Polarization and Public Health: Partisan Differences in Social Distancing during COVID-19

Last registered on September 07, 2020
View Trial History

Pre-Trial

Trial Information

General Information

Title
Polarization and Public Health: Partisan Differences in Social Distancing during COVID-19
RCT ID
AEARCTR-0005632
Initial registration date
April 05, 2020

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
April 06, 2020, 1:42 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
September 07, 2020, 5:31 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country
United States of America
Region

Primary Investigator

Name
Michael Thaler
Affiliation
UCL
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Jacob Conway
PI Affiliation
Stanford University
PI Name
Levi Boxell
PI Affiliation
Stanford University
PI Name
David Yang
PI Affiliation
Harvard University
PI Name
Matthew Gentzkow
PI Affiliation
Stanford University
PI Name
Hunt Allcott
PI Affiliation
New York University

Additional Trial Information

Status
Completed
Start date
2020-04-04
End date
2020-04-07
Keywords
Electoral, Health
Additional Keywords
JEL code(s)
Secondary IDs
Abstract
We study partisan differences in Americans' response to the COVID-19 pandemic. Political leaders and media outlets on the right and left have sent divergent messages about the severity of the crisis, and this could potentially undermine public compliance with key measures such as social distancing. Using a nationally-representative sample of Americans, we test whether there are partisan gaps between Republicans and Democrats in perceived risks of COVID-19, in social distancing, in media consumption, and in predictions of future cases. We test how differences in beliefs and actions about COVID-19 are related to differences in political attitudes. We test whether differences in beliefs are due to partisan cheerleading by randomly varying whether predictions are incentivized.
External Link(s)

Registration Citation

Citation
Allcott, Hunt et al. 2020. "Polarization and Public Health: Partisan Differences in Social Distancing during COVID-19." AEA RCT Registry. September 07. https://doi.org/10.1257/rct.5632-2.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2020-04-04
Intervention End Date
2020-04-07

Primary Outcomes

Primary Outcomes (end points)
See the analysis plan for more information.
Primary Outcomes (explanation)
See the analysis plan for more information.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Using a nationally-representative sample of Americans, we test whether there are partisan gaps between Republicans and Democrats in the following categories:
- Perceived risks of COVID-19
- Self-reported social distancing
- The effectiveness of social distancing
- The tradeoff between the economic costs and spread-mitigation benefits. of social distancing
- Media consumption and trust
- Predictions of future cases
We test whether differences in beliefs are due to partisan cheerleading by randomly varying whether predictions are incentivized. We discuss exploratory tests of motivated reasoning and partisan priming.
Experimental Design Details
Randomization Method
Randomization done by a computer.
Randomization Unit
Individual-level randomization.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2000 individuals
Sample size: planned number of observations
2000 individuals
Sample size (or number of clusters) by treatment arms
1000 incentivized predictions, 1000 unincentivized predictions
1000 see a COVID-19 cases prediction question first, 1000 see a Trump approval question first (denoted as a partisan prime)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
New York University University Committee on Activities Involving Human Subjects
IRB Approval Date
2017-05-31
IRB Approval Number
IRB-FY2017-938
IRB Name
Committee on the Use of Human Subjects: University-Area Institutional Review Board at Harvard
IRB Approval Date
2017-11-13
IRB Approval Number
IRB17-1725
Analysis Plan

Analysis Plan Documents

Pre-Analysis Plan for Polarization and Public Health: Partisan Differences in Social Distancing during COVID-19

MD5: 6b133937bc049b8e6c10b86fade92ce5

SHA1: a12fad327c7447904c8444c46d7d91f2f3520340

Uploaded At: April 05, 2020

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
April 07, 2020, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
April 07, 2020, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
2000 individuals
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
2000 individuals
Final Sample Size (or Number of Clusters) by Treatment Arms
1013 incentivized predictions, 987 unincentivized predictions. 1013 saw the COVID-19 cases prediction question first, 987 saw the Trump approval question first. Assignment in these groups was not correlated.
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Abstract
We study partisan differences in Americans’ response to the COVID-19 pandemic. Political leaders and media outlets on the right and left have sent divergent messages about the severity of the crisis, which could impact the extent to which Republicans and Democrats engage in social distancing and other efforts to reduce disease transmission. We develop a simple model of a pandemic response with heterogeneous agents that clarifies the causes and consequences of heterogeneous responses. We use location data from a large sample of smartphones to show that areas with more Republicans engaged in less social distancing, controlling for other factors including public policies, population density, and local COVID cases and deaths. We then present new survey evidence of significant gaps at the individual level between Republicans and Democrats in self-reported social distancing, beliefs about personal COVID risk, and beliefs about the future severity of the pandemic.
Citation
Allcott, Hunt, Levi Boxell, Jacob Conway, Matthew Gentzkow, Michael Thaler, and David Yang. Polarization and Public Health: Partisan Differences in Social Distancing during the Coronavirus Pandemic. Journal of Public Economics, forthcoming.
URL
https://doi.org/10.1016/j.jpubeco.2020.104254

Reports & Other Materials