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

A-Tier
Journal: Review of Economics and Statistics
Year: 2012
Volume: 94
Issue: 4
Pages: 1197-1201

Authors (2)

Samuel G. Hanson (Harvard University) Adi Sunderam (not in RePEc)

Score contribution per author:

2.011 = (α=2.01 / 2 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:tpr:restat:v:94:y:2012:i:4:p:1197-1201
Journal Field
General
Author Count
2
Added to Database
2026-01-25