Too Good to be True - Individual and Group Decision-Making with Correlated Signals

Last registered on December 09, 2024
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Pre-Trial

Trial Information

General Information

Title
Too Good to be True - Individual and Group Decision-Making with Correlated Signals
RCT ID
AEARCTR-0006323
Initial registration date
August 23, 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 31, 2020, 11:37 AM EDT

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

Last updated
December 09, 2024, 12:14 PM EST

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

Locations

Country
United Kingdom of Great Britain and Northern Ireland
Region
Online

Primary Investigator

Name
Sebastian Fehrler
Affiliation
University of Bremen
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Anna Hochleitner
PI Affiliation
NHH Bergen
Contact Investigator
PI Name
Moritz Janas
PI Affiliation
New York University Abu Dhabi
Contact Investigator

Additional Trial Information

Status
On going
Start date
2020-08-24
End date
2025-03-31
Keywords
Behavior
Additional Keywords
individual choice, group decision-making, correlated signals, voting
JEL code(s)
C92, D23, D71
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We conduct an online experiment on individual and group decision-making with correlated signals. In every
round, either one decision-maker individually or three decision makers collectively make a decision
under uncertainty that can be right or wrong. Our experiment follows a 2 (group or individual) x 2 (with or without bias) x 2 (with or without correlation) between-subjects design.
Depending on the treatment, we expect different success probabilities and communication patterns.
External Link(s)

Registration Citation

Citation
Fehrler, Sebastian, Anna Hochleitner and Moritz Janas. 2024. "Too Good to be True - Individual and Group Decision-Making with Correlated Signals." AEA RCT Registry. December 09. https://doi.org/10.1257/rct.6323-1.1
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
We conduct an online experiment. In every round, decision-makers have to make a decision (red or blue), either individually or collectively (in groups of three), depending on the treatment. If the correct decision is taken, i.e. if the decision equals the state of the world (red or blue), each player enjoys a positive payoff. A priori, each state is equally likely and signals (red or blue) are randomly drawn from an urn representing the state of the world. Our treatments vary the bias of the decision makers, the correlation structure of the signals and whether the decisions are made individually or collectively.


Intervention (Hidden)
see PAP pdf
Intervention Start Date
2020-08-24
Intervention End Date
2025-01-31

Primary Outcomes

Primary Outcomes (end points)
Decision accuracy rate
Primary Outcomes (explanation)
Correct decisions (all decisions are binary and either correct or wrong)

Secondary Outcomes

Secondary Outcomes (end points)
Communication honesty
Secondary Outcomes (explanation)
Communicated signals can be either true or false

Experimental Design

Experimental Design
Our experiment follows a 2 (group or individual) x 2 (with or without bias) x 2 (with or without correlation) between-subjects design. For the cell Group-No Bias-Correlation, we run an additional treatment with a message option. Hence, 9 treatments will be conducted in total.
Experimental Design Details
see PAP pdf
Randomization Method
Subjects are randomly assigned to treatments by the Prolific software
Randomization Unit
Individuals
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1900
Sample size: planned number of observations
1900
Sample size (or number of clusters) by treatment arms
100 for individual choice treatments
300 for group decision treatments
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
20 percentage points
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
German Association for Experimental Economic Research e.V.
IRB Approval Date
2020-08-23
IRB Approval Number
6aJqoedH
IRB Name
German Association for Experimental Economic Research e.V.
IRB Approval Date
2024-12-09
IRB Approval Number
EpQIeM7D
Analysis Plan

Analysis Plan Documents

Pre-Analysis-Plan 2020

MD5: 0fad3c72282e9c5d8b8cd3667bce966b

SHA1: f6a08d363747c71ebc21cf3ca79a665ae0b950aa

Uploaded At: August 23, 2020

Pre-Analysis-Plan Additional Treatment 2024

MD5: c1099e7abd1b6b728b2966a95cdf87a0

SHA1: 1f58c570a7742ae0ff50f0362265ef71c0128218

Uploaded At: December 09, 2024

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