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Journal of Economic Perspectives

ISSN 0895-3309 (Print) | ISSN 1944-7965 (Online)

Nonparametric Density and Regression Estimation

  • John DiNardo
  • Justin L. Tobias
Journal of Economic Perspectives
vol. 15, no. 4, Fall 2001
(pp. 11–28)
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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.

Citation

DiNardo, John, and Justin L. Tobias. 2001. "Nonparametric Density and Regression Estimation." Journal of Economic Perspectives, 15 (4): 11–28. DOI: 10.1257/jep.15.4.11

JEL Classification

  • C14 Semiparametric and Nonparametric Methods
  • C20 Single Equation Models; Single Variables: General
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