Forecasting and stress testing with quantile vector autoregression

A quantile vector autoregressive (VAR) model, unlike standard VAR, models the interaction among the endogenous variables at any quantile. Forecasts of multivariate quantiles are obtained by factorizing the joint distribution in a recursive structure. VAR identification strategies that impose restrictions on the joint distribution can be readily extended to quantile VAR. The model is estimated using real and financial variables for the euro area. The dynamic properties of the system change across quantiles. This is relevant for stress testing exercises, whose goal is to forecast the tail behavior of the economy when hit by large financial and real shocks. JEL Classification: C32, C53, E17, E32, E44