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Costly implementation of third party preferences with non-paternalistic motivation
Last registered on June 23, 2017

Pre-Trial

Trial Information
General Information
Title
Costly implementation of third party preferences with non-paternalistic motivation
RCT ID
AEARCTR-0002240
Initial registration date
May 24, 2017
Last updated
June 23, 2017 1:04 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
Department of Landscape Ecology, Norwegian Institute for Nature Research
Other Primary Investigator(s)
PI Affiliation
The Choice Lab, Department of Economics, Norwegian School of Economics
Additional Trial Information
Status
In development
Start date
2017-06-24
End date
2017-06-27
Secondary IDs
Abstract
In an experimental setting, we plan to test whether spectators have a willingness to pay to have an income distribution adhering to their fairness views implemented upon a pair of workers. Before spectators decide whether to implement their fairness views, we elicit participants' perceived prevalence of their own fairness views to see whether this is correlated with their willingness to implement. In one treatment, spectators are informed about the empirical prevalence of their fairness views among the workers, before their willingness to pay is elicited. We argue that existence of a statistically significant treatment effect would be indicative of non-paternalistic motivation of implementing fairness views.
External Link(s)
Registration Citation
Citation
Chen, Xianwen and Øivind Schøyen. 2017. "Costly implementation of third party preferences with non-paternalistic motivation." AEA RCT Registry. June 23. https://doi.org/10.1257/rct.2240-7.0.
Former Citation
Chen, Xianwen, Xianwen Chen and Øivind Schøyen. 2017. "Costly implementation of third party preferences with non-paternalistic motivation." AEA RCT Registry. June 23. http://www.socialscienceregistry.org/trials/2240/history/18907.
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2017-06-26
Intervention End Date
2017-06-27
Primary Outcomes
Primary Outcomes (end points)
workers' individual performances, redistribution preference (yes or no to redistribution), projected prevalence of one's own redistribution preference, empirical (actual) prevalence of one's own redistribution preference, decision of whether pay to implement one's own redistribution preference
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
In an experimental setting, we plan to test whether spectators have a willingness to pay to have an income distribution adhering to their fairness views implemented upon a pair of worker. Before spectators decide whether to implement their fairness views, we elicit participants perceived prevalence of their own fairness views to see whether this is correlated with their willingness to implement. In one treatment, spectators are informed about the empirical prevalence of their fairness views among the workers, before their willingness to pay is elicited. We argue that existence of a statistically significant treatment effect would be indicative of non-paternalistic motivation of implementing fairness views.
Experimental Design Details
In an experimental setting, we plan to test whether spectators have a willingness to pay to have an income distribution adhering to their fairness views implemented upon a pair of worker. Before spectators decide whether to implement their fairness views, we elicit participants perceived prevalence of their own fairness views to see whether this is correlated with their willingness to implement. In one treatment, spectators are informed about the empirical prevalence of their fairness views among the workers, before their willingness to pay is elicited. We argue that existence of a statistically significant treatment effect would be indicative of non-paternalistic motivation of implementing fairness views.
Randomization Method
randomization done by a computer program
Randomization Unit
individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
0 culster. We use turks from Amazon MTurk.
Sample size: planned number of observations
1008 participants
Sample size (or number of clusters) by treatment arms
336 workers, 336 spectators (control), 336 spectators (treatment)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan
Analysis Plan Documents
Analysis Plan - Chen and Schøyen (2017)

MD5: 7708c277b006fb586e0dac840f4543dc

SHA1: e6991e082324c86b437418ba24ea07cb86c4c966

Uploaded At: June 23, 2017

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