The Interaction of Communication, Social Preferences, and Inequality: An experimental study

Last registered on July 17, 2025

View Trial History

Pre-Trial

Trial Information

General Information

Title

The Interaction of Communication, Social Preferences, and Inequality: An experimental study

RCT ID

AEARCTR-0014317

Initial registration date

July 14, 2025

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

July 17, 2025, 7:16 AM EDT

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

Locations

Country

United States of America

Region

Primary Investigator

Name

Kirill Zhazhin

Affiliation

University of California, Santa Cruz

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Kristian Lopez Vargas

PI Affiliation

PI Name

Louis Putterman

PI Affiliation

Additional Trial Information

Status

In development

Start date

2025-07-08

End date

2025-08-10

Keywords

Behavior, Lab

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

This experiments studies the impact of communication on voter behavior in a lab setting. First, participants complete a series of tasks that can determine their starting position later. Then, they interact in a fixed group by sending messages to each other in an open-forum. Last, they vote for a tax that serves a redistributive and public-good creation purposes. Communication and voting stages are repeated for several rounds. We study the individual choice of messages, voting behavior, and distributional outcomes relative to the theoretical predictions. We wary access to communication and the initial income determination method across treatments.

External Link(s)

Registration Citation

Citation

Lopez Vargas, Kristian, Louis Putterman and Kirill Zhazhin. 2025. "The Interaction of Communication, Social Preferences, and Inequality: An experimental study." AEA RCT Registry. July 17. https://doi.org/10.1257/rct.14317-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

We use a 3×2 design that varies access to communication and the method of initial income determination. We consider a society of size N=9 individuals, who complete real-effort tasks and then interact with each other by communicating and then voting. Communication access is a between-group treatment, with three conditions: (i) free communication with no message cost, (ii) affordable communication with costly options to enhance the message, (iii) no communication. The initial income determination method is a within-group treatment. It varies across four rounds of repeated communication and voting stages, and can either be random (R) or effort-based (E), i.e., dependent on the relative performance of participants in the tasks that precede communication. We use a crossover approach with RREE and EERR options across four round in each group. Therefore, each treatment is a combination of one of the (i)-(iii) and RREE/EERR conditions. The payoff of participants depends on their initial income, their message and its cost, and the voting outcome.

Intervention (Hidden)

Intervention Start Date

2025-07-10

Intervention End Date

2025-08-10

Primary Outcomes

Primary Outcomes (end points)

Messages of individuals
Votes of individuals
Payoffs of individuals

Primary Outcomes (explanation)

Messages of individuals are the decisions to send a message and purchase enhancements of individuals
Votes of individuals are the submitted tax levels at the end of the voting stage.

Secondary Outcomes

Secondary Outcomes (end points)

Message content
Group outcome efficiency
Distributional outcomes

Secondary Outcomes (explanation)

Message content as it relates to the presence of key ideas of efficiency, fairness, and inequality
Group outcome efficiency relative to predicted equilibrium tax and the tax that maximizes the total income of the group
Distributional outcomes are the differences between post- and pre-tax distribution of income.

Experimental Design

In the experiment, each participant individually completes four real-effort tasks, then gets assigned to a group of size N=9. Then, participants interact inside each group in four rounds, while groups remain unchanged. In each round, participants get informed about their income and then vote on a tax that could either result in smaller or larger final payoff. Depending on the treatment, a communication stage precedes voting. The participants are allowed to send a message to others in an open-forum message, which can also be enhanced for small but noticeable price.

Participants earn experimental points based on their performance in the real-effort tasks, communication decision, and voted tax. At the end of each round, they receive feedback about their own choices, group outcome, and payoffs. Their final earnings are determined based on the post-tax outcome from a randomly selected round.

During the voting stage in each round, participants are also asked to predict the voting outcome. At the end of the experiment, participants fill out a survey about demographics, risk-, redistribution- and social- preferences.

The experiment is conducted online with participants recruited on Prolific, using o-Tree as software.

Experimental Design Details

Randomization Method

By the random order of arrival of participants to participate in the experiment on Prolific and "random" Python module.

Randomization Unit

Group level

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

Number of groups: 32

Sample size: planned number of observations

Number of observations: 32x9=288 participants

Sample size (or number of clusters) by treatment arms

Number of groups per each treatment arm:
6 in Free Communication & RREE, 6 in Free Communication & EERR,
6 in Affordable Communication & RREE, 6 in Affordable Communication & EERR
4 in No Communication & RREE, 4 in No Communication & EERR

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

Supporting Documents and Materials

IRB