Luck or Labor? Assessing Generosity Given Knowledge of Peer's Effort

Last registered on January 23, 2018
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Pre-Trial

Trial Information

General Information

Title
Luck or Labor? Assessing Generosity Given Knowledge of Peer's Effort
RCT ID
AEARCTR-0002613
Initial registration date
January 22, 2018

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
January 23, 2018, 12:14 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country
United States of America
Region
Northeast

Primary Investigator

Name
Paul Lapinski
Affiliation
Skidmore College
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Other Primary Investigator(s)

PI Name
Sandra Goff
PI Affiliation
Skidmore College
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PI Name
Edson Acosta
PI Affiliation
Skidmore College
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PI Name
Michael Barry
PI Affiliation
Skidmore College
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PI Name
Benjamin Rudman
PI Affiliation
Skidmore College
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PI Name
Mercy Paine
PI Affiliation
Skidmore College
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Additional Trial Information

Status
Completed
Start date
2017-12-07
End date
2017-12-16
Keywords
Labor
Additional Keywords
Generosity, Peer information, Income, Inequality
JEL code(s)
J22, J24
Secondary IDs
Abstract
The U.S is overall a rich country, yet since high-income individuals hold such a great percentage of the wealth, there is still a great deal of poverty and unemployment. Because of this inequality, recent literature in economics has explored how generous individuals are, as this information could be important to understanding how to better distribute the country’s wealth. We propose an experiment that manipulates people's perceptions of how their peers have generated income - either by fortuitous circumstances or from effortful work - in order to observe the impact that this socioeconomic judgement has on donation behavior. We implement a Qualtrics survey on Amazon Mechanical Turk in which participants engage in either a simple luck-based or labor-based task and then are given the opportunity to donate some of their earnings to individuals in a so-described "lower income bracket." We aim to establish how generous individuals are based on their knowledge of others' wages and then see how this decision changes when information about the task that they performed is made known.
External Link(s)

Registration Citation

Citation
Acosta, Edson et al. 2018. "Luck or Labor? Assessing Generosity Given Knowledge of Peer's Effort ." AEA RCT Registry. January 23. https://doi.org/10.1257/rct.2613-1.0
Former Citation
Acosta, Edson et al. 2018. "Luck or Labor? Assessing Generosity Given Knowledge of Peer's Effort ." AEA RCT Registry. January 23. https://www.socialscienceregistry.org/trials/2613/history/25205
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
We implement a Qualtrics survey on Amazon Mechanical Turk in which participants complete a luck-based or work-based task. The performance in this task earns each worker a certain monetary return. After completing the work, participants are given the opportunity to donate some of their money to other participants.
Intervention Start Date
2017-12-07
Intervention End Date
2017-12-16

Primary Outcomes

Primary Outcomes (end points)
Our key outcome variables are the donation amounts as well as the self-reported reasons subjects give for their donation behavior.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We implement a Qualtrics survey on Amazon Mechanical Turk in which participants complete a luck-based or work-based task. The performance in this task earns each worker a certain monetary return. After completing the work, participants are given the opportunity to donate some of their money to other participants.
Experimental Design Details
Stage I
Participants will first be randomly placed in one of two groups: the luck-based group, where the task will consist of guessing some random number, and the work-based group, where subjects will complete a real effort task (moving sliders to the center of a line on a computer screen). Participants will not be aware which group they are placed in, nor told that there is another type of task that differs from the one that they are completing. Participants will be paid a fixed rate per task they complete: participants in the luck-based task will receive 6 cents per correctly guessed number, and those in the skill-based task will receive 6 cents per correctly placed set of sliders. At this point in the in experiment, subjects are told their wage per correct answer but are unaware that there is a disparity in task between subjects. Each participant will be given 10 minutes to complete as many tasks as possible.
Participants will be then randomly placed in either the High-Earnings group or Low-Earnings group. Participants in the High-Earnings group will be told that their payoff from the task placed them in the top-50% of earnings acquired and, because of this, they will receive a bonus of $5. They are instructed to press continue to learn more. They will then be directed to Stage II. Participants in the Low-Earnings group will not be told any of this, and will instead be directed to a screen telling them they have finished their task and will be notified once the experiment has been completed in full.

Stage II
The second stage takes place immediately following the first. For the second stage of the experiment, stage-one participants who were assigned to High-Earnings group will be asked to participate in another experiment that should take less than 5 minutes and gives them the chance to grow their earnings.
High-Earnings participants from the first stage will play a dictator game. They will be given a new pot of money, 5 dollars, to do with as they please. They have the option of giving none, some, or all of this $5 to Low-Earnings earners. No donation that they give will be directed to a specific member of the Low-Earnings group. Instead, donations will be pooled together and redistributed to Low-Earnings equally.

Randomization Method
Randomization is done through MTurk. Workers come from a wide range of demographics.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
120 individuals
Sample size: planned number of observations
120 individuals
Sample size (or number of clusters) by treatment arms
120 individuals
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
Skidmore College Institutional Review Board
IRB Approval Date
2017-11-30
IRB Approval Number
1711-664
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
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