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Incorporating Asymmetric Preferences into Fan Charts and Path Forecasts

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  • Matei Demetrescu
  • Mu-Chun Wang

Abstract

type="main" xml:lang="en"> Ordinary fan charts consist of symmetric marginal forecast intervals, and do not take into consideration the concrete loss function of the user of the forecast. The note shows how to build fan charts that have exact joint coverage even under asymmetric loss, and maintain at the same time the intuition conveyed by ordinary fan charts. The proposed method is computationally simple, and easily implemented with any loss function. The differences between the information conveyed by fan charts with or without asymmetries, and with or without exact joint coverage, are illustrated with a Bayesian forecast exercise of US GDP growth rates.

Suggested Citation

  • Matei Demetrescu & Mu-Chun Wang, 2014. "Incorporating Asymmetric Preferences into Fan Charts and Path Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 287-297, April.
  • Handle: RePEc:bla:obuest:v:76:y:2014:i:2:p:287-297
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    File URL: http://hdl.handle.net/10.1111/j.1468-0084.2012.00723.x
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    References listed on IDEAS

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    Cited by:

    1. Yim, Ha-Neul & Riddell, Jordan R. & Wheeler, Andrew P., 2020. "Is the recent increase in national homicide abnormal? Testing the application of fan charts in monitoring national homicide trends over time," Journal of Criminal Justice, Elsevier, vol. 66(C).
    2. Anna Staszewska-Bystrova & Peter Winker, 2014. "Measuring Forecast Uncertainty of Corporate Bond Spreads by Bonferroni-Type Prediction Bands," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(2), pages 89-104, June.
    3. Wojciech Charemza & Carlos Diaz Vela & Svetlana Makarova, 2013. "Inflation fan charts, monetary policy and skew normal distribution," Discussion Papers in Economics 13/06, Division of Economics, School of Business, University of Leicester.
    4. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.
    5. Yim, Ha-Neul & Riddell, Jordan R. & Wheeler, Andrew Palmer, 2019. "Is the recent increase in national homicide abnormal? Testing the application of fan charts in monitoring national homicide trends over time," SocArXiv 7g32n, Center for Open Science.

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