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Calibration and Resolution Diagnostics for Bank of England Density Forecasts

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  • John W. Galbraith
  • Simon van Norden

Abstract

This paper applies new diagnostics to the Bank of England's pioneering density forecasts (fan charts). We compute their implicit probability forecast for annual rates of inflation and output growth that exceed a given threshold (in this case, the target inflation rate and 2.5% respectively.) Unlike earlier work on these forecasts, we measure both their calibration and their resolution, providing both formal tests and graphical interpretations of the results. These results both reinforce earlier evidence on some of the limitations of these forecasts and provide new evidence on their information content. Cet étude développe et applique des nouvelles techniques pour diagnostiquer les prévisions de densité de la Banque d'Angleterre (leur fan charts). Nous calculons leurs probabilités implicites pour des taux d'inflation et de croissance du PIB qui dépassent des seuils critiques (soit le taux d'inflation ciblé, soit 2.5%.) En contraste avec des travaux antérieurs sur ces prévisions, nous gaugeons leur calibration aussi bien que leur résolution, en donnant des tests formels et des interprétations graphiques. Les résultats renforcent des conclusions déjà existant sur les limites de ces prévisions et ils donnent de nouvelles évidences sur leurs valeurs ajoutées.

Suggested Citation

  • John W. Galbraith & Simon van Norden, 2009. "Calibration and Resolution Diagnostics for Bank of England Density Forecasts," CIRANO Working Papers 2009s-36, CIRANO.
    • Handle: RePEc:cir:cirwor:2009s-36
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    File URL: https://cirano.qc.ca/files/publications/2009s-36.pdf
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    References listed on IDEAS

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    1. John Galbraith & Simon van Norden, 2008. "The Calibration Of Probabilistic Economic Forecasts," Departmental Working Papers 2008-05, McGill University, Department of Economics.
    2. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
    3. John W. Galbraith & Greg Tkacz, 2007. "Forecast content and content horizons for some important macroeconomic time series," Canadian Journal of Economics, Canadian Economics Association, vol. 40(3), pages 935-953, August.
    4. Dean Croushore & Tom Stark, 2003. "A Real-Time Data Set for Macroeconomists: Does the Data Vintage Matter?," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 605-617, August.
    5. Tilmann Gneiting & Fadoua Balabdaoui & Adrian E. Raftery, 2007. "Probabilistic forecasts, calibration and sharpness," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(2), pages 243-268, April.
    6. Michael P. Clements, 2004. "Evaluating the Bank of England Density Forecasts of Inflation," Economic Journal, Royal Economic Society, vol. 114(498), pages 844-866, October.
    7. Lahiri, Kajal & Wang, J. George, 2013. "Evaluating probability forecasts for GDP declines using alternative methodologies," International Journal of Forecasting, Elsevier, vol. 29(1), pages 175-190.
    8. Rudebusch, Glenn D. & Williams, John C., 2009. "Forecasting Recessions: The Puzzle of the Enduring Power of the Yield Curve," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 492-503.
    9. Diebold, Francis X & Rudebusch, Glenn D, 1989. "Scoring the Leading Indicators," The Journal of Business, University of Chicago Press, vol. 62(3), pages 369-391, July.
    10. Corradi, Valentina & Swanson, Norman R., 2006. "Predictive Density Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 5, pages 197-284, Elsevier.
    11. Casillas-Olvera, Gabriel & Bessler, David A., 2006. "Probability forecasting and central bank accountability," Journal of Policy Modeling, Elsevier, vol. 28(2), pages 223-234, February.
    12. Kenneth F. Wallis, 1999. "Asymmetric density forecasts of inflation and the Bank of England's fan chart," National Institute Economic Review, National Institute of Economic and Social Research, vol. 167(1), pages 106-112, January.
    13. Dr. James Mitchell, 2008. "Evaluating Density Forecasts: Forecast Combinations, Model Mixtures, Calibration and Sharpness," National Institute of Economic and Social Research (NIESR) Discussion Papers 320, National Institute of Economic and Social Research.
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    Cited by:

    1. Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F., 2011. "Scoring rules and survey density forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 379-393.

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    Keywords

    calibration; density forecast; probability forecast; resolu; calibration; prévisions de densité; probabilités implicites; résolution.;
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