Replication: Growth and inequality in public good provision (No-Punish-10) by Gächter et al. (2017)

Last registered on July 27, 2021

Pre-Trial

Trial Information

General Information

Title
Replication: Growth and inequality in public good provision (No-Punish-10) by Gächter et al. (2017)
RCT ID
AEARCTR-0007902
Initial registration date
June 30, 2021
Last updated
July 27, 2021, 7:10 AM EDT

Locations

Region

Primary Investigator

Affiliation
Helmut Schmidt University

Other Primary Investigator(s)

PI Affiliation
Helmut Schmidt University
PI Affiliation
Helmut Schmidt University

Additional Trial Information

Status
Completed
Start date
2021-07-01
End date
2021-07-25
Secondary IDs
Abstract
We replicate Gächter et al.'s (2017) 10-period public good game without punishment and with dynamic interdependencies, where each agent’s wealth at the end of period t serves as her endowment in t+1. In contrast to the original experiment, we use a non-student sample in a remote online experiment. While experiment with repeated group interactions have been conducted with click workers on platforms such as Amazon's MTurk before, we investigate how well this experimental design can be applied to the general German population. For this reason, we will draw comparisons to Gächter et al.'s (2017) original data and consider methodological challenges such as dropouts. If dropouts do not turn out to be a concern, we will rund additional treatments that incorporate risk or uncertainty.

Gächter, S., Mengel, F., Tsakas, E., & Vostroknutov, A. (2017). Growth and inequality in public good provision. Journal of Public Economics, 150, 1-13. https://doi.org/10.1016/j.jpubeco.2017.03.002

Registration Citation

Citation
Berlemann, Michael, Hauke Roggenkamp and Stefan Traub. 2021. "Replication: Growth and inequality in public good provision (No-Punish-10) by Gächter et al. (2017)." AEA RCT Registry. July 27. https://doi.org/10.1257/rct.7902-2.0
Experimental Details

Interventions

Intervention(s)
As we replicate one of Gächter et al.'s (2017) treatments, we do not have an intervention. As we apply a different technology stack and use a different subject pool, we will model these differences as a treatment variable.
Intervention Start Date
2021-07-01
Intervention End Date
2021-07-23

Primary Outcomes

Primary Outcomes (end points)
Growth (measured as a group's income at the end of the last period), Inequality (measured as a group's Gini coefficient at the end of the last period), Dropouts
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Average Contributions (measured in absolute terms as well as the average share of endowments contributed, both over time), Each individual's first round contributions
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Same as in Gächter et al.'s (2017) No-Punish 10-period treatment.
Experimental Design Details
Randomization Method
None. We collect data from one treatment group and compare it to existing data.
Randomization Unit
None. We collect data from one treatment group and compare it to existing data.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
With a group size of 4, we conduct a pilot with approximately 120 participants, which equals 30 independent observations at the end of the last period.
Sample size: planned number of observations
Approximately 120 participants.
Sample size (or number of clusters) by treatment arms
As we collect data for the treatment group only, the answer is the same as above: With a group size of 4, we conduct a pilot with approximately 120 participants, which equals 30 independent observations at the end of the last period.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

Documents

Document Name
Read GMTV Data
Document Type
other
Document Description
Please read the documentation in this GitHub repository: https://github.com/Howquez/coopUncertainty/tree/July21Replication
File
Read GMTV Data

MD5: ac7ceea18ae1e78d578f11edbfbfd8e9

SHA1: acab0d23a680bcc12b48f2bef42e320dc331aaa0

Uploaded At: June 30, 2021

Document Name
Read Replicated Data
Document Type
other
Document Description
Please read the documentation in this GitHub repository: https://github.com/Howquez/coopUncertainty/tree/July21Replication
File
Read Replicated Data

MD5: 42f38794da927f877763413ec6da992a

SHA1: e192d08abb92a7afb49426705e9c4db8e744cffb

Uploaded At: June 30, 2021

Document Name
Analyses
Document Type
other
Document Description
Please read the documentation in this GitHub repository: https://github.com/Howquez/coopUncertainty/tree/July21Replication
File
Analyses

MD5: a5d2c4fa6b16c2a865adcd02bbff642b

SHA1: 686c093ef3d6967a614277f83d24f133a6c6fcbb

Uploaded At: June 30, 2021

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

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
July 25, 2021, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
July 23, 2021, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
29 (4-player-)groups
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
116 participants
Final Sample Size (or Number of Clusters) by Treatment Arms
As this was a replication of one specific treatment, there only is one treatment (that contains 29 groups).
Data Publication

Data Publication

Is public data available?
No

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Program Files

Program Files
Yes
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials