Cheating with Externalities and a Regular Audience

Last registered on April 16, 2024


Trial Information

General Information

Cheating with Externalities and a Regular Audience
Initial registration date
April 15, 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
April 16, 2024, 3:52 PM EDT

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


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Primary Investigator


Other Primary Investigator(s)

PI Affiliation
University of Arizona

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Reports, for example, tax returns, research findings, or peer evaluations, can in some instances be falsified. We develop an experiment to study how externalities affect an individual’s self-reporting behaviors. We modify the cheating game (Fischbacher & Föllmi-Heusi, 2013) by matching a reporter with a peer subject and manipulate the externality. Specifically, the reporter privately rolls a die and then issues a report on the outcome, which determines the earnings of both the reporter and the audience. Another design arm compares treatments with and without the experimenter observing the die-rolls. In the existing literature on the cheating game, the experimenter is typically assumed to serve as a relevant audience, which contrasts with the perceived role of the experimenter in most other laboratory experiments. We aim to explore whether the observability of die-rolls by the experimenter affects the decision-maker’s behavior when a regular audience is present.
External Link(s)

Registration Citation

Chen, Siyu and Martin Dufwenberg. 2024. "Cheating with Externalities and a Regular Audience." AEA RCT Registry. April 16.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
This paper aims to explore whether externalities and experimenter observability influence individuals' decisions regarding their reporting behavior.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The primary objective of this experiment is to investigate whether externalities influence individuals' self-reporting behaviors, with a secondary focus on assessing the impact of experimenter observability on these behaviors. We adapt the die-rolling game originally developed by Fischbacher & Föllmi-Heusi (2013) by incorporating a regular audience into the setup. We employ a 3 × 2 between-subjects design, varying the type of externality imposed on the audience by the reporter (negative, zero, or positive) and the visibility of the initial draw to the experimenter (non-observed vs. observed).

Experimental Design Details
Not available
Randomization Method
Approximately 216 undergraduate and graduate students from the University of Arizona will be randomly assigned to six treatments, irrespective of gender, ethnicity, or any demographic characteristics. Each treatment will include three sessions, with 12 participants per session. The randomization of participants will be handled by the online recruitment system at the Economic Science Laboratory (ESL) of the University of Arizona.
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
216 students
Sample size: planned number of observations
6 treatments*36 participants/treatment = 216 participants
Sample size (or number of clusters) by treatment arms
36 participants in treatment Negative Externality -- Non Observed, 36 participants in treatment Zero Externality -- Non Observed, 36 participants in treatment Positive Externality -- Non Observed, 36 participants in treatment Negative Externality -- Observed, 36 participants in treatment Zero Externality -- Observed, 36 participants in treatment Positive Externality -- Observed
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
University of Arizona IRB
IRB Approval Date
IRB Approval Number