Journal of Economic Perspectives: Vol. 15 No. 4 (Fall 2001)


Quick Tools:

Print Article Summary
Export Citation
Sign up for Email Alerts Follow us on Twitter


JEP - All Issues

Nonparametric Density and Regression Estimation

Article 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


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.

Article Full-Text Access

Full-text Article (Complimentary)


DiNardo, John (U MI)
Tobias, Justin L. (U CA, Irvine)

JEL Classifications

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


View Comments on This Article (0) | Login to post a comment

Journal of Economic Perspectives

Quick Tools:

Sign up for Email Alerts

Follow us on Twitter

Subscription Information
(Institutional Administrator Access)


JEP - All Issues

Virtual Field Journals

AEA Member Login:

AEAweb | AEA Journals | Contact Us