The Variance of Non-Parametric Treatment Effect Estimators in the Presence of Clustering
AbstractNonparametric estimators of treatment effects are often applied in settings where clustering may be important. We provide a general methodology for consistently estimating the variance of a large class of nonparametric estimators, including the simple matching estimator, in the presence of clustering. Software for implementing our variance estimator is available in Stata. © 2012 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.
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Bibliographic InfoArticle provided by MIT Press in its journal Review of Economics and Statistics.
Volume (Year): 94 (2012)
Issue (Month): 4 (November)
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Web page: http://mitpress.mit.edu/journals/
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
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