The Impact of COVID-19 Pronouncements and Policies on Attitudes towards Policies and Political Actors

There are wide partisan divides in opinions among the public on COVID-19, including about the seriousness of the disease, mask and other government mandates, and the handling of the pandemic at the federal level. These differences capture political divisions in three dimensions of public opinion: factual beliefs about the pandemic, policy preferences about how best to respond, and approval of how politicians have handled the pandemic. The degree to which sources of information are associated with these divisions can help adjudicate between two models of democratic representation. The first holds that objective facts influence voters' beliefs, which are then used to develop policy preferences against which competing political candidates are evaluated. The second reverses this ordering, hypothesizing that voters' partisan and ideological affiliations trump objective reality, and voters update their factual beliefs and policy preferences based on the information received via elite cues, even if detrimental to their objective welfare. Political scientist Jonathan Nagler and his colleagues will test theories of belief formation previously investigated in lab settings by examining how the public became so polarized over factual beliefs about, policy preferences for, and political support regarding COVID-19. They will address the following questions. First, what is the relative influence of facts versus elite cues on public perceptions about the pandemic and what factors are associated with variation in the relative influence? Second, how does the influence of elite cues vary by their source (e.g., the president or the Centers for Disease Control)? Third, to what extent do individuals update their beliefs, policy preferences, or evaluations of elected officials in response to a local policy? Finally, how did the response to the pandemic evolve over time? To test these hypotheses, the investigators will construct a novel dataset combining public opinions, elite pronouncements, public policies, and facts concerning COVID-19 based on multiple sources from January to November 2020.