Understanding cooperation to contain a pandemic. A behavioral economics analysis

Last registered on July 07, 2022

Pre-Trial

Trial Information

General Information

Title
Understanding cooperation to contain a pandemic. A behavioral economics analysis
RCT ID
AEARCTR-0005749
Initial registration date
April 28, 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 29, 2020, 11:38 AM EDT

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

Last updated
July 07, 2022, 4:58 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
MIT

Other Primary Investigator(s)

PI Affiliation
University of Nottingham

Additional Trial Information

Status
On going
Start date
2020-04-29
End date
2022-09-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Containing a pandemic, like the current Covid-19 pandemic, requires people to get vaccinated and to avoid unnecessary physical interactions with each other—that is, they have to stay at home and refrain from many social activities they normally like to undertake in the company of other people. This is a large-scale cooperation problem, where (some) people may have some incentives to break the rules for self-interested reasons but are thereby undermining the collective efficacy of containment strategies. Here, we are interested in the behavioral dimensions of people’s decisions to get vaccinated or not and to stay at home or not. There are several potentially relevant behavioral dimensions: People’s pro-social inclinations, their patience and risk preferences, their trust in the authorities, and their tendency to follow other people’s behavior may all play a part in decisions to get vaccinated and to stay at home. We therefore measure these preferences, using a mixture of tested survey tools (e.g., the Global Preference Survey and the Social Value Orientation test) and incentivized behavioral games (sequential prisoner’s dilemma, dictator game, and public goods game). We will also measure various motives to get vaccinated and to comply or not with the stay-at-home rules. We plan to run the study on Amazon Mechanical Turk in six waves of 600 participants each.
External Link(s)

Registration Citation

Citation
ARECHAR, ANTONIO and SIMON GAECHTER. 2022. "Understanding cooperation to contain a pandemic. A behavioral economics analysis." AEA RCT Registry. July 07. https://doi.org/10.1257/rct.5749
Experimental Details

Interventions

Intervention(s)
We invite 3,600 participants on Amazon Mechanical Turk (Mturk) to take part in an incentivized survey programmed in Qualtrics (see documents attached), implemented in three stages of 1,200 participants each:
- Stage 1: On 4/30/20 we recruit the first 600 participants and two weeks later, on 5/14/20, we recruit the next 600 new participants. This approach allows us to explore any temporal dynamics between those days, where the number of cases is likely to increase as the lockdown policies relax at the state level. This approach also allows us to test the robustness of our findings while replicating the results from the first days.
- Stage 2: Roughly a year later, we replicate the recruitment procedures of Stage 1 on 6/10/21 and on 6/24/21, when the lockdown policies have been further relaxed and vaccines have been applied to roughly half of the U.S. population. This second stage will further allow us to test the robustness of our findings and learn whether the behavioral regularities pertaining to social distancing extend to willingness to get vaccinated.
- Stage 3: Roughly a year later, we replicate the recruitment procedures of Stage 1 on 7/7/22 and on 7/21/22, when the lockdown policies have essentially disappeared and vaccines are freely available. This third stage will further allow us to test the robustness of our findings and learn whether the behavioral regularities pertaining to willingness to get vaccinated and social distancing extend over time.
The survey consists of three main sections, with the content of the three stages varying slightly with each other. Specifically, in the first section of the first and third stages we use three incentivized economic games to measure: i) cooperation using a one-shot public goods game; ii) conditional cooperation using a sequential prisoner’s dilemma game; iii) and altruism using an ad hoc donation task; whereas in the second stage we do not make use of the public goods game. In the second section we present participants of the first and third stages with hypothetical scenarios that also measure standard economic preferences, based on the Global Preference Survey (GPS) by Falk et al. 2018, and the Triple Dominance Measure of Social Value Orientation (SVO) by Van Lange et al. 1997; whereas in the second stage we only make use of the SVO component. In the third section we survey the participants’ opinions about the current epidemic, the behavior of other people, and the severity of the current crisis, and build an index of compliance with social distancing rules as a proxy for cooperation for the first stage, an index of compliance with vaccination as a proxy for cooperation for the second stage, and a combined index for the third stage. The second and third stages also include an exploratory 2-question experiment in a 2x2 design, where participants first assess the likelihood that a person is to get vaccinated if they live in a [county, community] where vaccines are available and [a high percentage, a low percentage] of the population have been vaccinated. Participants then determine what they would do if they were such a person: either get vaccinated, not get vaccinated, or wait until more people are vaccinated.
We conclude the study with an exploratory section where we assess the participants’ prosocial motives based in their demographics.
Between 9/9/21 and 9/30/22, we will conduct a follow-up study with the 1,200 participants surveyed in stage 2. They will be invited to complete a survey with the core elements that were not asked originally but that the 2,400 participants of the first and third stages did provide (i.e. cooperation using a one-shot public goods game, standard economic preferences based on the Global Preference Survey (GPS) by Falk et al. 2018, the Cognitive Reflective Test, education, and income).
Intervention Start Date
2020-04-29
Intervention End Date
2022-09-30

Primary Outcomes

Primary Outcomes (end points)
Overall cooperation / compliance across the three sections
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This study does not have a treatment or a control, and therefore no between-subject design. Instead, it surveys cooperative outcomes from all participants through different angles, and almost all measures are therefore within-subjects. Design details can be found in the attached Qualtrics surveys (available upon request).
Experimental Design Details
Not available
Randomization Method
Randomization done by the survey software qualtrics (to determine the order of some of the questions).
Randomization Unit
Individual question presented in the survey.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
3,600 MTurk participants.
Sample size: planned number of observations
3,600 MTurk participants.
Sample size (or number of clusters) by treatment arms
3,600 MTurk participants (600 different participants in each of the two waves of the three stages).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
MIT COUHES
IRB Approval Date
2018-06-13
IRB Approval Number
1806392996
IRB Name
The Nottingham School of Economics Research Ethics Committee
IRB Approval Date
2020-04-08
IRB Approval Number
N/A
Analysis Plan

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