Inference in Bayesian Proxy-SVARs

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

No 2018-13, Working Papers from FEDEA

Abstract: Motivated by the increasing use of external instruments to identify structural vector autoregressions (SVARs), we develop algorithms for exact finite sample inference in this class of time series models, commonly known as proxy-SVARs. Our algorithms make independent draws from the normal-generalized-normal family of conjugate posterior distributions over the structural parameterization of a proxy-SVAR. Importantly, our techniques can handle the case of set identification and hence they can be used to relax the additional exclusion restrictions unrelated to the external instruments often imposed to facilitate inference when morethan one instrument is used to identify more than one equation as in Mertens and Montiel-Olea (2018).

Date: 2018-11
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
https://documentos.fedea.net/pubs/dt/2018/dt2018-13.pdf (application/pdf)

Related works:
Journal Article: Inference in Bayesian Proxy-SVARs (2021)
Working Paper: Inference in Bayesian Proxy-SVARs (2018)
Working Paper: Inference in Bayesian Proxy-SVARs (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fda:fdaddt:2018-13

Access Statistics for this paper

More papers in Working Papers from FEDEA
Bibliographic data for series maintained by Carmen Arias ().