Using structural models to understand macroeconomic tail risks
Understanding asymmetric risks in macroeconomic variables is challenging. Most structural models used for policy analysis are linearised and therefore cannot generate asymmetries such as those documented in the empirical growth-at-risk (GaR) literature. This report examines how structural models can incorporate non-linearities to generate tail risks. The first part reviews the various extensions to dynamic stochastic general equilibrium (DSGE) models and the computational challenges involved in accounting for risk distributions.