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Cited by 257

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Nonparametric Density and Regression Estimation

DiNardo, John, Tobias, Justin L·2001·Journal of Economic Perspectives

Abstract

We provide a nontechnical review of recent nonparametric methods for estimating density and regression functions. The methods we describe make it possible for a researcher to estimate a regression function or density without having to specify in advance a particular--and hence potentially misspecified functional form. We compare these methods to more popular parametric alternatives (such as OLS), illustrate their use in several applications, and demonstrate their flexibility with actual data and generated-data experiments. We show that these methods are intuitive and easily implemented, and in the appropriate context may provide an attractive alternative to “simpler” parametric methods.

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Metadata

Authors
DiNardo, J., & Tobias, J. L.
Venue
Journal of Economic Perspectives
Published
2001-11-01
Volume
15
Issue
4
Pages
11-28
ISSN
0895-3309 (ISSN-L)
OpenAlex
W2119703862
Cited by
257
References
5
FWCI
10.65
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Nonparametric Density and Regression Estimation. https://app.cochat.ai/papers/10.1257/jep.15.4.11
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DiNardo, J., & Tobias, J. L. (2001). Nonparametric Density and Regression Estimation. Journal of Economic Perspectives. https://doi.org/10.1257/jep.15.4.11

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