Time Varying Structural Vector Autoregressions and Monetary Policy

Abstract

Monetary policy and the private sector behaviour of the U.S. economy are modelled as a time varying structural vector autoregression, where the sources of time variation are both the coefficients and the variance covariance matrix of the innovations. The paper develops a new, simple modelling strategy for the law of motion of the variance covariance matrix and proposes an efficient Markov chain Monte Carlo algorithm for the model likelihood/posterior numerical evaluation. The main empirical conclusions are: (1) both systematic and non-systematic monetary policy have changed during the last 40 years—in particular, systematic responses of the interest rate to inflation and unemployment exhibit a trend toward a more aggressive behaviour, despite remarkable oscillations; (2) this has had a negligible effect on the rest of the economy. The role played by exogenous non-policy shocks seems more important than interest rate policy in explaining the high inflation and unemployment episodes in recent U.S. economic history.