Age–Period–Cohort Analysis of Repeated Cross-Section Surveys: Fixed or Random Effects?

Yang and Land (2006) and Yang (forthcoming-b) developed a mixed (fixed and random) effects model for the age–period–cohort (APC) analysis of micro data sets in the form of a series of repeated cross-section sample surveys that are increasingly available to demographers. The authors compare the fixedversus random-effects model specifications for APC analysis. They use data on verbal test scores from 15 cross sections of the General Social Survey (GSS), 1974 to 2000, for substantive illustrations. Strengths and weaknesses are identified for both the random- and fixed-effects formulations. However, under each of the two data conditions studied, the random-effects hierarchical APC model is the most appropriate specification. While additional analyses and comparisons of random- and fixed-effects APC models using other data sets are necessary before generalizations can be drawn, this finding is consistent with results from other methodological studies with unbalanced data designs.