Fear Not Scarcity but Inequality,Not Poverty but Instability

About 2,800 years ago, in the land later called China, numerous states fiercely competed for dominance or survival. These competitions lasted for over 500 years. In the first half of this period alone (the Spring and Autumn Period, which was relatively peaceful in comparison to the later Warring States Period), 36 kings were killed, 52 states were eliminated, and at least 480 wars were staged. ¹ After viewing these many and fierce competitions, Confucius saw that the key for state success was not to fear scarcity but inequality, not poverty but instability. He asserted that poverty would disappear when there was equality, scarcity would vanish when there was harmony, and subversion would be nonexistent when there was stability. Confucius said this when being asked whether warlord Ji should attack warlord Zhuanyu. He warned that the trouble of Ji lay not in Zhuanyu but behind the walls of its own territory. ²

Confucius words are still relevant today. Contemporary researchers have documented the rampant effects of inequality, from concentrating poverty in urban neighborhoods (Sampson 2012; Wilson 1987) to increasing crime (Kelly 2000; Western 2006), from elevating teenage birthrates (Small and Newman 2001) to damaging health (Wilkinson and Pickett 2006; Williams and Sternthal 2010), and from propelling family disruption (Shihadeh and Steffensmeier 1994) to stirring political unrest (Massing 2000). These undesired outcomes may further exacerbate inequality and thus create a vicious cycle that can gradually wear down a state’s competitiveness.

Since its inception, sociology has seen inequality research as one of its core intellectual missions. Inequality research, however, can be contentious. Some of the research can be fueled by and, at the same time, evaluated through the lens of partisan ideology and identity politics. Given its potential contentiousness, the research methods and proof of evidence become even more important than usual. The past decade or so has witnessed massive methodological innovations. This special issue aims to present some of the methodological innovations that arise from new analytical methods, innovative study designs, and novel and large-scale data that are particularly useful for studying social inequality. The articles included in the special issue not only showcase methodological innovations but also share the common theme that social inequalities are often interconnected across domains of life, time, space, or different policies.

Jasso argues that inequality frequently comes in pairs of input and output such as schooling and income, and income and consumption. Her paper presents a novel mathematical framework that shows that inequality in inputs and inequality in outputs can be governed by distinctive mechanisms, that the link between the two is multiform (from linear to nonlinear), and that together they determine the states and consequences of inequality.

An and Glynn attempt to more precisely quantify the links between input and output inequalities. Based on the counterfactual framework, they present a treatment effect decomposition method to assess how covariate differences contribute to outcome difference (i.e., how much the omission of particular covariates can alter the estimated treatment effect). The method achieves what Oaxaca decomposition aims to do but has a more solid causal foundation.

Bloome and Schrage point out that past research typically examines inequality in only one domain of life at a time and tends to ignore that outcomes across domains can be correlated. They present covariance regressions to model the mean and covariance of multiple outcomes from different life domains, which helps to assess multiple inequality outcomes at once, test for heterogeneous treatment effects, and explain the structure across outcomes by using covariates.

Mustillo, Li, and Ferraro articulate a cumulative inequality theory, which specifies that the accumulation of misfortune and resources in younger ages can affect subsequent life course. They present a second-order hybrid latent model that allows early misfortune and protective factors from multiple domains to combine and interact to predict adult outcomes. Their results show that the new model outperforms traditional models in various aspects.

Phillips, Levy, Sampson, and others show that past measures of neighborhood segregation tend to be static in nature and neglect the dynamic character of urban life. Using mobility data extracted from millions of geotagged Tweets around the largest 50 cities in the United States over 18 months, the authors introduce new mobility- and network-based segregation measures that more precisely reflect the structural connectedness across neighborhoods in American cities.

Zhao and Garip study how network externalities can serve as a mechanism for social inequality under homophily (i.e., individuals connect to others with similar traits) and consolidation (i.e., correlation between traits). Using an agent-based model, they show that the link from homophily to unequal diffusion outcomes is contingent on high levels of consolidation. Surprisingly, under low consolidation, homophily can even alleviate intergroup inequality by facilitating diffusion.

It is challenging to establish causality between gender norms and housework inequality. To address that, Thebaud, Kornrich, and Ruppanner designed a novel experiment that randomly assigned participants to evaluate photos of clean or messy rooms. Results show that female room occupants are held to higher standards of cleanliness and more responsibility for housework. The study suggests that gendered beliefs are a root cause for gender inequality more broadly.

Jackson challenges the conventional view that educational expansion will reduce educational inequality. She argues that this view is flawed by poor measures of expansion and a simplistic understanding of the relationship between supply, demand, and educational inequality. She shows that if the old rules for admission persist, those from more privileged backgrounds are still more likely to obtain the new slots, which can maintain or exacerbate educational inequality.

I want to thank the contributors for their enthusiasm and patience for the special issue. I am very grateful to former editor-in-chief Christopher Winship for granting me to organize this special issue and to current editor-in-chief Felix Elwert for helping me complete the special issue. My deep appreciation goes to the managing editors Genevieve Butler and Lisa Charron for keeping things on track. I also thank my department Chairs Clifford Carrubba and Timothy Dowd and my colleagues at Emory for supporting me to work on this special issue.

Finally, let me end by encouraging researchers to continue their pursuit of rigorous methods for inequality research and also to engage more with comparative research on inequality, as other countries’ experiences can provide valuable lessons (Whyte 2010), and the ramifications of inequality increasingly spill over across countries (Beckfield 2006).