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The Reliability of Inflation Forecasts Based on Output Gaps in Real Time

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  • Athanasios Orphanides and Simon van Norden

Abstract

A stable predictive relationship between inflation and the output gap, often referred to as a Phillips curve, provides the basis for empirical formulations of countercyclical monetary policy in many models. However, evidence for the usefulness of output gap measures for forecasting inflation is often based on data that are not available when actual forecasts are made in practice. This ignores difficulties associated with estimation of the output gap in real-time and raises questions regarding the reliability of the resulting forecasts. In this paper we evaluate alternative multivariate methods for estimation of the output gap and assess their usefulness for predicting inflation. Our results suggest that inference based on ex-post constructed output gap measures severely overstates their usefulness for predicting inflation and, therefore, for the real-time policy process. Further, forecasts based on models that fail to control for the unreliability of the real-time estimates of the output gap are often less accurate than forecasts that abstract from the output gap concept altogether. These results bring into question the reliability of inflation forecasts based on output gaps for formulating monetary policy.

Suggested Citation

  • Athanasios Orphanides and Simon van Norden, 2001. "The Reliability of Inflation Forecasts Based on Output Gaps in Real Time," Computing in Economics and Finance 2001 247, Society for Computational Economics.
    • Handle: RePEc:sce:scecf1:247
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    Citations

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    Cited by:

    1. Athanasios Orphanides & John C. Williams, 2002. "Robust Monetary Policy Rules with Unknown Natural Rates," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 33(2), pages 63-146.
    2. Harrison, Richard & Kapetanios, George & Yates, Tony, 2005. "Forecasting with measurement errors in dynamic models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 595-607.
    3. Clements, Michael P. & Beatriz Galvão, Ana, 2010. "First announcements and real economic activity," European Economic Review, Elsevier, vol. 54(6), pages 803-817, August.
    4. Alberto Musso & Livio Stracca & Dick van Dijk, 2009. "Instability and Nonlinearity in the Euro-Area Phillips Curve," International Journal of Central Banking, International Journal of Central Banking, vol. 5(2), pages 181-212, June.
    5. Bernhardsen, Tom & Eitrheim, Oyvind & Jore, Anne Sofie & Roisland, Oistein, 2005. "Real-time data for Norway: Challenges for monetary policy," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 333-349, December.
    6. Clements, Michael P & Galvão, Ana Beatriz, 2006. "Macroeconomic Forecasting with Mixed Frequency Data : Forecasting US output growth and inflation," The Warwick Economics Research Paper Series (TWERPS) 773, University of Warwick, Department of Economics.
    7. Nelson, Edward & Nikolov, Kalin, 2003. "UK inflation in the 1970s and 1980s: the role of output gap mismeasurement," Journal of Economics and Business, Elsevier, vol. 55(4), pages 353-370.
    8. David E. Lindsey & Athanasios Orphanides & Robert H. Rasche, 2013. "The Reform of October 1979: How It Happened and Why," Review, Federal Reserve Bank of St. Louis, issue Nov, pages 487-542.
    9. Michael P. Clements & Ana Beatriz Galvão, 2007. "Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US Output Growth," Working Papers 616, Queen Mary University of London, School of Economics and Finance.
    10. Frédérick Demers, 2003. "The Canadian Phillips Curve and Regime Shifting," Staff Working Papers 03-32, Bank of Canada.
    11. Porshakov, A. & Ponomarenko, A. & Sinyakov, A., 2016. "Nowcasting and Short-Term Forecasting of Russian GDP with a Dynamic Factor Model," Journal of the New Economic Association, New Economic Association, vol. 30(2), pages 60-76.
    12. Harrison, Richard & Kapetanios, George & Yates, Tony, 2005. "Forecasting with measurement errors in dynamic models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 595-607.
    13. Tom Bernhardsen & ØYvind Eitrheim, 2005. "Real-time data for Norway: Output gap revisions and challenges for monetary policy," Computing in Economics and Finance 2005 274, Society for Computational Economics.
    14. Ciccarelli, Matteo & Altavilla, Carlo, 2007. "Information combination and forecast (st)ability evidence from vintages of time-series data," Working Paper Series 846, European Central Bank.
    15. Mr. Papa M N'Diaye & Mr. Douglas Laxton, 2002. "Monetary Policy Credibility and the Unemployment-Inflation Tradeoff: Some Evidence From 17 Industrial Countries," IMF Working Papers 2002/220, International Monetary Fund.

    More about this item

    Keywords

    Real-time data; business cycle measurement; inflation;
    All these keywords.

    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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