Structural Gaussian mixture vector autoregressive model

A structural version of the Gaussian mixture vector autoregressive model is introduced. The shocks are identified by combining simultaneous diagonalization of the error term covariance matrices with constraints on the time-varying B-matrix. This leads to more flexible identification conditions than in the conventional SVAR models, while some of the constraints are also testable. The empirical application considers a quarterly U.S. data covering the period from 1953Q3 to 2021Q1. Our model identifies two regimes: a stable inflation regime and an unstable inflation regime, of which the latter mainly prevails in late 1950's, 1970's, early 1980's, and during the Corona crisis. While the effects of monetary policy shocks are relatively symmetric in the unstable inflation regime, we found strong asymmetries with respect to the sign and size of the shock as well as to the initial state of the economy in the stable inflation regime. Large expansionary shocks, in particular, often drive the economy towards the unstable inflation regime and propagate high and persistent inflation. Consequently, the interest rate rises significantly, which appears to cause a strong contraction to the GDP after the initial short-term expansion. The accompanying, CRAN distributed R package gmvarkit provides easy-to-use tools for estimating the models and applying the introduced methods.