Decomposing indirect reciprocity

Last registered on March 30, 2023
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Pre-Trial

Trial Information

General Information

Title
Decomposing indirect reciprocity
RCT ID
AEARCTR-0010972
Initial registration date
March 27, 2023

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
March 30, 2023, 3:39 PM EDT

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

Locations

Country
Hungary
Region
Country
United States of America
Region

Primary Investigator

Name
L. Flóra Drucker
Affiliation
Institute of Economics, Centre for Economic and Regional Studies
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Other Primary Investigator(s)

PI Name
Sara Khayouti
PI Affiliation
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PI Name
Daniel Horn
PI Affiliation
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PI Name
Hubert Janos Kiss
PI Affiliation
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Additional Trial Information

Status
In development
Start date
2023-03-27
End date
2023-06-30
Keywords
Behavior, Lab
Additional Keywords
trust, reciprocity, altruism, inequality aversion
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We use the three-games design of Cox (2004) to identify the mechanisms behind first- and second-mover behavior in indirect reciprocity. We first look at upstream reciprocity, where Player X helps Player Y, and therefore Player Y helps Player Z. We aim to disentangle pure other-regarding preferences from strategic considerations in Player X's behavior, and other-regarding preferences from wanting to reciprocate a kind action in Player Y's behavior.
External Link(s)

Registration Citation

Citation
Drucker, L. Flóra et al. 2023. "Decomposing indirect reciprocity." AEA RCT Registry. March 30. https://doi.org/10.1257/rct.10972-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2023-03-27
Intervention End Date
2023-03-31

Primary Outcomes

Primary Outcomes (end points)
average amount sent and sent back by participants
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In the baseline three-games design of Cox (2004), Treatment A plays the classical trust game where Players X and Y start with the same endowment. Player X sends an amount of money to Player Y from her endowment, the amount gets tripled, and Player Y decides how much to send back to Player X from the tripled amount. In Treatment B, only Player X has a choice: she sends an amount to Player Y from her endowment, which gets tripled, and Player Y keeps this amount. In Treatment C, Player X has no choice: an amount is taken from their endowment and sent to Player Y. The amount then gets tripled, and Player Y decides how much to send back to Player X from the tripled amount.

We extend this design first to upstream reciprocity. In baseline Treatment A, three players start with the same endowment. Player X decides how much to send from her endowment to Player Y, where the sent amount gets tripled. Player Y then decides how much to send to Player Z from her total endowment, where the sent amount gets tripled again. In Treatment B, only Player A has a choice: she sends an amount to Player Y from her endowment, which gets tripled, and Player Y keeps this amount. Player Z also keeps her initial endowment. In Treatment C, only Player Y has a choice. First, an amount of money is taken from Player X's endowment and sent to Player Y. The amount then gets tripled, and Player Y decides how much to send to Player Z, where the sent amount gets tripled again.

The comparison of Treatments A and B shows whether, in the baseline treatment, the choices of Players X have a strategic component, i.e., whether they expect Players Y to send some of their endowment to Players Z. The comparison of Treatments A and C shows whether Players Y behave differently when their total endowment was a result of a kind action from Players X from when Players X did not have a choice.
Experimental Design Details
Randomization Method
by a computer
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
0
Sample size: planned number of observations
450 individuals
Sample size (or number of clusters) by treatment arms
50 groups of three per treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
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?
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