Incentives and lying in the cheating game

Last registered on April 29, 2026
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Pre-Trial

Trial Information

General Information

Title
Incentives and lying in the cheating game
RCT ID
AEARCTR-0018366
Initial registration date
April 23, 2026

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 29, 2026, 3:34 PM EDT

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

Locations

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Primary Investigator

Name
Alexandra Wellsjo
Affiliation
UC San Diego
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Other Primary Investigator(s)

PI Name
Uri Gneezy
PI Affiliation
UC San Diego
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PI Name
Sirikarn Phuchada
PI Affiliation
UC San Diego
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Additional Trial Information

Status
In development
Start date
2026-04-24
End date
2026-05-01
Keywords
Behavior, Lab
Additional Keywords
lying, incentives, hypothetical
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We explore whether incentives affect lying in the die roll game.
External Link(s)

Registration Citation

Citation
Gneezy, Uri, Sirikarn Phuchada and Alexandra Wellsjo. 2026. "Incentives and lying in the cheating game." AEA RCT Registry. April 29. https://doi.org/10.1257/rct.18366-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-04-24
Intervention End Date
2026-05-01

Primary Outcomes

Primary Outcomes (end points)
Our primary outcome is the share of 5s reported. We interpret values above the expected value (1/6) as lying.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
self-reported lying/truth-telling, satisfaction with result, willingness to participate in the study again, clicking die roll link and switching away from survey tab, predictions about the reporting of others
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We vary incentives in the die roll cheating game on prolific.
Experimental Design Details
Not available
Randomization Method
Randomization by qualtrics into one of the 5 treatments
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
NA
Sample size: planned number of observations
1250
Sample size (or number of clusters) by treatment arms
250 prolific participants per treatment arm
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
With sample sizes of 250 per treatment, we will have 80% power to detect lying rates of ~6-7pp (one-sided test of proportions compared to the expected share of 5s report (1/6)). Comparing across treatments, we will have 80% power to detect differences in reporting rates of ~12pp.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
UC San Diego IRB
IRB Approval Date
2026-03-16
IRB Approval Number
813815
Analysis Plan

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