Stochastic Model Specification Search for Time-Varying Parameter VARs
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.
Year of publication: |
2014-12
|
---|---|
Authors: | Eisenstat, Eric ; Chan, Joshua C.C. ; Strachan, Rodney |
Institutions: | Rimini Centre for Economic Analysis (RCEA) |
Saved in:
freely available
Saved in favorites
Similar items by person
-
Chan, Joshua C.C., (2014)
-
The Zero Lower Bound: Implications for Modelling the Interest Rate
Chan, Joshua C.C., (2014)
-
Modelling Inflation Volatility
Eisenstat, Eric, (2014)
- More ...