Skewed SVARs : Tracking the Structural Sources of Macroeconomic Tail Risks

This paper proposes a vector autoregressive model with structural shocks (SVAR) that are identified using sign restrictions and whose distribution is subject to time-varying skewness. It also presents an efficient Bayesian algorithm to estimate the model. The model allows for the joint tracking of asymmetric risks to macroeconomic variables included in the SVAR. It also provides a narrative about the structural reasons for the changes over time in those risks. Using euro area data, our estimation suggests that there has been a significant variation in the skewness of demand, supply and monetary policy shocks between 1999 and 2019. This variation lies behind a significant proportion of the joint dynamics of real GDP growth and inflation in the euro area over this period, and also generates important asymmetric tail risks in these macroeconomic variables. Finally, compared to the literature on growth- and inflation-at-risk, we found that financial stress indicators do not suffice to explain all the macroeconomic tail risks