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A structural Gaussian mixture vector autoregressive model is introduced. Theshocks are identified by combining simultaneous diagonalization of the reducedform error covariance matrices with constraints on the time-varying impactmatrix. This leads to flexible identification conditions, and some of theconstraints are also testable. The empirical application studies asymmetries inthe effects of the U.S. monetary policy shock and finds strong asymmetries withrespect to the sign and size of the shock and to the initial state of theeconomy. The accompanying CRAN distributed R package gmvarkit provides acomprehensive set of tools for numerical analysis.

Structural Gaussian mixture vector autoregressive model with application to the asymmetric effects of monetary policy shocks