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

Laurence Broze (), Christian Francq and Jean-Michel Zakoian

No 2000033, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: 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.

Keywords: autoregressive process; efficiency gains; GMM; empirical autocorrelations; Yule-Walker estimator. (search for similar items in EconPapers)
JEL-codes: C13 C22 (search for similar items in EconPapers)
Date: 2000-06
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Related works:
Journal Article: Non-redundancy of high order moment conditions for efficient GMM estimation of weak AR processes (2001)
Working Paper: Non-redundancy of high order moment conditions for efficient GMM estimation of weak AR processes (2001)
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Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:2000033

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