Structural vector autoregressive models with more shocks than variables identified via heteroskedasticity

Helmut Lütkepohl

Economics Letters, 2020, vol. 195, issue C

Abstract: In conventional structural vector autoregressive models it is assumed that there are at most as many structural shocks as there are variables in the model. It is pointed out that heteroskedasticity can be used to identify more shocks than variables. Results are provided that allow a researcher to assess how many shocks can be identified from specific forms of heteroskedasticity.

Keywords: Structural vector autoregression; Identification through heteroskedasticity; Structural shocks (search for similar items in EconPapers)
JEL-codes: C32 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0165176520302834
Full text for ScienceDirect subscribers only

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:eee:ecolet:v:195:y:2020:i:c:s0165176520302834

DOI: 10.1016/j.econlet.2020.109458

Access Statistics for this article

Economics Letters is currently edited by Economics Letters Editorial Office

More articles in Economics Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().