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Analyzing Macroeconomic Forecastability

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Abstract

This paper estimates, using stochastic simulation and a multicountry macroeconometric model, the fraction of the forecast-error variance of output changes and the fraction of the forecast-error variance of inflation that are due to unpredictable asset-price changes. The results suggest that between about 25 and 37 percent of the forecast-error variance of output growth over 8 quarters is due to asset-price changes and between about 33 and 60 percent of the forecast-error variance of inflation over 8 quarters is due to asset-price changes. These estimates provide limits to the accuracy that can be expected from macroeconomic forecasting.

Suggested Citation

  • Ray C. Fair, 2009. "Analyzing Macroeconomic Forecastability," Cowles Foundation Discussion Papers 1706, Cowles Foundation for Research in Economics, Yale University, revised Aug 2010.
  • Handle: RePEc:cwl:cwldpp:1706
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    File URL: http://cowles.yale.edu/sites/default/files/files/pub/d17/d1706.pdf
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    References listed on IDEAS

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    1. James D. Hamilton, 2009. "Causes and Consequences of the Oil Shock of 2007-08," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 40(1 (Spring), pages 215-283.
    2. Marcelle Chauvet & Simon Potter, 2005. "Forecasting recessions using the yield curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(2), pages 77-103.
    3. Dominguez, Kathryn M & Fair, Ray C & Shapiro, Matthew D, 1988. "Forecasting the Depression: Harvard versus Yale," American Economic Review, American Economic Association, vol. 78(4), pages 595-612, September.
    4. Rudebusch, Glenn D. & Williams, John C., 2009. "Forecasting Recessions: The Puzzle of the Enduring Power of the Yield Curve," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 492-503.
    5. Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Rafael, 2007. "On the Fit of New Keynesian Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 123-143, April.
    6. Ireland, Peter N., 2004. "A method for taking models to the data," Journal of Economic Dynamics and Control, Elsevier, vol. 28(6), pages 1205-1226, March.
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    Cited by:

    1. Fair, Ray C., 2012. "Has macro progressed?," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 2-10.
    2. Ray C. Fair, 2010. "Estimated Macroeconomic Effects of the U.S. Stimulus Bill," Cowles Foundation Discussion Papers 1756, Cowles Foundation for Research in Economics, Yale University.
    3. Ray C. Fair, 2009. "Has Macro Progressed?," Cowles Foundation Discussion Papers 1728, Cowles Foundation for Research in Economics, Yale University, revised Jul 2010.
    4. Ray C. Fair, 2010. "Possible Macroeconomic Consequences of Large Future Federal Government Deficits," NBER Chapters,in: Tax Policy and the Economy, Volume 25, pages 89-108 National Bureau of Economic Research, Inc.
    5. Ulrich Heilemann & Susanne Schnorr-Bäcker, 2016. "Could The Start Of The German Recession 2008-2009 Have Been Foreseen? Evidence From Real-Time Data," Working Papers 2016-003, The George Washington University, Department of Economics, Research Program on Forecasting.

    More about this item

    Keywords

    Macroeconomic forecasting; Recessions; Booms;

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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