Stochastic Model Specification Search for Time-Varying Parameter VARs

Eric Eisenstat, Joshua Chan and Rodney W. Strachan

CAMA Working Papers from Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University

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 timevarying 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 (search for similar items in EconPapers)
JEL-codes: C11 C52 E37 E47 (search for similar items in EconPapers)
Pages: 35 pages
Date: 2014-03
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (31)

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https://cama.crawford.anu.edu.au/sites/default/fil ... at_chan_strachan.pdf (application/pdf)

Related works:
Journal Article: Stochastic Model Specification Search for Time-Varying Parameter VARs (2016)
Working Paper: Stochastic Model Specification Search for Time-Varying Parameter VARs (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:een:camaaa:2014-23

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