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The Review of Economics and Statistics Vol. 94 No. 4 2012

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

Samuel Hanson; Adi Sunderam

Harvard Business School

open access

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.

DOI
10.1162/rest_a_00211
Volume
94
Issue
4
Pages
1197-1201
Language
en
Sources
openalex crossref

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