It’s a small world: effects of overlapping neighborhoods in the provision of public goods

Last registered on June 21, 2022

Pre-Trial

Trial Information

General Information

Title
It’s a small world: effects of overlapping neighborhoods in the provision of public goods
RCT ID
AEARCTR-0009451
Initial registration date
May 16, 2022

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
May 16, 2022, 5:27 PM EDT

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

Last updated
June 21, 2022, 6:20 AM EDT

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

Locations

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Primary Investigator

Affiliation
University of Hamburg

Other Primary Investigator(s)

PI Affiliation
University of Hamburg

Additional Trial Information

Status
In development
Start date
2022-05-23
End date
2022-07-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This project studies the voluntary provision of a weakest-link public good in overlapping neighborhoods. Located around a virtual table, each individual’s investment decision affects the provision of the public good of herself and her right- and left-hand neighbors. We hypothesize that the introduction of this spatial element can provide obstacles to the level at which the public good is provided and can create a dynamic to the provision level across space. We compare treatments in which the endowments are homogeneous with those where some subjects receive a large, some a low endowment. For this heterogeneous case, we specifically study how the spatial distribution of different income levels affects the investment decisions. We investigate and compare two different mechanisms through which subjects can invest at neighbors’ locations, a direct in-kind transfer system to any neighbour vs. one where subjects can contribute to a common common that is divided up among low income participants.
External Link(s)

Registration Citation

Citation
Lange, Andreas and Lorenzo Romero-Fernández. 2022. "It’s a small world: effects of overlapping neighborhoods in the provision of public goods." AEA RCT Registry. June 21. https://doi.org/10.1257/rct.9451
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2022-05-23
Intervention End Date
2022-07-31

Primary Outcomes

Primary Outcomes (end points)
We investigate the treatment effects on investment levels and transfer decisions.
Hypothesis 1: The overlapping-neighborhood setting will decrease the average investment levels.
For testing hypothesis 1, we will compare the investment levels in the treatments where there is no overlapping neighborhoods and where there is one with a homogeneous income distribution (treatment 1 vs. treatment 2).
Hypothesis 2.a: For the heterogeneous-income treatments, the spatial distribution of the different types will affect the investment decisions – in the distribution where the high- and low-income type are alternated the investment will be larger than where they are clustered.
Hypothesis 2.b: For the heterogeneous-income treatments, the spatial distribution of the different types will affect the transfer decisions – in the distribution where the high- and low-income type are alternated the transfers will be larger than where they are clustered.
For testing these two hypothesis, we will compare the investment and transfer decisions in the treatments where the agents are distributed alternatively and clustered regarding their income type (treatment 3 vs treatment 4, and separately treatment 5 vs. treatment 6)
Hypothesis 3.a: For the heterogeneous-income treatments, the common-chest transfer mechanism will give larger investments than the setting with direct transfers.
Hypothesis 3.b: For the heterogeneous-income treatments, the common-chest transfer mechanism will give larger transfers from the high-income types to the low-incomes types than the direct transfer case.
For testing these two hypothesis, we will compare the investment and transfer decisions in the treatments where the agents can make direct transfers and where the transfers are channelled through a common-chest mechanism (treatment 3 vs. treatment 5, and separately treatment 4 vs. treatment 6).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Hypothesis 4: The overlapping-neighborhood setting triggers a spatial dynamic of provision levels in which indirect neighbors decisions of the previous period affect the investment decision in the current period.
To gain insights into the dynamics of investment decisions across space, we compare the investment decisions in subsequent periods.
Control variables from a short questionnaire at the end of the experiment:
Demographics: Sex, age, field of study.
Social preferences: risk-taking, prosociality.
Task-related opinions: satisfaction with their own/their groupmates decisions, perceived generosity of their own/their groupmates decisions.
Task comprehension: What do the participants think that was the subject of the study.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This experiment will be conducted by the experimental laboratory of the University of Hamburg (Germany) in an online setting. The experiment will make use of a weakest-link public good game with 6 different treatments. In particular, participants will be assigned to groups of 6 players who interact in a 10-round public good game. The addition of overlapping neighborhoods extends the standard public good game in this study.
At the beginning of each of the 10 rounds, each participant is allotted again her initial income and the game is repeated. In other words, there is no possible transfer of tokens between rounds. Each plyer decides in each round how many tokens to invest in the public good in her own position, how many to invest by an in-kind transfer to any other location, and how many to keep in her account. At the end of each round, each participant will get an outcome given by the tokens that she has left minus the transfers that she made and the payback from the public good provided at her position. The public good has a unitary cost of 1 and each participant gets a benefit of 2.5 times the amount of public good provided at her place. The formula for the outcome for a player I is then: Outcome = Tokens remaining in own account MINUS Sum of Tokens invested in any location PLUS 2.5*Amount of total investment at her position.
In treatment 1, a group of 6 players is organised in 2 subgroups of 3 participants each. In this treatment, all participants have a homogeneous income of 30 tokens each. In each of these subgroups, each participant makes a decision on how many of these 30 tokens to invest in her own position and how many to transfer and to which groupmate. The investment in the public good are aggregated by a weakest-link technology, so the amount of public good provided to each participant in a subgroup is the minimum amount invested by any of them plus the potential transfers received from the others.
In treatment 2, a group of 6 players plays a public good game in a virtual circular neighbor. All 6 participants have a homogeneous income of 30 tokens. In this case, the provision of the public good in the position of a player will be driven by the minimum provided in the neighbourhood formed by her, and her right- and left-hand neighbors. This way of aggregating the investments will create 6 overlapping neighborhoods, one for each participant.
Treatments 3 and 4 have the same setting as treatment 2, but they have heterogeneous income for the participants – in each group, 3 participants will have a high income of 40 (H), and 3 will have a low income of 20 (L). In treatment 3, the participants are spatially distributed alternatively regarding their type (H-L-H-L-H-L), while in treatment 4 they are clustered together (H-H-H-L-L-L).
Treatment 5 and 6 have the same payoff structure as treatments 3 and 4, but investments can only be made at the own location of a participant and into a common chest. The total amount invested into the common chest works is divided up equally between the three low-endowment participants.
Experimental Design Details
Not available
Randomization Method
Randomization into treatments as well as locations and roles within the experiment done by computer.
Randomization Unit
Groups of six
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
None
Sample size: planned number of observations
432 observations/participants (6 treatments, each having 12 groups of 6 participants). Thus, 12 independent observations per treatment.
Sample size (or number of clusters) by treatment arms
None
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)

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IRB Approval Date
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