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The relative and absolute gain of dishonesty – An online study
Last registered on September 22, 2020


Trial Information
General Information
The relative and absolute gain of dishonesty – An online study
Initial registration date
September 22, 2020
Last updated
September 22, 2020 7:45 AM EDT
Primary Investigator
Other Primary Investigator(s)
PI Affiliation
Additional Trial Information
On going
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. 2020. "The relative and absolute gain of dishonesty – An online study." AEA RCT Registry. September 22. https://doi.org/10.1257/rct.6479-1.0.
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)
IRB Name
German Association for Experimental Economic Research e.V.
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)