  A structural Gaussian mixture vector autoregressive model is introduced. The
shocks are identified by combining simultaneous diagonalization of the reduced
form error covariance matrices with constraints on the time-varying impact
matrix. This leads to flexible identification conditions, and some of the
constraints are also testable. The empirical application studies asymmetries in
the effects of the U.S. monetary policy shock and finds strong asymmetries with
respect to the sign and size of the shock and to the initial state of the
economy. The accompanying CRAN distributed R package gmvarkit provides a
comprehensive set of tools for numerical analysis.
