Most of the poor in the developing world work in the informal economy, that is, in occupations that take place outside of the legal system of taxing, spending, and regulating. This article examines how informal work impacts the policy and electoral preferences of the poor. We emphasize the importance of the risks inherent in informal employment in shaping the responsiveness of citizens to clientelism and their policy and voting preferences. Since most informal workers are not covered by (formal) social insurance, they prefer material goods and candidates that produce targeted, clientelistic benefits rather than programmatically delivered insurance that is unlikely to reach them. As a result, we argue that informal workers are more likely to rely on clientelistic relations as a means of hedging risks than are formal workers; prefer policies that are delivered clientelistically via political mediators rather than programmatic solutions; and prefer clientelistic over programmatic local candidates. Our findings elucidate why the preferences of poor informal workers often diverge from those assumed by standard models of social insurance and have important implications for the political economy of social policy in a world where billions work outside work-based tax-transfer systems.

Google search is ubiquitous, and Google Trends (GT) is a potentially useful access point for big data on many topics the world over. We propose a new ‘variance-in-time’ method for forecasting events using GT. By collecting multiple and overlapping samples of GT data over time, our algorithm leverages variation both in the mean and the variance of a search term in order to accommodate some idiosyncracies in the GT platform. To elucidate our approach, we use it to forecast protests in the United States. We use data from the Crowd Counting Consortium between 2017 and 2019 to build a sample of true protest events as well as a synthetic control group where no protests occurred. The model’s out-of-sample forecasts predict protests with higher accuracy than extant work using structural predictors, high frequency event data, or other sources of big data such as Twitter. Our results provide new insights into work specifically on political protests, while providing a general approach to GT that should be useful to researchers of many important, if rare, phenomena.

Day-to-day policing represents a fundamental interface between citizens and states. Yet even in the most capable states, local policing varies enormously from one community to the next. The authors seek to understand this variation and in doing so make three contributions: First, they conceptualize communities and individuals as networks more or less capable of demanding high-quality policing. Second, they present original survey data and semistructured interviews on local policing from over one hundred sixty slums, eight thousand households, and one hundred seventy informal neighborhood leaders in India that contribute to the nascent empirical work on comparative policing and order. Third, they find evidence that well-connected individuals and densely connected neighborhoods express greater confidence in and satisfaction with local policing. Critically, these differences do not appear to be a function of a lower propensity for local conflict but rather of an increased capacity to leverage neighborhood leaders to mediate relations with the police. The combination of analytics and empirics in this article provides insight into the conditions under which individuals and communities experience the police as expropriators of rents or neutral providers of order.

Policymakers and scholars have turned their attention to federalism as a means for managing conflicts between central governments and subnational interests. But both the theoretical literature and the empirical track record of federations make for opposing conclusions concerning federalism's ability to prevent civil conflict. This article argues that the existing literature falls short on two accounts: first, it lacks a systematic comparison of peaceful and conflict-ridden cases across federal states, and second, while some studies acknowledge that there is no one-sizefits-all federal solution, the conditional ingredients of peace-preserving federalism have not been theorized. The authors make the argument that the peace-preserving effect of specific federal traits—fiscal decentralization, fiscal transfers, and political copartisanship—are conditional on a society's income level and ethnic composition. The argument is tested across twenty-two federal states from 1978 to 2000.

While increased exposure to the global economy is associated with increased welfare effort in the Organization for Economic Cooperation and Development (OECD), the opposite holds in the developing world. These differences are typically explained with reference to domestic politics. Tradables, unions, and the like in the developing world are assumed to have less power or interests divergent to those in the OECD—interests that militate against social spending. I claim that such arguments can be complemented with a recognition that developed and developing nations have distinct patterns of integration into global markets. While income shocks associated with international markets are quite modest in the OECD, they are profound in developing nations. In the OECD, governments can respond to those shocks by borrowing on capital markets and spending countercyclically on social programs. No such opportunity exists for most governments in the developing world, most of which have limited access to capital markets in tough times, more significant incentives to balance budgets, and as a result cut social spending at the times it is most needed. Thus, while internationally inspired volatility and income shocks seem not to threaten the underpinnings of the welfare state in rich nations, it undercuts the capacity of governments in the developing world to smooth consumption (and particularly consumption by the poor) across the business cycle.The author would like to thank Steph Haggard, Kristin Bakke, Wongi Choe, Tim Jones, and seminar participants at Duke University, Penn State University, Washington University, MIT, and the University of New Mexico for their helpful comments. Nancy Brune, Mark Hallerberg and Rolf Strauch, and Nita Rudra were very generous in providing their capital account, OECD fiscal, and potential labor power data, respectively.