Public good with a third party

Last registered on July 26, 2021

Pre-Trial

Trial Information

General Information

Title
Public good with a third party
RCT ID
AEARCTR-0007996
Initial registration date
July 22, 2021
Last updated
July 26, 2021, 4:20 PM EDT

Locations

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Primary Investigator

Affiliation
University of Otago

Other Primary Investigator(s)

PI Affiliation
University of Massachusetts Amherst
PI Affiliation
University of Otago
PI Affiliation
Vrije Universiteit Amsterdam

Additional Trial Information

Status
In development
Start date
2021-07-26
End date
2022-04-25
Secondary IDs
Abstract
There has been extensive work in economics studying public good provision and charitable giving. A large body of work uses the voluntary contributions mechanism (VCM) game, in which small groups of players invest in a public good, the benefits of which are returned to the group members. Another large body of work uses the dictator game, in which players divide their budgets between themselves and a recipient, where the recipient may be another player or a charitable cause. These settings have different features – both from the view of canonical neoclassical theory as well as more modern behavioural economic theory – leading to different predictions for individual behaviour. Hence, fundamental questions arise about the generalizability of existing findings: How well do insights from public goods games extend to dictator games, and vice versa? And, how well do findings from experimental VCM and experimental dictator games translate into real-world charitable giving and public good provision?

In this study we construct and analyse a supergame that subsumes the VCM and charitable dictator games as special cases. The supergame structure allows us to maintain comparability between disparate settings, thus allowing for a clean examination of how prosocial behaviour differs across informative subcases. Specifically, we will vary the extent to which subjects face a dictator game, a public good game, or a mix of both, and we will test for differences in average contribution behaviour across treatments. Delving deeper, we will also examine the role of participant characteristics, including charitable giving type, gender, numeracy, etc. For each of these characteristics, we will examine whether different subtypes are more or less sensitive to treatment variations.
External Link(s)

Registration Citation

Citation
Chan, Nathan et al. 2021. "Public good with a third party." AEA RCT Registry. July 26. https://doi.org/10.1257/rct.7996-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2021-07-26
Intervention End Date
2021-10-26

Primary Outcomes

Primary Outcomes (end points)
Understand the crucial differences between public good giving (cooperation) and dictator game giving (generosity).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Increase understanding why matching programmes are more successful in raising charitable funding than rebate programmes.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment will be conducted online using oTree and participants will be recruited using Prolific.

Participants are operating within groups of size three in which they have to decide how much to contribute to a public good. They make this decision in five different situations. The overall efficiency of contributions (i.e., the total benefits generated by each contribution) is the same in all five situations. The situations differ in the share of the benefits of the public good that goes back to the three group members; the remaining share is to be donated to a charity organization (Make-a-Wish). After decisions have been made, for each group the three members are paid out according to one randomly chosen decision situation.

Before being paid out, however, participants are given three more tasks. First, a short survey eliciting their numeracy, in particular, testing their understanding of ratios, probabilities and fractions. Second, a task where we elicit their giving type (e.g., warm-glow or altruistic). Third, few questions retrieving their opinion on classifying giving behaviour to charity in the presence of “rebates” and “matches”. Both instruments are often in place to encourage charitable giving, and are equivalent, but may be understood differently.

The current idea is, for the main task, to have all participants making all five decisions; that is, the “share” being a within-subjects variation. Our plan is to collect data in two waves. After the first wave, we will briefly investigate whether the within-subjects nature produces obscure behaviour. If not, we will continue collecting the remaining observations in a within-subjects format. Otherwise, we will consider switching to a between-subjects design. All information below concerns the within-subject design, and will be updated if and when we decide to switch to a between-subjects design.
Experimental Design Details
Not available
Randomization Method
All randomizations are computerized.
Randomization Unit
Order of decision tasks and on individual level; decision relevant for payment on group level; order of “matching” and “rebate” questions on individual level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1
Sample size: planned number of observations
150
Sample size (or number of clusters) by treatment arms
150
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Vrije University School of Business and Economics Research Ethics Review Board
IRB Approval Date
2021-07-22
IRB Approval Number
SBE7/21/2021kwk350
IRB Name
University of Otago Human Ethics Committee
IRB Approval Date
2021-07-21
IRB Approval Number
D21/237
Analysis Plan

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