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Stochastic Model Specification Search for Time-Varying Parameter VARs

Eric Eisenstat (), Joshua Chan and Rodney Strachan ()
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Eric Eisenstat: Faculty of Business Administration, University of Bucharest, Romania; RIMIR

Working Paper series from Rimini Centre for Economic Analysis

Abstract: 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.

New Economics Papers: this item is included in nep-ets
Date: 2014-12
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http://www.rcea.org/RePEc/pdf/wp44_14.pdf (application/pdf)

Related works:
Journal Article: Stochastic Model Specification Search for Time-Varying Parameter VARs (2016) Downloads
Working Paper: Stochastic Model Specification Search for Time-Varying Parameter VARs (2014) Downloads
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