Increasing partisan polarization has characterized American politics for decades. On January 6, 2021, both Republicans and Democrats in Congress expressed their horror at the violent invasion of the US Capitol, leading to the popular perception—emphasized by media accounts—that the attack generated a rare moment of bipartisan unity. We argue that while members of both parties condemned the attack, a marked partisan divide characterized their messaging even as events unfolded. We analyze all 1861 tweets by members of Congress on January 6th and find that Republicans were significantly more likely to characterize the invasion as a protest grown out of hand, while Democrats described it as an attack on democracy. The results strongly indicate that partisan polarization was alive and well on January 6th and may help to account for Republicans’ shift toward normatively positive portrayals of the day in subsequent months.

Although influential models of public opinion hold that group sentiments play an important role in shaping political beliefs, they often assume that group attitudes stem from socialization and are thus exogenous to politics. We challenge this assumption, arguing that group attitudes may themselves be the consequence of political views. Across three survey experiments that each uses a unique social group–issue pair, we consistently demonstrate that attitudes toward groups are influenced by information about the groups' policy views. These findings persist even when accounting for potential partisan signaling. Altogether, these results show that group sentiments should not be regarded as wholly exogenous to policy concerns and suggest that the use of group-based heuristics can be consistent with instrumental models of public opinion.

Among the greatest challenges facing scholars of public opinion are the potential biases associated with survey item nonresponse and preference falsification. This difficulty has led researchers to utilize nonresponse rates to gauge the degree of preference falsification across regimes. This article addresses the use of survey nonresponse rates to proxy for preference falsification. A simulation analysis exploring the expression of preferences under varying degrees of repression was conducted to examine the viability of using nonresponse rates to regime assessment questions. The simulation demonstrates that nonresponse rates to regime assessment questions and indices based on nonresponse rates are not viable proxies for preference falsification. An empirical examination of survey data supports the results of the simulation analysis.

Whether a topic is seen in a moral or moral-emotional light has significant political implications. Yet, we lack knowledge about the process of moralization: Who defines the way topics are communicated about? Where prior research has investigated the relative power of different actors to place a topic on the agenda or shape opinions, we study who sets the moral and moral-emotional tone of debate. To do so, we zoom in on immigration discourse in Germany and analyze fine-grained social media data from politicians, political parties, newspapers, and members of the public over a period of more than four years. After employing a transformer model to identify moral and moral-emotional appeals, we use structural vector autoregression models to demonstrate the important role of radical-right challengers in shaping public discourse in a negative moral-emotional direction. The results inform theories of moralization and political entrepreneurship.

What are the consequences of including a “don't know” (DK) response option to attitudinal survey questions? Existing research, based on traditional survey modes, argues that it reduces the effective sample size without improving the quality of responses. We contend that it can have important effects not only on estimates of aggregate public opinion, but also on estimates of opinion differences between subgroups of the population who have different levels of political information. Through a pre-registered online survey experiment conducted in the United States, we find that the DK response option has consequences for opinion estimates in the present day, where most organizations rely on online panels, but mainly for respondents with low levels of political information and on low salience issues. These findings imply that the exclusion of a DK option can matter, with implications for assessments of preference differences and our understanding of their impacts on politics and policy.

Several disciplines, such as economics, law, and political science, emphasize the importance of legislative quality, namely well-written legislation. Low-quality legislation cannot be easily implemented because the texts create interpretation problems. To measure the quality of legal texts, we use information from the syntactic and lexical features of their language and apply these measures to a dataset of European Union legislation that contains detailed information on its transposition and decision-making process. We find that syntactic complexity and vagueness are negatively related to member states’ compliance with legislation. The finding on vagueness is robust to controlling for member states’ preferences, administrative resources, length of texts, and discretion. However, the results for syntactic complexity are less robust.

Inverse probability weighting is a common remedy for missing data issues, notably in causal inference. Despite its prevalence, practical application is prone to bias from propensity score model misspecification. Recently proposed methods try to rectify this by balancing some moments of covariates between the target and weighted groups. Yet, bias persists without knowledge of the true outcome model. Drawing inspiration from the quasi maximum likelihood estimation with misspecified statistical models, I propose an estimation method minimizing a distance between true and estimated weights with possibly misspecified models. This novel approach mitigates bias and controls mean squared error by minimizing their upper bounds. As an empirical application, it gives new insights into the study of foreign occupation and insurgency in France.

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.

In this paper we test how much party labels influence vote choices between candidates when voters have access to realistically distributed information about candidate positions and demographics. We do not seek to adjudicate a long-running debate about the role of party labels, but present some nuances on the two archetypal theoretical views on vote choices. We use data from the Representative Audit of Britain (RAB) and the British Elections Study (BES) to generate electoral match-ups between randomly selected Conservative versus Labour candidates, with only half of respondents seeing party labels in addition to candidates’ positions and demographics. For our experiment fielded in October 2021, we find negligible to moderate effects of party labels on vote choices. Our results suggest the information on candidate positions and party labels largely act as substitutes for one another, with only modest changes when party labels are made explicit.

Civic associations are expected to foster civic, pro-social behavior, but this optimistic view is increasingly contested. We argue that populist radical right parties can strategically target and infiltrate associations to diffuse anti-establishment rhetoric and anti-democratic attitudes. We illustrate this phenomenon by examining the relationship between civic associations and compliance with government rules during Germany's first Covid-19 lockdown with a difference-in-differences design. Results show that areas with denser sport, nature, and culture clubs recorded higher mobility under lockdown. We document the infiltration mechanism and the spreading of anti-democratic attitudes within associations, using survey and election data and qualitative evidence including interviews. In doing so, we shed light on a negative effect of social networks and an understudied strategy of challenger populist parties.

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.

Prominent recent work argues that support for democracy behaves thermostatically—that democratic erosion boosts democratic support while deepening democracy yields public backlash—and further contends that there is no evidence for the classic argument that democracy itself increases democratic support over time. Here, we document how these conclusions depend on subtle choices in measurement coding that constitute “researcher degrees of freedom”: analyses employing alternative reasonable choices provide little or no support for the original conclusions. The fragility of the statistical results demonstrates that researcher degrees of freedom in measurement must be taken seriously and that the question of the relationship between democratic institutions and democratic support remains unsettled.

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.

Can democracies attract and elect politicians who are both high-ability and from diverse backgrounds? Using data covering the entire Danish population, including every candidate for local and national elections in 1990–2015, we explore the selection of political candidates. We show that Danish candidates and elected politicians have higher ability than the voters they represent, that selection on ability reflects individual skills rather than social background, that politicians are selected from economically diverse backgrounds, and that there is no substantial trade-off between ability and representation. Furthermore, we utilize a major structural reform, which significantly reduced the number of municipalities in Denmark, to show that increased political competition did not affect politicians’ ability, economic background, or the trade-off between the two.

We revisit Arunachalam and Watson's contention that a person's physical height may be used as instrument for income because it affects economic well-being solely by causing more conservative political preferences among people who are taller. To evaluate whether other early-life and genetic factors might serve as mechanisms connecting height and political preferences, we analyze a unique data source that includes political, economic, and demographic data on same-gender siblings. Models that include fixed effects for siblings provide a strong test of the Arunachalam and Watson thesis. We find that height is not a consistent predictor of political preferences once shared sibling characteristics are controlled in this way, raising doubt about whether height can in fact be used as an instrument for income.

Economic sanctions are a policy tool that great powers frequently use to interfere with domestic politics of another state. Regime change has been a primary goal of economic sanctions over the past decades. This article studies the relationship between leader-contingent sanctions—sanctions that are designed to impede the flow of revenue to a specific leader—and violent political conflict in target countries. I build a theoretical model to illuminate two mechanisms by which leader-contingent sanctions destabilize a regime—the Depletion Mechanism and the Instigation Mechanism. The Depletion Mechanism works when sanctions mechanically deplete the government's resources so that it becomes unable to buy off domestic opposition even by making the largest possible offer. The Instigation Mechanism implies that as sanctions decrease the benefit of negotiated settlement relative to war, the government may strategically choose to repress rather than buy off the opposition even when it is able to do so. Leader-contingent sanctions lead to bargaining failure by rewarding the opposition for revolt while reducing the government's ability and willingness to appease the opposition.

We study how an intervention combining youth intergroup contact and sports affects intergroup relations in the context of an active conflict. We first conduct a randomized controlled trial (RCT) of one-year program exposure in Israel. To track effects of a multiyear exposure, we then use machine-learning techniques to fuse the RCT with the observational data gathered on multiyear participants. This analytical approach can help overcome frequent limitations of RCTs, such as modest sample sizes and short observation periods. Our evidence cannot affirm a one-year effect on outgroup regard and ingroup regulation, although we estimate benefits of multiyear exposure among Jewish-Israeli youth, particularly boys. We discuss implications for interventions in contexts of active conflict and group status asymmetry.

Do policy priorities that candidates emphasize during election campaigns predict their subsequent legislative activities? We study this question by assembling novel data on legislative leadership posts held by Japanese politicians and using a fine-tuned transformer-based machine learning model to classify policy areas in over 46,900 statements from 1270 candidate manifestos across five elections. We find that a higher emphasis on a policy issue increases the probability of securing a legislative post in the same area. This relationship remains consistent across multiple elections and persists even when accounting for candidates' previous legislative leadership roles. We also discover greater congruence in distributive policy areas. Our findings indicate that campaigns provide meaningful signals of policy priorities.

Various robust communication effects have been identified, but evidence is overwhelmingly based on artificial survey treatments with limited real-world insight. I conducted a natural experiment on the impact of the European–Turkey statement closing the Balkan route during the 2015/16 European refugee crisis in Germany. This design tests the lasting effect of the statement's framing on public sentiment. I identify treatment and control groups based on timing to demonstrate its effect on perceptions of the crisis, asylum attitudes, and policy preferences. Effects are largest immediately following the announcement but decline rapidly. This shows political communication can significantly change opinion within a limited time frame. This study enhances our understanding of real-world communication effects and offers a broadly applicable methodology.