Matias D. Cattaneo, Michael Jansson, Xinwei Ma
arXiv 28 Nov 2018 · Econometrics · publishedJournal of the American Statistical Association (2019) · 662 citations (OpenAlex)
arXiv:1811.11512 · PDF · DOI · OpenAlex · Extracted main text
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.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Fan, J., and Gijbels, I (1996) Local Polynomial Modelling and Its Applications | 1.000 | 5 | 4 | 100% |
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