Inference in Bayesian Proxy-SVARs

Jonas E. Arias, Juan F Rubio-Ramirez and Daniel Waggoner

Journal of Econometrics, 2021, vol. 225, issue 1, 88-106

Abstract: Motivated by the increasing use of external instruments to identify structural vector autoregressions (SVARs), we develop an algorithm for exact finite sample inference in this class of time series models, commonly known as Proxy-SVARs. Our algorithm makes independent draws from any posterior distribution over the structural parameterization of a Proxy-SVAR. Our approach allows researchers to simultaneously use proxies and traditional zero and sign restrictions to identify structural shocks. We illustrate our methods with two applications. In particular, we show how to generalize the counterfactual analysis in Mertens and Montiel-Olea (2018) to identified structural shocks.

Keywords: SVARs; External instruments; Importance sampler (search for similar items in EconPapers)
JEL-codes: C15 C32 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (37)

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Related works:
Working Paper: Inference in Bayesian Proxy-SVARs (2018)
Working Paper: Inference in Bayesian Proxy-SVARs (2018)
Working Paper: Inference in Bayesian Proxy-SVARs (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:225:y:2021:i:1:p:88-106

DOI: 10.1016/j.jeconom.2020.12.004

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