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In the three decades since the first publications linking the Matthew Effect (Dannefer, 1987, 1988) and the cumulative advantage/disadvantage (CAD) model (Crystal & Shea, 1990) to the life course, a large CAD literature has emerged. This literature has benefited from improvements in longitudinal cohort data and increasing awareness of the challenges of growing inequality. But much remains to be understood about the multilevel processes that shape late-life outcomes across time, space, and social contexts. This important special issue brings together an outstanding and thought-provoking set of papers from researchers worldwide that can help to shape how we think about cumulative advantage processes for years to come. The point-counterpoint of a major theoretical formulation by Dale Dannefer (2020) and a series of thoughtful empirical papers sets up key issues about how we think about CAD. The diversity of nations represented is a particularly valuable contribution to a literature that was somewhat U.S.-centric for many years, reducing attention to the role of policy and institutional contexts in ameliorating, replicating, or magnifying the sources of inequality over the life course. Dale Dannefer, an influential theorist of CAD whose work has made important contributions to the conceptualization of CAD processes, presents an important new theoretical formulation that brings gerontological research on CAD into conversation with broader sociological theories in ways that will likely stimulate further dialogue across disciplines. Dannefer (2020) argues for a particular way of formulating the role of micro-, meso-, and macro-level processes in CAD. His essay is particularly useful to theoretical dialogue in taking a bold, thought-provoking position on the independent role of these levels. This essay leads off a set of empirical papers offering assessments and applications of cumulative advantage processes across multiple domains. Lee and Park (2020), using data from the Midlife in the United States (MIDUS) study, find that older adults who grew up in families of low socioeconomic status (SES) experience less favorable trajectories of body mass index (BMI) throughout the life course, with higher late-life BMI even after controlling for midlife SES, indicating an independent and robust effect of early-life conditions. Using dyadic data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey, Lam (2020) reports that poor childhood health of the male partner was associated with worse mental health and self-rated health of the female partner in later life. Greenfield, Akincigil, and Moorman (2020) use data from the Wisconsin Longitudinal Survey (WLS) in a thoughtful paper on the relationship between college completion and cognition in later life. They find that college completion by age 25 was associated with better late-life cognition for both men and women, with associations among men strongest for those less likely as adolescents to complete college. This paper contributes to the long-running debate about education’s “causal” versus “credentialing” function, tending to support the former interpretation. As also shown in other papers in the collection, this article illustrates that close empirical attention to life-course trajectories often shows these processes to be more complex than suggested by a simple CAD story line. For example, the authors show how college completion could, in different scenarios, both contribute to and mitigate effects of early advantages. Taylor, Min, and Reid (2020) examine end-of-life impairment patterns in a North Carolina cohort aged 65+ at baseline in the mid-1980s, with most born in the 1920s and 1930s. They find that in the 2-year period preceding death, black–white disparities in impairment increased, primarily by hip fracture. Education effects on health diminished approaching the end of life. This study illustrates the challenging methodological problems posed by informative censoring (they found patterns of convergence that likely reflect “hardy survivor” effects) as well as the importance of situating CAD studies in the particular time, place, and social context of the cohort members’ lives. African Americans in this cohort experienced life-long effects of a racial caste system, enforced by Jim Crow norms and policies that severely limited access to health care, education, and other key resources. Placing these disparities in historical and social context can illuminate the consequences of social policies chosen through the political process that maintain particular economic and social regimes. Wildman (2020) shifts to a qualitative, micro-lens on CAD, drawing on interviews with 27 members of a baby boom cohort in the United Kingdom. Reminiscent of the powerful narratives of class status maintenance in Michael Apted’s powerful BBC series Up following posh and impoverished Britons from ages 7 to 63, Wildman provides granular insights into how an assertedly “meritocratic” education system interacted with initial social position to progressively narrow aspirations and opportunities, creating later-life winners and losers in the property market. Finally, two papers using Survey of Health, Ageing and Retirement in Europe (SHARE) data reveal the critical role of differing European welfare regimes in mitigating or exacerbating disparate later-life outcomes (Sieber et al., 2020; van der Linden, 2020). Taken together, these empirical papers and Dannefer’s theoretical framework generate and start to address key questions about CAD. How should we frame the distinctive yet intertwined roles of enduring processes of accumulation and increasing heterogeneity inherent in the life course; social change through historical contingencies (e.g., wars, epidemics, economic trends) with each cohort encountering different environments at key life stages; and social change in policies and institutions that reflect political choices and power relations? Are these separate and distinct domains best understood as following their own internal dynamics, or do they structurally shape one another? Dannefer constructively frames this pervasive issue— critical both theoretically and for the way citizens can understand and engage with the sources of social inequity—by staking out a clear position with provocative assertions on the independence of these domains. For example, he states that “As a regular feature of cohort aging, CDA processes are entirely independent of social change.” He distinguishes between the separate levels of “obdurate features of social structure that operate predictably on each succeeding cohort as it moves through its collective life course … e.g. age-graded, stratified schooling, age-graded life transitions, institutionalized pension regimes” and the level of social change as “discrete events…that may impact intracohort trajectories of inequality” but have zero effect on the underlying systemic tendencies that generate CDA.” An alternative formulation, the integrative CAD model, may be more useful for understanding the important interactions between individual life courses on the one hand and social change and policy choices on the other. This alternative perspective explicitly focuses on the dynamics of interlevel interaction in shaping patterns of inequality over the life course. The integrative CAD approach can be stated as follows. The systemic tendencies that generate CDA are not simply inherent features of social life, but vary with historical and cohort circumstances. These processes are shaped by collective and political decisions about how to structure “rules of the game” that enhance or limit opportunities for the acquisition of human, social and health capital, and economic, social, health, and functional outcomes across the life course. The integrative model therefore focuses on the interaction between changing economic, social, and institutional contexts on the one hand, and the life-course experience of particular populations, in particular national policy regimes, on the other. The integrative model draws attention to cross-cohort and cross-national comparisons that illustrate the embeddedness of CAD processes in specific social and economic contexts. In this model, individual life courses and historical change interact over each cohort’s developmental experience, as members of each cohort experience distinctive economic and social circumstances at particular critical stages of their educational, occupational and health trajectories. As distinct from a focus on micro-level processes of increasing divergence over the life course as an inherent or obdurate feature of social structure operating predictably on each succeeding cohort, which may or may not be offset by social policies, the approach emphasizes the way in which these processes themselves are shaped differently for different cohorts encountering distinctive social and economic contexts. The model also draws attention not simply to the impact of individual policies and institutions, but also to the synergistic impact of policy and institutional choices in multiple domains (e.g., education, taxation, health, retirement systems, corporate governance) that operate together to regulate individuals’ ability at critical life-course stages to move through the occupational structure, cumulate assets, maintain health status, and access other resources that shape their later-life experience. The role of social change and social choice in this model, therefore, is not simply as a “plus” or “minus” factor that can offset or exacerbate the effects of micro-level processes inherent in social life. Rather, the key research questions in this approach focus on the way in which social change and social choice shape these micro-level processes themselves. Thus, while having many areas of consistency with the important model presented by Dannefer (2020), the model seeks to “cut nature at its joints” in a somewhat different fashion and with different emphases. While all models (including this one) are wrong, some are useful, and are useful for different purposes. The integrative model seeks to be useful in understanding just how societal choices affect cumulative inequality, and informing social action to address these disparities. Important examples of the need to consider how the micro-level processes of cumulative advantage and disadvantage can themselves be shaped by social and economic contexts are studies showing declining intergenerational mobility between income quintiles (Acs & Zimmerman, 2008) and the dramatic increases in inequality worldwide, and increased returns to schooling, that affect different cohorts in quite different fashions, creating different cohort trajectories of inequality (Crystal, Shea, & Reyes, 2017), as Dannefer (2020) notes. These changes, driven both by broad economic transformations like globalization and by the cumulative effects of deliberate political and policy choices in many domains, vary significantly across countries (Piketty, 2020). Another illustration of the nonindependence of these domains is seen in the dramatically increasing rates of disability and premature mortality among noncollege-educated midlife Americans documented by Case & Deaton (2020). Ironically, as in Wildman’s account, many Americans whose lives have been derailed by deindustrialization, globalization, addiction, divorce, and other obstacles attribute these problems to their own failings of character, in a “deservingness” narrative that lays blame on the individual and diverts attention from the structural and political roots of these personal shipwrecks (Kristof & Wu-Dunn, 2020). The complex interplay of micro and policy domains is evident in the two papers using SHARE data to investigate the role of differing European welfare regimes on life-course health trajectories (Sieber et al., 2020; van der Linden et al., 2020). Health trajectories varied greatly between Scandinavian-style regimes with strong social protection and redistributional features; Bismarckian employment-based regimes that tend to perpetuate occupational advantages and disadvantages; and Southern and Eastern European regimes. In some regimes, trajectories from midlife to later life converged rather than diverged. These results reveal the power of social policies in shaping how early advantages may or may not lead to cumulative disparities, depending on the availability of buffering/leveling resources and on the nature of institutions that facilitate, or moderate, transmission of advantage within and across generations. Admission policies under which very few students from the lower half of the income distribution are admitted to elite higher education are among many examples of the way in which institutional choices intersect with life courses at critical life stages to generate life-long inequalities. Individual CAD trajectories are shaped, across national and historical contexts, by the cumulative, synergistic effects of many such discrete yet related choices. In the United States, these have included, during recent decades, massive shifts of postsecondary education costs from public payers to students via student loans; and the virtual elimination of inheritance taxes. They have also included a dysfunctional and inequitable health care system that magnifies economic and health inequality (Case & Deaton, 2020); tax policies that have dramatically reduced tax responsibility of the wealthy and encouraged tax evasion; corporate governance and norms that dramatically increase executive compensation and make more workers contingent; the carceral state; and erosion of employer-based pension systems, among many other inequality-generating choices. While globalization and technological changes have contributed to growing inequality within most high-income nations, research has shown many differences in inequality patterns across national policy regimes and in that sense, it may be fair to say that “inequality is a choice” (Stiglitz, 2015; p. 118). Similarly, looking at the way federal policies exacerbated inequality by prioritizing help to Wall Street over help to Main Street following the 2008 financial crisis, Nicholas Kristof observed: “Yet while we broadly lament inequality, we treat it as some natural disaster imposed upon us. That’s absurd. The roots of inequality are complex and, to some extent, reflect global forces, but they also reflect our policy choices.” (Kristof, 2015). This perspective contrasts with a focus on the view that inequality over the life course is an obdurate tendency of social life in general. A new historical contingency, the COVID-19 epidemic, has created profound health and economic shocks worldwide, with sharply varying impact on individuals with differing access to social and health resources. The consequences of these and other shocks to follow will challenge many institutions and policies, and shape the cumulative outcomes experienced by affected cohorts for years to come. In such a period, this special issue is especially timely. Crises create new opportunities for societies to consider what it is that makes them communities, and what contributions and sacrifices should be asked from which individuals. In societies around the world, and especially in the United States, COVID-19 laid bare the risks associated with inequities in health care, housing, and infrastructure for social protection, presaging many struggles to come over social protection and community responsibility amidst turbulent economic circumstances. Continuing research on the drivers of inequality is necessary to inform these debates. This research will require rigorous methods and high-quality data to enable longitudinal examinations of life-course trajectories, as in the papers in this volume. Future studies also should address the complex yet crucial interactions across domains of individual life-course processes, historical contingency, and shared choices for policies and institutions that shape individual life courses in fundamental ways.
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