While presidents frequently create new policies through unilateral power, empirical scholarship generally focuses on executive orders and overlooks other categories of directives. We introduce data on more than 50,000 unilateral directives issued between 1877 and 2020 and use machine learning techniques to characterize their substantive importance and issue areas. Our measures reveal significant increases in unilateral activity over time, driven largely by increases in foreign affairs and through the substitution of memoranda for executive orders. We use our measures to formally evaluate the historical development of the unilateral presidency and reassess theoretical claims about public opinion and unilateral power. Our research provides new evidence about variation in the use of presidential authority and opens new avenues for empirical inquiry.

Under closed-list proportional representation, a party's electoral list determines the order in which legislative seats are allocated to candidates. When candidates differ in their ability, parties face a trade-off between competence and incentives. Ranking candidates in decreasing order of competence ensures that elected politicians are most competent. Yet, party lists create incentives for candidates that may lead parties not to place their best candidates at the top of the list. We examine this trade-off in a game-theoretical model in which parties rank their candidates on a list, candidates choose their campaign effort, and the election is a team contest for multiple prizes. We analyze how the candidates’ objectives, voters’ attention and media coverage, incumbency, the number of parties competing in the election, and the electoral environment influence how parties rank candidates.

How do international crises unfold? We conceptualize international relations as a strategic chess game between adversaries and develop a systematic way to measure pieces, moves, and gambits accurately and consistently over a hundred years of history. We introduce a new ontology and dataset of international events called ICBe based on a very high-quality corpus of narratives from the International Crisis Behavior (ICB) Project. We demonstrate that ICBe has higher coverage, recall, and precision than existing state of the art datasets and conduct two detailed case studies of the Cuban Missile Crisis (1962) and the Crimea-Donbas Crisis (2014). We further introduce two new event visualizations (event iconography and crisis maps), an automated benchmark for measuring event recall using natural language processing (synthetic narratives), and an ontology reconstruction task for objectively measuring event precision. We make the data, supplementary appendix, replication material, and visualizations of every historical episode available at a companion website crisisevents.org.

Liberalization is a perennial topic in politics and political science. We first review a broad scholarly debate, showing that the mainstream theories make rival and contradictory claims regarding the role of political parties in (de)liberalization reforms. We then develop a framework of conditional partisan influence, arguing that and under what conditions parties matter. We test our (and rival) propositions with a new dataset on (de)liberalization reforms in 23 democracies since 1973 covering several policy areas. Methodologically, we argue that existing quantitative studies are problematic: They rely on time-series cross-section models using country-year observations; but governments do not change annually, so that the number of observations is artificially inflated, resulting in incorrect estimates. We propose mixed-effects models instead, with country-year observations nested in cabinets, which are nested in countries and years. The results show under what conditions parties matter for (de)liberalization. More generally, the paper argues that mixed-effects models should become the new standard for studying partisan influences.

Coercive institutions' internal structures remain poorly understood. Bureaucratic reorganizations within security institutions cause significant variation in their behavior, however. Intra-agency reforms interact with officers' careerist incentives to cause changes in coercive capacity or repression. In this paper, I test the effects of intra-agency reforms on surveillance capacity. I exploit a rare source of exogenous variation in the structure of the secret police in communist Poland. Difference-in-differences models find that when security headquarters were duplicated through an administrative reform, the proliferation of higher-level posts within the service caused a large and statistically significant increase in the number of informants it employed. Intra-agency reform substantially altered the agency's coercive capacity. Previously overlooked dynamics within coercive institutions have important effects on authoritarian repression.

Does providing information about the costs and benefits of automation affect the perceived fairness of a firm's decision to automate or support for government policies addressing automation's labor market consequences? To answer these questions, we use data from vignette and conjoint experiments across four advanced economies (Australia, Canada, the UK, and the US). Our results show that despite people's relatively fixed policy preferences, their evaluation of the fairness of automation—and therefore potentially the issue's political salience—is sensitive to information about its trade-offs, especially information about price changes attributable to automated labor. This suggests that the political impact of automation may depend on how it is framed by the media and political actors.

The study of coup-proofing holds significant importance in political science as it offers insights into critical topics such as military coups, authoritarian governance, and international conflicts. However, due to the multifaceted nature of coup-proofing and empirical inconsistencies with existing indicators, there is a need for a more profound understanding and a new measurement methodology. We propose a new measure of the extent of coup-proofing, utilizing a Bayesian item response theory. We estimate the extent of coup-proofing using a sample of 76 countries between 1965 and 2005 and theoretically relevant observed indicators. The findings from the estimation demonstrate that the extent of coup-proofing varies across regime type, country, and time. Furthermore, we verify the construct validity of our measurement.

Political polarization has become an increasingly salient issue worldwide, but a systematic examination of the variation and sources of mass polarization across countries is limited by current measurement methods. This work proposes a nonparametric, entropy-based measure of mass political polarization. It exploits the specific structure of ordinal distributions in public opinion data, makes no prior assumptions about the form and spacing of the data, and can still draw reliable measures of issue-based polarization. We demonstrate the theoretical and practical superiority of the measure with analytical comparisons and simulations. We then apply the proposed measure to questions about mass polarization in the USA, the relationship between radical parties and polarization in Europe, and cross-country trends in affective and ideological polarization.

Hyperparameters critically influence how well machine learning models perform on unseen, out-of-sample data. Systematically comparing the performance of different hyperparameter settings will often go a long way in building confidence about a model's performance. However, analyzing 64 machine learning related manuscripts published in three leading political science journals (APSR, PA, and PSRM) between 2016 and 2021, we find that only 13 publications (20.31 percent) report the hyperparameters and also how they tuned them in either the paper or the appendix. We illustrate the dangers of cursory attention to model and tuning transparency in comparing machine learning models’ capability to predict electoral violence from tweets. The tuning of hyperparameters and their documentation should become a standard component of robustness checks for machine learning models.

Is populism electorally effective and, if so, why? Scholars agree that populism is a set of people-centric, anti-pluralist, and anti-elitist ideas that can be combined with various ideological positions. It is difficult, yet important, to disentangle populism from its hosting ideology in evaluating populism's effectiveness and its potential conditional effects on the hosting ideology. We conduct a novel US conjoint experiment asking respondents to evaluate pairs of realistic campaign messages with varying populism-related messages and hosting policy positions given by hypothetical primary candidates. Although party-congruent policy positions are expectedly much more popular, we find that none of the populist features have an independent or combined effect on candidate choice.

This research note investigates how the voting behavior of middle-income citizens explains why right-wing parties tend to govern under majoritarian electoral rule. The growing literature that investigates the ideological effects of electoral systems has mostly focused on institutional explanations. However, whether the electoral rules overrepresent parties with some specific ideologies is also a matter of behavior. Building on Iversen and Soskice (2006), we test two arguments. First, middle-income groups are more likely to vote for the right under majoritarian rules because they fear the redistributive consequences of a victory of the left in these contexts. Second, middle-income earners particularly concerned with tax rates are particularly prone to vote differently across electoral systems. Combining survey evidence from the Comparative Study of Electoral Systems and the New Zealand Election Study, we show that the voting behavior of middle-income citizens is indeed responsible for the predominance of the right under majoritarian systems.

When surveyed, clear majorities express concern about inequality and view the government as responsible for addressing it. Scholars often interpret this view as popular support for redistribution. We question this interpretation, contending that many people have little grasp of what reducing inequality actually entails, and that this disconnect masks important variation in preferences over concrete policies. Using original survey and experimental US data, we provide systematic evidence in line with these conjectures. Furthermore, when asked about more concrete redistributive measures, support for government action changes significantly and aligns more closely with people's self-interest. These findings have implications for how egalitarian policies can be effectively communicated to the public, as well as methodological implications for the study of preferences on redistribution.

A large literature has shown that ballot order and ballot structure can influence vote choice. We focus on another behavioral cue for voting, the symbols that are assigned to candidates in many democracies. We take advantage of a naturally occurring experiment in India, where independent candidates can choose from a list of free symbols and conflicting choices are resolved by a drawing of lots. We find that winning the draw has a substantial positive effect on vote share. We also find some evidence that candidates attempt to choose their symbols strategically, for instance choosing household goods common in their constituencies.

What drives voters' perceptions of partisan cooperation? In this note, we investigate whether voters have accurate beliefs about which parties regularly cooperate with one another, and whether these beliefs follow the real-time portrait of cooperation and conflict between parties that is reported in the news. We combine original survey data of voters' perceptions of party cooperation in four countries over two time periods with a measure of parties' public relationships as reported by the media. We find that voters' perceptions of cooperation and conflict among parties do reflect actual patterns of interactions. This pattern holds even after controlling for policy differences between parties as well as joint cabinet membership. Furthermore, we show that the impact of contemporary events on cooperation perceptions is most pronounced for voters who monitor the political news more carefully. Our findings have important implications for partisan cooperation and mass–elite linkages. Specifically, we find that contrary to the usual finding that voters are generally uninformed about politics, voters hold broadly accurate beliefs about the patterns of partisan cooperation, and importantly, these views track changes in relevant news. This reflects positively on the masses' capacities to infer parties' behaviors.

Policymakers and scholars have long proposed that willingness to participate in armed conflict is influenced by citizens' income-earning opportunities. Testing this opportunity cost mechanism has led to mixed results. One reason for this might be the fact that current proxies can also serve as indicators to test grievance-based theories. In this study, we construct a more suitable measure. We use crop calendars and crop location data to build an index of agricultural idle time for first administration units on the African continent from 1990 to 2017. We test the explanatory power of this measure by examining its relationship with armed conflict. Our results show that agricultural idle time increases the probability of observing armed conflict by more than 20 percent.