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

This paper considers GMM estimation of autoregressive processes. It is shown that, contrary to the case where the noise is independent (see Kim, Qian and Schmidt (1999)), using high-order moments can provide substantial efficiency gains for estimating the AR(p) model when the noise is only uncorrelated.

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Year of publication:	2000-06
Authors:	BROZE, Laurence ; FRANCQ, Christian ; ZAKOIAN, Jean-Michel
Institutions:	Center for Operations Research and Econometrics (CORE), École des Sciences Économiques de Louvain
Subject:	autoregressive process \| efficiency gains \| GMM \| empirical autocorrelations \| Yule-Walker estimator

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Extent:	application/pdf
Series:	CORE Discussion Papers.
Type of publication:	Book / Working Paper
Notes:	The text is part of a series UNIVERSITE CATHOLIQUE DE LOUVAIN, Center for Operations Research and Econometrics (CORE) Number 2000033
Classification:	C13 - Estimation ; C22 - Time-Series Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005065430