Misinformation During a Pandemic

Abstract

Media outlets often present diverging, even conflicting, perspectives on reality-not only informing, but potentially misinforming audiences. We study the extent to which misinformation broadcast on mass media at the early stages of the coronavirus pandemic influenced health outcomes. We first document large differences in content between the two most popular cable news shows in the US, both on the same network, and in the adoption of preventative behaviors among viewers of these shows. Through both a selection-on-observables strategy and an instrumental variable approach, we find that areas with greater exposure to the show downplaying the threat of COVID-19 experienced a greater number of cases and deaths. We assess magnitudes through an epidemiological model highlighting the role of externalities and provide evidence that contemporaneous information exposure is a key underlying mechanism.

Polarization and Public Health: Partisan Differences in Social Distancing during the Coronavirus Pandemic

“…Painter and Qiu (2020) examine partisan heterogeneity in response to state-level, stay-at-home orders. Bursztyn et al (2020) and Simonov et al (2020) find that individuals social distance less if quasi-randomly exposed to less concerned news, suggesting a possible driver for our result. 2 Our work contributes to a broader literature on what drives responses to pandemics (e.g., Blendon et al 2008;Vaughan and Tinker 2009;Fineberg 2014).…”

Strong Social Distancing Measures In The United States Reduced The COVID-19 Growth Rate

“…In computing the growth rate, we followed a recent COVID-19 study and added one to the case counts to avoid dropping counties that started with zero cases. 18 Covariates The data on the timing of state and local government social distancing interventions was gathered from a host of sources and made available by Johns Hopkins University. 19 Part A of the online appendix explains a few corrections we made to the dates and provides a list of state-and county-level policies used in the analysis.…”

Understanding Spatial Variation in COVID-19 across the United States

“…Second, a measure of social capital from , bears a positive relationship with cases and deaths in Table 1, but this result does not hold up when looking at the intensive margin only ( Table 2). 5 State fixed-effects. Tables 1 and 2 report results with or without state fixed effects.…”