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

Détails

ID Serval
serval:BIB_3050BF118F3D
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Statistical inference for independent component analysis: Application to structural VAR models
Périodique
Journal of Econometrics
Auteur⸱e⸱s
Gouriéroux C., Monfort A., Renne J.-P.
ISSN
0304-4076
Statut éditorial
Publié
Date de publication
01/2017
Peer-reviewed
Oui
Volume
196
Numéro
1
Pages
111-126
Langue
anglais
Résumé
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.
Mots-clé
Independent component analysis, Pseudo maximum likelihood, Identification, Cayley transform, Structural shocks, Structural VAR, Impulse response functions
Création de la notice
30/11/2016 14:30
Dernière modification de la notice
21/08/2019 6:17
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