Effectiveness of Information Manipulation - An Experimental Investigation of Informational Autocracies

Last registered on October 07, 2024
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Pre-Trial

Trial Information

General Information

Title
Effectiveness of Information Manipulation - An Experimental Investigation of Informational Autocracies
RCT ID
AEARCTR-0014479
Initial registration date
October 02, 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
October 07, 2024, 7:16 PM 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
Christian Höhne
Affiliation
University of Cambridge
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Other Primary Investigator(s)

PI Name
Edoardo Gallo
PI Affiliation
University of Cambridge
Contact Investigator

Additional Trial Information

Status
In development
Start date
2024-10-08
End date
2024-10-19
Keywords
Behavior
Additional Keywords
online experiment, information, communication
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The purpose of this project is to investigate if communication by a group leader can increase contributions to a public good by the other group members if the communicated information is unverifiable and incentives between the leader and members are misaligned. This is to experimentally approximate the environment of informational autocracy (Guriev and Treisman, 2019, 2020) while abstracting from the existence of motivated beliefs and identity.
External Link(s)

Registration Citation

Citation
Gallo, Edoardo and Christian Höhne. 2024. "Effectiveness of Information Manipulation - An Experimental Investigation of Informational Autocracies." AEA RCT Registry. October 07. https://doi.org/10.1257/rct.14479-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Intervention (Hidden)
Intervention Start Date
2024-10-13
Intervention End Date
2024-10-18

Primary Outcomes

Primary Outcomes (end points)
- contribution to public good
- beliefs about public good contribution
- embezzlement behavior
- choice of communication
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
To model this decision environment, we use a game design combining dynamics of public good (PG) and trust games. Four participants -- of Type A -- can contribute to a public good, while one player -- Participant B -- can either add to or embezzle from the public good. Participant B thus plays a version of TG with multiple investors, while Participants of Type A play a PG with uncertain return.
The payoff for Participants of Type A depends on three components: their individual contribution to the public good, contributions by other Type A's and Participant B's action. Type As know their own contribution, the final size of the group account, and their payoff for each round. They may also receive information about the composition of contributions leading to the final size of the public good, that is overall contributions by all Participants of Type A and Participant B's action choice.
We experimentally vary whether the provided information is verifiable to Participants of Type A and whether it can be manipulated by Participant B. This way we can identify differences in contribution and embezzlement behavior under different informational regimes and evaluate the effectiveness of information manipulation.
Experimental Design Details
Randomization Method
Algorithmic randomisation to experimental sessions based on availability and algorithmic randomisation to groups and roles within the session.
Randomization Unit
We randomize the treatment by experimental session. In each session, we randomly assign 5 participants to one group. Within this group, we randomly assign one participant the role 'B' and all the remaining participants play role "A".
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
100 groups
Sample size: planned number of observations
500 participants
Sample size (or number of clusters) by treatment arms
25 groups or 125 participants by treatment arm
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Director of Research, Faculty of Economics, University of Cambridge,
IRB Approval Date
2023-10-02
IRB Approval Number
UCAM-FoE-23-02
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