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Second order asymptotic efficiency in a partial linear model

Author

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  • Hua, Liang
  • Ping, Cheng

Abstract

In this paper, the authors discuss the second order asymptotic efficiency of estimators of [beta] based on MLE for Y=X[beta]+g(T)+[epsilon], where X,T, [epsilon] are independent, g is unknown, [epsilon] [approximate] [phi](·) is known with mean 0 and variance [sigma]2.

Suggested Citation

  • Hua, Liang & Ping, Cheng, 1993. "Second order asymptotic efficiency in a partial linear model," Statistics & Probability Letters, Elsevier, vol. 18(1), pages 73-84, August.
    • Handle: RePEc:eee:stapro:v:18:y:1993:i:1:p:73-84
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    Citations

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    Cited by:

    1. Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
    2. He, Xuming & Liang, Hua, 1997. "Quantile regression estimates for a class of linear and partially linear errors-in-variables models," SFB 373 Discussion Papers 1997,103, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    3. Linton, Oliver, 2002. "Edgeworth approximations for semiparametric instrumental variable estimators and test statistics," Journal of Econometrics, Elsevier, vol. 106(2), pages 325-368, February.
    4. Härdle, Wolfgang & Liang, Hua & Sommerfeld, Volker, 1997. "Bootstrap approximations in a partially linear regression model," SFB 373 Discussion Papers 1997,102, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    5. Gao, Jiti & Liang, Hua, 1995. "Asymptotic normality of pseudo-LS estimator for partly linear autoregression models," Statistics & Probability Letters, Elsevier, vol. 23(1), pages 27-34, April.

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