Impulse Response Functions in the Dynamic Stochastic General Equilibrium Vector Autoregression Model

Abstract

The model considered in the paper is defined as VAR with the prior
distribution for parameters generated by the dynamic stochastic general
equilibrium (DSGE) model. The degree of economic restrictions in the DSGEVAR model is controlled by the weighting parameter. In the paper there is
investigated the impact of the weighting parameter prior specifications for the
posterior shape of impulse response functions (IRFs). In case of conditional
models the paths of IRFs highly depend on the value of the weighting parameter
that is set arbitrary. When considering full estimation with different prior types,
means and gradual change in the dispersion the posterior time paths of IRFs
are similar in models with high values of the marginal data density.