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Should we be surprised by the unreliability of real-time output gap estimates? Density estimates for the Euro area

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  • James Mitchell

    () (NIESR NIESR, London)

Abstract

Recent work has found that, without the benefit of hindsight, it can prove difficult for policy-makers to pin down accurately the current position of the output gap; real-time estimates are unreliable. However, attention primarily has focused on output gap point estimates alone. But point forecasts are better seen as the central points of ranges of uncertainty; therefore some revision to real-time estimates may not be surprising. To capture uncertainty fully density forecasts should be used. This paper introduces, motivates and discusses the idea of evaluating the quality of real-time density estimates of the output gap. It also introduces density forecast combination as a practical means to overcome problems associated with uncertainty over the appropriate output gap estimator. An application to the Euro area illustrates the use of the techniques. Simulated out-of-sample experiments reveal that not only can real-time point estimates of the Euro area output gap be unreliable, but so can measures of uncertainty associated with them. The implications for policy-makers use of Taylor-type rules are discussed and illustrated. We find that Taylor-rules that exploit real-time output gap density estimates can provide reliable forecasts of the ECB's monetary policy stance only when alternative density forecasts are combined

Suggested Citation

  • James Mitchell, 2005. "Should we be surprised by the unreliability of real-time output gap estimates? Density estimates for the Euro area," Computing in Economics and Finance 2005 52, Society for Computational Economics.
  • Handle: RePEc:sce:scecf5:52
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    Keywords

    Output gap; Real-Time; Density Forecasts; Density Forecast Combination; Taylor Rules;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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