Mean-square-error Calculations for Average Treatment Effects
AbstractThis paper develops a new efficient estimator for the average treatment effect, if selection for treatment is on observables. The new estimator is linear in the first-stage nonparametric estimator. This simplifies the derivation of the means squared error (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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Bibliographic InfoPaper provided by Institute of Economic Policy Research (IEPR) in its series IEPR Working Papers with number 05.34.
Length: 49 pages
Date of creation: Sep 2005
Date of revision:
Nonparametric Estimation; Imputation; Mean Squared Error; Order Selection;
Other versions of this item:
- Guido W. Imbens & Whitney Newey & Geert Ridder, 2006. "Mean-squared-error Calculations for Average Treatment Effects," IEPR Working Papers 06.57, Institute of Economic Policy Research (IEPR).
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
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