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The Variance of Non-Parametric Treatment Effect Estimators in the Presence of Clustering

Samuel Hanson and Adi Sunderam
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Adi Sunderam: Harvard Business School

The Review of Economics and Statistics, 2012, vol. 94, issue 4, 1197-1201

Abstract: Nonparametric 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.

Keywords: treatment effects; matching estimators; clustering (search for similar items in EconPapers)
JEL-codes: C14 C21 (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (7)

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The Review of Economics and Statistics is currently edited by Pierre Azoulay, Olivier Coibion, Will Dobbie, Raymond Fisman, Benjamin R. Handel, Brian A. Jacob, Kareen Rozen, Xiaoxia Shi, Tavneet Suri and Yi Xu

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