The relative and absolute gain of dishonesty – An online study

Last registered on April 13, 2021


Trial Information

General Information

The relative and absolute gain of dishonesty – An online study
Initial registration date
September 22, 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
September 22, 2020, 7:45 AM EDT

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

Last updated
April 13, 2021, 6:14 AM EDT

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



Primary Investigator


Other Primary Investigator(s)

PI Affiliation

Additional Trial Information

Start date
End date
Secondary IDs
The standard economic model of crime predicts that people lie more when material incentives are higher. Yet, most experimental studies find no effect of monetary incentives on dishonesty. In most existing studies, changes of payoffs are implemented by multiplying honest and dishonest payoffs by a certain factor. An explanation for the lacking effect could be that it becomes not only more profitable to be dishonest but also to be honest. The goal of our research is to examine the importance of the absolute and relative difference of payoffs for dishonesty in an online study. Subjects participate in a wheel of fortune game in which they can increase their payoff by lying. Our treatments vary the absolute and the relative difference in payoffs.
External Link(s)

Registration Citation

Le Maux, Benoit and Sarah Necker. 2021. "The relative and absolute gain of dishonesty – An online study." AEA RCT Registry. April 13.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Correct guesses in the wheel game; we will examine the fraction of correct guesses in a period as well as the aggregate fraction of correct guesses across all ten periods
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The goal of our study is to examine the importance of the absolute and relative difference of payoffs for dishonesty. In our study, individuals participate in ten rounds of a wheel of fortune game. The wheel of fortune shows the first 6 letters of the alphabet, from A to F. The task is to guess which letter the wheel of fortune will show and report if the guess was correct. If individuals report “Yes”, they receive a high payoff while those that report “No” receive a low payoff. Thus, individuals have a financial incentive to always report that they guessed correctly. As is common in the literature, dishonesty is not observable but can be inferred from deviations from chance.

Experimental Design Details
The study will be implemented online using Amazon Mturk. The task will be advertised in a Human Intelligence Task (HIT). We will only accept workers that have an approval rate of 95% and completed at least 500 HITs. Interested Mturkers start the survey by accepting the HIT. They will receive a participation fee of $1 (conditional on answering all control questions correctly and completing the study) and are able to win a bonus payment depending on the treatment, their decisions, and chance.
The procedure of the experiment is as follows. Before the experiment starts, subjects will have to pass a bot control (captcha) and sign an informed consent form. They will then participate in two games. The first game is a memory game which has the purpose to focus people’s attention on memorizing letters. The second game is the cheating game described above. Subjects have to answer control questions to assure that they understood the payment scheme. After the two games, they are asked to fill in a follow-up survey, inquiring their risk aversion, shame and guilt proneness, perception of the game, and socio-demographic information (e.g., age, gender, education, country of origin). After completing all steps of the experiment, they receive a completion code which allows them to collect their payment from Amazon Mturk.
Randomization Method
Survey software (Qualtrics)
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
no clustering
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
German Association for Experimental Economic Research e.V.
IRB Approval Date
IRB Approval Number


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Intervention Completion Date
September 30, 2020, 12:00 +00:00
Data Collection Complete
Data Collection Completion Date
September 30, 2020, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
Final Sample Size (or Number of Clusters) by Treatment Arms
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials