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Forecasting Exchange Rates Out-of-Sample with Panel Methods and Real-Time Data

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  • Onur Ince

Abstract

This paper evaluates out-of-sample exchange rate forecasting with Purchasing Power Parity (PPP) and Taylor rule fundamentals for 9 OECD countries vis-à-vis the U.S. dollar over the period from 1973:Q1 to 2009:Q1 at short and long horizons. In contrast with previous work, which reports “forecasts” using revised data, I construct a quarterly real-time dataset that incorporates only the information available to market participants when the forecasts are made. Using bootstrapped out-of-sample test statistics, the exchange rate model with Taylor rule fundamentals performs better at the one-quarter horizon and panel estimation is not able to improve its performance. The PPP model, however, forecasts better at the 16-quarter horizon and its performance increases in panel framework. The results are in accord with previous research on long-run PPP and Taylor rule models. Key Words: Exchange Rate Forecasting, Taylor Rules, Real-Time Data, Out-of-Sample Test Statistics

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Paper provided by Department of Economics, Appalachian State University in its series Working Papers with number 13-04.

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Date of creation: 2013
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Handle: RePEc:apl:wpaper:13-04
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Find related papers by JEL classification:
  • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
  • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
  • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
  • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
  • F31 - International Economics - - International Finance - - - Foreign Exchange
  • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

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Cited by:

  1. Minford, Patrick & Xu, Yongdeng & Zhou, Peng, 2014. "How good are out of sample forecasting Tests on DSGE models?," CEPR Discussion Papers 10239, C.E.P.R. Discussion Papers.
  2. Galimberti, Jaqueson K. & Moura, Marcelo L., 2010. "Taylor Rules and Exchange Rate Predictability in Emerging Economies," Insper Working Papers wpe_214, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
  3. Christian D. Dick & Ronald MacDonald & Lukas Menkhoff, 2014. "Exchange Rate Forecasts and Expected Fundamentals," Kiel Working Papers 1974, Kiel Institute for the World Economy.
  4. Michele Ca’ Zorzi & Jakub Muck & Michal Rubaszek, 2016. "Real Exchange Rate Forecasting and PPP: This Time the Random Walk Loses," Open Economies Review, Springer, vol. 27(3), pages 585-609, July.
  5. Byrne, Joseph P & Korobilis, Dimitris & Ribeiro, Pinho J, 2014. "Exchange Rate Predictability in a Changing World," MPRA Paper 53684, University Library of Munich, Germany.
  6. Kumar, Anil & Orrenius, Pia M., 2014. "A closer look at the Phillips curve using state-level data," Working Papers 1409, Federal Reserve Bank of Dallas.
  7. Ca' Zorzi, Michele & Kolasa, Marcin & Rubaszek, Michał, 2016. "Exchange rate forecasting with DSGE models," Working Paper Series 1905, European Central Bank.

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