Reporting Misconduct

Last registered on June 15, 2026
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Pre-Trial

Trial Information

General Information

Title
Reporting Misconduct
RCT ID
AEARCTR-0018796
Initial registration date
June 04, 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
June 15, 2026, 9:53 AM 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
Ketki Sheth
Affiliation
UC Merced
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Other Primary Investigator(s)

PI Name
Quy Lam
PI Affiliation
UC Merced
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Additional Trial Information

Status
In development
Start date
2026-06-05
End date
2027-07-15
Keywords
Behavior, Crime, Violence, & Conflict
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Punishment is commonly used by lawmakers to deter criminal behavior. Punishments do not just punish offenders, but they also deter other people from committing the same crimes. In monitoring and investigating crimes, the inside knowledge or tips provided by private citizens who have knowledge of the crime offer valuable information to the authority. However, it is unclear about the relationship between the severity of punishment and likelihood of reporting crimes. In this study, we examine whether the severity of sanctions will affect people’s decision to report crimes, and how this decision is affected by the relative magnitude of harm and good.
External Link(s)

Registration Citation

Citation
Lam , Quy and Ketki Sheth. 2026. "Reporting Misconduct." AEA RCT Registry. June 15. https://doi.org/10.1257/rct.18796-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-06-06
Intervention End Date
2026-06-30

Primary Outcomes

Primary Outcomes (end points)
Reporting of subjects who break the law
Deciding to break the law given information on reporting rates of subjects
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We employ two experimental game in which subjects are assigned to be in groups. In the main stage of the game, one subject is randomly assigned to be a person that has the opportunity to "break the law". Breaking the law benefits the law-breaker, but harms subjects in the experiment. We randomly assign the severity of the penalty for breaking the law and whether the relative benefit is greater than the harm inflicted. We conclude the experiment with a series of survey questions.

Experimental Design Details
Not available
Randomization Method
Randomization done using Lioness platform
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No clusters
Sample size: planned number of observations
For In-Group Experiment: 200 potential law-breakers; 1,250 potential reporters For Bystander Experiment: 200 potential law-breakers; 1,000 potential reporters
Sample size (or number of clusters) by treatment arms
Aggregating across both experiments:
HighGain, 5% penalty: 60 potential law-breakers; 338 potential reporters
High Gain, 40% penalty: 40 potential law-breakers; 225 potential reporters
High Gain, 70% penalty: 40 potential law-breakers; 225 potential reporters
High Gain, 100%penalty: 60 potential law-breakers; 338 potential reporters
Low Gain, 5% penalty: 60 potential law-breakers; 338 potential reporters
Low Gain, 40% penalty: 40 potential law-breakers; 225 potential reporters
Low Gain, 70% penalty: 40 potential law-breakers; 225 potential reporters
Low Gain, 100%penalty: 60 potential law-breakers; 338 potential reporters
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Tennessee Knoxville
IRB Approval Date
2026-05-07
IRB Approval Number
STUDY00000320
Analysis Plan

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