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Breakdown Point Theory for Implied Probability Bootstrap

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Abstract

This paper studies robustness of bootstrap inference methods under moment conditions. In particular, we compare the uniform weight and implied probability bootstraps by analyzing behaviors of the bootstrap quantiles when outliers take arbitrarily large values, and derive the breakdown points for those bootstrap quantiles. The breakdown point properties characterize the situation where the implied probability bootstrap is more robust than the uniform weight bootstrap against outliers. Simulation studies illustrate our theoretical findings.

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  • Lorenzo Camponovo & Taisuke Otsu, 2011. "Breakdown Point Theory for Implied Probability Bootstrap," Cowles Foundation Discussion Papers 1793, Cowles Foundation for Research in Economics, Yale University.
    • Handle: RePEc:cwl:cwldpp:1793
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    File URL: https://cowles.yale.edu/sites/default/files/files/pub/d17/d1793.pdf
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    1. Matías Salibián-Barrera & Stefan Aelst & Gert Willems, 2008. "Fast and robust bootstrap," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(1), pages 41-71, February.
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    1. repec:cep:stiecm:/2014/572 is not listed on IDEAS
    2. Lorenzo Camponovo & Taisuke Otsu, 2015. "Robustness of Bootstrap in Instrumental Variable Regression," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 352-393, March.
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    4. Ferrari, Davide & Zheng, Chao, 2016. "Reliable inference for complex models by discriminative composite likelihood estimation," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 68-80.
    5. Cristian Roner & Claudia Di Caterina & Davide Ferrari, 2021. "Exponential Tilting for Zero-inflated Interval Regression with Applications to Cyber Security Survey Data," BEMPS - Bozen Economics & Management Paper Series BEMPS85, Faculty of Economics and Management at the Free University of Bozen.

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    More about this item

    Keywords

    Bootstrap; Breakdown point; GMM;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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