How does a candidate's racial background affect the inferences voters make about them? Prior work finds that Black candidates are perceived to be more liberal. Using two survey experiments, we test whether this effect persists when candidate partisanship and issue positions are specified and also consider other consequential voter perceptions. We make two contributions. First, we show that while Black candidates are perceived to be more liberal than White candidates with the same policy positions, this difference is smaller for Black candidates who adopt more conservative positions on race-related issues. Second, we find that voters, both Black and White, believe Black candidates will prioritize the interests of Black constituents over those of White constituents, regardless of candidate positions.

Scholars disagree as to whether Americans’ attitudes toward local issues are structured ideologically and whether these are related to national policy ideology. We use two surveys of American adults to assess whether and to what extent Americans' local policy attitudes exhibit a similar structure as do national policy attitudes. We find that items asking about local policy are just as likely to reflect a latent dimension of policy preferences as those asking about national policy. Additionally, when local and national items are scaled separately, those scales are highly correlated. Our findings indicate that attitudes toward many local issues are aligned with national ideology. A smaller subset of attitudes about local issues appears distinctively local and possibly structured by non-ideological cleavages.

Disseminating data is a core mission of international organizations. The Bretton Woods Institutions (BWIs), in particular, have become a main data source for research and policy-making. Due to their extensive lending activities, the BWIs often find themselves in a position to assist and pressure governments to increase the amount of economic data that they provide. In this study, we explore the association between loans from the BWIs and an index of economic transparency derived from the data-reporting practices of governments to the World Bank. Using a matching method for causal inference with panel data complemented by a multilevel regression analysis, we examine, separately, loan commitments and disbursements from the IMF and the World Bank. The multilevel regression analysis finds a significant association between BWI loans and the improvement of economic transparency in all developing countries; the matching method identifies a causal effect in democracies.

Scholars studying organizations often work with multiple datasets lacking shared identifiers or covariates. In such situations, researchers usually use approximate string (“fuzzy”) matching methods to combine datasets. String matching, although useful, faces fundamental challenges. Even where two strings appear similar to humans, fuzzy matching often struggles because it fails to adapt to the informativeness of the character combinations. In response, a number of machine learning methods have been developed to refine string matching. Yet, the effectiveness of these methods is limited by the size and diversity of training data. This paper introduces data from a prominent employment networking site (LinkedIn) as a massive training corpus to address these limitations. By leveraging information from the LinkedIn corpus regarding organizational name-to-name links, we incorporate trillions of name pair examples into various methods to enhance existing matching benchmarks and performance by explicitly maximizing match probabilities. We also show how relationships between organization names can be modeled using a network representation of the LinkedIn data. In illustrative merging tasks involving lobbying firms, we document improvements when using the LinkedIn corpus in matching calibration and make all data and methods open source.

Networks among legislators shape politics and policymaking within legislative institutions. In past work on legislative networks, the ties between legislators have been defined on those who serve in the same legislature or chamber. Online information networks, which have been found to play important roles in legislative communication at the national level, are not bounded by individual legislative bodies. We collect original data for over four thousand US state legislators and study patterns of connection among them on Twitter. We look at three types of Twitter networks—follower, retweets, and mentions. We describe these networks and estimate the relationships between ties and salient attributes of legislators. We find that networks are organized largely along geographic and partisan lines and that identity attributes—namely gender and race—exhibit strong associations with the formation of ties.

Ecological inference is a statistical technique used to infer individual behavior from aggregate data. A particularly relevant instance of ecological inference involves the estimation of the inner cells of a set of R × C related contingency tables when only their aggregate margins are known. This problem spans multiple disciplines, including quantitative history, epidemiology, political science, marketing, and sociology. This paper proposes new models for solving the problem using the latent structure theory, and presents the ecolRxC package, an R implementation of this methodology. This article exemplifies, explains, and statistically documents the new extensions and, using real inner cell election data, shows how the new models in ecolRxC lead to significantly more accurate solutions than ecol and VTR, two Stata routines suggested within this framework. ecolRxC also holds its own against ei.MD.bayes and nslphom, the two algorithms currently identified in the literature as the most accurate to solve this problem. ecolRxC records accuracies as good as those reported for ei.MD.bayes and nslphom. Besides, from a theoretical perspective, ecolRxC stands up for modeling a causal theory of political behavior to build its algorithm. This distinguishes it from other procedures proposed from different frameworks (such as ei.MD.bayes and nslphom) which model expected behaviors, instead of modeling how voters make choices based on their underlying preferences as ecolRxC does.

In this article, we explore the rhetorical space structuring the debates in the United Nations General Assembly's (UNGA) Committee on Disarmament and International Security. To this end, we unfold states' speeches by combining three established methods. First, we estimate terms' relevance for latent topics structuring the debates with structural topic modeling. Second, we estimate topic-specific positions based on the Wordfish algorithm. Third, we map these positions onto a lower-dimensional rhetorical space using principal component analysis. We identify two latent conflicts. First, a debate over conventional weapons with states emphasizing security interests on the one end and humanitarian interests on the other. Second, a conflict over weapons of mass destruction that divides defenders and challengers of the status quo.

Lobbying expenditures are widely used as a proxy variable for measuring lobbying activity. However, the validity of this approach has rarely been examined and existing justifications do not account for heterogeneity in expenditure formats across types of lobbyists. I address the question using unique lobbying disclosure data from Wisconsin, where lobbying organizations report both expenditures on lobbying-related activities and lobbyists’ hours worked. Strong overall correlations between changes in expenditures and hours worked within organization–lobbyist dyads indicate that lobbying expenditures can serve as a reasonable proxy. However, caution is warranted due to substantial heterogeneity, with contract lobbyist relationships exhibiting weaker correlations than in-house relationships. I conclude by providing suggestions to improve empirical analyses that rely on lobbying expenditures.

Recent years have seen a surge of politicians campaigning on policies that aim to deter asylum applicants. We present a game-theoretic model in which foreign nationals consider applying for asylum and bureaucrats decide their case if they apply. We show that while policies that make the asylum application less attractive decrease the probability that foreign nationals apply, they also endogenously raise the credibility of applicants’ claims to political persecution and, therefore, may not decrease the number of admitted refugees. Investigating how these competing effects shape asylum policy-making, we show how policy choices depend on bureaucrats’ leniency and politicians’ objectives. Our analysis speaks to the causes of restrictive asylum policies and their limited effectiveness in reducing immigration.

Ethnic movements continue to challenge state governments globally, with many ethnic conflicts revolving around the status of groups’ territories. Yet, politically mobilized ethnic groups vary considerably in their territorial demands: some press for increased autonomy or even outright secession, while others do not make such demands at all and prefer integration in the existing state. What explains this divergence in ethnic group demands with respect to the group's territorial status? We argue that the expected benefits of ethno-regional autonomy or secession compared to integration in a centralized state differ across distinct segments within the group as a function of three structural factors: heterogeneity in the group's income sources, cultural divisions, and territorial fragmentation, leading to disagreement over self-determination demands between different political organizations representing the same ethnic group. We test our argument using an expanded version of the Ethnic Power Relations–Organizations (EPR-O) dataset. Our pre-registered study finds support for one of our hypotheses: heterogeneity in groups’ income sources increases disagreement over self-determination demands. This finding sheds new light on the structural sources of internal divisions within ethno-political movements.

This study examines how voters’ perceptions of ideological incongruence with political parties affect their satisfaction with democracy. Using panel data from the British Election Study, we first demonstrate that greater misperception of party positions correlates with higher perceived ideological distance from one's preferred party. We then show that this increased perceived incongruence is associated with lower satisfaction with democracy when controlling for objective measures of incongruence. These findings are consistent across several alternative measures and specifications, and similar results are found in cross-sectional data from Europe. The results suggest that subjective perceptions of representation, potentially distorted by misperceptions, play a role in shaping citizens’ attitudes toward the political system. While the limitations of the study warrant caution in interpretation, the study contributes to the literature by highlighting the importance of perceived ideological congruence for understanding the link between representation and satisfaction with democracy.

We study how the electoral success of radical right populist parties (RRPPs) affects mainstream parties' defense policy positions. The success of RRPPs threatens the credibility of established left-wing parties with coalition and international partners due to substantive overlap between their and RRPPs' defense-skeptical position. We argue that left parties adopt more assertive defense positions to distinguish themselves from RRPPs, thus increasing mainstream consensus on defense policy. Examining 27 European countries between the end of the Cold War and Russia's occupation of Crimea (1990–2013), we test this argument based on a regression discontinuity design around electoral thresholds for obtaining parliamentary seats. We find that, in response to RRPP success, left parties adopt more assertive defense policy positions, whereas center-right parties stand their ground. This study yields evidence for an adversarial response to the radical right, often thought to have lost out to accommodation, and for mechanisms other than electoral incentives, in a highly consequential domain.

How well do existing survey instruments differentiate between opinions that affect individual behavior and opinions that don't? To answer this question, we randomly assigned U.S. respondents to one of three survey instruments: Likert items (Likert), Likert items followed by personal importance items (Likert+) and Quadratic Voting for Survey Research (QVSR), which gives respondents a fixed budget to buy “favor” or “oppose” votes, with the price for each vote increasing quadratically. We find that, relative to Likert, both Likert+ and QVSR better identify people who care enough about an issue to act in opinion-congruent ways, with QVSR offering the most consistent improvement overall. Building on these results, we show how conclusions regarding the relationship between policy opinions and self-interest can differ across measurement strategies.

Scholars often use monetary incentives to boost participation rates in online surveys. This technique follows existing literature from western countries, which suggests egoistic incentives effectively boost survey participation. Positing that incentives’ effectiveness vary by country context, we tested this proposition through an experiment in Australia, India, and the USA. We compared three types of monetary lotteries to narrative and altruistic appeals. We find that egoistic rewards are most effective in the USA and to some extent, in Australia. In India, respondents are just as responsive to altruistic incentives as to egoistic incentives. Results from an adapted dictator game corroborate these patterns. Our results caution scholars against exporting survey participation incentives to areas where they have not been tested.

Scholars and policymakers warn that with rising affective polarization, politicians will find support from the public and permission from military professionals to use military force to selectively crack down on political opponents. We test these claims by conducting parallel survey experiments among the US public and mid-career military officers. We ask about two hypothetical scenarios of domestic partisan unrest, randomly assigning the partisan identity of protesters. Surprisingly, we find widespread public support for deploying the military and no significant partisanship effects. Meanwhile, military officers were very resistant to deploying the military, with nearly 75 percent opposed in any scenario. In short, there is little evidence that public polarization threatens to escalate domestic disputes, and strong evidence for military opposition.

Why does vote buying persist under the secret ballot? We argue initiating vote-buying transactions allows politicians to undermine voter confidence in the secret ballot, and thus to induce voter compliance. Our analysis consists of three parts. First, we present evidence from a survey experiment in Mexico that shows receiving material goods from a candidate diminishes voter confidence in ballot integrity. Next, we introduce an informational theory of vote buying that explains this phenomenon. Specifically, we develop a model of vote buying as a signaling game, in which a voter who is ex ante uncertain about a politician's capacity to monitor voter behavior learns new information from the politician's actions. Finally, we test the key insights from the model in a lab experiment. Our results suggest that, under certain conditions, offering material goods to voters is sufficient to erode their confidence in ballot secrecy, making vote buying effective.

Does resident diplomacy influence international outcomes? Theoretically, I argue that resident diplomats tend to adopt uniquely cooperative stances toward their hosts. I test this expectation using a natural experiment involving British visa issuance. Starting in 2007, the UK transferred visa decision making from local diplomatic posts to centralized hubs, located either at third country diplomatic posts or domestically. I study this rollout to credibly estimate the causal effects of visa adjudication by local posts. I find that resident diplomats implement a much more lenient visa policy—transferring adjudication to an outside hub reduces issuance by about fifteen percent. There is a robust difference between the behavior of local and third-country posts, showing that this cooperative effect of diplomacy is relationship-specific.

There is a long-standing interest in how the visual appearance of politicians predicts their success. Usually, the scope of such studies is limited by the need for human-rated facial features. We instead fine-tune pre-trained image classification models based on convolutional neural networks to predict facial features of 7,080 Danish politicians. Attractiveness and trustworthiness scores correlate positively and robustly with both ballot paper placement (proxying for intra-party success) and the number of votes gained in local and national elections, while dominance scores correlate inconsistently. Effect sizes are at times substantial. We find no moderation by politician gender or election type. However, dominance scores correlate significantly with outcomes for conservative politicians. We discuss possible causal mechanisms behind our results.

An extensive theoretical and practitioner literature addresses the drivers and consequences of transformation of violent rebel actors during conflicts. However, measurement challenges constrain large-N empirical study of the effects and consequences of such transformations. This Research Note introduces a strategy to identify periods of transformation and change in the operation of non-state armed militant groups via computational text analysis of trends in reporting on activities. It presents the measurement approach and demonstrates scalability to a corpus of more than 200 militant groups operating from 1989 to 2020. The study concludes by extending a recent analysis of the impacts of uncertainty on conflict termination. An online Appendix demonstrates the advantages and drawbacks of the measurement through a series of case studies.

Concerns over free riding in NATO are widespread. An intuitive approach to analyzing free riding is treating it as a systematic pattern of spatial interdependence between the allies: how does a NATO member's defense spending react to changes in other allies' military expenditures? While recent work has found statistically significant free riding (negative spatial interdependence in the outcomes), it suffers from important limitations. First, this research does not adequately account for temporal dependence. Second, it does not quantify the effect of interest. Accounting directly for temporal dependence provides a meaningfully distinct perspective on the within-alliance dynamics, demonstrating that the spatiotemporal effect of free riding is, in fact, more substantial than its short-run effect, challenging inferences of static spatial models. We discuss the relevant practical and theoretical implications.