Assessing macroeconomic tail risk

Abstract

Real GDP and industrial production in the US display substantial asymmetry and tail risk. Is this asymmetry driven by a specific structural shock? Our empirical approach, based on quantile regressions and local projections, suggests otherwise. We find that the 10th percentile of predictive growth distributions responds between three and six times more than the median to monetary policy shocks, financial shocks, uncertainty shocks, and oil price shocks, indicating a common transmission mechanism. We present two data-generating processes that are capable of matching this finding: A threshold VAR model and a nonlinear equilibrium model.