A Mechanism-Based Approach to the Identification of Age–Period–Cohort Models

February 7, 2010

Christopher Winship and David J. Harding A Mechanism-Based Approach to the Identification of Age–Period–Cohort Models Sociological Methods & Research 2008 36: 362-401. SMR 36:3 was a Special Issue on Age-Period-Cohort Analysis.

Chris Winship, SMR EditorThis article offers a new approach to the identification of age–period–cohort (APC) models that builds on Pearl’s work on nonparametric causal models, in particular his front-door criterion for the identification of causal effects. Read the rest of this entry »


Herbert L. Smith Advances in Age–Period–Cohort Analysis Sociological Methods & Research 2008 36: 287-296.

February 7, 2010

Social indicators and demographic rates are often arrayed over time by age. The patterns of rates by age at one point in time may not reflect the effects associated with aging, which are more properly studied in cohorts. Cohort succession, aging, and period-specific historical events provide accounts of social and demographic change. Because cohort membership can be defined by age at a particular period, the statistical partitioning of age from period and cohort effects focuses attention on identifying restrictions. When applying statistical models to social data, identification issues are ubiquitous, so some of the debates that vexed the formative literature on age–period–cohort models can now be understood in a larger context. Four new articles on age–period–cohort modeling call attention to the multilevel nature of the problem and draw on advances in methods including nonparametric smoothing, fixed and random effects, and identification in structural or causal models.

Key Words: APC models • cohorts • identification strategies