Estimating aggregate autoregressive processes when only macro data are available

Détails

ID Serval
serval:BIB_48210CB4FB8A
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Estimating aggregate autoregressive processes when only macro data are available
Périodique
Economics Letters
Auteur⸱e⸱s
Jondeau E., Pelgrin F.
ISSN
0165-1765
Statut éditorial
Publié
Date de publication
09/2014
Peer-reviewed
Oui
Volume
124
Numéro
3
Pages
341-347
Langue
anglais
Résumé
The aggregation of individual random AR(1) models generally leads to an AR(infinity) process. We provide two consistent estimators of aggregate dynamics based on either a parametric regression or a minimum distance approach for use when only macro data are available. Notably, both estimators allow us to recover some moments of the cross-sectional distribution of the autoregressive parameter. Both estimators perform very well in our Monte-Carlo experiment, even with finite samples.
Mots-clé
Autoregressive process, Aggregation, Heterogeneity
Web of science
Création de la notice
18/08/2017 10:29
Dernière modification de la notice
21/08/2019 6:12
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