Causal Effect Heterogeneity

PWP-CCPR-2012-005

Abstract

Individuals differ not only in background characteristics, often called “pre-treatment heterogeneity,” but also in how they respond to a particular treatment, event, or intervention. For causal inference in the social sciences, a principal interaction for understanding selection bias is between the treatment of interest and the propensity of treatment. Although the importance of “treatment effect heterogeneity,” so defined, has also been widely recognized in the causal inference literature, empirical quantitative social science research has not fully absorbed these lessons. In this chapter, we describe key estimation strategies for the study of heterogeneous treatment effects; discuss recent research in education that attends to causal effect heterogeneity, and what we gain from such attention; and demonstrate the methods we discuss with an example of the effects of college on civic participation. The primary goal of this chapter is to encourage researchers to routinely examine treatment effect heterogeneity with the same rigor that they devote to pre-treatment heterogeneity.