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Competition and cooperation with multiple identities
Last registered on July 08, 2020

Pre-Trial

Trial Information
General Information
Title
Competition and cooperation with multiple identities
RCT ID
AEARCTR-0006123
Initial registration date
July 08, 2020
Last updated
July 08, 2020 5:02 PM EDT
Location(s)

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Primary Investigator
Affiliation
University of Warwick
Other Primary Investigator(s)
PI Affiliation
University of Warwick
PI Affiliation
Nanyang Technological University
Additional Trial Information
Status
In development
Start date
2020-07-15
End date
2021-01-15
Secondary IDs
Abstract
We all have many identities whether it be our gender, age/cohort, class, political affiliation, race, religion or dietary preferences. There is a large literature on the role of identity in decision-making but very little on the interaction between different identities in different contexts. We set out to explore the scope for shifts in the salience of different identities and how these can impact on behavior in competitive and cooperative environments.
External Link(s)
Registration Citation
Citation
Sgroi, Daniel, Jonathan Yeo and Shi Zhuo. 2020. "Competition and cooperation with multiple identities." AEA RCT Registry. July 08. https://doi.org/10.1257/rct.6123-1.0.
Experimental Details
Interventions
Intervention(s)
In the study, we have a 3 X 2 between individual design.
On one dimension, we vary the context of the interaction: It is either a competitive or a cooperative social context.
On the other dimension, we vary the number and type of identity dimensions which are salient to the participant: it is either
1) Gender, 2) Political Affiliation, or 3) Gender and Political Affiliation.
Intervention Start Date
2020-07-15
Intervention End Date
2021-01-15
Primary Outcomes
Primary Outcomes (end points)
Effort put into production task, Final strength of identity dimension(s)
Primary Outcomes (explanation)
Final (relative) strength of each identity dimension will be constructed from their decisions in a third-party allocation task.
Secondary Outcomes
Secondary Outcomes (end points)
Beliefs about the amount of effort put in by individuals with particular identity characteristics. Initial strength of identity dimension(s).
Secondary Outcomes (explanation)
Initial (relative) strength of each identity dimension will be constructed from their answers to survey questions about their identity in the first stage of the experiment.
Experimental Design
Experimental Design
Subjects will be invited to participate in an online study conducted on Amazon Mechanical Turk.
They will be assigned at random to one of 6 treatments. This will be a 3 X 2 between individual design.
On one dimension, we vary the context of the interaction: subjects will complete either a cooperative or a competitive production task with a randomly assigned partner.
On the other dimension, we we vary the number and type of the identity dimensions which are salient to the participant: it is either
1) Gender (Male/Female), 2) Political Affiliation (Democratic/Republican), or 3) Gender and Political Affiliation.

There will be 3 main stages in the experiment.
In the first stage, a survey will be conducted to elicit which gender group and political affiliation they belong to. Subjects' strength in these dimensions will also be elicited via a series of survey questions.

In the second stage, participants will complete a production task with a randomly assigned partner under a cooperative or a competitive social context. In the task they will have to choose via the strategy method, how much effort they wish to put in given information about their partner's characteristics (Gender and/or Political Affiliation depending on the treatment).

In the third stage, participants will complete a third party allocation task which aims to elicit their final levels of identity strength in each dimension. In this task, they will decide how to distribute a number of Credits between 2 randomly assigned participants.
This will be done via the strategy method.

Finally, after all stages are complete, they will be asked to complete a post-experiment questionnaire which elicits their demographic variables and beliefs about others in the experiment.

Participants will be required to provide their MTurk ID at the end of the study. They will be credited with their payoff after the study is complete and payoffs are calculated for the randomisations.






Experimental Design Details
Not available
Randomization Method
Randomization by computer
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
1000-2000 participants
Sample size: planned number of observations
1000-2000 participants
Sample size (or number of clusters) by treatment arms
250-500 participants in Gender and Political Affiliation X Cooperative Task
250-500 participants in Gender and Political Affiliation X Competitive Task
125-250 participants in Gender X Cooperative Task
125-250 participants in Gender X Competitive Task
125-250 participants in Political Affiliation X Cooperative Task
125-250 participants in Political Affiliation X Competitive Task
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Here, we perform calculations for treatment effects in the competitive and cooperative treatments separately. In all calculations, a power of 0.8 is assumed. We will combine the 2 one dimension treatments, and compare with the two dimension treatment. A two-sided test is assumed for calculations. With N= 500 (250 in each group), power of 0.8, alpha = 0.05, equal SD, the MDE is 0.251. With alpha=0.025 as a bonferroni correction to take into account two main outcomes (effort in production task, final identity strength), MDE increases to 0.277. Since the two outcomes are expected to be positively correlated, alpha=0.025 is a conservative adjustment. In Chen and Li (2009), chatting with one's ingroup results in an increase in ingroup bias with effect sizes ranging from 0.08 to 0.29 SD. We take an intermediate value of around 0.2 SD as an estimate for our effect size. With this effect size, we will need N=788 (alpha=0.05) or N=954 (alpha=0.025) in each of the cooperative and competitive treatments. Since we do not know the exact effect size and underlying variation, we will first target a sample size of 500 in each of the cooperative and competitive treatments. After gaining a better idea of the variance of the underlying population, we will potentially follow up with a larger sample size if needed.
Supporting Documents and Materials

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IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Humanities and Social Sciences Research Ethics Committee
IRB Approval Date
2020-06-09
IRB Approval Number
HSSREC 178/19-20