Partisan endorsement experiments do not affect mass opinion on COVID-19

The partisan politics and polarized messaging surrounding COVID-19 have attracted wide interest. We present the findings of a novel survey experiment, fielded March 21-23, 2020, on a nationally-representative sample of Americans. We found no statistically significant effects of partisan endorsements or messaging from President Trump on a wide range of health behaviors and policy attitudes. We speculate on potential explanations for these null results, such as America’s saturated media environment or heterogeneous effects by party. Our results suggest that priming experiments face serious obstacles when implemented at the same time as a national crisis is unfolding

Partisanship, health behavior, and policy attitudes in the early stages of the COVID-19 pandemic

ObjectiveTo study the U.S. public's health behaviors, attitudes, and policy opinions about COVID-19 in the earliest weeks of the national health crisis (March 20-23, 2020).MethodWe designed and fielded an original representative survey of 3,000 American adults between March 20-23, 2020 to collect data on a battery of 38 health-related behaviors, government policy preferences on COVID-19 response and worries about the pandemic. We test for partisan differences COVID-19 related policy attitudes and behaviors, measured in three different ways: party affiliation, intended 2020 Presidential vote, and self-placed ideological positioning. Our multivariate approach adjusts for a wide range of individual demographic and geographic characteristics that might confound the relationship between partisanship and health behaviors, attitudes, and preferences.ResultsWe find that partisanship-measured as party identification, support for President Trump, or left-right ideological positioning-explains differences in Americans across a wide range of health behaviors and policy preferences. We find no consistent evidence that controlling for individual news consumption, the local policy environment, and local pandemic-related deaths erases the observed partisan differences in health behaviors, beliefs, and attitudes. In further analyses, we use a LASSO regression approach to select predictors, and find that a partisanship indicator is the most commonly selected predictor across the 38 dependent variables that we study.ConclusionOur analysis of individual self-reported behavior, attitudes, and policy preferences in response to COVID-19 reveals that partisanship played a central role in shaping individual responses in the earliest months of the COVID-19 pandemic. These results indicate that partisan differences in responding to a national public health emergency were entrenched from the earliest days of the pandemic

Structural Topic Models for Open-Ended Survey Responses

Collection and especially analysis of open-ended survey responses are relatively rare in the discipline and when conducted are almost exclusively done through human coding. We present an alternative, semiautomated approach, the structural topic model (STM) (Roberts, Stewart, and Airoldi 2013; Roberts et al. 2013), that draws on recent developments in machine learning based analysis of textual data. A crucial contribution of the method is that it incorporates information about the document, such as the author's gender, political affiliation, and treatment assignment (if an experimental study). This article focuses on how the STM is helpful for survey researchers and experimentalists. The STM makes analyzing open-ended responses easier, more revealing, and capable of being used to estimate treatment effects. We illustrate these innovations with analysis of text from surveys and experiments

Off to the Courts? Or the Agency? Public Attitudes on Bureaucratic and Legal Approaches to Policy Enforcement

A key curiosity in the operation of the American regulatory state lies with its hybrid structure, defined by centralized, bureaucratic approaches but also more decentralized actions such as lawsuits brought by private citizens in the courts. While current research on these two pathways focuses at the elite level—exploring how and why political actors and institutions opt for legal or administrative strategies for implementing different public policies—there is little research that examines public attitudes toward how policy is enforced in the U.S. Given that the public is a key partner in this process, this paper integrates public attitudes into the discussion, tapping into conceptions of “big government,” privatization, and the tort reform movement. Using original data from a series of vignette-based experiments included in the 2014 Cooperative Congressional Election Survey, we examine public preferences about how policy is regulated—by private citizens in the courts or by government officials in agencies—across a broad number of policy areas. We offer one of the first studies that adjudicates the boundaries of public attitudes on litigation and bureaucratic regulation in the U.S., offering implications for how elites might approach the design of policy implementation for different issue areas

Voting Can Be Hard, Information Helps

Many U.S. elections provide voters with precious little information about candidates on the ballot. In local contests, party labels are often absent. In primary elections, party labels are not useful. Indeed, much of the time, voters have only the name of the candidate to go by. In these contexts, how do voters make decisions? Using several experiments, we find that voters use candidates’ race, ethnicity, and gender as cues for whom to support—penalizing candidates of color and benefiting women. But we also demonstrate that providing even a small amount of information to voters—such as candidate occupation—virtually erases the effects of candidate demographics on voter behavior, even among voters with high levels of racial and gender prejudice

Racial resentment and support for COVID-19 travel bans in the United States

Abstract: Travel bans were a globally prevalent policy response to the COVID-19 pandemic. In the United States, travel bans against China and European countries proved a broadly popular mitigation tool among Americans. Why did Americans support COVID-19 travel bans? We fielded two novel survey experiments, surveying 3000 American citizens across five waves (between March 2020 and March 2021). In randomizing the country of origin of those potentially subject to travel ban measures, we find consistent evidence that racial attitudes drive support for travel bans. The strength of this relationship varies across political parties and across hypothetical target countries but is not explained by objective caseloads that change across countries and over the course of the pandemic

Morbid Polarization

Relationship between exposure to COVID-19 and political polarizatio