EconPapers    
Economics at your fingertips  
 

Generating Univariate Fractional Integration within a Large VAR(1)

Guillaume Chevillon (), Alain Hecq () and Sébastien Laurent ()

No 1844, AMSE Working Papers from Aix-Marseille School of Economics, France

Abstract: This paper shows that a large dimensional vector autoregressive model (VAR) of finite order can generate fractional integration in the marginalized univariate series. We derive high-level assumptions under which the final equation representation of a VAR(1) leads to univariate fractional white noises and verify the validity of these assumptions for two specific models.

Keywords: long memory; vector autoregressive model; marginalization; final equation representation (search for similar items in EconPapers)
JEL-codes: C10 C32 C55 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
Date: 2018-12
References: Add references at CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
https://www.amse-aixmarseille.fr/sites/default/fil ... /wp_2018_-_nr_44.pdf (application/pdf)

Related works:
Journal Article: Generating univariate fractional integration within a large VAR(1) (2018) Downloads
Working Paper: Generating univariate fractional integration within a large VAR(1) (2018) Downloads
Working Paper: Generating Univariate Fractional Integration within a Large VAR(1) (2018) Downloads
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:aim:wpaimx:1844

Access Statistics for this paper

More papers in AMSE Working Papers from Aix-Marseille School of Economics, France AMU - AMSE 5-9 Boulevard Maurice Bourdet, CS 50498 ​ 13205 Marseille Cedex 1. Contact information at EDIRC.
Bibliographic data for series maintained by Grégory Cornu ().

 
Page updated 2019-09-15
Handle: RePEc:aim:wpaimx:1844