American Politics Research

We analyze AP VoteCast survey data to determine if opinions toward the 2020 presidential election shaped participation and vote choice in the 2021 Georgia Senate runoff contests. Specifically, we estimate the impact of election denial and voter confidence on self-reported participation and voter preferences in the 2021 Georgia Senate runoffs. Election denial dampened the likelihood of voting in the 2021 Georgia Senate runoffs, and particularly among respondents aligned with President Trump. With respect to vote choice in these contests, election denial sided more with Republican preferences, whereas voter confidence increased Democratic support. This research highlights how opinions toward the 2020 presidential election registered notable effects on political behavior in the ensuing Georgia Senate runoffs, which decided partisan control of Congress’ upper chamber.

In this study, we examine if and how exposure to hate crimes is associated with the method of vote utilized by African American voters in the 2016 general election. Specifically, we are interested in how exposure to heightened levels of hate crimes at the county-level influences African Americans’ decision to vote-by-mail (VBM) as opposed to in-person (either early or election day voting). We examine the question using the 2016 Collaborative Multiracial Post-Election Survey and FBI county-level hate crime data (2013–2016). The FBI Uniform Crime Report hate crime dataset provides information on the physical location of the hate crime events. We merge the hate crime data with the CMPS data to examine if and how heightened rates of hate crime affect choice of voting mode. Consistent with expectations, we find that African Americans living in areas with higher levels of hate crimes are more likely to vote-by- mail rather than in person, potentially as a way to avoid the risk of encountering hate crimes.

Do voters have an intrinsic preference for democracy? Assessing attitudes toward trustee or delegate models of representation risks conflating intrinsic and instrumental orientations toward democracy. To clarify the gap between intrinsic and instrumental support for political representation, we use a survey experiment to investigate whether US voters want representatives to enact the individual voter’s own preferences, regardless of countervailing attitudes held by the representative themselves or by their constituents. We find considerable support for this third, personal model of representation. We argue that this poses two important questions for democratic theorists. First, how do citizens’ observed preferences for dictating outcomes challenge normative democratic principles of representation? Furthermore, if we rethink how citizens engage in democratic processes, how does it change our understanding of democracy’s intrinsic worth in the public?

The US Congress is the world’s most studied legislature, but data on its many facets often remains isolated. This note introduces an updated version of CongressData, a database of over 1300 member-year and district-year level variables between 1789 and 2024 that compiles district demographics and economic variables, legislator characteristics, lawmaking behavior, and committee membership. We also introduce an R package that makes it easy to subset and cite data and an associated web app. We first draw attention to the metadata in CongressData. Then, leveraging CongressData, we highlight analyses that cut across these types of data. Our illustration uses dimensional analysis on the the determinants of bill introduction by Members of Congress. In doing so, we assess several prominent explanations for bill in-troduction. Exploring the factors that govern this focus, we find that committee membership is more associated than party, ideology, member characteristics, or district demographics. The dataset will aid scholars of Congress and American institutions, enabling them to adjudicate between different factors to explain the phenomena of interest to them.

Recent surveys suggest that Americans’ trust in institutions has decreased, including trust in science and government. Such trends could have significant effects on the health of democracy, scientific advancement, information consumption, and more. However, trust can stem from different considerations. In some cases, a lack of trust arises from ill will or suspicion over integrity, that is, concerns about immorality or wrong doing. It can also arise from pessimism about competence. These different causes elicit distinct reactions, which could motivate varied reactions toward groups that are not trusted. Using multiple original surveys of US adults (total N = 3,894), including an original experiment, we find that seeing scientists and politicians as morally bad - but not as incompetent - leads to lower trust in these individuals. This suggests that perceptions of moral wrongdoing are stronger drivers of lower political and scientific trust in recent years, compared to perceived incompetence. These results hold in correlational analysis, although the effects vary somewhat by partisanship. Together, these results have important implications for understanding the driver of major ills that threaten the functioning of society and government.

Many recent studies have offered contrasting conclusions as to whether voters punish elected officials in response to “irrelevant events.” One prominent case considers whether shark attacks in New Jersey in 1916, which negatively impacted the tourism industry in the state, prompted voters to punish Woodrow Wilson in his reelection bid. Achen and Bartels (2004, 2016) provide evidence of an electoral penalty, while Fowler and Hall (2018) argue there is no consistent evidence of this penalty – findings Achen and Bartels rebut (2018). This short article revisits this debate by introducing new data on communities’ susceptibility to the negative economic consequences alleged to have prompted electoral harm for Wilson: the size of the local hotel industry. Incorporating information about New Jersey hotels obtained from a contemporaneous travel guide, we find no evidence communities proximate to beaches with large hotel industries exacted stronger penalties against Wilson relative to beach communities without a large concentration of hotels or to non-beach communities. Our findings highlight the importance of incorporating into studies of the electoral consequences of irrelevant events historical context and tests of the mechanisms posited to link events to electoral outcomes.

How do information environments shape political preferences among rural Americans? This study examines how variation in local television news exposure shapes rural Americans’ political preferences about government spending on law enforcement. These governmental spending preferences are often shaped by skepticism grounded in rural place-based identity. Drawing on agenda-setting theory, I argue that exposure to different media markets—particularly those from more populous urban areas where coverage of crime and law enforcement is more prevalent—creates distinct informational contexts that influence political preferences. Using survey data from rural respondents in the 2016, 2020, and 2022 Cooperative Election Studies and a matching design, the analysis finds that rural Americans exposed to local television news from urban media markets express greater support for increasing law enforcement spending, even at the expense of other public services. These findings challenge the idea that rural Americans hold rigid, identity-based political preferences rooted in place. Instead, this study demonstrates that rural political preferences are malleable and shaped by information environments.

Public goods like schools and recreational facilities can foster a sense of community, but their benefits are not equally shared. This paper uses survey data from the 2020 Collaborative Multi-Racial Post-Election Survey (CMPS) to understand urban and rural Americans’ satisfaction with the public goods in their communities. I theorize that people compare current public goods with their prior experiences — this retrospective analysis drives public goods satisfaction. I create an original measure of community public goods satisfaction based on the provision of five public goods: parks, schools, police, health care, and transit. I find that rural residents are less satisfied with public goods than urban residents. Additionally, this rural-urban gap varies by length of time a person has lived in the community. Those who have lived in a rural community for many years exhibit lower satisfaction, particularly in terms of health care and transit, which is consistent with characterizations of the hollowing out of rural America.

This study examines public perceptions of state level political corruption in the United States using original data from two national public opinion surveys conducted in 2014 and 2022. Our analyses reveal several important insights about the underpinnings of state corruption perceptions. First, we find that perceptions of state corruption are modestly related to the actual state corruption context—people are able to connect their perceptions to reality. Second, consistent with previous research on partisanship, partisan biases play a substantial role in shaping perceptions of state level corruption, with people being much more likely to perceive corruption when the incumbent governor in their state is an out-partisan. Finally, the relationship between corruption perceptions and the state corruption context is not significantly moderated by political knowledge.

Assessing ideological representation can be difficult because perceived ideology and party identification correlate strongly among presidential nominees. Democratic nominees are consistently liberal, and Republican nominees are consistently conservative. However, Trump’s 2016 candidacy included ambiguous, liberal, and extremely conservative positions. While in-office, Trump repositioned to uniformly conservative policy positions. This presents an opportunity to assess changes in candidate ideology that are difficult to observe outside of experiments. With unique panel data, I used self-placed ideology in 2012 to create spatial distances to Trump and the Democratic nominees in 2016 and 2020. This design allowed for over-time variation of candidate evaluations while keeping self-placed ideology pre-Trump. I find that Trump was perceived as moderate in 2016, and this translated into a vote choice advantage relative to Clinton. However, respondents substantially reevaluated Trump as being conservative in 2020, which changed the vote choice advantage to Biden. These results show that perceived ideology influenced voting even in an era of strong partisanship, and this typically cannot be observed because of the ubiquitous connection between ideology and party among presidential candidates.

Can mass protests for racial justice influence police patrol tactics? Which racial and spatial mechanisms underlie these changes? Previous literature suggests that high-profile events can lead individual agents to alter their enforcement activities by ‘de-policing.’ However, literature is scarce (and conflicting) about the relationship of de-policing with crime, and effects across racial groups are underexplored. In this article, I argue that this apparent de-policing is, in reality, a positive reform of police patrol tactics induced by public pressure, which forced law enforcement to reconsider its approach to police-civilian interactions and focus on adopting a conservative stopping strategy, more targeted against higher-risk individuals, and more sensitive regarding the unequal treatment of minorities. To do so, I analyze this issue combining pedestrian stops and crime data from Chicago, asking whether the 2020 BLM protests led the Chicago Police Department to change its patrol strategy. When protests erupted, crime and policing got progressively decoupled: when criminality rose, stops did not. While overall crime simply returned to its pre-BLM (and pre-COVID-19) trends and levels, policing changed radically: stops, searches and arrests dropped and became stationary, while hit rates rose sharply. Stops also decreased differently across racial groups: almost exclusively for Black civilians, and mostly in minority districts. This decline in minority policing is evident across all officer groups, further indicating that the change reflects a broad shift in policing tactics rather than individual-level shirking.

The American electorate is divided along educational lines. The 2024 presidential election was marked by the largest-ever educational divide in vote choice. Typically, we frame this divide as a split between people with college degrees and those without. In this paper, I argue that there is significant polarization along the entire educational attainment spectrum. I show that the divide between BA and graduate degree holders is just as pronounced on many dimensions as the divide between BA holders and high school graduates. This point is especially critical because graduate degree holders are the fastest-growing educational category, moving from 9% of the population in 2000 to 14.5% today. I use ANES and US Census data to show that educational polarization encompasses political attitudes, engagement, and vote choice. As people become more educated, they become more liberal on social, cultural, and economic issues, become more likely to participate in politics, and support the Democrats. I also show that educational polarization combined with demographic changes has dramatically reshaped the party coalitions, with the Democratic Party’s base becoming more educated while the Republican coalition is little changed. I also show that the proportion of the population with a graduate degree was one of the strongest demographic predictors of county-level vote share in the 2024 election. All told, the American electorate is polarized along the entire educational attainment spectrum.