Aarhus University Seal

Simple Local Polynomial Density Estimators

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Matias D. Cattaneo, Princeton University
  • ,
  • Michael Jansson
  • Xinwei Ma, University of California at San Diego

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.

Original languageEnglish
JournalJournal of the American Statistical Association
Pages (from-to)1449-1455
Number of pages7
Publication statusPublished - Jul 2020

Bibliographical note

Publisher Copyright:
© 2019 American Statistical Association.

    Research areas

  • Density estimation, Local polynomial methods, Manipulation test, Regression discontinuity

See relations at Aarhus University Citationformats

ID: 229620185