Model-Based Globally-Consistent Risk Assessment

29 Pages Posted: 10 Jun 2020

See all articles by Michal Andrle

Michal Andrle

International Monetary Fund (IMF)

Ben Hunt

International Monetary Fund (IMF) - Research Department

Date Written: May 2020


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.

Keywords: Economic models, Economic policy, Business cycles, Monetary policy, Fiscal policy, DSGE models, predictive density, nonlinear, non-Gaussian, skew, fat tails, WP, economic shock, policy space, ELB, nominal interest rate, risk assessment

JEL Classification: C60, E3, E52, E62, E01, E31, E32

Suggested Citation

Andrle, Michal and Hunt, Benjamin, Model-Based Globally-Consistent Risk Assessment (May 2020). IMF Working Paper No. 20/64, Available at SSRN:

Michal Andrle (Contact Author)

International Monetary Fund (IMF) ( email )

700 19th Street, N.W.
Washington, DC 20431
United States

Benjamin Hunt

International Monetary Fund (IMF) - Research Department ( email )

700 19th Street NW
Washington, DC 20431
United States

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