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Forecast Uncertainty, Its Representation And Evaluation

In: Econometric Forecasting And High-Frequency Data Analysis

Author

Listed:
  • Kenneth F. Wallis

    (Department of Economics, University of Warwick, Coventry CV4 7AL, United Kingdom)

Abstract

The following sections are included:IntroductionMotivationOverviewA theoretical illustrationExampleGeneralisationsForecast evaluationMeasuring and Reporting Forecast UncertaintyModel-based measures of forecast uncertaintyThe linear regression modelEstimation error in multi-step forecastsStochastic simulation in non-linear modelsLoss functionsModel uncertaintyEmpirical measures of forecast uncertaintyReporting forecast uncertaintyForecast intervalsDensity forecastsGraphical presentationsAdditional examplesForecast scenariosUncertainty and disagreement in survey forecastsEvaluating Interval and Density ForecastsLikelihood ratio tests of interval forecastsChi-squared tests of interval forecastsExtensions to density forecastsThe probability integral transformationThe inverse normal transformationThe Bank of England's inflation forecastsComparing density forecastsConclusionReferences

Suggested Citation

  • Kenneth F. Wallis, 2008. "Forecast Uncertainty, Its Representation And Evaluation," World Scientific Book Chapters, in: Roberto S Mariano & Yiu-Kuen Tse (ed.), Econometric Forecasting And High-Frequency Data Analysis, chapter 1, pages 1-51, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812778963_0001
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    Citations

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    Cited by:

    1. Tsyplakov, Alexander, 2010. "The links between inflation and inflation uncertainty at the longer horizon," MPRA Paper 26908, University Library of Munich, Germany.
    2. Malte Knüppel, 2015. "Evaluating the Calibration of Multi-Step-Ahead Density Forecasts Using Raw Moments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 270-281, April.
    3. Coutiño, Alfredo, 2016. "Pitfalls in monetary policy decisions based on the output gap," Journal of Policy Modeling, Elsevier, vol. 38(1), pages 54-64.
    4. Simionescu, Mihaela, 2017. "Prediction intervals for inflation and unemployment rate in Romania. A Bayesian approach," GLO Discussion Paper Series 82, Global Labor Organization (GLO).
    5. Tsyplakov Alexander, 2010. "The links between inflation and inflation uncertainty at the longer horizon," EERC Working Paper Series 10/09e, EERC Research Network, Russia and CIS.

    More about this item

    Keywords

    Econometric Forecasting; High-Frequency Data; Time Series; Seasonality; Compound Autoregressive Processes; Affine Processes; Macroeconomic Modeling; Evaluating Forecast Uncertainty; Financial Data Analysis;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory

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