Initial Endowment and Redistribution: Growth and Inequality in Dynamic Public Good Game

Last registered on April 26, 2023
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Pre-Trial

Trial Information

General Information

Title
Initial Endowment and Redistribution: Growth and Inequality in Dynamic Public Good Game
RCT ID
AEARCTR-0011143
Initial registration date
April 20, 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
April 26, 2023, 5:12 PM EDT

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

Locations

Country
China
Region
Wuhan

Primary Investigator

Name
Lian XUE
Affiliation
Wuhan University
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Other Primary Investigator(s)

PI Name
Edward Cartwright
PI Affiliation
De Montfort University
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PI Name
Gergely Horváth
PI Affiliation
Duke Kunshan University
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PI Name
Friederike Mengel
PI Affiliation
University of Essex
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Additional Trial Information

Status
On going
Start date
2023-03-01
End date
2024-06-30
Keywords
Behavior, Lab, Welfare
Additional Keywords
dynamic public good game; taxation; redistribution policy;
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Why do some economic systems thrive while others fail? We explore the question in an experimental framework with the dynamic public good game (Gachter et al., 2017), where each agent's wealth at the end of period t serves as her endowment in t+1. We exogenously vary the initial endowment equality and the existence of market institutions for redistribution across treatments to examine factors that affect growth and inequality within and across experimental groups. In a 2 by 3 between-subject design, we vary two key factors: (1) whether participants' initial endowment is equal or unequal (with half of the participants receiving twice the endowment). (2) whether participants have the opportunity to redistribute, through uniform taxation, at the end of a period. Additionally, we compare whether the redistribution policy is endogenously voted among group members or exogenous given by the experimenter.
At the end of the experiment, we also elicit for individuals' individual characteristics and risk-, social- and redistributive preferences.
We aim to identify the causal impact of initial equality and redistribution policies on growth and inequality, the correlation between individual preferences and cooperative behaviour (i.e., contribution and voting) and heterogeneous effects across individuals.


Reference
Gächter, Simon, Friederike Mengel, Elias Tsakas, and Alexander Vostroknutov. "Growth and inequality in public good provision." Journal of Public Economics 150 (2017): 1-13.
External Link(s)

Registration Citation

Citation
Cartwright, Edward et al. 2023. "Initial Endowment and Redistribution: Growth and Inequality in Dynamic Public Good Game." AEA RCT Registry. April 26. https://doi.org/10.1257/rct.11143-1.0
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Experimental Details

Interventions

Intervention(s)
Our experiment has a 2-by-3 experimental design, varying initial endowments and market institutions. Specifically, we manipulate two treatment arms:
(1) Inequal initial endowment and Equal initial endowment (between-subject): We first vary whether four players in a group receive the same initial endowment or the rich halves receive twice as much endowment as the poor halves.
(2) Market institutions: We next vary the existence and structure of the institutions regarding redistribution. NoTax treatments serve as a baseline where there is no market(between-subject). In EndogeneousTax treatments, participants can vote for their preferred tax rate, ranging from 0%, 10%, 25% and 50%, every 3 rounds for 5 times across the 15 rounds, with the dictator rule where a randomly selected dictator's choice is implemented. In ExogenousTax treatments, participants face an exogenous tax rate every 3 rounds predetermined by the experimenter.
Intervention Start Date
2023-04-22
Intervention End Date
2024-06-30

Primary Outcomes

Primary Outcomes (end points)
Within-group wealth and inequality, measured by the mean and standard deviation or the Gini coefficient at the end of the 15th round, within groups among four group members.
Across-group wealth and inequality, measured by the mean and standard deviation or the gini coefficient, across groups in each treatment.
Primary Outcomes (explanation)
We have the following null hypotheses regarding the final wealth level across treatments:
H1: (equality of initial endowment) Final wealth in the Unequal-NoTax treatment is the same as with Equal-NoTax treatment.
H2: (equality of initial endowment) Final wealth in Unequal-Tax treatment is the same as with Equal-Tax treatment.
H3: (availability of redistribution) Final wealth in Unequal-Tax treatment is the same as with Unequal-NoTax treatment.
H4: (availability of redistribution) Final wealth in Equal-Tax treatment is the same as with Equal-NoTax treatment.
H5: (autonomy) Final wealth in Endogeneous tax treatment is the same as with Exogensous tax treatment.

Secondary Outcomes

Secondary Outcomes (end points)
Redistributive preferences
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We adapted the dynamic public good game framework following Gachter et al. (2017). Participants in groups of four play the public good game in a repeated interaction of 15 periods. Unlike standard public good games, there are dynamic interdependencies across periods in our game, i.e., each participant's payoff (wealth after tax) at the end of period t serves as her endowment in t+1 period.
We vary initial endowments and institutions across treatments. For equal endowment treatments, the initial endowment is 30 tokens for each participant. For unequal endowment treatments, the initial endowments are 20 and 40 for each half of the participants in a group. The MPCR is set at 1.5.
At the end of the experiment, participants complete a questionnaire about their individual characteristics and economic preferences, including risk, prosocial and redistributive preferences.
Participants will be paid based on their final earnings at the end of the 15th round, with 1 token converted to 0.05 yuan, in addition to a 20 yuan participation payment.

Reference
Gächter, Simon, Friederike Mengel, Elias Tsakas, and Alexander Vostroknutov. "Growth and inequality in public good provision." Journal of Public Economics 150 (2017): 1-13.
Experimental Design Details
Not available
Randomization Method
Standard laboratory randomization in recruitment using the Weikeyan System.
Randomization Unit
The unit of observation can be at the individual-period level; group-period level; or group level; depending on the designated hypotheses testing.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
We have conducted power analysis after collecting data from 6 groups for each treatment. We use two-sample Mann-Whitney non-parametric tests to compare the treatments. The outcomes are the final wealth level and the final Gini-coefficient in the group measured in period 15. One group thus yields one observation of the outcome variables. We compute the standard deviation of outcomes across groups using this sample of 6 groups.

We intend to collect at least 20 groups of data. We computed the estimated effect size we will be able to detect with 20 groups at conventional power level of 80% and significance level of 0.05.
Sample size: planned number of observations
480 participants.
Sample size (or number of clusters) by treatment arms
80 participants in each treatment arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We make the following main treatment comparisons: Comparison 1: Equal NoTax vs. Equal EndoTax Null hypotheses: Final wealth in Equal NoTax = Final wealth in Equal EndoTax Final Gini coefficient in Equal NoTax = Final Gini coefficient in Equal EndoTax With 20 groups we will be able to detect an effect size 0.931*standard deviation which is equal to A wealth difference of 1090.55 and a Gini coefficient difference of 0.092 with the current data. Comparison 2: Inequal NoTax vs. Inequal EndoTax Null hypotheses: Final wealth in Inequal NoTax = Final wealth in Inequal EndoTax Final Gini coefficient in Unequal NoTax = Final Gini coefficient in Inequal EndoTax With 20 groups we will be able to detect an effect size 0.931*standard deviation which is equal to A wealth difference of 2454.94 and a Gini coefficient difference of 0.066 with the current data. Comparison 3: Equal Notax vs. Inequal Notax Null hypotheses: Final wealth in Equal NoTax = Final wealth in Inequal Notax Final Gini coefficient in Equal NoTax = Final Gini coefficient in Inequal Notax With 20 groups we will be able to detect an effect size 0.931*standard deviation which is equal to A wealth difference of 2279.7 and a Gini coefficient difference of 0.102 with the current data.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Center of Behavior and Economic Research, Wuhan Univerisity
IRB Approval Date
2022-09-14
IRB Approval Number
E20220339
Analysis Plan