EconPapers    
Economics at your fingertips  
 

Identification of Structural Vector Autoregressions by Stochastic Volatility

Dominik Bertsche and Robin Braun

Annual Conference 2018 (Freiburg, Breisgau): Digital Economy from Verein für Socialpolitik / German Economic Association

Abstract: We propose to exploit stochastic volatility for statistical identification of Structural Vector Autoregressive models (SV-SVAR). We discuss full and partial identification of the model and develop efficient EM algorithms for Maximum Likelihood inference. Simulation evidence suggests that the SV-SVAR works well in identifying structural parameters also under misspecification of the variance process, particularly if compared to alternative heteroskedastic SVARs. We apply the model to study the interdependence between monetary policy and stock markets. Since shocks identified by heteroskedasticity may not be economically meaningful, we exploit the framework to test conventional exclusion restrictions as well as Proxy SVAR restrictions which are overidentifying in the heteroskedastic model.

Keywords: Structural Vector Autoregression (SVAR); Identification via heteroskedasticity; Stochastic Volatility; Proxy SVAR (search for similar items in EconPapers)
JEL-codes: C32 C32 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ore
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (2) Track citations by RSS feed

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/181631/1/VfS-2018-pid-14039.pdf (application/pdf)

Related works:
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:zbw:vfsc18:181631

Access Statistics for this paper

More papers in Annual Conference 2018 (Freiburg, Breisgau): Digital Economy from Verein für Socialpolitik / German Economic Association Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().

 
Page updated 2018-11-24
Handle: RePEc:zbw:vfsc18:181631