Simple Local Polynomial Density Estimators

Matias Cattaneo, Michael Jansson and Xinwei Ma

Papers from arXiv.org

Abstract: This paper 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 pre-binning 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.

Date: 2018-11, Revised 2019-06
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (93)

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http://arxiv.org/pdf/1811.11512 Latest version (application/pdf)

Related works:
Journal Article: Simple Local Polynomial Density Estimators (2020)
Working Paper: Simple Local Polynomial Density Estimators (2020)
Working Paper: Simple Local Polynomial Density Estimators (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1811.11512

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