Battleground States Research Articles

The Selective Enforcement of Government Regulations: Battleground States, State Regulators, and the Environmental Protection Agency

The Selective Enforcement of Government Regulations: Battleground States, State Regulators, and the Environmental Protection Agency

Battleground State: Texas and the Fight to Dismantle All-White Primaries

Battleground State: Texas and the Fight to Dismantle All-White Primaries

Studying U.S. Hispanics: Challenges and Opportunities

This article argues for academic researchers to adopt new methodologies when studying the U.S. Hispanic population’s political participation and civic engagement. For decades scholars have used sound but limiting approaches to study this diverse and ever-growing population segment. As the number of Hispanics participating in U.S. electoral politics increases, so does the need to better understand their attitudes and behaviors. Hispanics now make up a significant portion of the population in battleground states with key Electoral College votes—most notably in states outside of the Southwest. Over the years, robust quantitative studies have provided great insight into the Hispanic electorate; qualitative studies have aided in this pursuit, though they are more limited in scope and number. The growth of technology has brought forth new forms of interpersonal communication and news consumption among citizens, U.S. Latinos included. Recent changes call for us to reexamine our current research methodologies and consider adopting a mixed methods approach.

We Are Still Here: Omission and Perceived Discrimination Galvanized Civic Engagement Among Native Americans

Leading up to the 2020 U.S. presidential election, Native American organizations and tribes launched get-out-the-vote campaigns that motivated Native peoples to vote in record numbers and helped flip battleground states. We conducted four studies (total N = 11,661 Native American adults) to examine the social and cultural factors explaining this historic Native civic engagement (e.g., campaigning). Results revealed that the more participants identified as being Native, the more they reported (a) engaging in civic activities, including get-out-the-vote behaviors during the 2020 election (Study 1); (b) civic engagement more broadly across a 5-year period (pilot study, Study 2); and (c) intentions to engage in civic activities in the future (Study 3). Moreover, participants who more strongly identified as Native were more likely to recognize the omission of their group from society and perceive greater group discrimination, which both independently and serially predicted greater civic engagement. These results suggest that leveraging the link between Native identification and group injustices can motivate action.

Misperceptions in sociopolitical context: belief sensitivity’s relationship with battleground state status and partisan segregation

AbstractNumerous studies have shown that individuals’ belief sensitivity—their ability to discriminate between true and false political statements—varies according to psychological and demographic characteristics. We argue that sensitivity also varies with the political and social communication contexts in which they live. Both battleground state status of the state in which individuals live and the level of partisan segregation in a state are associated with Americans’ belief sensitivity. We leverage panel data collected from two samples of Americans, one collected in the first half of 2019 and the other during the 2020 U.S. presidential campaign season. Results indicate that the relationship between living in battleground states and belief sensitivity is contingent on political ideology: living in battleground states, versus in Democratic-leaning states, is associated with lower belief sensitivity among conservatives and higher belief sensitivity among liberals. Moreover, living in a less politically segregated state is associated with greater belief sensitivity. These relationships were only in evidence in the election year.

SEEDING DOUBTS ABOUT VOTING BROADLY AND STRATEGICALLY: TRUMP AND BIDEN RHETORIC ONLINE IN THE 2020 U.S. PRESIDENTIAL ELECTION

When rioters attacked the U.S. Capitol on January 6, 2021, they did so mistrusting the electoral process and believing that Donald Trump had been robbed of the presidency. Presidential rhetoric has the power to shape the attitudes of the public and steer the country (Mercieca, 2020). Indeed, presidential rhetoric has the power to shape what Taylor (2004) describes as the social imaginary – the rhetorical construction of a version of a shared reality that takes hold in public discourse and public consciousness. Trump’s rhetoric in 2020 around the vote continued a narrative that he had started when he took office. In this study, using the framework of social imaginaries, we qualitatively and inductively analyze messaging on campaign social media accounts around the 2020 presidential campaign. We also examine the Facebook advertisements and the targets of those ads specifically around the vote. We compare Trump’s rhetoric to that of his opponent Joe Biden to contrast the distinct imaginaries around the vote each political candidate articulated. We find that Trump relied on his social media accounts to sow distrust of the vote process and doubt about the accuracy of the vote count on Election Day. More concerning, we also find that Trump attacked the voting process through his paid advertising on Facebook, targeting voters in key battleground states.

Not Just White Soccer Moms: Voting in Suburbia in the 2016 and 2020 Elections

Conventional narratives of the 2020 presidential election typically overlook the growing importance of voters of color in suburbia, especially in battleground states such as Georgia and Virginia. Using novel precinct-level voting data for twenty-two states for the 2016 and 2020 presidential elections, we analyze the relationship between precinct-level Democratic vote shares and the racial composition of suburban precincts. Predominantly White suburban precincts turned modestly toward the Democratic Party in 2020 relative to 2016, but had the election been decided in the precincts in which most White suburban voters live, Donald Trump would have won both elections handily. The outcome in 2020 depended on turnout in heavily Black suburban precincts, which voted overwhelmingly for Biden, and in Asian and Latinx precincts that also supported Democrats, though less strongly. As the suburbs become increasingly diverse, the new racial demography of suburbs should change conventional understandings of voting behavior in these spaces.

A 2 million-person, campaign-wide field experiment shows how digital advertising affects voter turnout.

We present the results of a large, US$8.9 million campaign-wide field experiment, conducted among 2 million moderate- and low-information persuadable voters in five battleground states during the 2020 US presidential election. Treatment group participants were exposed to an 8-month-long advertising programme delivered via social media, designed to persuade people to vote against Donald Trump and for Joe Biden. We found no evidence that the programme increased or decreased turnout on average. We found evidence of differential turnout effects by modelled level of Trump support: the campaign increased voting among Biden leaners by 0.4 percentage points (s.e. = 0.2 pp) and decreased voting among Trump leaners by 0.3 percentage points (s.e. = 0.3 pp) for a difference in conditional average treatment effects of 0.7 points (t1,035,571 = -2.09; P = 0.036; [Formula: see text] points; 95% confidence interval = -0.014 to 0). An important but exploratory finding is that the strongest differential effects appear in early voting data, which may inform future work on early campaigning in a post-COVID electoral environment. Our results indicate that differential mobilization effects of even large digital advertising campaigns in presidential elections are likely to be modest.

Redistricting for Proportionality

Abstract American democracy is currently heavily reliant on plurality in single-member districts, or PSMD, as a system of election. But public perceptions of fairness are often keyed to partisan proportionality, or the degree of congruence between each party’s share of the vote and its share of representation. PSMD has not tended to secure proportional outcomes historically, partially due to gerrymandering, where line-drawers intentionally extract more advantage for their side. But it is now increasingly clear that even blind PSMD is frequently disproportional, and in unpredictable ways that depend on local political geography. In this paper we consider whether it is feasible to bring PSMD into alignment with a proportionality norm by targeting proportional outcomes in the design and selection of districts. We do this mainly through a close examination of the “Freedom to Vote Test,” a redistricting reform proposed in draft legislation in 2021. We find that applying the test with a proportionality target makes for sound policy: it performs well in legal battleground states and has a workable exception to handle edge cases where proportionality is out of reach.

Covid-19 and the 2020 presidential election

Whether deserved on not, US Presidents often receive the blame or the credit for the nature of the economy and direction of the country. Therefore, the status of the economy and the country in an election year can be a very important factor in election success for an incumbent President (or his party if an incumbent is not running). This is especially true in ‘battleground states’ due to the presence of the Electoral College system where Presidential candidates need only win different combinations of states in order to become President. However, the 2020 Presidential election was vastly different from past election cycles in that an additional variable, COVID-19, was added to the decision calculus of voters. Eventually, the 2020 election came down to the extremely slim margins in three states (Arizona, Georgia, and Wisconsin) and thin margins in two others (Pennsylvania and Michigan). This paper shows that deaths from COVID-19 at the county level played a small role in demotivating voters to turnout in 2020 to cast their vote for Joe Biden as President. In other words, without Covid-19, President Trump’s losses within these five states would have been even larger.

Ideology and COVID-19 Vaccination Intention: Perceptual Mediators and Communication Moderators

Widespread COVID-19 vaccination is critical to slow the spread of the illness. This study investigates how political ideology is associated with COVID-19 vaccine intention via perceived effectiveness of the vaccine, perceived side effects, and perceived severity of the illness, three key aspects of the Health Belief Model (HBM). This study also examines how partisan information flow moderates the effects of ideology on these three HBM components. Using survey data collected from two battleground states in the 2020 election (N = 1849), regression, mediation and moderation analyses revealed that conservatives were less likely to intend to get vaccinated against COVID-19, and this association was significantly mediated by perceived effectiveness and perceived side effects of vaccination, as well as perceived severity of COVID-19. In addition, partisanship of news sources and discussion partners were significant moderators of ideology’s association with perceived vaccine effectiveness, with conservatives viewing COVID-19 vaccination as less effective if they were frequently exposed to liberal news, and if they had frequent conversations with fellow conservatives. This suggests boomerang effects for cross-cutting mass media exposure, and reinforcement effect for interpersonal communication. Implications for efforts to promote COVID-19 vaccine uptake are discussed, including tailored and targeted campaign strategies.

The longer-term electoral effect of carrying a state in U.S. presidential elections

Under the U.S. Electoral College system, battleground states receive a degree of attention from candidates and political parties that is out of proportion to their contribution to the vote total because they can effectively determine the outcome of a presidential election. Although the public and researchers tend to focus on the immediate impact of winning a battleground state on the current contest, the outcome of a following election may also be affected. In this paper, I investigate the effect of winning a state on the outcome of the next election, using a regression discontinuity (RD) design. The results of my RD analyses indicate that winning a state increases the party’s vote share in the next election. I also find evidence of a positive spillover effect of winning a state in a presidential election on later House of Representatives elections.

A Misuse of Statistical Reasoning: The Statistical Arguments Offered by Texas to the Supreme Court in an Attempt to Overturn the Results of the 2020 Election

In December 2020, Texas filed a motion to the U.S. Supreme Court claiming that the four battleground states: Pennsylvania, Georgia, Michigan, and Wisconsin did not conduct their 2020 presidential elections in compliance with the Constitution. Texas supported its motion with a statistical analysis purportedly demonstrating that it was highly improbable that Biden had more votes than Trump in the four battleground states. This article points out that Texas’s claim is logically flawed and the analysis submitted violated several fundamental principles of statistics.

Donald Trump and changing rural/urban voting patterns

In 2016, Donald Trump won the U.S. presidential election by securing a very large share of the rural vote. In the 2020 election, his margin of victory in rural America was even greater. This time, however, voter turnout in urban areas was much higher, an even larger share of these urban voters cast their ballot for Biden, and Trump lost the election. Analysis revealed that two variables were especially important predictors of county-level voting behavior. Counties that Trump won had a large proportion of non-Hispanic white residents and a low proportion of college graduates. When controlling for other independent variables, the effects of rural/urban residence largely disappeared. Thus, Trump's dominance in rural counties is explained by the fact that rural counties have large numbers of non-Hispanic white residents and lower levels of educational attainment than urban counties. These same variables were important in explaining the vote in five key battleground states. The relevance of these findings for the future of U.S. democracy in an era of deep political division is discussed.

A Battleground No More: Cosmopolitanism, the Culture Wars, and the Urban-Rural Divide in Ohio Elections, 2004-2020

Long a battleground state in presidential elections, Ohio trended toward the GOP in both 2016 and 2020. Despite losing the national popular vote, Trump secured the state’s electoral votes by comfortable margins in both elections, sparking the question of what explains this shift? We ground this question broadly in the realignment literature, testing two slightly overlapping theoretical viewpoints: geo-cultural and socioeconomic/cosmopolitanism. The geo-cultural viewpoint emphasizes the urban-rural divide in American politics, arguing that the culture is completely different on opposite ends of the urban-rural continuum, resulting in disparate election results. The socioeconomic/cosmopolitan viewpoint acknowledges that culture and social issues play a role in elections, but that the global economy of the 21st century drives results. To test these viewpoints, we use data on Ohio’s communities from the American Community Survey. Running spatial regressions, we find that there is evidence for both viewpoints present in Ohio over the past 20 years. Specifically, both Democrats and Republicans made gains in their geographic strongholds, but Democrats have made larger inroads in more cosmopolitan communities. However, Republicans made huge gains along the cultural dimension, giving them a strong advantage throughout the state. These results have implications for not only future presidential campaigns and how they target Ohio’s persuadable voters, but also for down ballot races in both the primary and general elections.

Seeking Evidence of The MAGA Cult and Trump Derangement Syndrome: An Examination of (A)symmetric Political Bias

Three studies sought to explore the existence of (a)symmetric bias regarding Donald Trump. In Study 1, participants read one of three statements expressing different degrees of favorability toward electing the President of the United States via a National Popular Vote attributed to Trump or an anonymous source. In Study 2, participants read one of two statements either favoring or disfavoring the name change of the Washington NFL franchise, and the statement was attributed to either Trump or an anonymous source. In Study 3, Trump and Biden voters were asked to rate their support or opposition to counting all the votes in battleground states when continued counting was expected to either help Trump or Biden. Results for all three studies supported the asymmetric bias hypothesis. Trump supporters consistently showed bias in favor of the interests and ostensible positions of Trump, whereas Trump’s detractors did not show an opposing bias.

Did Gary Johnson and Jill Stein Cost Hillary Clinton the Presidency? A Counterfactual Analysis of Minor Party Voting in the 2016 US Presidential Election

Abstract Hillary Clinton won the national popular vote for president in 2016, but lost to Donald Trump in the Electoral College. Trump’s margin of victory in several decisive battleground states was smaller than the combined vote for the two leading minor party candidates: Gary Johnson, of the Libertarian Party, and Jill Stein, of the Green Party. The perception that Johnson and Stein “stole” the 2016 presidential election from Clinton is widespread, and potentially consequential for future minor party candidacies, but it has not yet been rigorously tested. In this article, we extend the analysis of minor party voting in the 1992 election from Lacy, D., and B. C. Burden. 1999. “The Vote-Stealing and Turnout Effects of Ross Perot in the 1992 U.S. Presidential Election.” American Journal of Political Science 43 (1): 233–55, by using data from the 2016 Cooperative Congressional Election Study to estimate a multinomial probit model of voting behavior—including outcomes for vote choice and abstention—and calculate the predicted probabilities that Johnson and Stein voters would have voted for another candidate or abstained from voting, had one or both of these candidates been excluded from the ballot. We then reallocate Johnson’s and Stein’s votes accordingly, to estimate Clinton’s and Trump’s counterfactual vote shares nationally and within key battleground states. Our analysis indicates that Johnson and Stein did not deprive Clinton of an Electoral College majority, nor Trump the legitimacy of winning the national popular vote. We estimate that most Johnson and Stein voters would have abstained from voting if denied the choice to vote for their preferred candidate, and that most of Johnson’s remaining voters would have supported Trump.

Does Electoral Politics Affect Corporate Investment? Evidence from Battleground States

I examine the link between election year political incentive and corporate investment. Using battleground states as a source of plausibly exogenous variation in political importance, I find that firms located in battleground states increase corporate investment by 4.2% relative to firms located elsewhere during election years. The increase in corporate investment appears to be due to improved investment efficiency. Further analyses reveal battleground state firms appear to be more likely to receive Paycheck Protection Program loans following the onset of the COVID-19 crisis and more government contracts. My results also suggest firms located in battleground states are more insulated from political uncertainty and being perceived as politically important can lead to more efficient capital allocation.

A Gross Misuse of Statistical Reasoning: The Statistical Arguments Offered by Texas to the Supreme Court in an Attempt to Overturn the Results of the 2020 Election

In December 2020, Texas filed a motion to the U.S. Supreme Court, claiming that the four battleground states: Pennsylvania, Georgia, Michigan and Wisconsin did not conduct their 2020 presidential elections in compliance with the Constitution. The motion requested permission to file a complaint that would deny the voters in the four defendant states their chosen elector in the 2020 presidential election. The Court rejected the motion. Texas supported its motion with a statistical analysis purportedly demonstrating that it was highly improbable that Biden had more votes than Trump in the four battleground states. This paper points out that the analysis submitted by Texas violated several fundamental principles of statistics and repeatedly misinterpreted the p-value of a statistical test. We hope this paper will help judges detect flawed statistical analyses when they review them for admissibility and will be an example that educators can use to show students mistakes they should avoid when analyzing data.

Recovering election winner probabilities from stock prices

After the 2020 U.S. presidential election, counting votes and calling states took more time than usual, particularly in battleground states. In the days following the election, winning probabilities changed frequently as new results were tabulated. Based on the sensitivity of stocks to changes in winning probabilities observed before the election, we show how the stock market’s assessment of the unobserved post-election winning probabilities can be backed out from stock prices. Our approach is based solely on publicly available data.