1932

Abstract

Originating in econometrics and statistics, the counterfactual model provides a natural framework for clarifying the requirements for valid causal inference in the social sciences. This article presents the basic potential outcomes model and discusses the main approaches to identification in social science research. It then addresses approaches to the statistical estimation of treatment effects either under unconfoundedness or in the presence of unmeasured heterogeneity. As an update to Winship & Morgan's (1999) earlier review, the article summarizes the more recent literature that is characterized by a broader range of estimands of interest, a renewed interest in exploiting experimental and quasi-experimental designs, and important progress in the areas of semi- and nonparametric estimation of treatment effects, difference-in-differences estimation, and instrumental variable estimation. The review concludes by highlighting implications of the recent econometric and statistical literature for sociological research practice.

Loading

Article metrics loading...

/content/journals/10.1146/annurev.soc.012809.102702
2010-08-11
2024-03-29
Loading full text...

Full text loading...

/content/journals/10.1146/annurev.soc.012809.102702
Loading
  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error