Equal Opportunity 2

Last registered on April 19, 2024

Pre-Trial

Trial Information

General Information

Title
Equal Opportunity 2
RCT ID
AEARCTR-0013323
Initial registration date
April 08, 2024

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 16, 2024, 1:06 PM EDT

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

Last updated
April 19, 2024, 1:57 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
Texas A&M University

Other Primary Investigator(s)

PI Affiliation
Texas A&M University
PI Affiliation
Texas A&M University

Additional Trial Information

Status
On going
Start date
2024-04-08
End date
2024-06-14
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
This study is an update from our initial equal opportunity experiment. The initial equal opportunity experiment is now considered a pilot experiment.

Equal opportunity has wide applicability throughout society. It touches upon access to education, employment, legal representation, etc. Given that equal opportunity has different meanings to different people (i.e., equal opportunity in outcomes, resources, access, etc.), we use a simplified definition based on the different types of equal opportunity mentioned in Arneson (2018). We define equal opportunity to mean that individuals should have similar access to “resources” except when one’s innate ability leads to a difference in resource allocation.

This project explores how economic inequality created by an institution affects productivity, and how productivity resulting from the institutional structure affects views on fairness and redistribution. We do this by setting up a controlled laboratory experiment in a two-person competitive environment consisting of a real-effort task where we vary the amount of time subjects have to perform the task. We use time as a resource in our competitive environment and we vary the amount of resources to compete under institutions that provide an advantage to subjects based on different inequality sources. More specifically we set up three inequality institutions that provide an advantage to the higher performer, the lower performer individual, or randomly to one of the individuals in the group. The control condition has the same amount of time for both participants.

The pre-analysis plan includes details on the structure of the experiment and our empirical strategy.
External Link(s)

Registration Citation

Citation
Eckel, Catherine, Marco Palma and Samuel Priestley. 2024. "Equal Opportunity 2." AEA RCT Registry. April 19. https://doi.org/10.1257/rct.13323-1.1
Experimental Details

Interventions

Intervention(s)
This experiment consists of four conditions, each varying the degree of economic inequality by changing the amount of time subjects have to compete in a real effort task.
Intervention Start Date
2024-04-08
Intervention End Date
2024-06-14

Primary Outcomes

Primary Outcomes (end points)
Production. Production is based on the subjects' performance in the real-effort task.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Redistribution and fairness
Secondary Outcomes (explanation)
Redistribution and fairness are measured by the amount of income a subject gives to another subject and the belief elicitation question.

Experimental Design

Experimental Design
Throughout the experiment, subjects participate in a real-effort production assignment in three different phases. Aspects of the production assignment will be altered during each phase. The production assignment involves subjects having to correctly solve two two-digit addition problems within a limited amount of time. Subjects’ earnings are based on the correct number of problems they solve. Each phase consists of one or more blocks. A block consists of five rounds each. Subjects will be paired with another subject in each session. After the production assignment, subjects will complete a survey. In the next subsections, we explain details of each phase of the production assignment, instructions given to each subject, and survey details.
Experimental Design Details
5 Design

Throughout the experiment, subjects participate in a real-effort production assignment in four different phases. Aspects of the production assignment will be altered during each phase. The production assignment involves subjects having to correctly solve two two-digit addition problems within a limited amount of time. Subjects’ earnings are based on the correct number of problems they solve. Each phase consists of a blocks. A block consists of five rounds each. Subjects will be paired with another subject in each session. The production assignment consists of four phases: ability, tournament, treatment, and redistribution. After the production assignment, subjects will complete a survey. In the next subsections, we explain details of each phase of the production assignment, instructions given to each subject, and survey details.

5.1 Ability Phase

The ability phase consists of one block (five rounds) and is used to measure subjects’ ability. Subjects have 40 seconds per round to independently solve as many addition problems as possible. At the end of the phase, each subject is randomly paired with another subject from the same session and for the remainder of the experiment.
Ability is measured as the total number of math problems correctly solved by each subject. A subject is considered high (low) ability if they solved more (fewer) problems correctly than the counterpart they are paired with. Subjects are informed of why they were assigned a specific type. For example, a high-ability subject will receive the following prompt, “You are assigned Player A because you solved more problems correctly in Block 1 compared to the other player you are paired with.” In the case subjects solve the same number of problems correctly, we compare who has a higher percentage of correct problems to break the tie, which is the total number of correct problems divided by the total number of problems a subject tried to answer. This is used as an additional measure to reduce the probability of randomly assigning subjects to an ability type due to a tie. If a tie occurs after applying the secondary rubric, then subjects are randomly assigned an ability type and are told their assignment was random.
We do not consider treatment conditions exploring if knowledge about ability creates a priming effect in our experiment due to a lack of replication of social priming experiments across multiple disciplines, including economics (Chivers 2019; Yong 2012). We include priming conditions in our exploratory analysis section as possible extensions in case initial results indicate that priming might need to be investigated.

5.2 Competition Phase

During the second phase of the experiment, each pair engages in a competition to determine who can solve more problems correctly during each round. This phase consists of one block (5 rounds). The winner of a round earns a bonus of 10 ECUs, which equals $1. This earning structure is meant to mimic real-life conditions where individuals who win competitions tend to accumulate a larger piece of the pie. Both subjects have 40 seconds per round during this phase.

5.3 Competition Phase with Treatment

Phase 3 is the same as the competition phase except the treatment is implemented. This phase lasts for one block (5 rounds). The treatments are explained in section 5.6.

5.4 Redistribution Phase

Phase 4 consists of the same competition as phase 3, but it is followed by a redistribution dictator game at the end of this phase. The redistribution phase consists of one blocks (5 rounds). At the end of the block, the subject with the highest-earnings will have an opportunity to transfer any amount from their earnings to the losing subject. We call the subject making the transfer decision the redistributor and the subject receiving the transfer the receiver. The purpose of the dictator game is to capture the winner’s fairness views based on the inequality institution. The rationale for the fairness views is explained in a later section. While the winning subject is making this choice, the losing subject will complete two belief elicitation tasks. One task will gauge how much earnings they believe the winning subject will transfer. The other task will gauge the normative beliefs of how much the losing subject believes should be transferred. The first task is meant to capture the losing subject’s expectations of what they will receive, which is why it is incentivized since we want to see how well subjects can predict the amount they will receive. The second task is meant to capture their fairness view.

Belief elicitation for measuring expected transfers
Please state how much you EXPECT TO RECEIVE from the other player. You will earn 1 ECU if you correctly guess within 1 ECU above or below the amount the other player transferred. [Subject enters an amount ranging from zero to max amount of the other player’s available endowment]

Belief elicitation for measuring fairness view
Please state how much you BELIEVE YOU SHOULD RECEIVE from the other player. You will not earn anything for this question. [Subject enters an amount ranging from zero to max amount of the other player’s available endowment]

5.5 Survey

After the main experiment, subjects will complete non-incentivized survey questions. The survey is used to collect self-reported demographic information, and views on political leaning, equality, competitiveness, confidence, effort, ability, and redistribution. We also ask subjects what they think the objective of the experiment is and how they felt about how time was allocated in the experiment. The survey is in the supplementary material. Some survey questions come from Almås, Cappelen, and Tungodden (2020).
Randomization Method
Computer
Randomization Unit
Randomization is done at the group level.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
160 people.
Sample size: planned number of observations
3,200 rounds.
Sample size (or number of clusters) by treatment arms
40 people per treatment arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Texas A&M University IRB
IRB Approval Date
2022-06-23
IRB Approval Number
IRB2022-0490D
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials