Paper by Paolo Gorgi, Siem Jan Koopman and Julia Schaumburg, published online in the Journal of Econometrics

Abstract

We introduce a new and general methodology for analyzing vector autoregressive models with time-varying coefficient matrices and conditionally heteroskedastic disturbances. The proposed approach is transparent and simple to implement. It allows the derivation of well-defined impulse response functions that rely on the overall stability of the system. We present the finite sample properties of the model in a simulation study. In an empirical illustration we investigate the possibly time-varying relationships between U.S. industrial production, inflation, and bond spread. We empirically identify a time-varying linkage between economic and financial variables which are effectively described by a common dynamic factor. The impulse response analysis identifies substantial differences in the effects of financial shocks on output and inflation during crisis and non-crisis periods. The results also illustrate how the widely-used approach of fixing the VAR coefficients in the derivation of the impulse responses leads to a sizeable underestimation of the impact of a financial shock on output and inflation during some of the crises in our sample.

Article citation

Paolo Gorgi, Siem Jan Koopman and Julia Schaumburg, Vector autoregressions with dynamic factor coefficients and conditionally heteroskedastic errors, Journal of Econometrics, published online May 2024, doi.org/10.1016/j.jeconom.2024.105750.