Non-redundancy of high order moment conditions for efficient GMM estimation of weak AR processes

Laurence Broze; Christian Francq; Jean Michel Zakoïan

doi:10.1016/S0165-1765(01)00387-1

Non-redundancy of high order moment conditions for efficient GMM estimation of weak AR processes

Université de Lille
Université du Littoral Côte d'Opale

Résultats de recherche: Contribution à un journal › Article › Revue par des pairs

Résumé

This paper considers GMM estimation of autoregressive processes. It is shown that, contrary to the case where the noise is independent [see Kim et al., Economics Letters 62 (1999) 265-270], using high-order moments can provide substantial efficiency gains for estimating the AR(p) model when the noise is only uncorrelated.

langue originale	Anglais
Pages (de - à)	317-322
Nombre de pages	6
journal	Economics Letters
Volume	71
Numéro de publication	3
Les DOIs	https://doi.org/10.1016/S0165-1765(01)00387-1
état	Publié - 1 janv. 2001
Modification externe	Oui

Accès au document

10.1016/S0165-1765(01)00387-1

Contient cette citation

@article{7a255fc8cf6c45b2a227068615dbe0aa,

title = "Non-redundancy of high order moment conditions for efficient GMM estimation of weak AR processes",

abstract = "This paper considers GMM estimation of autoregressive processes. It is shown that, contrary to the case where the noise is independent [see Kim et al., Economics Letters 62 (1999) 265-270], using high-order moments can provide substantial efficiency gains for estimating the AR(p) model when the noise is only uncorrelated.",

keywords = "Autoregressive process, C13, C22, Efficiency gains, Empirical autocorrelations, GMM, Yule-Walker estimator",

author = "Laurence Broze and Christian Francq and Zako{\"i}an, \{Jean Michel\}",

year = "2001",

month = jan,

day = "1",

doi = "10.1016/S0165-1765(01)00387-1",

language = "English",

volume = "71",

pages = "317--322",

journal = "Economics Letters",

issn = "0165-1765",

number = "3",

}

TY - JOUR

T1 - Non-redundancy of high order moment conditions for efficient GMM estimation of weak AR processes

AU - Broze, Laurence

AU - Francq, Christian

AU - Zakoïan, Jean Michel

PY - 2001/1/1

Y1 - 2001/1/1

N2 - This paper considers GMM estimation of autoregressive processes. It is shown that, contrary to the case where the noise is independent [see Kim et al., Economics Letters 62 (1999) 265-270], using high-order moments can provide substantial efficiency gains for estimating the AR(p) model when the noise is only uncorrelated.

AB - This paper considers GMM estimation of autoregressive processes. It is shown that, contrary to the case where the noise is independent [see Kim et al., Economics Letters 62 (1999) 265-270], using high-order moments can provide substantial efficiency gains for estimating the AR(p) model when the noise is only uncorrelated.

KW - Autoregressive process

KW - C13

KW - C22

KW - Efficiency gains

KW - Empirical autocorrelations

KW - GMM

KW - Yule-Walker estimator

U2 - 10.1016/S0165-1765(01)00387-1

DO - 10.1016/S0165-1765(01)00387-1

M3 - Article

AN - SCOPUS:0035614562

SN - 0165-1765

VL - 71

SP - 317

EP - 322

JO - Economics Letters

JF - Economics Letters

IS - 3

ER -

Non-redundancy of high order moment conditions for efficient GMM estimation of weak AR processes

Résumé

Accès au document

Empreinte digitale

Contient cette citation