Simple Local Polynomial Density Estimators

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.

• Publication year

  2018

• Venue

  Journal of the American Statistical Association

• Publication date

  2018-11-28

• Fields of study

  Mathematics, Computer Science, Economics

• Identifiers
  DOI 10.1080/01621459.2019.1635480arXiv 1811.11512
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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