Is there a link between wealth inequality and deception? – An experimental analysis of different subject pools
Last registered on February 07, 2020

Pre-Trial

Trial Information
General Information
Title
Is there a link between wealth inequality and deception? – An experimental analysis of different subject pools
RCT ID
AEARCTR-0005399
Initial registration date
February 05, 2020
Last updated
February 07, 2020 1:53 PM EST
Location(s)
Region
Primary Investigator
Affiliation
Martin Luther University Halle-Wittenberg
Other Primary Investigator(s)
Additional Trial Information
Status
In development
Start date
2020-02-16
End date
2020-03-16
Secondary IDs
German Research Foundation (DFG, German Research Foundation) –388911356.
Abstract
This paper investigates experimentally the relationship between inequality in initial wealth and deception. Our basic design is adopted from Gneezy (2005): two players interact in a deception game. It is common knowledge that player 1 has private information about the payoffs for both players of two alternative actions. Player 1 sends a message to player 2, indicating which alternative putatively will end up in a higher payoff for player 2. The message, which can either be true or false, does not affect the payoffs of the players. Player 2 has no information about the payoffs. However, player 2 selects one of the two alternatives A or B, which is payoff-relevant for both players. We extend Gneezy (2005) by two elements. First, we systematically vary the initial wealth of the players 1 and 2 (common knowledge to both of them). Second, we do not limit ourselves to the standard population of university students but also recruit chess players that are not enrolled in any degree program. Doing so, we want to find out if our results remain robust over a non-standard subject population which is known to be experienced to some extent in strategic interactions.
External Link(s)
Registration Citation
Citation
Gruener, Sven. 2020. "Is there a link between wealth inequality and deception? – An experimental analysis of different subject pools ." AEA RCT Registry. February 07. https://doi.org/10.1257/rct.5399-1.0.
Experimental Details
Interventions
Intervention(s)
We extend the basic idea of Gneezy’s (2005) design to systematic variations in wealth. Altogether, we examine 3 scenarios (1 reference scenario and 2 treatment scenarios; Table 2). While there is no variation of the initial wealth in the reference scenario (both players have €0 initial wealth), treatment 1 provides player 1 with a surplus in initial wealth and treatment 2 provides player 2 a surplus. Player 1 and player 2 know that the initial wealth in the respective treatments is common knowledge to both players.
Intervention Start Date
2020-02-16
Intervention End Date
2020-03-16
Primary Outcomes
Primary Outcomes (end points)
Primary outcome variables: Depending on the role of the experimental subject (either player 1 or player 2), the key variable of interest is either “decision player 1” (honest/dishonest message) or “decision player 2” (follow/not follow message).
We are mostly interested in the behavioral influence of the treatments on these primary outcome variables.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The basic structure of the experiment is adopted from Gneezy’s (2005) 2-person deception game. Two players play against each other in a one-shot experiment. We extend the basic idea of Gneezy’s (2005) design to systematic variations in wealth as well as a comparison of students and chess players.
Experimental Design Details
--> Complete Design is attached as a separate file.
Randomization Method
Subjects are equally likely to be part of one of the treatments. Randomization is done by the software which we use.
Randomization Unit
Subjects are randomly assigned to one treatment. Thus, individual is our randomization unit.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
We have 6 treatments (chess players) and 6 treatments (students); we do not cluster them.
Sample size: planned number of observations
We observe the decisions of N=360 subjects in a one-shot experiment.
Sample size (or number of clusters) by treatment arms
 We plan to recruit N=180 students and N=180 non-student chess-players. The total number of subjects per scenario and population (N=30) results from budget constraints.
 Uncertainty about the success in recruiting non-students: we are ex-ante not sure if a sufficient number of non-student chess players could be recruited or if the spectrum of non-students has to be extended to subjects that are not playing chess in a club.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
German Association for Experimental Economic Research e.V.
IRB Approval Date
2020-01-23
IRB Approval Number
sZXeRf5E
Analysis Plan

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Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers