Analyzing Age-Period-Cohort Data: A Review and Critique

Age-period-cohort (APC) analysis has a long, controversial history in sociology and related fields. Despite the existence of hundreds, if not thousands, of articles and dozens of books, there is little agreement on how to adequately analyze APC data. This article begins with a brief overview of APC analysis, discussing how one can interpret APC effects in a causal way. Next, we review methods that obtain point identification of APC effects, such as the equality constraints model, Moore-Penrose estimators, and multilevel models. We then outline techniques that entail point identification using measured causes, such as the proxy variables approach and mechanism-based models. Next, we discuss a general framework for APC analysis grounded in partial identification using bounds and sensitivity analyses. We conclude by outlining a general step-by-step procedure for conducting APC analyses, presenting an empirical example examining temporal shifts in verbal ability.