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A simple recursive forecasting model

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Author Info

  • Branch, William A.
  • Evans, George W.

Abstract

We compare the performance of alternative recursive forecasting models. A simple constant gain algorithm, used widely in the learning literature, both forecasts well out of sample and also provides the best fit to the Survey of Professional Forecasters.

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File URL: http://www.sciencedirect.com/science/article/B6V84-4JVTBK3-2/2/76d78068e170e36779157eb5cba7fac7
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Bibliographic Info

Article provided by Elsevier in its journal Economics Letters.

Volume (Year): 91 (2006)
Issue (Month): 2 (May)
Pages: 158-166

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Handle: RePEc:eee:ecolet:v:91:y:2006:i:2:p:158-166

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  1. Tom Stark & Dean Croushore, 2001. "Forecasting with a real-time data set for macroeconomists," Working Papers 01-10, Federal Reserve Bank of Philadelphia.
  2. Wiliam Branch & George W. Evans, 2005. "Model Uncertainty and Endogenous Volatility," University of Oregon Economics Department Working Papers 2005-21, University of Oregon Economics Department, revised 26 Oct 2006.
  3. Stark, Tom & Croushore, Dean, 2002. "Reply to the comments on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 563-567, December.
  4. Pesaran, M Hashem & Timmermann, Allan, 1995. " Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-28, September.
  5. Evans, George W. & Honkapohja , Seppo, 2003. "Policy interaction, expectations and the liquidity trap," Research Discussion Papers 22/2003, Bank of Finland.
  6. Milani, Fabio, 2007. "Expectations, learning and macroeconomic persistence," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2065-2082, October.
  7. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
  8. James H. Stock & Mark W. Watson, 1994. "Evidence on Structural Instability in Macroeconomic Time Series Relations," NBER Technical Working Papers 0164, National Bureau of Economic Research, Inc.
  9. Cho, In-Koo & Kasa, Kenneth, 2008. "Learning Dynamics And Endogenous Currency Crises," Macroeconomic Dynamics, Cambridge University Press, vol. 12(02), pages 257-285, April.
  10. Kenneth Kasa, 2000. "Learning, large deviations, and recurrent currency crises," Working Paper Series 2000-10, Federal Reserve Bank of San Francisco.
  11. Cho, In-Koo & Sargent, Thomas J., 2000. "Escaping Nash inflation," Working Paper Series 0023, European Central Bank.
  12. James B. Bullard & John Duffy, 2004. "Learning and structural change in macroeconomic data," Working Papers 2004-016, Federal Reserve Bank of St. Louis.
  13. William Poole, 2002. "Flation," Speech 49, Federal Reserve Bank of St. Louis.
  14. Andrew C. Harvey, 1990. "The Econometric Analysis of Time Series, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 026208189x, December.
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