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Does the FOMC Have Expertise, and Can It Forecast?

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Author Info
Philip Hans Franses (Econometric Institute, Erasmus University Rotterdam)
Michael McAleer (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute and Center for International Research on the Japanese Economy (CIRJE), Faculty of Economics, University of Tokyo)
Rianne Legerstee (Econometric Institute and Tinbergen Institute, Erasmus University Rotterdam)

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Abstract

The primary purpose of the paper is to answer the following two questions regarding the performance of the influential Federal Open Market Committee (FOMC) of the Federal Reserve System, in comparison with the forecasts contained in the "Greenbooks" of the professional staff of the Board of Governors: Does the FOMC have expertise, and can it forecast better than the staff? The FOMC forecasts that are analyzed in practice are nonreplicable forecasts. In order to evaluate such forecasts, this paper develops a model to generate replicable FOMC forecasts, and compares the staff forecasts, non-replicable FOMC forecasts, and replicable FOMC forecasts, considers optimal forecasts and efficient estimation methods, and presents a direct test of FOMC expertise on nonreplicable FOMC forecasts. The empirical analysis of Romer and Romer (2008) is reexamined to evaluate whether their criticisms of the FOMC's forecasting performance should be accepted unreservedly, or might be open to alternative interpretations.

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Paper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE F-Series with number CIRJE-F-648.

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Length: 27 pages
Date of creation: Aug 2009
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Handle: RePEc:tky:fseres:2009cf648

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  1. McAleer, Michael, 1992. "Efficient Estimation: The Rao-Zyskind Condition, Kruskal's Theorem and Ordinary Least Squares," The Economic Record, The Economic Society of Australia, vol. 68(200), pages 65-72, March.
  2. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2009. "Expert opinion versus expertise in forecasting," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 334-346. [Downloadable!] (restricted)
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  3. Patton, Andrew J. & Timmermann, Allan, 2007. "Testing Forecast Optimality Under Unknown Loss," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1172-1184, December. [Downloadable!] (restricted)
  4. Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October. [Downloadable!] (restricted)
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  5. Christina D. Romer & David H. Romer, 2004. "A New Measure of Monetary Shocks: Derivation and Implications," American Economic Review, American Economic Association, vol. 94(4), pages 1055-1084, September. [Downloadable!]
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  6. McAleer, Michael, 1995. "The significance of testing empirical non-nested models," Journal of Econometrics, Elsevier, vol. 67(1), pages 149-171, May. [Downloadable!] (restricted)
  7. Fiebig, Denzil G. & McAleer, Michael & Bartels, Robert, 1992. "Properties of ordinary least squares estimators in regression models with nonspherical disturbances," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 321-334. [Downloadable!] (restricted)
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