Stochastic Model Specification Search for Time-Varying Parameter VARs
35 Pages Posted: 6 Mar 2014 Last revised: 7 Mar 2014
Date Written: March 1, 2014
This article develops a new econometric methodology for performing stochastic model specification search (SMSS) in the vast model space of time-varying parameter VARs with stochastic volatility and correlated state transitions. This is motivated by the concern of over-fitting and the typically imprecise inference in these highly parameterized models. For each VAR coefficient, this new method automatically decides whether it is constant or time-varying. Moreover, it can be used to shrink an otherwise unrestricted time-varying parameter VAR to a stationary VAR, thus providing an easy way to (probabilistically) impose stationarity in time-varying parameter models. We demonstrate the effectiveness of the approach with a topical application, where we investigate the dynamic effects of structural shocks in government spending on U.S. taxes and GDP during a period of very low interest rates.
Keywords: Bayesian Lasso, shrinkage, fiscal policy
JEL Classification: C11, C52, E37, E47
Suggested Citation: Suggested Citation