Are preferences for redistribution affected by the source of inequality and information about peer preferences?

Last registered on June 07, 2023

Pre-Trial

Trial Information

General Information

Title
Are preferences for redistribution affected by the source of inequality and information about peer preferences?
RCT ID
AEARCTR-0010211
Initial registration date
October 15, 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
October 17, 2022, 5:33 PM EDT

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

Last updated
June 07, 2023, 4:36 AM EDT

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

Locations

Primary Investigator

Affiliation
University of Copenhagen

Other Primary Investigator(s)

PI Affiliation
UNU-WIDER
PI Affiliation
Universidade Eduardo Mondlane
PI Affiliation
Central Institute for Economic Management (CIEM)
PI Affiliation
University of Copenhagen

Additional Trial Information

Status
On going
Start date
2022-11-14
End date
2023-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Evidence from previous studies suggests that attitudes to inequality and preferences for redistribution are influenced by the perceived fairness of the source of inequality. Specifically, several studies have found that inequality resulting from differences in performance (or hard work) is more accepted than inequality due to luck or factors outside of individual control. This study uses an economic experiment to test whether varying the source of inequality affects how individuals make distribution decisions, thus addressing the question: ‘Does the source of inequality, in particular merit or luck, affect preferences for redistribution?’
Moreover, we extend the analysis to consider changes in behaviour due to strategic interaction with other participants. In line with previous studies showing that pro-social behaviour is affected by the observation of others behaving pro-socially, we ask a similar question in the context of preferences for redistribution: ‘Does exposure to peer preferences affect decisions to redistribute?’
We implement this economic experiment together with other games and a survey to collect background information on participants in both Mozambique and Vietnam.
More details are presented in the pre-analysis plan.
External Link(s)

Registration Citation

Citation
Tarp, Finn et al. 2023. "Are preferences for redistribution affected by the source of inequality and information about peer preferences?." AEA RCT Registry. June 07. https://doi.org/10.1257/rct.10211-3.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2022-11-14
Intervention End Date
2023-03-31

Primary Outcomes

Primary Outcomes (end points)
Measure of redistribution given by the ratio of the absolute value of the difference between the allocations to both players proposed by the participant and the initial difference between the allocation of the player with high endowment (Player B) and the player with low endowment (Player A). As an alternative measure, we will consider a similar indicator without the absolute value in the numerator.
We use the measure of redistribution to compare the distribution decisions in the luck and merit sessions, and to test whether there is more redistribution in the sessions with the luck treatment.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
We will use the amount allocated to the player with the low initial endowment to identify the changes in the decisions taken by both players and the guesses of each player of the other’s decisions.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment involves three phases: a production phase, an allocation phase and a distribution phase. During the production phase, participants perform an effort task, involving the copying of shapes. They are given blocks of squares containing both white and black squares. Next to each block, there is a copy containing white squares and grey squares in the same positions as the ‘original’ block. The goal is to put crosses in the grey squares, in order to copy the shape of the original block. Participants are given a few minutes to go through as many blocks of squares as possible.
In the allocation phase, we group participants into pairs – Player A and Player B – who are playing in different rooms. Player A is endowed with three units (low endowment) and Player B is endowed with seven units (high endowment). We have two treatments. In the luck treatment (our control group), the initial endowments of players is determined randomly based on their participant ID number (which is randomly allocated to participants in the beginning of the session). In the merit treatment, the initial endowments of players are based on their performance in the effort task. Together, each pair has a total production of ten units.
The distribution phase consists of two similar stages, in each of which participants make distributive choices about these ten units between themselves and their pair. In the first stage, both participants make their choices independently and these are not communicated to the other player until the end of the experiment, when the final amounts are paid to all participants.
In the second stage, we maintain the same initial allocation, but induce a change in power between the participants. Faced with an unequal initial distribution of incomes, the player with a low endowment has grabbing power, but the player with the high endowment may veto the final transfers. Thus, the decisions are sequential and Player B has the power over the final distribution. While Player A is the first to propose their distribution decision, this choice is then shown to Player B, who has the highest endowment, and the power to decide whether they agree or disagree with the proposal. The final distribution corresponds to the decision of Player B and we match the payment of both participants according to this decision. In addition to collecting their choices, we ask each participant to anticipate the decision of the other player: Player A will guess the decision of Player B after proposing the distribution, and Player B will guess the proposal of Player A before seeing their decision.
The design of the study is based on between-subject comparison. In each country, we initially run a total of 40 sessions, 20 in rural settings and 20 in urban settings (see more details on the sampling in section 3) and we will add an additional round of 40 sessions, 20 in rural settings and 20 in urban settings, in the South of Vietnam. Within each location (which can be rural or urban), we run an even number of sessions and each treatment is randomly allocated to half of these sessions. The assignment of participants between sessions in each location is random.
Experimental Design Details
Randomization Method
The randomization is done through a Stata code.
Randomization Unit
Each of the treatments (luck or merit) is randomly allocated to half of the sessions in the rural settings and half of the sessions in the urban settings, so that in each location there is an even number of sessions for each treatment (done in a random order). In each location (rural or urban), individuals are randomly allocated between luck treatment sessions and merit treatment sessions (with stratification by gender).
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1,040 individuals in Mozambique and 2,080 individuals in Vietnam (total of 3,120 individuals).
Sample size: planned number of observations
1,040 individuals in Mozambique and 2,080 individuals in Vietnam (total of 3,120 individuals).
Sample size (or number of clusters) by treatment arms
In each data collection effort (Mozambique, North of Vietnam and South of Vietnam), 520 individuals receive the luck treatment and 520 individuals receive the merit treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Joint Ethical Review Board (ERB) of UNU
IRB Approval Date
2022-03-29
IRB Approval Number
202203/01
IRB Name
Joint Ethical Review Board (ERB) of UNU
IRB Approval Date
2023-05-25
IRB Approval Number
202203/01_Amend
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