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Multiplier Bootstrap for Empirical Processes

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Abstract

Multiplier bootstrap (MB) has been used to approximate the limiting processes of empirical processes in various papers. In this paper, we consider multiplier bootstrap in three cases. First, we consider MB for standard empirical process. Second, we extend the MB to account for estimation effects of the pre-estimated parameters or unknown nonparametric functions. Last, we consider MB for Nadaraya-Waston nonparametric kernel estimators. JEL Classification: C01, C15

Suggested Citation

  • Yu-Chin Hsu, 2016. "Multiplier Bootstrap for Empirical Processes," IEAS Working Paper : academic research 16-A010, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    • Handle: RePEc:sin:wpaper:16-a010
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    File URL: https://www.econ.sinica.edu.tw/~econ/pdfPaper/16-A010.pdf
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    Cited by:

    1. Yoichi Arai & Yu‐Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2022. "Testing identifying assumptions in fuzzy regression discontinuity designs," Quantitative Economics, Econometric Society, vol. 13(1), pages 1-28, January.
    2. Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
    3. Hsu, Yu-Chin & Shen, Shu, 2019. "Testing treatment effect heterogeneity in regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 208(2), pages 468-486.

    More about this item

    Keywords

    Empirical Process; Multiplier Bootstrap; Nonparametric Estimator;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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