Counterfactuals and causal inference: Methods and principles for social research

"Most quantitative empirical analyses are motivated by the desire to estimate the causal effect of an independent variable on a dependent variable. Although the randomized experiment is the most powerful design for this task, in most social science research done outside of psychology, experimental designs are infeasible. (Winship & Morgan, 1999, p. 659)." This quote from earlier work by Winship and Morgan, which was instrumental in setting the groundwork for their book, captures the essence of our review of Morgan and Winship's book: It is about causality in nonexperimental settings.

Testing mediation: The endogeneity problem and the solution

A mediator is a dependent variable, m (e.g., charisma), that is thought to channel the effect of an independent variable, x (e.g., receiving training or not), on another dependent variable (e.g., subordinate satisfaction), y. In experimental settings x is manipulated-subjects are randomized to treatment-to isolate the causal effect of x on other variables. If m is not or cannot be manipulated, which is often the case, its causal effect on other variables cannot be determined; thus, standard mediation tests cannot inform policy or practice. I will show how an econometric procedure, called instrumental-variable estimation, can examine mediation in such cases.