The Political Feasibility of Redistributive Policies in Europe

Last registered on July 06, 2026
View Trial History

Pre-Trial

Trial Information

General Information

Title
The Political Feasibility of Redistributive Policies in Europe
RCT ID
AEARCTR-0018965
Initial registration date
June 30, 2026

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
July 06, 2026, 7:32 AM EDT

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

Locations

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Name
Gregory Sun
Affiliation
Washington University in St Louis
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2026-07-13
End date
2026-07-17
Keywords
Behavior, Electoral
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study aims to quantify heterogeneity in how people think about trading off various dimensions of redistribution policy. I ask individuals to consider a number of scenarios where the government performs redistribution in a number of different ways, with a number of different economic consequences, and ask whether across these scenarios, people find the redistribution to be worthwhile. The answers to these questions will inform a model of the distribution of weights people assign to various dimensions of redistribution policy, which can in turn be used to quantify the proportion of people who would in principle be in favor of different counterfactual policy proposals. I aim to then connect the results of this experiment with a structural model, predicting the economic impacts of various income guarantee proposals to find the set of politically feasible income guarantee programs.

A previous trial studied the same question in the context of the United States. The current one extends the same methodology to a European sample.
External Link(s)

Registration Citation

Citation
Sun, Gregory. 2026. "The Political Feasibility of Redistributive Policies in Europe." AEA RCT Registry. July 06. https://doi.org/10.1257/rct.18965-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Each individual in my experiment will receive a survey. The first half of the survey asks about basic demograhpic information. The second half of the survey asks individuals.
Intervention Start Date
2026-07-13
Intervention End Date
2026-07-17

Primary Outcomes

Primary Outcomes (end points)
The primary outcomes of interest will be the binary decisions of individuals in responding to the hypothetical redistribution outcomes asked about in the survey are desirable.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Each subject will fill out a simple, short survey. Part 1 will collect basic demograhpic information about subjects (Gender, Age, Marital Status, Children, Ethnicity/Race, US Citizenship, State of Residence, Education, Employment Status, Income, President Vote, Political Identity).

In the second part, I will ask them to answer a series of questions of the following form:
"Suppose that the government spent $1,000, and as a result transfers $Y {in cash/in value through currently existing welfare programs} on top of current benefits to a household who 1) currently makes income I, 2) will respond to the transfer by reducing labor supply by D. {In addition, the household in question has a job which is consider to be at high risk of being automated due to AI., In addition, the household in question has a job which is not considered to be at high risk of being automated due to AI.} Do you think this transfer was a net positive or net negative for society?"

From question to question, I vary Y, I, D, as well as the discrete options in braces and record the survey-taker's response to each question.
Experimental Design Details
Not available
Randomization Method
Randomization is done through the JavaScript code underlying the Qualtrics survey.
Randomization Unit
Questions will be randomized at the individual-question level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1000 subjects
Sample size: planned number of observations
1000 subjects answering 10 binary choice questions.
Sample size (or number of clusters) by treatment arms
The distribution of "treatments" is drawn from a continuum of values, so this question is poorly defined for my setting.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
This is the sample size of the previous trial, while delivered sufficiently precise results.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Washington University in St Louis IRB
IRB Approval Date
2026-06-30
IRB Approval Number
202606165
Analysis Plan

Analysis Plan Documents

PAP

MD5: 828db07bbe2303c6edd20c78beaecbbd

SHA1: e483d7ea75fc21106c76ca0f9a1d72995655a2a6

Uploaded At: June 18, 2026