This article introduces and demonstrates the utility of a new event dataset on democratic erosion around the world. Through case studies of Turkey and Brazil, we show that our Democratic Erosion Event Dataset (DEED) can help to resolve debates about the extent to which democracy is backsliding based on prominent cross-national indicators, focusing in particular on the Varieties of Democracy (V-Dem) and Little and Meng (L&M) indices. V-Dem suggests that democracies are deteriorating worldwide; L&M argue that this may be an artifact of subjectivity and coder bias and that more “objective” indicators reveal little to no global democratic backsliding in recent years. Using DEED, we show that—at least in these cases—objective indices may underestimate the extent of democratic erosion whereas subjective indices may overestimate it. Our analyses illustrate the ways in which DEED can complement existing indices by illuminating the nature and dynamics of democratic erosion as it occurs on the ground.

Oil discoveries, paired with delays in production, have created a new phenomenon: sustained post-discovery, pre-production periods. While research on the resource curse has debated the effects of oil on governance and conflict, less is known about the political effects of oil discoveries absent production. Using comprehensive electoral data from Uganda and a difference-in-differences design with heterogeneous effects, we show that oil discoveries increased electoral support for the incumbent chief executive in localities proximate to discoveries, even prior to production. Moreover, the biggest effects occurred in localities that were historically most electorally competitive. Overall, we show that the political effects of oil discoveries vary subnationally depending on local political context and prior to production, with important implications for understanding the roots of the political and conflict curses.

While recent evidence suggests that women exhibit a high capacity to cooperate in all-women groups, existing research focuses on how women cooperate among themselves versus in mixed-gender situations. We still know little, however, about how social differences among women affect their collective action capacity. We examine this by implementing a public goods experiment in Lebanon in which 713 women and men were randomly assigned to play in same-gender groups that were either homogeneous or heterogeneous in their class and sectarian compositions. We show that women contribute significantly less in mixed-class groups while men contribute more, reinforcing that this pattern is unique to women. We also demonstrate that class differences can undermine women’s cooperation more than sectarian differences. These findings highlight how social differences – and class differences in particular – can impede women’s collective action capacity, revealing the potential barriers to building broad, gender-based coalitions to advance women’s rights and interests.

We present new methods to estimate causal effects retrospectively from micro data with the assistance of a machine learning ensemble. This approach overcomes two important limitations in conventional methods like regression modeling or matching: (i) ambiguity about the pertinent retrospective counterfactuals and (ii) potential misspecification, overfitting, and otherwise bias-prone or inefficient use of a large identifying covariate set in the estimation of causal effects. Our method targets the analysis toward a well-defined “retrospective intervention effect” based on hypothetical population interventions and applies a machine learning ensemble that allows data to guide us, in a controlled fashion, on how to use a large identifying covariate set. We illustrate with an analysis of policy options for reducing ex-combatant recidivism in Colombia.

It is widely believed that rents from windfall revenue undermine accountability. An enduring explanation is that windfalls free leaders from the need to tax, producing a quiescent population. Yet, there is little direct evidence of how windfalls and taxes affect citizen political action. I use novel revenue and information experiments to examine whether and why windfalls (compared to taxes) affect how citizens participate in politics. The experiments were embedded in a public awareness campaign conducted with 1,863 citizens in Indonesia. The results—from an original survey and postcard campaign—indicate that the tax treatment increased monitoring and anti-incumbent political action. Yet, when given spending information, citizens in the windfall treatment cared just as much about misused revenue as those in the tax treatment. The findings have important implications for understanding not only how revenue affects citizen political behavior but also how people acquire and process information on government spending.

This article examines the significance of the Legislation Law (lifa fa), passed by the National People's Congress (NPC) in March 2000. The Legislation Law represents an attempt by the NPC to rationalize China's legal system, establish a uniform legislative hierarchy and consolidate its authority over other important lawmaking institutions. The politics behind the Law's development therefore offer insight into the balance of power in China's lawmaking arena, revealing how key institutions – the NPC, the State Council and local people's congresses – engaged in bureaucratic bargaining over fundamental questions of their existence and authority within an evolving system. While the promulgated Law reveals the mixed results of this complex process, it also makes possible a more open and consultative legislative process by sanctioning the emergence of public legislative hearings. Now gaining currency around China, hearings are a new development and could be an important step in institutionalizing more meaningful citizen participation in the legislative process.