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Nonparametric Density and Regression Estimation

  • John DiNardo
  • Justin L. Tobias

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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File URL: http://www.aeaweb.org/articles.php?doi=10.1257/jep.15.4.11
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Article provided by American Economic Association in its journal Journal of Economic Perspectives.

Volume (Year): 15 (2001)
Issue (Month): 4 (Fall)
Pages: 11-28

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Handle: RePEc:aea:jecper:v:15:y:2001:i:4:p:11-28
Note: DOI: 10.1257/jep.15.4.11
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  1. 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.
  2. Yatchew, A., 1997. "An elementary estimator of the partial linear model," Economics Letters, Elsevier, vol. 57(2), pages 135-143, December.
  3. Hardle, W., 1992. "Applied Nonparametric Methods," Papers 9206, Tilburg - Center for Economic Research.
  4. 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.
  5. 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.
  6. Adonis Yatchew, 1998. "Nonparametric Regression Techniques in Economics," Journal of Economic Literature, American Economic Association, vol. 36(2), pages 669-721, June.
  7. Oliver LINTON, . "Applied nonparametric methods," Statistic und Oekonometrie 9312, Humboldt Universitaet Berlin.
  8. 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.
  9. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-54, July.
  10. 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.
  11. 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.
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