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Understanding cooperation to contain a pandemic. A behavioral economics analysis
Last registered on May 14, 2020


Trial Information
General Information
Understanding cooperation to contain a pandemic. A behavioral economics analysis
Initial registration date
April 28, 2020
Last updated
May 14, 2020 11:47 AM EDT
Primary Investigator
Other Primary Investigator(s)
PI Affiliation
University of Nottingham
Additional Trial Information
In development
Start date
End date
Secondary IDs
Containing a pandemic, like the current Covid-19 pandemic, requires people not to interact physically 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 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 stay at home or not. 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 comply or not with the stay-at-home rules. We plan to run the study on Amazon Mechanical Turk in two waves of 600 participants each.
External Link(s)
Registration Citation
ARECHAR, ANTONIO and SIMON GAECHTER. 2020. "Understanding cooperation to contain a pandemic. A behavioral economics analysis." AEA RCT Registry. May 14. https://doi.org/10.1257/rct.5749-1.2000000000000002.
Experimental Details
We invite 1,200 participants on Amazon Mechanical Turk (Mturk) to take part in an incentivized survey programmed in Qualtrics (see document attached). The survey consists of three main sections.
In the first one 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.
In the second section we present participants 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.
In the third section we survey the participants’ opinions about the current epidemic, the behavior about other people, the severity of the current crisis, and build an index of compliance with social distancing rules as a proxy for cooperation.
We conclude the study with an exploratory section where we assess the participants’ prosocial motives based in their demographics.
Our intervention will be implemented in two stages: on April 30th we will recruit the first 600 participants and two weeks later, on May 14th, we will recruit the last 600 new participants. This approach will allow us to explore any temporal dynamics between those days, where the number of cases are likely to increase as the lockdown policies relax at the state level. This approach will also allow us to test the robustness of our findings while replicating the results from the first stage.
Intervention Start Date
Intervention End Date
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 survey (available upon request).
Experimental Design Details
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?
Experiment Characteristics
Sample size: planned number of clusters
1,200 MTurk participants.
Sample size: planned number of observations
1,200 MTurk participants.
Sample size (or number of clusters) by treatment arms
1,200 MTurk participants (600 different participants in each of the two waves).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB Name
The Nottingham School of Economics Research Ethics Committee
IRB Approval Date
IRB Approval Number
IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)