IMF Working Papers

Model-Based Globally-Consistent Risk Assessment

By Michal Andrle, Benjamin L Hunt

May 22, 2020

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Format: Chicago

Michal Andrle, and Benjamin L Hunt. Model-Based Globally-Consistent Risk Assessment, (USA: International Monetary Fund, 2020) accessed September 19, 2024

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Summary

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.

Subject: Financial services, Fiscal policy, Interest rate floor, Monetary policy, Production, Production growth, Zero lower bound

Keywords: Distribution, Distribution change, Distribution of shock, DSGE model, DSGE models, Economic policy, Fat tails, Fiscal policy rule, Global, Growth distribution, Headline inflation, Interest rate floor, Model dynamics, Monetary policy, Non-Gaussian, Nonlinear, Normal distribution, Output distribution, Output growth distribution, Predictive density, Predictive distribution, Production growth, Risk assessment, Shock distribution, Skew, WP, Zero lower bound

Publication Details

  • Pages:

    28

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

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  • Series:

    Working Paper No. 2020/064

  • Stock No:

    WPIEA2020064

  • ISBN:

    9781513536460

  • ISSN:

    1018-5941