The Chinese regime has launched a number of online government transparency initiatives to increase the volume of publicly available information about the activities of lower-level governments. By analyzing online content produced by local government officials to fulfill these transparency requirements—a random sample of 1.92 million county-level government web pages—this paper shows how websites are commandeered by local-level officials to construct their public image. The majority of content on government websites emphasizes either the competence or benevolence of county executives, depending on where leaders are in the political tenure cycle. Early tenure county executives project images of benevolence by emphasizing their attentiveness and concern toward citizens. Late tenure executives project images of competence by highlighting their achievements. These findings shift the nature of debates concerning the role of the Internet in authoritarian regimes from a focus on regime–society interactions to an examination of dynamics among regime insiders. By focusing on communication and the flow of information between upper-level leaders and lower-level regime agents, this paper reveals how the Internet becomes a vehicle of self-promotion for local politicians.

China’s rapid rise on the global economic stage has substantial and unequal employment effects in advanced industrialized democracies given China’s large volume of low-wage labor. Thus far, these effects have not been analyzed in the comparative political economy literature. Building on pooled time-series data, we analyze the effects of Chinese trade competition across 17 sectors in 18 countries. We devote attention to a new channel, increased competition from China in foreign export markets. Our empirical findings reveal overall employment declines in sectors more exposed to Chinese imports. Furthermore, our results suggest that employment effects are not equally shared across skill levels, as the share of hours worked worsens for low-skilled workers.

The onset of intrastate conflict has two requisite conditions: that prospective insurgents have an incentive to rebel, and that the state lacks the capacity to deter such a rebellion. We outline a simple rationalist argument grounded in gains from economic growth—to both individual income and state revenue—to argue that modernization has the potential to affect the likelihood of civil conflict through both of these conditions. The shift away from a rent-seeking economy affects opportunity costs for rebellion by increasing the cost of recruitment, broadening the time horizon for gain, and decreasing looting possibilities. On the state side, modernization increases state military, economic, and institutional capacity, allowing governments to deter rebellion. We construct an index of modernization from World Bank data and apply a strategic model to explore the effect of modernization on both states and rebels simultaneously. We find that the modernization process describes an arc that may increase the likelihood of unrest in the early stages, but has long-term stabilizing effects.

The prevention of terrorist attacks is an important concern for many governments. In democracies, officials also fear the electoral consequences of successful attacks. As a result, counterterrorism policy-making and electoral concerns are tightly intertwined. To understand the implications of this link, I develop a game-theoretic model and show that left-wing incumbents respond to terror threats more aggressively than their right-wing counterparts in order to convince voters that they can be trusted in fighting terrorism. Terrorist attacks improve right-wing incumbents’ reputation, while they worsen the reputation of left-wing incumbents. When the terrorist threat is high, voters ignore right-wing incumbents’ reputation, reelecting them independently of their performance. Finally, I consider the strategic consequences of maintaining counterterrorism policies hidden from the public eye.

Which factors make it more likely that states militarily intervene in ongoing intrastate wars? We develop the argument that migrants, i.e., (1) people coming from the civil-war state living in a potential intervener state (immigrants) and (2) those living in the country at war who stem from the third party (emigrants), influence the decision of external states to intervene in civil wars. Our theoretical framework is thus based on a joint focus on domestic-level determinants in a civil-war country and in foreign states. Primarily based on an accountability rationale, we also claim that the third-party’s regime type has an intervening influence. Using quantitative methods, our empirical results generally support the theory, although there is only weak evidence for the intervening influence of a third party’s level of democracy.

In close elections, a sufficiently high share of invalid ballots—if driven by voter mistakes or electoral fraud—can jeopardize the electoral outcome. We study how the closeness of electoral race relates to the share of invalid ballots, under the traditional paper-ballot hand-counted voting technology. Using a large micro-level data set from the Italian parliamentary elections in 1994–2001, we find a strong robust negative relationship between the margin of victory of the leading candidate over the nearest rival and the share of invalid ballots. We argue that this relationship is not driven by voter mistakes, protest, or electoral fraud. The explanation that garners most support is that of rational allocation of effort by election officers and party representatives, with higher rates of detection of invalid ballots in close elections.

A growing literature in political science has pointed to the importance of heuristics in explaining citizens’ political attitudes, beliefs, and behaviors. At the same time, the multidisciplinary research on heuristics in general has revealed that individuals seem to use heuristics sensibly—applying them (perhaps subconsciously) when they are likely to be helpful but not otherwise. We extend this multidisciplinary work to political behavior and present a general theory of contextual variation in political heuristic use applied to discover under what conditions (i.e., what political contexts) voters will use a partisanship heuristic to infer the legislative votes of their legislators in imperfectly disciplined voting contexts. More specifically, we predict that US constituents of loyal partisan senators will use the partisanship heuristic more often than constituents of less loyal senators. Our empirical analysis reveals strong support for our theory, contributing to our understanding of political heuristics in general and adding nuance to our understanding of the partisanship heuristic in particular.

This manuscript presents a new measure of safety net program effectiveness—a “poverty relief ratio”—that is based on the estimated relationship between market income and social transfers, and reports the amount of income support provided, relative to the amount required to provide for all low-income households’ basic needs. In an important advance over the standard poverty reduction rate measures, the poverty relief ratio preserves the rank order of observations across varying poverty thresholds. In this paper, we introduce this measure and demonstrate its validity by tracking major changes in federal policy and cross-state variation in safety net programs.

This study uses a discordant sibling-based design to assess the extent to which education is proxying for pre-adult experiences and predispositions rooted in the family. It draws on a unique data set that combines official voting records with Census data on siblings and their parents. The results show that the association between education and voting is considerably reduced when parental education, parental voting and unobserved characteristics that are shared by siblings within the same family are taken into account. This finding is confirmed by a variety of robustness checks. We end with a discussion of the benefits and limitations of sibling-based designs for testing causal hypotheses.

Many commonly used data sources in the social sciences suffer from non-random measurement error, understood as mis-measurement of a variable that is systematically related to another variable. We argue that studies relying on potentially suspect data should take the threat this poses to inference seriously and address it routinely in a principled manner. In this article, we aid researchers in this task by introducing a sensitivity analysis approach to non-random measurement error. The method can be used for any type of data or statistical model, is simple to execute, and straightforward to communicate. This makes it possible for researchers to routinely report the robustness of their inference to the presence of non-random measurement error. We demonstrate the sensitivity analysis approach by applying it to two recent studies.

Collecting network information on political elites using conventional methods such as surveys and text records is challenging in authoritarian and/or conflict-ridden states. I introduce a data collection method for elite networks using scraping algorithms to capture public co-appearances at political and social events. Validity checks using existing data show the method effectively replicates interaction-based networks but not networks based on behavioral similarities; in both cases, measurement error remains a concern. Applying the method to Nigeria illustrates that patronage—measured in terms of public connectivity—does not drive national oil companies appointments. Given that theories of elite behavior aim to understand individual-level interactions, the applicability of data using this technique is well-suited to situations where intrusive data collection is costly or prohibitive.