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Bootstrap estimation of covariance matrices via the percentile method


  • José A. F. Machado
  • Paulo Parente


Consistency of the bootstrap second moments does not usually follow from the proofs of consistency of the distribution of the bootstrap. Here it is shown that the convergence of the bootstrap distribution to a normal variate implicitly defines a consistent estimator for the asymptotic second moments. The estimator is based on the L-estimation of the scale parameter of arbitrary linear combinations of the bootstrap sequence and uses Classical Minimum Distance techniques to impose the positive semi-definiteness restrictions. Copyright 2005 Royal Economic Society

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  • José A. F. Machado & Paulo Parente, 2005. "Bootstrap estimation of covariance matrices via the percentile method," Econometrics Journal, Royal Economic Society, vol. 8(1), pages 70-78, March.
  • Handle: RePEc:ect:emjrnl:v:8:y:2005:i:1:p:70-78

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    References listed on IDEAS

    1. Karim M. Abadir & Jan R. Magnus, 2002. "Notation in econometrics: a proposal for a standard," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 76-90, June.
    2. Harvey, A. C. & Phillips, G. D. A., 1974. "A comparison of the power of some tests for heteroskedasticity in the general linear model," Journal of Econometrics, Elsevier, vol. 2(4), pages 307-316, December.
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    Cited by:

    1. Daniel Ackerberg & Xiaohong Chen & Jinyong Hahn & Zhipeng Liao, 2014. "Asymptotic Efficiency of Semiparametric Two-step GMM," Review of Economic Studies, Oxford University Press, vol. 81(3), pages 919-943.
    2. Fernandes, Marcelo & Guerre, Emmanuel & Horta, Eduardo, 2017. "Smoothing quantile regressions," Textos para discussão 457, FGV/EESP - Escola de Economia de São Paulo, Getulio Vargas Foundation (Brazil).

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