Learning about other's rewards: punishment and sorting in hierarchical groups

Last registered on September 13, 2020

View Trial History

Pre-Trial

Trial Information

General Information

Title

Learning about other's rewards: punishment and sorting in hierarchical groups

RCT ID

AEARCTR-0006252

Initial registration date

August 07, 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

August 10, 2020, 10:48 AM EDT

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

Last updated

September 13, 2020, 5:35 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

Andrea Kiss

Affiliation

Duke University

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Victoria Lee

PI Affiliation

Duke University

Contact Investigator

Additional Trial Information

Status

In development

Start date

2020-08-10

End date

2021-10-31

Keywords

Labor, Welfare

Additional Keywords

JEL code(s)

C91, D91, D63, J31

Secondary IDs

Abstract

We run a online experiment to understand what is the effect of learning other players' payment in a hierarchical group. The participants will complete two games: a costly punishment game and a sorting task. In the punishment game the players can reduce the payment of the other group members at a cost, while in the sorting task they will choose which group would they want to join. We randomly vary the information participants see about their peers' payment.

External Link(s)

Registration Citation

Citation

Kiss, Andrea and Victoria Lee. 2020. "Learning about other's rewards: punishment and sorting in hierarchical groups." AEA RCT Registry. September 13. https://doi.org/10.1257/rct.6252-1.3

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

We randomly vary the amount of information that the players have about others' payment.

Intervention Start Date

2020-08-10

Intervention End Date

2020-10-30

Primary Outcomes

Primary Outcomes (end points)

Punishment behavior, choice in sorting task.

Primary Outcomes (explanation)

We specify the outcomes in the pre-analysis plan.

Secondary Outcomes

Secondary Outcomes (end points)

Beliefs about self, beliefs about other's payments, estimated social preferences.

Secondary Outcomes (explanation)

We specify the outcomes in the pre-analysis plan.

Experimental Design

Our main experimental variation changes the information that a participant has about other players' payment. We will test how information changes the agents behavior in two games: in a costly punishment game and in a sorting game.

The detailed experimental design is in the pre-analysis plan.

Experimental Design Details

The detailed experimental design is in the pre-analysis plan. Here we provide a summary.

The experiment follows the frame of a workplace, where people are organized to working-groups of three people and get a supervisor. The supervisor learns the quality of the workers and then allocates a fixed amount of money among the workers. One worker in each team, the agent, is randomized into one of the two experimental conditions. In the transparency condition, the agent learns the entire allocation that the supervisor chose and also the supervisor's payment. In the secrecy condition, however, the agent sees only her own payment. Next, the agent participates in a punishment game. She can reduce the points of others at a cost.

The other game is a sorting game in which the agents recieve two offers from two teams and they will have to choose which one they would like to choose. We vary the information level within-subject in this game: each participant completes the task in a secrecy condition (when they only know their own payment in their future teams) and in a transparency condition (when they know everyone's payment in the two teams.

Randomization Method

The randomization is implemented by the survey software.

Randomization Unit

individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

350 people

Sample size: planned number of observations

350 people

Sample size (or number of clusters) by treatment arms

In the punishment game: 150 individuals in the hidden information, 150 individuals in the full information.
The sorting game is a within subject variation.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

IRB