Nonparametric Density and Regression Estimation
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.
Volume (Year): 15 (2001)
Issue (Month): 4 (Fall)
|Contact details of provider:|| Web page: https://www.aeaweb.org/jep/|
More information through EDIRC
|Order Information:||Web: https://www.aeaweb.org/subscribe.html|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- HÄRDLE, Wolfgang, 1992.
"Applied nonparametric methods,"
CORE Discussion Papers
1992003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Härdle, W.K., 1992. "Applied Nonparametric Methods," Discussion Paper 1992-6, Tilburg University, Center for Economic Research.
- Wolfgang Hardle & Oliver Linton, 1994. "Applied Nonparametric Methods," Cowles Foundation Discussion Papers 1069, Cowles Foundation for Research in Economics, Yale University.
- Hardle, W., 1992. "Applied Nonparametric Methods," Papers 9204, Catholique de Louvain - Institut de statistique.
- Hardle, W., 1992. "Applied Nonparametric Methods," Papers 9206, Tilburg - Center for Economic Research.
- Oliver LINTON, .
"Applied nonparametric methods,"
Statistic und Oekonometrie
9312, Humboldt Universitaet Berlin.
- A. Yatchew, 2000. "Scale economies in electricity distribution: a semiparametric analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(2), pages 187-210.
- McKinley L. Blackburn & David Neumark, 1991.
"Omitted-Ability Bias and the Increase in the Return to Schooling,"
NBER Working Papers
3693, National Bureau of Economic Research, Inc.
- Blackburn, McKinley L & Neumark, David, 1993. "Omitted-Ability Bias and the Increase in the Return to Schooling," Journal of Labor Economics, University of Chicago Press, vol. 11(3), pages 521-44, July.
- Subramanian, Shankar & Deaton, Angus, 1996.
"The Demand for Food and Calories,"
Journal of Political Economy,
University of Chicago Press, vol. 104(1), pages 133-62, February.
- James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998.
"Characterizing Selection Bias Using Experimental Data,"
NBER Working Papers
6699, National Bureau of Economic Research, Inc.
- James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
- Horowitz, Joel L., 2001. "The Bootstrap," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 52, pages 3159-3228 Elsevier.
- Tobias, Justin, 2001.
"Are Returns to Schooling Concentrated Among the Most Able? A Semiparametric Analysis of the Ability-Earnings Relationships,"
Staff General Research Papers
12016, Iowa State University, Department of Economics.
- Tobias, J.L., 2000. "Are Return to Schooling Concentrated Among the Most Able? A Semiparametric Analysis of the Ability-Earnings Relationship," Papers 00-01-12, California Irvine - School of Social Sciences.
- Adonis Yatchew, 1998. "Nonparametric Regression Techniques in Economics," Journal of Economic Literature, American Economic Association, vol. 36(2), pages 669-721, June.
- Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-54, July.
- Yatchew, A., 1997. "An elementary estimator of the partial linear model," Economics Letters, Elsevier, vol. 57(2), pages 135-143, December.
When requesting a correction, please mention this item's handle: RePEc:aea:jecper:v:15:y:2001:i:4:p:11-28. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Jane Voros)or (Michael P. Albert)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.