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Real-Time Properties of the Federal Reserve's Output Gap

Author

Listed:
  • Rochelle M. Edge

    (Board of Governors of the Federal Reserve System)

  • Jeremy B. Rudd

    (Board of Governors of the Federal Reserve System)

Abstract
We consider the revision properties of Federal Reserve Board staff estimates of the output gap after the mid-1990s and examine the usefulness of these estimates for inflation forecasting. Over this period, we find that the Federal Reserve's output gap is more reliably estimated in real time than previous studies have documented for earlier periods and alternative estimation techniques. In contrast to previous work, we also find no deterioration in forecast performance when inflation projections are conditioned on real-time rather than on final estimates of the output gap.

Suggested Citation

  • Rochelle M. Edge & Jeremy B. Rudd, 2016. "Real-Time Properties of the Federal Reserve's Output Gap," The Review of Economics and Statistics, MIT Press, vol. 98(4), pages 785-791, October.
    • Handle: RePEc:tpr:restat:v:98:y:2016:i:4:p:785-791
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    References listed on IDEAS

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    Cited by:

    1. Günes Kamber & James Morley & Benjamin Wong, 2018. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 550-566, July.
    2. Olivier Coibion & Yuriy Gorodnichenko & Mauricio Ulate, 2017. "Secular Stagnation: Policy Options and the Cyclical Sensitivity in Estimates of Potential Output," Working Papers 01/2017, National Bank of Ukraine.
    3. Camila Figueroa & Jorge Fornero & Pablo García, 2019. "Hindsight vs. Real time measurement of the output gap: Implications for the Phillips curve in the Chilean Case," Working Papers Central Bank of Chile 854, Central Bank of Chile.
    4. Travis J. Berge, 2023. "Time-Varying Uncertainty of the Federal Reserve's Output Gap Estimate," The Review of Economics and Statistics, MIT Press, vol. 105(5), pages 1191-1206, September.
    5. Croushore, Dean & van Norden, Simon, 2019. "Fiscal Surprises at the FOMC," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1583-1595.
    6. Josefine Quast & Maik H. Wolters, 2022. "Reliable Real-Time Output Gap Estimates Based on a Modified Hamilton Filter," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 152-168, January.
    7. Dovern, Jonas & Zuber, Christopher, 2020. "How economic crises damage potential output – Evidence from the Great Recession," Journal of Macroeconomics, Elsevier, vol. 65(C).
    8. Agnello, Luca & Castro, Vítor & Sousa, Ricardo M., 2023. "A quest between fiscal and market discipline," Economic Modelling, Elsevier, vol. 119(C).
    9. Francesco Furlanetto & Kåre Hagelund & Frank Hansen & Ørjan Robstad, 2020. "Norges Bank Output Gap Estimates: Forecasting Properties, Reliability and Cyclical Sensitivity," Working Paper 2020/7, Norges Bank.
    10. Davide Fantino & Sara Formai & Alessandro Mistretta, 2021. "Firm characteristics and potential output: a growth accounting approach," Questioni di Economia e Finanza (Occasional Papers) 616, Bank of Italy, Economic Research and International Relations Area.
    11. Pichette, Lise & Robitaille, Marie-Noëlle & Salameh, Mohanad & St-Amant, Pierre, 2019. "Dismiss the output gaps? To use with caution given their limitations," Economic Modelling, Elsevier, vol. 76(C), pages 199-215.
    12. Olivier Coibion & Yuriy Gorodnichenko & Mauricio Ulate, 2018. "The Cyclical Sensitivity in Estimates of Potential Output," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 49(2 (Fall)), pages 343-441.
    13. Cobus Vermeulen, 2023. "The inherent uncertainties in output gap estimation a South African perspective," Working Papers 11051, South African Reserve Bank.
    14. Mr. Alvar Kangur & Koralai Kirabaeva & Jean-Marc Natal & Simon Voigts, 2019. "How Informative Are Real Time Output Gap Estimates in Europe?," IMF Working Papers 2019/200, International Monetary Fund.

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    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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