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Abstract
Two long-standing research problems of interest to sociologists are sources of variations in social inequalities and differential contributions of the temporal dimensions of age, time period, and cohort to variations in social phenomena. Recently, scholars have introduced a model called Variance Function Regression for the study of the former problem, and a model called Hierarchical Age-Period-Cohort regression has been developed for the study of the latter. This article presents an integration of these two models as a means to study the evolution of social inequalities along distinct temporal dimensions. We apply the integrated model to survey data on subjective health status. We find substantial age, period, and cohort effects, as well as gender differences, not only for the conditional mean of self-rated health (i.e., between-group disparities), but also for the variance in this mean (i.e., within-group disparities)-and it is detection of age, period, and cohort variations in the latter disparities that application of the integrated model permits. Net of effects of age and individual-level covariates, in recent decades, cohort differences in conditional means of self-rated health have been less important than period differences that cut across all cohorts. By contrast, cohort differences of variances in these conditional means have dominated period differences. In particular, post-baby boom birth cohorts show significant and increasing levels of within-group disparities. These findings illustrate how the integrated model provides a powerful framework through which to identify and study the evolution of variations in social inequalities across age, period, and cohort temporal dimensions. Accordingly, this model should be broadly applicable to the study of social inequality in many different substantive contexts.
Keywords
Hierarchical-Age-Period-Cohort-Variance-Function-Regression Model, Hierarchical Age-Period-Cohort Model, Variance Function Regression Model, health disparities
A longstanding core analytic tool of sociology is the study of inequality through regression models (Blau and Duncan 1966; Morris and Western 1999). Another is the study of social change through age-period-cohort (APC) analysis (Mason and Fienberg 1985; Ryder 1965). Use of regression-based models in APC analysis closely relates the study of cohort change to the study of inequality - substantively and methodologically - yet there have been no analytic tools for systematic examination of age and temporal (i.e., period and cohort) variations in inequalities beyond those captured by conditional means of regression models.
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