Stochastic model specification search for time-varying parameter VARs

Eisenstat, Eric, Chan, Joshua C. C. and Strachan, Rodney W. (2016) Stochastic model specification search for time-varying parameter VARs. Econometric Reviews, 1-28. doi:10.1080/07474938.2015.1092808

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Author Eisenstat, Eric
Chan, Joshua C. C.
Strachan, Rodney W.
Title Stochastic model specification search for time-varying parameter VARs
Journal name Econometric Reviews   Check publisher's open access policy
ISSN 1532-4168
Publication date 2016-01-05
Year available 2015
Sub-type Article (original research)
DOI 10.1080/07474938.2015.1092808
Open Access Status Not Open Access
Start page 1
End page 28
Total pages 28
Place of publication New York, NY, United States
Publisher Taylor and Francis
Subject 2002 Cultural Studies
Abstract This article develops a new econometric methodology for performing stochastic model specification search (SMSS) in the vast model space of time-varying parameter vector autoregressions (VARs) with stochastic volatility and correlated state transitions. This is motivated by the concern of overfitting 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 gross domestic product (GDP) during a period of very low interest rates.
Keyword Bayesian Lasso
Fiscal policy
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Economics Publications
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Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 3 times in Scopus Article | Citations
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Created: Sat, 16 Jan 2016, 02:43:57 EST by Rodney Strachan on behalf of Learning and Research Services (UQ Library)