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The (Un)Reliability of Real-Time Output Gap Estimates with Revised Data

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  • Onur Ince
  • David H. Papell

Abstract

This paper investigates the differences between real-time and ex-post output gap estimates using a newly-constructed international real-time data set over the period from 1973:Q1 to 2012:Q3. We extend the findings in Orphanides and van Norden (2002) for the United States that the use of ex-post information in calculating potential output, not the data revisions themselves, is the major cause of the difference between real-time and ex-post output gap estimates to nine additional OECD countries. The results are robust to the use of linear, quadratic, Hodrick-Prescott, Baxter-King, and Christiano-Fitzgerald detrending methods. By using quasi real-time methods, reliable real-time output gap estimates can be constructed with revised data. Key Words: Output gap, real-time data, data revision, business cycles

Suggested Citation

  • Onur Ince & David H. Papell, 2013. "The (Un)Reliability of Real-Time Output Gap Estimates with Revised Data," Working Papers 13-02, Department of Economics, Appalachian State University.
  • Handle: RePEc:apl:wpaper:13-02
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    References listed on IDEAS

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    Cited by:

    1. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    2. Jaqueson K. Galimberti & Marcelo L. Moura, 2011. "Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts," Centre for Growth and Business Cycle Research Discussion Paper Series 159, Economics, The Univeristy of Manchester.
    3. Jan Capek, 2014. "Historical Analysis of Monetary Policy Reaction Functions: Do Real-Time Data Matter?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(6), pages 457-475, December.
    4. Ince, Onur & Molodtsova, Tanya & Papell, David H., 2016. "Taylor rule deviations and out-of-sample exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 69(C), pages 22-44.
    5. repec:eee:ecmode:v:64:y:2017:i:c:p:153-171 is not listed on IDEAS
    6. Capek Jan, 2015. "Estimating DSGE model parameters in a small open economy: Do real-time data matter?," Review of Economic Perspectives, De Gruyter Open, pages 89-114.
    7. Ince, Onur, 2014. "Forecasting exchange rates out-of-sample with panel methods and real-time data," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 1-18.
    8. Galimberti, Jaqueson K. & Moura, Marcelo L., 2016. "Improving the reliability of real-time output gap estimates using survey forecasts," International Journal of Forecasting, Elsevier, pages 358-373.
    9. Beblavý, Miroslav & Lenaerts, Karolien & Maselli, Ilaria, 2017. "Design of a European Unemployment Benefit Scheme," CEPS Papers 12263, Centre for European Policy Studies.

    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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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