When radical critics of capitalism become desperate for empirical models that embody their aspirations, wishful thinking can triumph over sober assessments. The complementary danger is cynicism; there is great cachet among intellectuals in debunking naïve enthusiasm. What is needed, then, are accounts of empirical cases that are neither gullible nor cynical, but try to fully recognize the complexity and dilemmas as well as the real potentials of practical efforts at social empowerment. – Erik Olin

The study of intergenerational income mobility has witnessed more visibility in academic and public policy circles in light of the new estimates generated by Chetty and colleagues. The distribution of race-based estimates of intergenerational income mobility demonstrates strong spatial patterning, such that the success of a child’s traversal to the top income quintile in the United States is spatially conditioned and dependent on locality. However, research drawing on the new estimates of intergenerational income mobility

Why do countries diverge significantly in the levels of income inequality across the Global North? Most scholars believe that the answer lies in the ways that economic resources are organized through institutions. Drawing on a country-level, longitudinal dataset from 1985 to 2016 matched with three other data sources, the author explains how and to what extent institutions matter for income inequality across the “varieties of capitalism.” To sort countries based on their institutional similarities, the

This article explores the regional and national determinants of workplace discrimination complaints across the US states from 2009–2018. Drawing on the EEOC charge data supplemented with a number of additional data sources, the authors examine the extent to which socioeconomic, demographic, and political environments explain variation in the rate of total, race, and sex-based employment discrimination charges. Building on the neoinstitutional and power resource theories, the authors examine the role of social-structural factors as important

This study investigates the regional determinants of collective action in the era of “American Resistance.” Drawing on a new dataset from “Count Love”—a machine learning tool that collects data on protest events, timing, location, and number of attendees—we explore the regional determinants of collective action in the first three years following President Trump’s election. In particular, we investigate how socio-economic factors, political partisanship and demographic composition of states affect the rate of protest events and