Pre-Analysis Plan: What drives refugees’ return after conflict? Evidence from a conjoint experiment among Ukrainian refugees.

Last registered on July 01, 2024

Pre-Trial

General Information

Title

RCT ID

AEARCTR-0013914

Initial registration date

June 29, 2024

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 01, 2024, 4:48 PM EDT

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

Locations

Country

Germany

Region

Primary Investigator

Name

Joop Adema

Affiliation

ifo Institute

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Panu Poutvaara

PI Affiliation

LMU Munich and ifo Institute

Contact Investigator

PI Name

Lasha Chargaziia

PI Affiliation

LMU Munich and ifo Institute

Contact Investigator

PI Name

Sarah Necker

PI Affiliation

Contact Investigator

Additional Trial Information

Status

In development

Start date

2024-07-01

End date

2024-07-31

Keywords

Crime, Violence, & Conflict, Post-conflict

Additional Keywords

Refugees, Return Migration, Conjoint experiment

JEL code(s)

Secondary IDs

F22

Prior work

This trial is based on or builds upon one or more prior RCTs.

Abstract

Refugees' decisions on whether to return are of great importance both to their country of origin and host country. These decisions affect the prospects of rebuilding the country of origin after a conflict ends. Return plans also affect refugees' incentives to invest in host-country specific human capital, thereby affecting their integration outcomes. While previous literature has largely focused on the role of safety after a conflict ends, also many other aspects can play an important role, including economic opportunities and perceived risk of a future conflict. In this Pre-analysis Plan, we describe how we study Ukrainian refugees' return decisions using a conjoint experiment among Ukrainian refugees in various European countries. Our conjoint experiment includes the following main dimensions: outcome of the war, when the war ends, security guarantees and the prospect of EU membership, as well as economic opportunities and corruption in Ukraine.

External Link(s)

Registration Citation

Citation

Adema, Joop et al. 2024. "Pre-Analysis Plan: What drives refugees’ return after conflict? Evidence from a conjoint experiment among Ukrainian refugees.." AEA RCT Registry. July 01. https://doi.org/10.1257/rct.13914-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Each respondent is shown a hypothetical scenarios for post-war Ukraine and asked to indicate on a 0-100 scale how likely they would return in such situation. We repeat this five times per respondent with different hypothetical scenarios.

Intervention (Hidden)

Intervention Start Date

2024-07-02

Intervention End Date

2024-07-31

Primary Outcomes

Primary Outcomes (end points)

A slider with step size 1 ranging from 0 to 100, where 0 is labelled "Definitely would not return" and 100 is labelled "Definitely would return". We interpret effects on this outcome as changes in the self-assessed probability of returning.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

There are no clusters in the typical sense of an RCT. The hypothetical scenarios vary along 8 dimensions. Given that every respondent has to make five hypothetical choices, we cluster standard errors on the individual level as in its absence the correlation between the responses of the same individual may lead to overstate precision.

Experimental Design Details

Randomization Method

Randomization of dimensions in post-war Ukraine is done by survey software, according to the rules specified in the PAP document.

Randomization Unit

Individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

There are no clusters in the typical sense of an RCT. The scenarios vary along 8 dimensions. Given that every respondent has to do five rounds, we cluster standard errors on the individual level as in its absence the correlation between the responses of the same individual may lead to overstate precision.

Sample size: planned number of observations

About 1000 respondents in the Verian survey and 2000 respondents in the ifo survey.

Sample size (or number of clusters) by treatment arms

In each round for each individual, the characteristics of the eight dimensions are independently randomized. All alternatives in each dimension have the same probability, with one exception: as most conflicts end in peace agreements, we make the probability that a peace agreement is drawn 50 percent and the other two options 25 percent each in the category ``How did the fighting end''.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

To test the significance of our effect, we always use two-sided tests with $\alpha = 0.05$. We aim to detect effect sizes of 5 points on the scale of 100 (AMCE), which is relatively small compared to effect sizes found in the literature. We performed a power analysis using the R package cjpowR (Schuessler and Freitag, 2020), calculating the power with a combined sample size of 3,000 individuals who perform 5 rounds each. For the combined sample, the statistical tests of the main effects dimensions with 3 attribute levels when the true effect size is 5 points have a power exceeding 99\%. The power to detect internal interaction effects of 5 points between two dimensions with 3 attribute levels each is 54%. Subgroup analyses on a subsample of 30% (which is approximately the share of those planning to return soon or planning to settle outside of Ukraine in previous survey waves) of the full sample have a power of 78\%. Hence, our studies are reasonably powered to test aforementioned hypotheses.

Supporting Documents and Materials

IRB