Statistical inference for independent component analysis: Application to structural VAR models

Details

Serval ID
serval:BIB_3050BF118F3D
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Statistical inference for independent component analysis: Application to structural VAR models
Journal
Journal of Econometrics
Author(s)
Gouriéroux C., Monfort A., Renne J.-P.
ISSN
0304-4076
Publication state
Published
Issued date
01/2017
Peer-reviewed
Oui
Volume
196
Number
1
Pages
111-126
Language
english
Abstract
The well-known problem of non-identifiability of structural VAR models disappears if the structural shocks are independent and if at most one of them is Gaussian. In that case, the relevant estimation technique is the Independent Component Analysis (ICA). Since the introduction of ICA by Comon (1994), various semi-parametric estimation methods have been proposed for “orthogonalizing” the error terms. These methods include pseudo maximum likelihood (PML) approaches and recursive PML. The aim of our paper is to derive the asymptotic properties of the PML approaches, in particular to study their consistency. We conduct Monte Carlo studies exploring the relative performances of these methods. Finally, an application based on real data shows that structural VAR models can be estimated without additional identification restrictions in the non-Gaussian case and that the usual restrictions can be tested.
Keywords
Independent component analysis, Pseudo maximum likelihood, Identification, Cayley transform, Structural shocks, Structural VAR, Impulse response functions
Create date
30/11/2016 13:30
Last modification date
21/08/2019 5:17
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