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Simple Local Polynomial Density Estimators

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  • Cattaneo, Matias D
  • Jansson, Michael
  • Ma, Xinwei

Abstract

© 2019, © 2019 American Statistical Association. 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.

Suggested Citation

  • Cattaneo, Matias D & Jansson, Michael & Ma, Xinwei, 2019. "Simple Local Polynomial Density Estimators," University of California at San Diego, Economics Working Paper Series qt9vt997qn, Department of Economics, UC San Diego.
  • Handle: RePEc:cdl:ucsdec:qt9vt997qn
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    References listed on IDEAS

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    1. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2018. "On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 767-779, April.
    2. Jens Ludwig & Douglas L. Miller, 2007. "Does Head Start Improve Children's Life Chances? Evidence from a Regression Discontinuity Design," The Quarterly Journal of Economics, Oxford University Press, vol. 122(1), pages 159-208.
    3. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881.
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    Cited by:

    1. Matias D. Cattaneo & Michael Jansson & Xinwei Ma, 2019. "lpdensity: Local Polynomial Density Estimation and Inference," Papers 1906.06529, arXiv.org.
    2. Bedri Kamil Onur Tas, 2019. "Bunching Below Thresholds to Manipulate Public Procurement," RSCAS Working Papers 2019/17, European University Institute.

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