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June 26, 2019Journal of the American Statistical Association682 citations

Simple Local Polynomial Density Estimators

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MCMatias D. CattaneoPrinceton UniversityMJMichael JanssonBerkeley CollegeXMXinwei MaHebei University of Technology

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Abstract

This article introduces an intuitive and easy-to-implement nonparametric density estimator based on local polynomial techniques. The estimator is fully boundary adaptive and automatic, but does not require prebinning or any other transformation of the data. We study the main asymptotic properties of the estimator, and use these results to provide principled estimation, inference, and bandwidth selection methods. As a substantive application of our results, we develop a novel discontinuity in density testing procedure, an important problem in regression discontinuity designs and other program evaluation settings. An illustrative empirical application is given. Two companion Stata and R software packages are provided.

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Cite This Study

Cattaneo et al. (2019) studied this question.

synapsesocial.com/papers/69fff63f64548b97a42d7897https://doi.org/10.1080/01621459.2019.1635480
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