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Self-serving norm acquisition
Last registered on December 14, 2020

Pre-Trial

Trial Information
General Information
Title
Self-serving norm acquisition
RCT ID
AEARCTR-0006865
Initial registration date
December 13, 2020
Last updated
December 14, 2020 10:30 AM EST
Location(s)
Region
Primary Investigator
Affiliation
University of Cologne
Other Primary Investigator(s)
PI Affiliation
WWU M√ľnster
Additional Trial Information
Status
In development
Start date
2020-12-14
End date
2020-12-23
Secondary IDs
Abstract
Recently spectator designs have become a popular tool in a variety of different fields of experimental economics. Examples include repugnance, ethics, cooperation, privacy and paternalism. In such experiments third parties serve as observers, judges, punishers or choice architects. In this project we are investigating how roles affect behavior. Do first- and third-parties react differently to norm information? Do first- and third-parties differ in the type of norm (i.e. injunctive or descriptive) they choose to acquire and follow?
External Link(s)
Registration Citation
Citation
Breuer, Kevin and Christoph Feldhaus. 2020. "Self-serving norm acquisition." AEA RCT Registry. December 14. https://doi.org/10.1257/rct.6865-1.0.
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2020-12-14
Intervention End Date
2020-12-23
Primary Outcomes
Primary Outcomes (end points)
Norm choice
Primary Outcomes (explanation)
Interaction of norm choice with demographics and risk, time and social preferences.
Secondary Outcomes
Secondary Outcomes (end points)
taking decision, choice restriction
Secondary Outcomes (explanation)
Interaction of taking decision and choice restrictionwith demographics and risk, time and social preferences.
Experimental Design
Experimental Design
Dictator Game in take-frame and beforehand provision of norm information. Decision-Maker (DM) distributes money between himself and unknown charity. Choice-Architect (CA) might costly restrict choice set of DM.

2 x 2 Treatment Design (dimensions: (DM,CA),(High,Low))
"DM" treatments: DM taking decision is implemented with "low" (1%) or "high" (99%) probability. No choice set restriction by CA (only observes decision of DM).
"CA" treatments: DM taking decision is implemented with certainty. CA choice set restriction is implemented with "low" (1%) or "high" (99%) probability.

Experimental Design Details
Randomization Method
Lottery by a computer
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
not clustered
Sample size: planned number of observations
960 observations
Sample size (or number of clusters) by treatment arms
120 subjects for each role and treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Research Ethics Review Faculty of Management, Economics, and Social Sciences University of Cologne
IRB Approval Date
2019-10-10
IRB Approval Number
19025KB
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