Working Paper: CEPR ID: DP15464
Authors: Maria Milosh; Marcus Painter; Konstantin Sonin; David Van Dijcke; Austin L. Wright
Abstract: Political polarization may undermine public policy response to collective risk, especially in periods of crisis, when political actors have incentives to manipulate public perceptions. We study these dynamics in the United States, focusing on how partisanship has influenced the use of face masks to stem the spread of COVID-19. Using a wealth of micro-level data, machine learning approaches, and a novel quasi-experimental design, we establish the following: (1) mask use is robustly correlated with partisanship; (2) the impact of partisanship on mask use is not offset by local policy interventions; (3) partisanship is the single most important predictor of local mask use, not COVID-19 severity or local policies; (4) president Trump's unexpected mask use at Walter Reed on July 11, 2020 and endorsement of masks on July 20, 2020 significantly increased social media engagement with and positive sentiment towards mask-related topics. These results unmask how partisanship undermines effective public responses to collective risk and how messaging by political agents can increase public engagement with policy measures.
Keywords: partisanship; polarization; COVID-19
JEL Codes: H12; I18
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Trump's endorsement of mask use (D79) | Social media engagement (Z13) |
| Trump's endorsement of mask use (D79) | Positive sentiment towards mask-related topics (Z13) |
| Partisanship (D72) | Mask Use (Y20) |
| Local policies (J18) | Mask Use (Y20) |
| Severity of COVID-19 (I12) | Mask Use (Y20) |