Simple Local Polynomial Density Estimators

Matias D. Cattaneo, Michael Jansson, Xinwei Ma

Research output: Contribution to journalArticlepeer-review

168 Scopus citations


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 (US)
Pages (from-to)1449-1455
Number of pages7
JournalJournal of the American Statistical Association
Issue number531
StatePublished - Jul 2 2020

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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


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