The study of mobility effects is an important subject of study for sociologists. Empirical investigations of individual mobility effects, however, have been hindered by one fundamental limitation, the unidentifiability of mobility effects when origin and destination are held constant. Given this fundamental limitation, we propose to reconceptualize mobility effects from the micro to the macro level. Instead of micro-level mobility effects, the primary focus of the past literature, we ask alternative research questions about macro-level mobility effects: what happens to the population distribution of an outcome if we manipulate the mobility regime, that is, if we alter the observed association between social origin and social destination? The proposed method bridges the macro and micro agendas in social stratification research, and has wider applications in social stratification beyond the study of mobility effects. We illustrate the method with two analyses that evaluate the impact of social mobility on average fertility and income inequality in the United States respectively.
Scholars of social determinants of health have long been interested in how parents’ (origin) and adult children’s educational attainment (destination) influence health behaviors and outcomes. However, the heterogeneous effects of origin and destination on health—that is, education conveys health benefits for what socioeconomic group—remain unclear. Because of selection and interdependent pathways, a standard regression model is not suitable for addressing this question. Using clearly-defined estimands and multilevel models, we analyzed data from the Panel Study of Income Dynamics to investigate the heterogeneous and dynamic effects of origin and destination education over the life course on multiple health outcomes. We found that the protective effects of college education against risky behaviors and negative health outcomes were remarkably similar regardless of father’s or mother’s educational attainment. In contrast, parent’s education appeared to have a larger effect when children’s education level is lower. Our results also suggest distinct life-course patterns among the health variables examined. We conclude by discussing the policy implications and future directions.
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