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Jointly Evaluating the Federal Reserve’s Forecasts of GDP Growth and Inflation

Author

Listed:
  • Tara M. Sinclair

    (Department of Economics, George Washington University)

  • Edward N. Gamber

    (Department of Economics and Business, Lafayette College)

  • H.O. Stekler

    (Department of Economics, George Washington University)

  • Elizabeth Reid

    (Department of Economics, George Washington University)

Abstract
In this paper we jointly evaluate the Federal Reserve staff forecasts of U.S. real output growth and the inflation rate assuming the forecasts are to be used as inputs for the Taylor rule. Our simple methodology generates “policy forecast errors” which have a direct interpretation for the impact of forecast errors on the target interest rate given by the Taylor rule. Without interest rate smoothing, we find that, on average, the Taylor rule target interest rate would have been approximately a full percentage point away from the intended target because of errors in forecasting output growth and inflation. Our results are robust to changes in the forecast horizon and to changes in the weights on the variables in the policy rule.

Suggested Citation

  • Tara M. Sinclair & Edward N. Gamber & H.O. Stekler & Elizabeth Reid, 2008. "Jointly Evaluating the Federal Reserve’s Forecasts of GDP Growth and Inflation," Working Papers 2008-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Mar 2011.
    • Handle: RePEc:gwc:wpaper:2008-002
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Carlos Barros & Luis Gil-Alana, 2013. "Inflation Forecasting in Angola: A Fractional Approach," African Development Review, African Development Bank, vol. 25(1), pages 91-104.
    2. Pao‐Lin Tien & Tara M. Sinclair & Edward N. Gamber, 2021. "Do Fed Forecast Errors Matter?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 686-712, June.
    3. Bel, K. & Paap, R., 2013. "Modeling the impact of forecast-based regime switches on macroeconomic time series," Econometric Institute Research Papers EI 2013-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Sinclair, Tara M. & Stekler, H.O. & Carnow, Warren, 2015. "Evaluating a vector of the Fed’s forecasts," International Journal of Forecasting, Elsevier, vol. 31(1), pages 157-164.
    5. Tara M. Sinclair & H. O. Stekler & Warren Carnow, 2012. "A new approach for evaluating economic forecasts," Economics Bulletin, AccessEcon, vol. 32(3), pages 2332-2342.
    6. Zisimos Koustas & Jean-François Lamarche, 2012. "Instrumental variable estimation of a nonlinear Taylor rule," Empirical Economics, Springer, vol. 42(1), pages 1-20, February.
    7. Michael T. Belongia & Peter N. Ireland, 2018. "Monetary Policy Lessons from the Greenbook," Boston College Working Papers in Economics 955, Boston College Department of Economics.
    8. Mihaela Simionescu, 2014. "Directional accuracy for inflation and unemployment rate predictions in Romania," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 7(2), pages 129-138, September.
    9. Bel, Koen & Paap, Richard, 2016. "Modeling the impact of forecast-based regime switches on US inflation," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1306-1316.
    10. Döpke, Jörg & Müller, Karsten & Tegtmeier, Lars, 2018. "The economic value of business cycle forecasts for potential investors – Evidence from Germany," Research in International Business and Finance, Elsevier, vol. 46(C), pages 445-461.

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    More about this item

    Keywords

    Evaluating Forecasts; Macroeconomic Forecasts; Loss Function; Inflation Forecasting; GDP Growth Forecasting; Monetary Policy;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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