection between exchange rates and economic fundamentals: economic variables contain information useful in forecasting the distributions of exchange rates. The benchmark Taylor rule model is also found to perform better than the monetary and PPP models. Second, the inference framework proposed in this paper for forecast-interval evaluation, can be applied in a broader context, such as inflation forecasting, not just to the models and interval forecasting methods used in this paper.

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File URL: http://hdl.handle.net/10.1111/j.1538-4616.2011.00470.x
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Bibliographic Info

Article provided by Blackwell Publishing in its journal Journal of Money, Credit and Banking.

Volume (Year): 44 (2012)
Issue (Month): 1 (02)
Pages: 103-144

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Handle: RePEc:mcb:jmoncb:v:44:y:2012:i:1:p:103-144

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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0022-2879

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Citations

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Cited by:
  1. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
  2. Mahir Binici & Yin-Wong Cheung, 2011. "Exchange Rate Dynamics Under Alternative Optimal Interest Rate Rules," Working Papers 362011, Hong Kong Institute for Monetary Research.
  3. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2011. "Can Oil Prices Forecast Exchange Rates?," CEPR Discussion Papers 8635, C.E.P.R. Discussion Papers.
  4. Apergis, Nicholas, 2014. "Can gold prices forecast the Australian dollar movements?," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 75-82.
  5. Bernd Hayo & Britta Niehof, 2013. "Studying International Spillovers in a New Keynesian Continuous Time Framework with Financial Markets," MAGKS Papers on Economics 201342, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  6. Uddin, Gazi Salah & Tiwari, Aviral Kumar & Arouri, Mohamed & Teulon, Frédéric, 2013. "On the relationship between oil price and exchange rates: A wavelet analysis," Economic Modelling, Elsevier, vol. 35(C), pages 502-507.
  7. Onur Ince & Tanya Molodtsova, 2013. "Real-Time Out-of-Sample Exchange Rate Predictability," Working Papers 13-03, Department of Economics, Appalachian State University.
  8. Bratu, Mihaela, 2013. "The Assessment And Improvement Of The Accuracy For The Forecast Intervals," Working Papers of Macroeconomic Modelling Seminar 132602, Institute for Economic Forecasting.
  9. Charles Engel, 2013. "Exchange Rates and Interest Parity," NBER Working Papers 19336, National Bureau of Economic Research, Inc.

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