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Forecasting FOMC Forecasts

Author

Listed:
  • S. Yanki Kalfa

    (International Monetary Fund)

  • Jaime Marquez

    (Johns Hopkins School of Advanced International Studies (SAIS))

Abstract

Summarizing Hendry’s forty years of work on taming uncertainty is "clear and distinct": Test, test, test. Sure - but test what? Test the maintained assumptions of the disturbances. Test the parameter restrictions of a given model. Test the explanatory power of a model against a rival model. In brief, test everything that is not clear and distinct. We implement Hendry’s view to forecast FOMC forecasts. Specifically, monetary policy is forward looking and, in its pursuit of transparency, it communicates its economic projections to the public at large. As a result, there is interest in whether these projections are credible. We argue that central to that credibility is the public’s ability to replicate FOMC’s projections using publicly available data only. In other words, is it possible to anticipate, reliably and independently, what the FOMC will anticipate for the federal funds rate? To address this question, we assemble FOMC projections from 1992 to 2017; examine their statistical properties; postulate models to predict FOMC projections; estimate the parameters of these models; and generate out-of-sample predictions for inflation, unemployment, and the federal funds rate for 2018. As the reader will soon realize, there is a lot more testing to be done.

Suggested Citation

  • S. Yanki Kalfa & Jaime Marquez, 2018. "Forecasting FOMC Forecasts," Working Papers 2018-007, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  • Handle: RePEc:gwc:wpaper:2018-007
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    References listed on IDEAS

    as
    1. Phillips, Peter C.B., 2005. "Automated Discovery In Econometrics," Econometric Theory, Cambridge University Press, vol. 21(1), pages 3-20, February.
    2. David Romer, 2010. "A New Data Set on Monetary Policy: The Economic Forecasts of Individual Members of the FOMC," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(5), pages 951-957, August.
    3. Natsuki Arai, 2016. "Evaluating the Efficiency of the FOMC's New Economic Projections," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(5), pages 1019-1049, August.
    4. Fendel, Ralf & Rülke, Jan-Christoph, 2012. "Are heterogeneous FOMC forecasts consistent with the Fed’s monetary policy?," Economics Letters, Elsevier, vol. 116(1), pages 5-7.
    5. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2017. "Evaluating Forecasts, Narratives and Policy Using a Test of Invariance," Econometrics, MDPI, vol. 5(3), pages 1-27, September.
    6. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423, Enero-Abr.
    7. Nakazono, Yoshiyuki, 2013. "Strategic behavior of Federal Open Market Committee board members: Evidence from members’ forecasts," Journal of Economic Behavior & Organization, Elsevier, vol. 93(C), pages 62-70.
    8. Stekler, Herman & Symington, Hilary, 2016. "Evaluating qualitative forecasts: The FOMC minutes, 2006–2010," International Journal of Forecasting, Elsevier, vol. 32(2), pages 559-570.
    9. Clements, Michael P. & Hendry, David F., 1998. "Forecasting economic processes," International Journal of Forecasting, Elsevier, vol. 14(1), pages 111-131, March.
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    Cited by:

    1. Jaime Marquez, 2023. "Stylized Facts of the FOMC’s Longer-Run Forecasts," JRFM, MDPI, vol. 16(3), pages 1-20, February.
    2. Thomas L. Hogan, 2022. "The calculus of dissent: Bias and diversity in FOMC projections," Public Choice, Springer, vol. 191(1), pages 105-135, April.

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    More about this item

    Keywords

    Autometrics; Federal Funds Rate; FOMC; Survey of Professional Forecasters;
    All these keywords.

    JEL classification:

    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics

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