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Bandwith choice for average derivative estimation

Author

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  • HÄRDLE, Wolfgang
  • HART, Jeffrey
  • MARRON, Steve
  • TSYBAKOV, Alexander

Abstract

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Suggested Citation

  • HÄRDLE, Wolfgang & HART, Jeffrey & MARRON, Steve & TSYBAKOV, Alexander, 1992. "Bandwith choice for average derivative estimation," LIDAM Reprints CORE 977, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvrp:977
    DOI: 10.1080/01621459.1992.10475195
    Note: In : Journal of the American Statistical Association, 87(417), 218-226, 1992
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    Cited by:

    1. Yukitoshi Matsushita & Taisuke Otsu, 2017. "Likelihood inference on semiparametric models: Average derivative and treatment effect," STICERD - Econometrics Paper Series 592, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    2. Yukitoshi Matsushita & Taisuke Otsu, 2018. "Likelihood Inference on Semiparametric Models: Average Derivative and Treatment Effect," The Japanese Economic Review, Springer, vol. 69(2), pages 133-155, June.
    3. Yoshihiko Nishiyama & Peter M. Robinson, 2005. "The Bootstrap and the Edgeworth Correction for Semiparametric Averaged Derivatives," Econometrica, Econometric Society, vol. 73(3), pages 903-948, May.
    4. Linton, Oliver, 1995. "Second Order Approximation in the Partially Linear Regression Model," Econometrica, Econometric Society, vol. 63(5), pages 1079-1112, September.
    5. Lewbel, Arthur, 2000. "Semiparametric qualitative response model estimation with unknown heteroscedasticity or instrumental variables," Journal of Econometrics, Elsevier, vol. 97(1), pages 145-177, July.
    6. Thomas Knox & James H. Stock & Mark W. Watson, 2004. "Empirical Bayes Regression With Many Regressors," Working Papers 2004-1, Princeton University. Economics Department..
    7. Oliver Linton & Douglas Steigerwald, 2000. "Adaptive testing in arch models," Econometric Reviews, Taylor & Francis Journals, vol. 19(2), pages 145-174.
    8. Marian Hristache, 2002. "Are Efficient Estimators in Single-Index Models Really Efficient? A Computational Discussion," Computational Statistics, Springer, vol. 17(4), pages 453-464, December.

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