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Real-time model uncertainty in the United States: 'Robust' policies put to the test

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  • Robert J. Tetlow

Abstract

I study 46 vintages of FRB/US, the principal macro model used by Federal Reserve Board staff for forecasting and policy analysis, as measures of real-time model uncertainty. I also study the implications of model uncertainty for the robustness of commonly applied, simple monetary policy rules. I first document that model uncertainty poses substantial challenges for policymakers in that key model properties differ in important ways across model vintages. Then I show that the parameterization of optimized simple policy rule--rules that are intended to be robust with respect to model uncertainty--also differ substantially across model vintages. Included in the set of rules are rules that eschew feedback on the output gap, rules that target nominal income growth, and rules that allow for time variation in the equilibrium real interest rate. I find that many rules, which previous research has shown to be robust in artificial economies, would have failed to provide adequate stabilization in the real-time, real-world environment seen by the Fed staff. However, I do identify certain policy rules that would have performed relatively well, and I characterize the key features of those rules to draw more general lessons about the design of monetary policy under model uncertainty.

Suggested Citation

  • Robert J. Tetlow, 2010. "Real-time model uncertainty in the United States: 'Robust' policies put to the test," Finance and Economics Discussion Series 2010-15, Board of Governors of the Federal Reserve System (US).
  • Handle: RePEc:fip:fedgfe:2010-15
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    References listed on IDEAS

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    1. McCallum, Bennett T. & Nelson, Edward, 1999. "Nominal income targeting in an open-economy optimizing model," Journal of Monetary Economics, Elsevier, vol. 43(3), pages 553-578, June.
    2. Glenn D. Rudebusch, 2002. "Assessing Nominal Income Rules for Monetary Policy with Model and Data Uncertainty," Economic Journal, Royal Economic Society, vol. 112(479), pages 402-432, April.
    3. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    4. Aoki, Kosuke, 2003. "On the optimal monetary policy response to noisy indicators," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 501-523, April.
    5. Kimura, Takeshi & Kurozumi, Takushi, 2007. "Optimal monetary policy in a micro-founded model with parameter uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 399-431, February.
    6. Jacopo Cimadomo, 2012. "Fiscal Policy in Real Time," Scandinavian Journal of Economics, Wiley Blackwell, vol. 114(2), pages 440-465, June.
    7. Orphanides, Athanasios & Porter, Richard D. & Reifschneider, David & Tetlow, Robert & Finan, Frederico, 2000. "Errors in the measurement of the output gap and the design of monetary policy," Journal of Economics and Business, Elsevier, vol. 52(1-2), pages 117-141.
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    Cited by:

    1. Orphanides, Athanasios & Williams, John C., 2008. "Learning, expectations formation, and the pitfalls of optimal control monetary policy," Journal of Monetary Economics, Elsevier, vol. 55(Supplemen), pages 80-96, October.
    2. Athanasios Orphanides & John C. Williams, 2009. "Imperfect Knowledge and the Pitfalls of Optimal Control Monetary Policy," 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 4, pages 115-144 Central Bank of Chile.
    3. Szabolcs Deák & Paul Levine & Afrasiab Mirza & Joseph Pearlman, 2019. "Designing Robust Monetary Policy Using Prediction Pools," School of Economics Discussion Papers 1219, School of Economics, University of Surrey.
    4. Athanasios Orphanides & John C. Williams, 2013. "Monetary Policy Mistakes and the Evolution of Inflation Expectations," NBER Chapters,in: The Great Inflation: The Rebirth of Modern Central Banking, pages 255-288 National Bureau of Economic Research, Inc.
    5. Williams, John C., 2016. "Rules of engagement," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.
    6. repec:eee:jmacro:v:54:y:2017:i:pa:p:59-71 is not listed on IDEAS
    7. Ironside, Brian & Tetlow, Robert J., 2005. "Real-Time Model Uncertainty in the United States: the Fed from 1996-2003," CEPR Discussion Papers 5305, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    Monetary policy ; Uncertainty ; Economic forecasting;

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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