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A Simple Recursive Forecasting Model

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Author Info
Wiliam Branch (University of California - Irvine)
George W. Evans () (University of Oregon Economics Department)

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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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Publisher Info
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

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Related research
Keywords: constant gain; recursive learning; expectations;

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

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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  5. Thomas Sargent & Noah Williams & Tao Zha, 2006. "The Conquest of South American Inflation," NBER Working Papers 12606, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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    Other versions:
  7. A. Orphanides & J. Williams, 2003. "The decline of activist stabilization policy: natural rate misperceptions, learning, and expectations," Proceedings, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
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  8. Fackler, James S., 2002. "Comment on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 559-562, December. [Downloadable!] (restricted)
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  13. Elliott, Graham, 2002. "Comments on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 533-539, December. [Downloadable!] (restricted)
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    Other versions:
  15. George W. Evans & Seppo Honkapohja, 2003. "Policy Interaction, Expectations and the Liquidity Trap," University of Oregon Economics Department Working Papers 2003-33, University of Oregon Economics Department, revised 06 Jul 2004. [Downloadable!]
    Other versions:
  16. 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. [Downloadable!] (restricted)
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  17. Bruce McGough, 2003. "Shocking Escapes," Computing in Economics and Finance 2003 294, Society for Computational Economics. [Downloadable!]
    Other versions:
  18. George W. Evans & William A. Branch, 2005. "Model Uncertainty and Endogenous Volatility," Computing in Economics and Finance 2005 33, Society for Computational Economics.
    Other versions:
  19. Cho, In-Koo & Williams, Noah & Sargent, Thomas J, 2002. "Escaping Nash Inflation," Review of Economic Studies, Blackwell Publishing, vol. 69(1), pages 1-40, January.
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  20. Fabio Milani, 2005. "Expectations, Learning and Macroeconomic Persistence," Macroeconomics 0510022, EconWPA. [Downloadable!]
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  21. George W. Evans & Garey Ramey, 2001. ""Adaptive Expectations, Underparameterization and the Lucas Critique," University of Oregon Economics Department Working Papers 2001-8, University of Oregon Economics Department, revised 01 Dec 2004. [Downloadable!]
    Other versions:
  22. 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.
    Other versions:
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