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Mean-squared-error Calculations for Average Treatment Effects

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Author Info
Guido W. Imbens () (Department of Economics, UC Berkeley and NBER)
Whitney Newey () (Department of Economics, MIT)
Geert Ridder () (Department of Economics, University of Southern California)
Abstract

This paper develops a new nonparametric series estimator for the average treatment effect for the case with unconfounded treatment assignment, that is, where selection for treatment is on observables. The new estimator is efficient. In addition we develop an optimal procedure for choosing the smoothing parameter, the number of terms in the series by minimizing the mean squared error (MSE). The new estimator is linear in the first-stage nonparametric estimator. This simplifies the derivation of the MSE of the estimator as a function of the number of basis functions that is used in the first stage nonparametric regression. We propose an estimator for the MSE and show that in large samples minimization of this estimator is equivalent to minimization of the population MSE.

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File URL: http://www.usc.edu/dept/LAS/economics/IEPR/Working%20Papers/IEPR_06.56_%5BMoon,%20Schorfheide%5D.pdf
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Publisher Info
Paper provided by Institute of Economic Policy Research (IEPR) in its series IEPR Working Papers with number 06.57.

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Length: 48 pages
Date of creation: Nov 2006
Date of revision:
Handle: RePEc:scp:wpaper:06-57

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Related research
Keywords: Nonparametric Estimation; Imputation; Mean Squared Error; Order Selection;

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Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

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References listed on IDEAS
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Cited by:
(explanations, 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.)

  1. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Nonparametric Tests for Treatment Effect Heterogeneity," NBER Technical Working Papers 0324, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  2. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens, 2006. "Moving the Goalposts: Addressing Limited Overlap in Estimation of Average Treatment Effects by Changing the Estimand," IZA Discussion Papers 2347, Institute for the Study of Labor (IZA). [Downloadable!]
    Other versions:
  3. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Moving the Goalposts: Addressing Limited Overlap in the Estimation of Average Treatment Effects by Changing the Estimand," NBER Technical Working Papers 0330, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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