Policies to Incentivize Ukrainian Refugees to Return

Last registered on March 23, 2026
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Pre-Trial

Trial Information

General Information

Title
Policies to Incentivize Ukrainian Refugees to Return
RCT ID
AEARCTR-0018178
Initial registration date
March 20, 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
March 23, 2026, 7:59 AM EDT

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

Locations

Country
Austria
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Belgium
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Bulgaria
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Switzerland
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Czechia
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Germany
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Denmark
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Estonia
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Spain
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Finland
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France
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United Kingdom of Great Britain and Northern Ireland
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Greece
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Croatia
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Hungary
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Ireland
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Italy
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Lithuania
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Latvia
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Moldova (Republic of)
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Netherlands
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Norway
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Poland
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Portugal
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Romania
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Sweden
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Slovenia
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Slovakia
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Ukraine
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Primary Investigator

Name
Panu Poutvaara
Affiliation
LMU Munich and ifo Institute
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Other Primary Investigator(s)

PI Name
Lasha Chargaziia
PI Affiliation
ifo Institute, LMU Munich
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PI Name
Yvonne Giesing
PI Affiliation
ifo Institute, LMU Munich
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PI Name
Gabriele Gurrieri
PI Affiliation
ifo Institute, LMU Munich
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PI Name
Yuliya Kosyakova
PI Affiliation
IAB, University of Bamberg
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PI Name
Sebastian Schirner
PI Affiliation
ifo Institute, LMU Munich
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PI Name
Kerstin Tanis
PI Affiliation
BAMF-FZ
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PI Name
Hanna Vakhitova
PI Affiliation
Kyiv School of Economics
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PI Name
Volodymyr Vakhitov
PI Affiliation
American University Kyiv
Contact Investigator
PI Name
Nataliia Zaika
PI Affiliation
American University Kyiv
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PI Name
Sabine Zinn
PI Affiliation
DIW Berlin
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Additional Trial Information

Status
In development
Start date
2026-03-22
End date
2026-09-30
Keywords
Behavior, Education, Governance, Labor, Post-conflict
Additional Keywords
Refugees, Return migration, Ukraine, Reconstruction
JEL code(s)
F22
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Russia’s full-scale invasion of Ukraine in 2022 triggered one of the largest refugee crises in recent history, with millions of Ukrainians seeking safety abroad. Their decisions on whether to return are crucial for Ukraine’s recovery and long-term prospects. While previous literature has largely focused on safety and security guarantees, less is known about the role of specific post-conflict reconstruction measures. Safety is
a necessary condition for large-scale repatriation, but it is not sufficient. Once the fighting ends, refugees face complex economic and social trade-offs regarding where to rebuild their lives. Hence, studying how specific origin country policies affect return to post-war Ukraine can deliver new insights on how governments can shape return migration beyond the cessation of hostilities. Furthermore, the design of such policies involves critical trade-offs, not only in terms of economic efficiency but also regarding social cohesion. Post-war resources are inherently scarce, and policies that favor returnees might create tensions with the population that remained in the country, potentially undermining the social fabric necessary for successful reconstruction.
We study policies that can influence return plans of Ukrainian refugees and social cohesion between Ukrainian refugees and Ukrainians who have stayed in Ukraine through a conjoint experiment. In the conjoint, we present respondents with two alternative policy packages (Package 1 vs. Package 2) intended to reconstruct Ukraine, support both returning refugees and Internally Displaced Persons (IDPs), and incentivize return. For each pair of profiles, respondents are asked to indicate which of the two packages they prefer. Refugees are also asked how likely they would be to return to Ukraine if that specific package were implemented. The dimensions we include are: (1) housing support; (2) minimum wage levels; (3) healthcare coverage; (4) a one-time cash payment transferred upon return; (5) children’s school reintegration policies; and (6) childcare subsidies.
External Link(s)

Registration Citation

Citation
Chargaziia, Lasha et al. 2026. "Policies to Incentivize Ukrainian Refugees to Return." AEA RCT Registry. March 23. https://doi.org/10.1257/rct.18178-1.0
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Experimental Details

Interventions

Intervention(s)
We perform a forced-choice conjoint analysis asking Ukrainian refugees and Ukrainians in Ukraine to choose between two hypothetical policy packages that the government might implement in a post-war context. We ask the respondents to indicate the package that they would prefer to be implemented and Ukrainian refugees to evaluate their return probability in case each of the packages were implemented.
Intervention Start Date
2026-03-23
Intervention End Date
2026-09-30

Primary Outcomes

Primary Outcomes (end points)
(1) Policy Preference. We ask respondents to make a forced choice between the two profiles by answering: “Which of the two policy packages would you prefer to be implemented?”
(2) Return Intentions. We ask respondents to score their likelihood of returning for each specific package on a scale ranging from 0 to 10, where 0 is labelled “Not likely at all” and 10 is labelled “Extremely likely”. We interpret effects on this continuous outcome as changes in the self-assessed probability of returning to Ukraine conditional on the specific policy mix.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We show each respondent four sets of profile pairs. Each profile has six dimensions. Randomization is performed by fully random draws. For the cash transfer attribute (hryvnias), a continuous value is drawn from a uniform distribution within the specified range [5,000 Hryvnias, 250,000 Hryvnias] and rounded to the nearest 10,000 Hryvnias.
Experimental Design Details
Not available
Randomization Method
Randomization is done by computer.
Randomization Unit
Randomization is done independently for each attribute in each profile for each respondent.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
We have five different samples, with following expected numbers of respondents:
Survey I: IAB-BAMF-SOEP (Refugees in Germany): 4,640 individuals
Survey II: ifo (Refugees in Germany): 1,000 respondents
Survey III: Voice of Ukraine survey by Verian (Refugees across Europe): 1,000 respondents
Survey IV: Refugees who have returned to Ukraine by Gradus Research: 1,100 respondents
Survey V: Ukrainians who have stayed in Ukraine by Gradus Research: 1,100 respondents
Sample size: planned number of observations
6640 respondents in the refugee surveys and 2,200 respondents in surveys of Ukrainians in Ukraine
Sample size (or number of clusters) by treatment arms
In a conjoint experiment, each pair is an own treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
In our study, we aim to detect effect sizes of 5 percentage points (AMCE). • Given the granularity of our policy attributes (e.g., specific wage increments or subsidy levels), having sufficient power to distinguish subtle differences is crucial. We perform a power analysis using the R package cjpowR (Schuessler and Freitag, 2020). • Given an anticipated sample size of 6640 observations in the refugee sample (effective N = 53120), the study has >99% power to detect an effect size of 5%. In the sample of Ukrainians in Ukraine, we anticipate a sample size of 2200 respondents (effective N = 17 600), providing us with 98% power to detect an effect of 5%.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics Commission, Department of Economics, University of Munich (LMU)
IRB Approval Date
2026-02-06
IRB Approval Number
2026-03
Analysis Plan

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