Mean-square-error Calculations for Average Treatment Effects
Abstract
This 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.Download Info
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Paper 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:
Handle: RePEc:scp:wpaper:05-34
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Web page: http://www.usc.edu/dept/LAS/economics/IEPR/
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Related research
Keywords: 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-10-29 (All new papers)
- NEP-ECM-2005-10-29 (Econometrics)
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Martin Huber & Michael Lechner & Conny Wunsch, 2010.
"How to control for many covariates? Reliable estimators based on the propensity score,"
University of St. Gallen Department of Economics working paper series 2010
2010-30, Department of Economics, University of St. Gallen.
- Huber, Martin & Lechner, Michael & Wunsch, Conny, 2010. "How to Control for Many Covariates? Reliable Estimators Based on the Propensity Score," IZA Discussion Papers 5268, Institute for the Study of Labor (IZA).
- Busso, Matias & Kline, Patrick, 2008.
"Do Local Economic Development Programs Work? Evidence from the Federal Empowerment Zone Program,"
Working Papers
36, Yale University, Department of Economics.
- Matias Busso & Patrick Kline, 2008. "Do Local Economic Development Programs Work? Evidence from the Federal Empowerment Zone Program," Cowles Foundation Discussion Papers 1639, Cowles Foundation for Research in Economics, Yale University.
- Bryan S. Graham & Cristine Campos de Xavier Pinto & Daniel Egel, 2008.
"Inverse Probability Tilting for Moment Condition Models with Missing Data,"
NBER Working Papers
13981, National Bureau of Economic Research, Inc.
- Bryan S. Graham & Cristine Campos De Xavier Pinto & Daniel Egel, 2012. "Inverse Probability Tilting for Moment Condition Models with Missing Data," Review of Economic Studies, Oxford University Press, vol. 79(3), pages 1053-1079.
- Michael Lechner & Blaise Melly, 2010. "Partial Idendification of Wage Effects of Training Programs," Working Papers 2010-8, Brown University, Department of Economics.
- Guido Imbens & Jeffrey Wooldridge, 2008.
"Recent developments in the econometrics of program evaluation,"
CeMMAP working papers
CWP24/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
- Imbens, Guido W. & Wooldridge, Jeffrey M., 2008. "Recent Developments in the Econometrics of Program Evaluation," IZA Discussion Papers 3640, Institute for the Study of Labor (IZA).
- Guido M. Imbens & Jeffrey M. Wooldridge, 2008. "Recent Developments in the Econometrics of Program Evaluation," NBER Working Papers 14251, National Bureau of Economic Research, Inc.
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