Age Period Cohort Characteristic Models

Age Period Cohort Characteristic (APCC) models provide a powerful method for testing theories that involve age, period, and cohort effects, but much of that power remains unrecognized. Studies that use this method almost always focus on a single explanatory cohort characteristic and control for only age groups and periods. Even with this simple model, we note that the relationship between the dependent variable and the cohort characteristic is controlled not only for historical period and for age, but also for the period in which the cohort was born. The APCC models can accommodate controls for “contemporaneous” variables such as age/period-specific measures of percentage Black as well as for additional cohort characteristics. Autocorrelated errors, due to cohort residuals, can arise in APCC models, and we derive methods to detect and deal with this autocorrelation. OLS or WLS typically are employed to estimate the parameters in APCC models; we note that other estimation techniques, e.g., Poisson regression or logistic regression may at times be more appropriate. An empirical example illustrates these refinements and extensions using a substantively important data set.