IDEAS home Printed from https://ideas.repec.org/p/ore/uoecwp/2005-3.html
   My bibliography  Save this paper

A Simple Recursive Forecasting Model

Author

Listed:
  • 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.

Suggested Citation

  • Wiliam Branch & George W. Evans, 2005. "A Simple Recursive Forecasting Model," University of Oregon Economics Department Working Papers 2005-3, University of Oregon Economics Department, revised 01 Feb 2005.
  • Handle: RePEc:ore:uoecwp:2005-3
    as

    Download full text from publisher

    File URL: http://economics.uoregon.edu/papers/UO-2005-3_Evans_Simple_Forecasting.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    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. Orphanides, Athanasios & Williams, John C., 2005. "The decline of activist stabilization policy: Natural rate misperceptions, learning, and expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1927-1950, November.
    4. 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.
    5. 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.
    6. 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, February.
    7. William Poole & Robert H. Rasche, 2002. "Flation," Review, Federal Reserve Bank of St. Louis, vol. 84(Nov), pages 1-6.
      • William Poole, 2002. "Flation," Speech 49, Federal Reserve Bank of St. Louis.
    8. Cho, In-Koo & Kasa, Kenneth, 2008. "Learning Dynamics And Endogenous Currency Crises," Macroeconomic Dynamics, Cambridge University Press, vol. 12(2), pages 257-285, April.
    9. 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.
    10. 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.
    11. 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.
    12. Milani, Fabio, 2007. "Expectations, learning and macroeconomic persistence," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2065-2082, October.
    13. 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.
    14. 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.
    15. James B. Bullard & John Duffy, 2004. "Learning and structural change in macroeconomic data," Working Papers 2004-016, Federal Reserve Bank of St. Louis.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dmitri Kolyuzhnov & Anna Bogomolova, 2004. "Escape Dynamics: A Continuous Time Approximation," Econometric Society 2004 Latin American Meetings 27, Econometric Society.
    2. Massimiliano Marcellino, 2008. "A linear benchmark for forecasting GDP growth and inflation?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 305-340.
    3. Evans, George W. & Honkapohja, Seppo & Mitra, Kaushik, 2009. "Anticipated fiscal policy and adaptive learning," Journal of Monetary Economics, Elsevier, vol. 56(7), pages 930-953, October.
    4. Martin Ellison & Liam Graham & Jouko Vilmunen, 2006. "Strong Contagion with Weak Spillovers," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 9(2), pages 263-283, April.
    5. Kevin X.D. Huang & Zheng Liu & Tao Zha, 2009. "Learning, Adaptive Expectations and Technology Shocks," Economic Journal, Royal Economic Society, vol. 119(536), pages 377-405, March.
    6. 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.
    7. George W. Evans & Seppo Honkapohja, 2009. "Expectations, Learning and Monetary Policy: An Overview of Recent Research," Central Banking, Analysis, and Economic Policies Book Series, in: Klaus Schmidt-Hebbel & Carl E. Walsh & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series (ed.),Monetary Policy under Uncertainty and Learning, edition 1, volume 13, chapter 2, pages 027-076, Central Bank of Chile.
    8. Thomas Sargent & Noah Williams & Tao Zha, 2009. "The Conquest of South American Inflation," Journal of Political Economy, University of Chicago Press, vol. 117(2), pages 211-256, April.
    9. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the plausibility of adaptive learning in macroeconomics: A puzzling conflict in the choice of the representative algorithm," Centre for Growth and Business Cycle Research Discussion Paper Series 177, Economics, The University of Manchester.
    10. Carceles-Poveda, Eva & Giannitsarou, Chryssi, 2007. "Adaptive learning in practice," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2659-2697, August.
    11. Dmitri Kolyuzhnov & Anna Bogomolova, 2004. "Escape Dynamics: A Continuous Time Approximation," Econometric Society 2004 Far Eastern Meetings 557, Econometric Society.
    12. George W. Evans & Seppo Honkapohja, 2009. "Expectations, Learning and Monetary Policy: An Overview of Recent Research," Central Banking, Analysis, and Economic Policies Book Series, in: Klaus Schmidt-Hebbel & Carl E. Walsh & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series (ed.),Monetary Policy under Uncertainty and Learning, edition 1, volume 13, chapter 2, pages 027-076, Central Bank of Chile.
    13. Dmitri Kolyuzhnov & Anna Bogomolova, 2004. "Escape Dynamics: A Continuous Time Approximation," Computing in Economics and Finance 2004 190, Society for Computational Economics.
    14. Kim, Young Se, 2009. "Exchange rates and fundamentals under adaptive learning," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 843-863, April.
    15. Brecht Boone & Ewoud Quaghebeur, 2017. "Real-Time Parameterized Expectations And The Effects Of Government Spending," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 17/939, Ghent University, Faculty of Economics and Business Administration.
    16. In-Koo Cho & Kenneth Kasa, 2015. "Learning and Model Validation," Review of Economic Studies, Oxford University Press, vol. 82(1), pages 45-82.
    17. Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.
    18. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    19. James Bullard & Stefano Eusepi, 2005. "Did the Great Inflation Occur Despite Policymaker Commitment to a Taylor Rule?," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 324-359, April.
    20. Bullard, James & Cho, In-Koo, 2005. "Escapist policy rules," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1841-1865, November.

    More about this item

    Keywords

    constant gain; recursive learning; expectations;
    All these keywords.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ore:uoecwp:2005-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Bill Harbaugh (email available below). General contact details of provider: https://edirc.repec.org/data/deuorus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.