Non redundancy of high order moment conditions for efficient GMM estimation of weak AR processes
AbstractThis 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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Bibliographic InfoPaper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2000033.
Date of creation: 00 Jun 2000
Date of revision:
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autoregressive process; efficiency gains; GMM; empirical autocorrelations; Yule-Walker estimator.;
Other versions of this item:
- Broze, Laurence & Francq, Christian & Zakoian, Jean-Michel, 2001. "Non-redundancy of high order moment conditions for efficient GMM estimation of weak AR processes," Economics Letters, Elsevier, vol. 71(3), pages 317-322, June.
- BROZE, Laurence & FRANCQ , Christian & ZAKOIAN, Jean-Michel, . "Non-redundancy of high order moment conditions for efficient GMM estimation of weak AR processes," CORE Discussion Papers RP -1576, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kim, Yangseon & Qian, Hailong & Schmidt, Peter, 1999. "Efficient GMM and MD estimation of autoregressive models," Economics Letters, Elsevier, vol. 62(3), pages 265-270, March.
- Christian Francq & Jean-Michel Zakoïan, 1997.
"Estimating Weak Garch Representations,"
97-40, Centre de Recherche en Economie et Statistique.
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- HAFNER, Christian, 2001.
"Fourth moments of multivariate GARCH processes,"
CORE Discussion Papers
2001046, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- West,K.D. & Wong,K.-F. & Anatolyev,S., 2001.
"Instrumental variables estimation of heteroskedastic linear models using all lags of instruments,"
20, Wisconsin Madison - Social Systems.
- Kenneth West & Ka-fu Wong & Stanislav Anatolyev, 2009. "Instrumental Variables Estimation of Heteroskedastic Linear Models Using All Lags of Instruments," Econometric Reviews, Taylor & Francis Journals, vol. 28(5), pages 441-467.
- Kenneth D. West & Ka-fu Wong & Stanislav Anatolyev, 2007. "Instrumental Variables Estimation of Heteroskedastic Linear Models Using All Lags of Instruments," NBER Working Papers 13134, National Bureau of Economic Research, Inc.
- Kenneth D. West & Ka-fu Wong & Stanislav Anatolyev, 2007. "Instrumental Variables Estimation of Heteroskedastic Linear Models Using All Lags of Instruments," NBER Technical Working Papers 0338, National Bureau of Economic Research, Inc.
- Carrasco, Marine & Florens, Jean-Pierre, 2003.
"On the Asymptotic Efficiency of GMM,"
IDEI Working Papers
173, Institut d'Économie Industrielle (IDEI), Toulouse.
- Jean-Pierre Florens & Marine Carrasco, 2004. "On the Asymptotic Efficiency of GMM," Econometric Society 2004 North American Winter Meetings 436, Econometric Society.
- Stanislav Anatolyev, 2005.
"Optimal Instruments in Time Series: A Survey,"
w0069, Center for Economic and Financial Research (CEFIR).
- West, Kenneth D., 2002. "Efficient GMM estimation of weak AR processes," Economics Letters, Elsevier, vol. 75(3), pages 415-418, May.
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