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 InfoArticle provided by Elsevier in its journal Economics Letters.
Volume (Year): 71 (2001)
Issue (Month): 3 (June)
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Web page: http://www.elsevier.com/locate/ecolet
Other versions of this item:
- 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).
- BROZE, Laurence & FRANCQ, Christian & ZAKOIAN, Jean-Michel, 2000. "Non redundancy of high order moment conditions for efficient GMM estimation of weak AR processes," CORE Discussion Papers 2000033, 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
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