Simple Local Polynomial Density Estimators

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...

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Bibliographic Details
Published in:Journal of the American Statistical Association Vol. 115; no. 531; pp. 1449 - 1455
Main Authors: Cattaneo, Matias D., Jansson, Michael, Ma, Xinwei
Format: Journal Article
Language:English
Published: Alexandria Taylor & Francis 02.07.2020
Taylor & Francis Ltd
Subjects:
Americans
Asymptotic properties
computer software
Density
Density estimation
Discontinuity
Inference
Local polynomial methods
Manipulation test
Polynomials
Program evaluation
Property
Regression analysis
Regression discontinuity
selection methods
Statistical methods
Statistics
Transformation
ISSN:0162-1459, 1537-274X, 1537-274X
Online Access:Get full text
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Summary: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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ISSN:0162-1459
1537-274X
1537-274X
DOI:10.1080/01621459.2019.1635480