Policies to Incentivize Ukrainian Refugees to Return

Last registered on March 23, 2026

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

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Primary Investigator

Affiliation
LMU Munich and ifo Institute

Other Primary Investigator(s)

PI Affiliation
ifo Institute, LMU Munich
PI Affiliation
ifo Institute, LMU Munich
PI Affiliation
ifo Institute, LMU Munich
PI Affiliation
IAB, University of Bamberg
PI Affiliation
ifo Institute, LMU Munich
PI Affiliation
BAMF-FZ
PI Affiliation
Kyiv School of Economics
PI Affiliation
American University Kyiv
PI Affiliation
American University Kyiv
PI Affiliation
DIW Berlin

Additional Trial Information

Status
In development
Start date
2026-03-22
End date
2026-09-30
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 (Hidden)
Respondents are presented with a specific post-war scenario to frame their decision: “Imagine the fighting and aerial attacks in Ukraine have stopped, and there are Western peacekeepers on the ground. However, Ukraine was not able to regain control over occupied territories. Negotiations to join the EU are progressing. The Ukrainian economy is recovering. The Ukrainian government and its international partners are planning to implement one of the following policy packages to reconstruct Ukraine, support Internally Displaced Persons (IDPs), and incentivize the return of refugees. Which of the two policy packages would you prefer to be implemented?”
• Following the notation of Hainmueller et al. (2014), a conjoint experiment consists of N respondents, K tasks (or rounds), with J alternatives, with L attributes which have Dl components (or levels) each. J=2 in a paired conjoint. We draw K = 4 sets of profile pairs for each respondent. We choose L = 6 dimensions based on their policy relevance while keeping the number of dimensions tractable for respondents as suggested by Bansak et al. (2021).

In designing the attributes of the conjoint tasks, we aimed to include dimensions that are (1) most relevant to the decision to return, (2) actionable by the Ukrainian government and international partners, and (3) realistic within the proposed post-war context. The selected attributes are from three broad categories, with monetary values provided in Hryvnias (1 Euro corresponded to approximately 50 to 51 Hryvnias between January and March 2026).
• Economic Incentives:
(1) Minimum wage ∈ {Remains at the level of 8700 Hryvnias per month, Increased to 10 000 Hryvnias per month, Increased to 12 000 Hryvnias per month, Increased to 14 000 Hryvnias per month, Increased to 16 000 Hryvnias per month}
(2) One-time payment (Cash Transfer) ∈ {Random value drawn from a range (5000 Hryvnias , 250 000 Hryvnias ) and rounded to the nearest 10 000 Hryvnias. If taking it, recipients lose access to social assistance in other European countries for one year.}
• Social Support:
(3) Housing (applies to those who have no home to return to) ∈ {There are no additional housing benefits for returnees to Ukraine, Free social dormitories for three months, Free social dormitories for one year, Free separate social apartments for one year}
(4) Healthcare ∈ {Returnees receive standard Ukrainian health coverage, Health and medication costs of returnees are fully covered by the previous host country for 6 months after return, Health and medication costs of returnees in Ukraine are fully covered by the previous host country for one year after return}
• Child-related Policies:
(5) Children’s reintegration ∈ {The child is guaranteed a place in the school according to their knowledge level, The child is guaranteed a place in the school according to their age (without state-funded reintegration programs), The child is guaranteed a place in the school according to their age (with state-funded reintegration programs)}
(6) Childcare ∈ {There are no changes in public and private childcare, There is a subsidy which covers 20% of costs in private childcare facilities, There is a subsidy which covers 50% of costs in private childcare facilities, There is a subsidy which covers 80% of costs in private childcare facilities, A spot for a child is guaranteed in public childcare facilities}
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
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%.
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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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