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

Samuel Hanson; Adi Sunderam

Harvard Business School

The Review of Economics and Statistics 2012 open access

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.

DOI
10.1162/rest_a_00211
Volume
94 (4)
Pages
1197-1201
Language
en
Export
BibTeX
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