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Motivated Motive Selection
Last registered on November 30, 2018

Pre-Trial

Trial Information
General Information
Title
Motivated Motive Selection
RCT ID
AEARCTR-0003617
Initial registration date
November 30, 2018
Last updated
November 30, 2018 11:41 AM EST
Location(s)
Region
Primary Investigator
Affiliation
Lund University
Other Primary Investigator(s)
PI Affiliation
WZB Berlin
PI Affiliation
WZB Berlin
Additional Trial Information
Status
In development
Start date
2018-12-03
End date
2019-12-02
Secondary IDs
Abstract
Lying costs and social preferences are perhaps the two most well-documented deviations from selfish maximization behavior in the economic literature. We hypothesize that in situations where both these motives are present and are in conflict, individuals may in a self-serving way put more weight on the motive that helps them maximize their earnings. We test this hypothesis using a laboratory experiment that allows us to document whether such motivated motive selection is present.
External Link(s)
Registration Citation
Citation
Barrron, Kai, Robert Stüber and Roel van Veldhuizen. 2018. "Motivated Motive Selection." AEA RCT Registry. November 30. https://doi.org/10.1257/rct.3617-1.0.
Former Citation
Barrron, Kai et al. 2018. "Motivated Motive Selection." AEA RCT Registry. November 30. http://www.socialscienceregistry.org/trials/3617/history/38147.
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2018-12-03
Intervention End Date
2018-12-14
Primary Outcomes
Primary Outcomes (end points)
Dummy variable for whether participants selected the equality motive in part 2.
Dummy variable for whether participants selected the truth-telling motive in part 2.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Difference in the appropriateness score of the (1) truth-telling and (2) equality motive in part 3.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We use a laboratory experiment that shares a common basic structure with both the classic dictator game and the Fischbacher and Föllmi-Heusi (2013) lying game. In part 1 of the experiment, participants take on the role of the dictator and report a number that determines their payment and the payment of the recipient. In part 2 of the experiment, participants take on the role of a third-party dictator. In part 3, we elicit the social appropriateness of different choices in part 2 in an incentive-compatible way.
Experimental Design Details
The experiment proceeds in three parts. For Part 1 and Part 2, participants are randomly assigned to one of two groups – Active and Passive players. There are 4 Passive players per session, and up to 20 Active players, depending on the number of participants who show up for a given session. Part 1 involves a first party lying/dictator game in which Active participants are matched into pairs of two. Each member of the pair first draws a random number by clicking on one of eleven boxes on her screen (as in Gneezy, Kajackaite and Sobel, 2018). This therefore involves a random draw from a uniformly distributed variable with support {0,1,2,3,4,5,6,7,8,9,10}. After the random draw, participants are asked to report the number they saw. They can do so in one of four ways: (1) Tell the truth and report: “The number I saw was [number seen].” (2) Equalize payments and report: “The number I saw was 5.” (3) Maximize your payment and report: “The number I saw was 10.” (4) Maximize the other participant’s payment and report: “The number I saw was 0.” As in the lying game (Fischbacher and Föllmi-Heusi, 2013), the subject will be paid the value of the number she reports, € r. As in the dictator game, any remaining money € 10-r will be sent to her matched partner. One choice out of every pair (revealed at the end of the session) is randomly determined to be payoff relevant. Participants know that if their choice is payoff relevant, their report will be communicated to the recipient. Participants also know that after making their report they will be asked to provide a short written explanation for why they chose the motive. Passive players make no decisions in part 1, though they are able to read the Active players’ instructions. Part 2 involves a third party lying/dictator game in which Active participants play a game that is similar to Part 1. The key difference is that instead of choosing a payoff allocation between themselves and another participant, they are now choosing a payoff allocation between two Passive players. Otherwise, the game is the same – participants are asked to click on one of the eleven boxes to reveal a random number, and report the number in one of four ways: (1) Tell the truth and report: “The number I saw was [number seen]. (2) Equalize payments and report: “The number I saw was 5.” (3) Maximize passive player A’s payment and report: “The number I saw was 10.” (4) Maximize passive player B’s payment and report: “The number I saw was 0.” At the end of the experiment, two of the Active players’ reports are randomly chosen to be implemented, one for each pair of Passive players. Part 3 involves a Krupka and Weber (2013) norm elicitation task in which participants are asked to evaluate how “socially appropriate” each of the four possible reports in Part 2 are. Specifically, we ask participants to consider the four possible reports made by a hypothetical participant with a random draw of 8. At the end of the experiment the computer then randomly draws one of the four evaluations to be payoff relevant. Participants are then paid € 2 if their choice is the modal choice within the session (any ties are broken randomly). References: Fischbacher, Urs and Franziska Föllmi-Heusi. 2013. ”Lies in Disguise—An Experimental Study on Cheating.” Journal of the European Economic Association, 11(3): 525-547. Gneezy, Uri, Agne Kajackaite, and Joel Sobel. 2018. "Lying Aversion and the Size of the Lie." American Economic Review, 108(2): 419-53. Krupka, Erin L., and Roberto A. Weber. 2013. "Identifying social norms using coordination games: Why does dictator game sharing vary?." Journal of the European Economic Association, 11(3): 495-524.
Randomization Method
Random number drawn by a computer
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
140 individuals (approximately 116 Active and 24 Passive players)
Sample size: planned number of observations
140 individuals (approximately 116 Active and 24 Passive players)
Sample size (or number of clusters) by treatment arms
50 Individuals (estimated)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
See the attached power calculations for details
Supporting Documents and Materials

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IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number
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, Papers & Other Materials
Relevant Paper(s)
REPORTS & OTHER MATERIALS