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A Simple Recursive Forecasting Model

Author Info

Listed author(s):
  • Wiliam Branch

    (University of California - Irvine)

  • George W. Evans

    ()

    (University of Oregon Economics Department)

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://economics.uoregon.edu/papers/UO-2005-3_Evans_Simple_Forecasting.pdf
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Paper provided by University of Oregon Economics Department in its series University of Oregon Economics Department Working Papers with number 2005-3.

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Length: 10
Date of creation: 01 Feb 2005
Date of revision: 01 Feb 2005
Handle: RePEc:ore:uoecwp:2005-3
Contact details of provider: Postal:
1285 University of Oregon, 435 PLC, Eugene, OR 97403-1285

Phone: (541) 346-8845
Fax: (541) 346-1243
Web page: http://economics.uoregon.edu/
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Keywords: constant gain; recursive learning; expectations;

Other versions of this item:

Find related papers by JEL classification:
  • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
  • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
  • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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  1. William Branch & George W. Evans, 2007. "Model Uncertainty and Endogenous Volatility," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 10(2), pages 207-237, April.
  2. George W. Evans & Seppo Honkapohja, 2005. "Policy Interaction, Expectations and the Liquidity Trap," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 303-323, April.
  3. 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.
  4. Kenneth Kasa, 2004. "Learning, Large Deviations, And Recurrent Currency Crises," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(1), pages 141-173, 02.
  5. William Poole & Robert H. Rasche, 2002. "Flation," Review, Federal Reserve Bank of St. Louis, issue Nov, pages 1-6.
    • William Poole, 2002. "Flation," Speech 49, Federal Reserve Bank of St. Louis.
  6. Cho, In-Koo & Kasa, Kenneth, 2008. "Learning Dynamics And Endogenous Currency Crises," Macroeconomic Dynamics, Cambridge University Press, vol. 12(02), pages 257-285, April.
  7. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
  8. In-Koo Cho & Noah Williams & Thomas J. Sargent, 2002. "Escaping Nash Inflation," Review of Economic Studies, Oxford University Press, vol. 69(1), pages 1-40.
  9. Andrew C. Harvey, 1990. "The Econometric Analysis of Time Series, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 026208189x, July.
  10. 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.
  11. Milani, Fabio, 2007. "Expectations, learning and macroeconomic persistence," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2065-2082, October.
  12. Pesaran, M Hashem & Timmermann, Allan, 1995. " Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.
  13. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
  14. James B. Bullard & John Duffy, 2004. "Learning and structural change in macroeconomic data," Working Papers 2004-016, Federal Reserve Bank of St. Louis.
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