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Model-Based Globally-Consistent Risk Assessment

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  • Michal Andrle
  • Mr. Benjamin L Hunt

Abstract

This paper outlines an approach to assess uncertainty around a forecast baseline as well as the impact of alternative policy rules on macro variability. The approach allows for non-Gaussian shock distributions and non-linear underlying macroeconomic models. Consequently, the resulting distributions for macroeconomic variables can exhibit skewness and fat tails. Several applications are presented that illustrate the practical implementation of the technique including confidence bands around a baseline forecast, the probabilities of global growth falling below a specified threshold, and the impact of alternative fiscal policy reactions functions on macro variability.

Suggested Citation

  • Michal Andrle & Mr. Benjamin L Hunt, 2020. "Model-Based Globally-Consistent Risk Assessment," IMF Working Papers 2020/064, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2020/064
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    File URL: http://www.imf.org/external/pubs/cat/longres.aspx?sk=49253
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    References listed on IDEAS

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    8. Michal Andrle & Patrick Blagrave & Pedro Espaillat & Ms. Keiko Honjo & Mr. Benjamin L Hunt & Mika Kortelainen & René Lalonde & Mr. Douglas Laxton & Eleonara Mavroeidi & Mr. Dirk V Muir & Susanna Mursu, 2015. "The Flexible System of Global Models – FSGM," IMF Working Papers 2015/064, International Monetary Fund.
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    Cited by:

    1. Andrew Binning, 2022. "An Efficient Application of the Extended Path Algorithm in Matlab with Examples," Treasury Working Paper Series 22/02, New Zealand Treasury.
    2. Francisco Louçã & Alexandre Abreu & Gonçalo Pessa Costa, 2021. "Disarray at the headquarters: Economists and Central bankers tested by the subprime and the COVID recessions [Forward guidance without common knowledge]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(2), pages 273-296.

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