Logo
Munich Personal RePEc Archive

Matching Estimators with Few Treated and Many Control Observations

Ferman, Bruno (2017): Matching Estimators with Few Treated and Many Control Observations.

This is the latest version of this item.

[thumbnail of MPRA_paper_89212.pdf]
Preview
PDF
MPRA_paper_89212.pdf

Download (415kB) | Preview

Abstract

We analyze the properties of matching estimators when there are few treated, but many control observations. We show that, under standard assumptions, the nearest neighbor matching estimator for the average treatment effect on the treated is asymptotically unbiased in this framework. However, when the number of treated observations is fixed, the estimator is not consistent, and it is generally not asymptotically normal. Since standard inferential techniques are inadequate in this setting, we propose alternative inferential procedures based on the theory of randomization tests under approximate symmetry.

Available Versions of this Item

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.