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.
|Date of creation:||00 Jun 2000|
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- Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
- Francq, Christian & Zako an, Jean-Michel, 2000.
"Estimating Weak Garch Representations,"
Cambridge University Press, vol. 16(05), pages 692-728, October.
- 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.
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