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

PSC In The News

RSS Feed icon

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

Weitzman says China's one-child policy has had devastating effects on first-born daughters


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"

Yu Xie photo

Population Heterogeneity and Causal Inference

Publication Abstract

Download PDF versionXie, Yu. 2011. "Population Heterogeneity and Causal Inference." PSC Research Report No. 11-731. March 2011.

Population heterogeneity is ubiquitous in social science research. The very objective of social science is not to discover abstract and universal laws but to understand population heterogeneity. Due to population heterogeneity, causal inference with observational data in social science is impossible without strong assumptions. There are two potential sources of bias. The first is bias in unobserved pretreatment factors affecting the outcome even in the absence of treatment. The second is bias due to heterogeneity in treatment effects. In this paper, I show how “composition bias” due to population heterogeneity arises when treatment propensity is systematically associated with heterogeneous treatment effects. Of particular interest is the way in which composition bias, a form of selection bias, arises even under the classic assumption of ignorability, as I demonstrate with a simple simulation example.

Browse | Search : All Pubs | Next