Bootstrapping density-weighted average derivatives

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Bootstrapping density-weighted average derivatives. / Cattaneo, Matias D.; Crump, Richard K.; Jansson, Michael.

In: Econometric Theory, Vol. 30, No. 6, 01.01.2014, p. 1135-1164.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

Vancouver

Cattaneo MD, Crump RK, Jansson M. Bootstrapping density-weighted average derivatives. Econometric Theory. 2014 Jan 1;30(6):1135-1164. doi: 10.1017/S0266466614000127

Author

Cattaneo, Matias D. ; Crump, Richard K. ; Jansson, Michael. / Bootstrapping density-weighted average derivatives. In: Econometric Theory. 2014 ; Vol. 30, No. 6. pp. 1135-1164.

Bibtex

@article{7134791310a54b6cb961d3e1101d4714,

title = "Bootstrapping density-weighted average derivatives",

abstract = "We investigate the properties of several bootstrap-based inference procedures for semiparametric density-weighted average derivatives. The key innovation in this paper is to employ an alternative asymptotic framework to assess the properties of these inference procedures. This theoretical approach is conceptually distinct from the traditional approach (based on asymptotic linearity of the estimator and Edgeworth expansions), and leads to different theoretical prescriptions for bootstrap-based semiparametric inference. First, we show that the conventional bootstrap-based approximations to the distribution of the estimator and its classical studentized version are both invalid in general. This result shows a fundamental lack of robustness of the associated, classical bootstrap-based inference procedures with respect to the bandwidth choice. Second, we present a new bootstrap-based inference procedure for density-weighted average derivatives that is more robust to perturbations of the bandwidth choice, and hence exhibits demonstrable superior theoretical statistical properties over the traditional bootstrap-based inference procedures. Finally, we also examine the validity and invalidity of related bootstrap-based inference procedures and discuss additional results that may be of independent interest. Some simulation evidence is also presented.",

author = "Cattaneo, {Matias D.} and Crump, {Richard K.} and Michael Jansson",

year = "2014",

month = jan,

day = "1",

doi = "10.1017/S0266466614000127",

language = "English",

volume = "30",

pages = "1135--1164",

journal = "Econometric Theory",

issn = "0266-4666",

publisher = "Cambridge University Press",

number = "6",

}

RIS

TY - JOUR

T1 - Bootstrapping density-weighted average derivatives

AU - Cattaneo, Matias D.

AU - Crump, Richard K.

AU - Jansson, Michael

PY - 2014/1/1

Y1 - 2014/1/1

N2 - We investigate the properties of several bootstrap-based inference procedures for semiparametric density-weighted average derivatives. The key innovation in this paper is to employ an alternative asymptotic framework to assess the properties of these inference procedures. This theoretical approach is conceptually distinct from the traditional approach (based on asymptotic linearity of the estimator and Edgeworth expansions), and leads to different theoretical prescriptions for bootstrap-based semiparametric inference. First, we show that the conventional bootstrap-based approximations to the distribution of the estimator and its classical studentized version are both invalid in general. This result shows a fundamental lack of robustness of the associated, classical bootstrap-based inference procedures with respect to the bandwidth choice. Second, we present a new bootstrap-based inference procedure for density-weighted average derivatives that is more robust to perturbations of the bandwidth choice, and hence exhibits demonstrable superior theoretical statistical properties over the traditional bootstrap-based inference procedures. Finally, we also examine the validity and invalidity of related bootstrap-based inference procedures and discuss additional results that may be of independent interest. Some simulation evidence is also presented.

AB - We investigate the properties of several bootstrap-based inference procedures for semiparametric density-weighted average derivatives. The key innovation in this paper is to employ an alternative asymptotic framework to assess the properties of these inference procedures. This theoretical approach is conceptually distinct from the traditional approach (based on asymptotic linearity of the estimator and Edgeworth expansions), and leads to different theoretical prescriptions for bootstrap-based semiparametric inference. First, we show that the conventional bootstrap-based approximations to the distribution of the estimator and its classical studentized version are both invalid in general. This result shows a fundamental lack of robustness of the associated, classical bootstrap-based inference procedures with respect to the bandwidth choice. Second, we present a new bootstrap-based inference procedure for density-weighted average derivatives that is more robust to perturbations of the bandwidth choice, and hence exhibits demonstrable superior theoretical statistical properties over the traditional bootstrap-based inference procedures. Finally, we also examine the validity and invalidity of related bootstrap-based inference procedures and discuss additional results that may be of independent interest. Some simulation evidence is also presented.

U2 - 10.1017/S0266466614000127

DO - 10.1017/S0266466614000127

M3 - Journal article

AN - SCOPUS:84911448645

VL - 30

SP - 1135

EP - 1164

JO - Econometric Theory

JF - Econometric Theory

SN - 0266-4666

IS - 6

ER -

Department of Economics and Business Economics