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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