Minimum Contribution Mechanism

Last registered on March 27, 2023
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Pre-Trial

Trial Information

General Information

Title
Minimum Contribution Mechanism
RCT ID
AEARCTR-0008612
Initial registration date
November 23, 2021

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
November 29, 2021, 8:19 AM EST

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

Last updated
March 27, 2023, 4:22 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

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Primary Investigator

Name
Nathaniel Neligh
Affiliation
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Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2021-11-29
End date
2023-12-31
Keywords
Behavior
Additional Keywords
Public Goods
JEL code(s)
D90, H41
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study examines a public goods mechanism
External Link(s)

Registration Citation

Citation
Neligh, Nathaniel. 2023. "Minimum Contribution Mechanism." AEA RCT Registry. March 27. https://doi.org/10.1257/rct.8612-3.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Participants will engage in several public goods games with different mechanisms
Intervention Start Date
2021-11-29
Intervention End Date
2023-12-31

Primary Outcomes

Primary Outcomes (end points)
Contributions under each mechanism
Mechanism Efficiency
Primary Outcomes (explanation)
Efficiency taken in the strong sense (maximizing sum of payoffs)

Secondary Outcomes

Secondary Outcomes (end points)
Beliefs about mechanism efficiency
Secondary Outcomes (explanation)
Which mechanism do people expect to have higher payoffs in?

Experimental Design

Experimental Design
Participants will engage in several public goods games with different mechanisms
Experimental Design Details
Not available
Randomization Method
By computer online or in person
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
300 people
Sample size: planned number of observations
300 people
Sample size (or number of clusters) by treatment arms
100 people per position
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
Univeristy of Tennessee Knoxville Institutional Review Board
IRB Approval Date
2021-06-10
IRB Approval Number
UTK IRB-21-06573-XM
Analysis Plan