UC Berkeley

This paper develops a design-based approach to identifying cohort effects in APC analyses. Cohort effects arise when one cohort is treated by a unique set of formative socialization experiences, which causes it to differ from other cohorts in relevant outcomes. APC analyses typically compare treated and untreated cohorts from a single population. Our approach introduces a second group-a control group, in which no unit is treated but that is otherwise similar to the first-and adapts difference-in-differences estimation to the APC framework. The approach yields two identification strategies, each based on transparent and testable assumptions. We illustrate how the method works and what is to be gained through three examples. © 2013 Elsevier Ltd.