Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Weir's 2009 report on NFL brain injuries got more attention than neurological findings published in 2005

Edin and Shaefer's book a call to action for Americans to deal with poverty

Weir says pain may underlie rise in suicide and substance-related deaths among white middle-aged Americans


MCubed opens for new round of seed funding, November 4-18

PSC News, fall 2015 now available

Barbara Anderson appointed chair of Census Scientific Advisory Committee

John Knodel honored by Thailand's Chulalongkorn University

Next Brown Bag

Monday, Dec 7 at noon, 6050 ISR-Thompson
Daniel Eisenberg, "Healthy Minds Network: Mental Health among College-Age Populations"

Propensity-Score-Based Methods versus MTE-Based Methods in Causal Inference

Publication Abstract

Download PDF versionZhou, Xiang, and Yu Xie. 2011. "Propensity-Score-Based Methods versus MTE-Based Methods in Causal Inference." PSC Research Report No. 11-747. December 2011.

Since the seminal introduction of the propensity score by Rosenbaum and Rubin, propensity-score-based (PS-based) methods have been widely used for drawing causal inferences in the behavioral and social sciences. However, the propensity score approach depends on the ignorability assumption: there are no unobserved confounders once observed covariates are taken into account. For situations where this assumption may be violated, Heckman and his associates have recently developed a novel approach based on marginal treatment effects (MTE). In this paper, we (1) explicate consequences for PS-based methods when aspects of the ignorability assumption are violated; (2) compare PS-based methods and MTE-based methods by making a close examination of their identification assumptions and estimation performances; (3) illustrate these two approaches in estimating the economic return to college using data from NLSY 1979 and discuss discrepancies in results. When there is a sorting gain but no systematic baseline difference between treated and untreated units given observed covariates, PS-based methods can identify the treatment effect of the treated (TT). The MTE approach performs best when there is a valid and strong instrumental variable (IV).

Country of focus: United States of America.

Browse | Search : All Pubs | Next