Should we start telling real stories? A survey experiment about Immigration and Redistribution in Austria

Last registered on April 24, 2026
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Pre-Trial

Trial Information

General Information

Title
Should we start telling real stories? A survey experiment about Immigration and Redistribution in Austria
RCT ID
AEARCTR-0018367
Initial registration date
April 16, 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
April 24, 2026, 8:22 AM EDT

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

Locations

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Primary Investigator

Name
Luca Hechenblaikner
Affiliation
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Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2026-04-16
End date
2026-06-30
Keywords
Behavior, Welfare
Additional Keywords
Immigration, Redistribution
JEL code(s)
D72 · D91 · H21 H23 · H24 · H41
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We conduct an online survey experiment in Austria to test whether a positively framed
narrative about a Syrian refugee shifts attitudes toward immigration and preferences for redistribu
tion. Approximately 1,000 respondents are randomly assigned to watch either a short video telling
the success story of a refugee who founded a bakery in Vienna (treatment) or a video about the
voting age of 16 in Austria (active control). We measure immigration attitudes along three channels:
labor market concerns, welfare state concerns, cultural concerns and elicit beliefs about support
for immigration as well as preferred government spending allocations, income tax progressivity,
and general support for redistribution. We also elicit prior and posterior beliefs about immigrant
population shares to test for belief updating.
External Link(s)

Registration Citation

Citation
Hechenblaikner, Luca. 2026. "Should we start telling real stories? A survey experiment about Immigration and Redistribution in Austria ." AEA RCT Registry. April 24. https://doi.org/10.1257/rct.18367-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Approximately 1,000 respondents are randomly assigned to watch either a short video telling
the success story of a refugee who founded a bakery in Vienna (treatment) or a video about the voting age of 16 in Austria (active control)
Intervention Start Date
2026-04-16
Intervention End Date
2026-05-16

Primary Outcomes

Primary Outcomes (end points)
- Support for immigration, measured with the variable Immigration not a Problem. The variable is equal to 1 if the respondent thinks that immigration is not a problem or not a problem at all.


- Redistribution preferences, measured via a COFOG-based government budget allocation task,
- Preferred income tax rates across four income groups - Measured by Tax Progressivity
- self-reported 7-point support for redistribution scale
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Immigration attitudes along three channels:
- labor market concerns,
- welfare magnet argument
- cultural concerns

Belief updating about the share of immigrants in the Austrian population.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We conduct a two-arm online survey experiment in Austria with approximately 1,000 respondents. Participants are randomly assigned at the individual level to either a treatment or an active control condition.

Convenience sample recruited via SurveyCircle, SurveySwap, university lectures at the University of Innsbruck, and in-person interception at a rural restaurant. Eligible respondents must be born in Austria, hold Austrian citizenship, and be aged 16–99.

Experimental Design Details
Not available
Randomization Method
Respondents are randomly assigned at the individual level to one of two conditions (treatment vs. active control) with equal probability (1:1 ratio). Randomization is implemented directly in LimeSurvey at the point of survey entry.
Randomization Unit
Individual respondent
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
0
Sample size: planned number of observations
1000
Sample size (or number of clusters) by treatment arms
500 per arm (500 treatment, 500 active control)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
1000 subjects (500 per survey arm) gives us 0.8 power to detect an e ect size of 0.18 of a standard deviation between treatment and the control group in the main study at .05 signi cance level.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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