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On teh inconsistency of bootstrap distribution estimators

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  • HALL, P.
  • HARDLE, W.
  • SIMAR, L.

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  • Hall, P. & Hardle, W. & Simar, L., 1991. "On teh inconsistency of bootstrap distribution estimators," LIDAM Discussion Papers CORE 1991020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvco:1991020
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    Cited by:

    1. Zhexiao Lin & Fang Han, 2023. "On the failure of the bootstrap for Chatterjee's rank correlation," Papers 2303.14088, arXiv.org, revised Apr 2023.
    2. Myungsup Kim & Yangseon Kim & Peter Schmidt, 2007. "On the accuracy of bootstrap confidence intervals for efficiency levels in stochastic frontier models with panel data," Journal of Productivity Analysis, Springer, vol. 28(3), pages 165-181, December.
    3. Berger, Allen N. & Humphrey, David B., 1997. "Efficiency of financial institutions: International survey and directions for future research," European Journal of Operational Research, Elsevier, vol. 98(2), pages 175-212, April.
    4. B.U.PARK & Wolfgang HAERDLE, "undated". "Testing increasing dispersion," Statistic und Oekonometrie 9314, Humboldt Universitaet Berlin.
    5. Qu Feng & William C. Horrace, 2012. "Alternative technical efficiency measures: Skew, bias and scale," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(2), pages 253-268, March.
    6. Leopold SIMAR & Wolfgang HAERDLE, "undated". "Iterated bootstrap with applications to frontier models," Statistic und Oekonometrie 9302, Humboldt Universitaet Berlin.
    7. Feng, Qu & Horrace, William C., 2012. "Estimating technical efficiency in micro panels," Economics Letters, Elsevier, vol. 117(3), pages 730-733.
    8. Hardle, W. & Park, B. U., 1995. "Testing increasing dispersion," Computational Statistics & Data Analysis, Elsevier, vol. 19(6), pages 641-653, June.
    9. Yangseon Kim & Peter Schmidt, 2000. "A Review and Empirical Comparison of Bayesian and Classical Approaches to Inference on Efficiency Levels in Stochastic Frontier Models with Panel Data," Journal of Productivity Analysis, Springer, vol. 14(2), pages 91-118, September.

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