Does perceived labor-market competition increase out-group discrimination between refugees and hosts? Evidence from Uganda and Ethiopia.

Last registered on June 27, 2022

Pre-Trial

Trial Information

General Information

Title
Does perceived labor-market competition increase out-group discrimination between refugees and hosts? Evidence from Uganda and Ethiopia.
RCT ID
AEARCTR-0008912
Initial registration date
January 29, 2022

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
February 01, 2022, 6:06 PM EST

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

Last updated
June 27, 2022, 8:13 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Primary Investigator

Affiliation
Fafo Institute for Labour and Social Research

Other Primary Investigator(s)

PI Affiliation
KU Leuven
PI Affiliation
Universität Göttingen
PI Affiliation
Institute of Development Policy (IOB), University of Antwerp
PI Affiliation
FNRS and LIDAM, UCLouvain
PI Affiliation
University of Minnesota
PI Affiliation
FAFO Institute for Labour and Social Research

Additional Trial Information

Status
In development
Start date
2022-01-29
End date
2022-07-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Labor market integration of refugees, a critical step towards their self-reliance and local integration, can be impeded by local perceptions of labor market competition in an environment where job opportunities are limited. This, in addition to anti-refugee rhetoric stressing rivalry over job opportunities, may contribute to resentments, mistrust, and discrimination between refugees and hosts. To date, it is unclear whether perceptions of labor market competition between refugees and hosts compromise community-building efforts across the two groups. Our study seeks to evaluate whether perceptions of labor market competition negatively influence out-group attitudes. We use a randomized questionnaire module that exposes the survey respondents to narratives about the out-group, stressing either differences or commonalities in the labor market characteristics between the respondent and a fictitious in-group or out-group individual.
External Link(s)

Registration Citation

Citation
Bousquet, Julie et al. 2022. "Does perceived labor-market competition increase out-group discrimination between refugees and hosts? Evidence from Uganda and Ethiopia.." AEA RCT Registry. June 27. https://doi.org/10.1257/rct.8912
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Experimental Details

Interventions

Intervention(s)
Our study consists of a randomized questionnaire module that will be implemented as part of a large labor-market-related survey.
We are targeting refugee populations and host community members living in close proximity in rural and urban settings in Uganda and Ethiopia.

Our survey sample will cover approximately
2400 refugees and 2400 hosts across rural and urban areas of Uganda
2400 refugees and 2400 hosts across rural and urban areas of Ethiopia

As part of this survey, respondents will be randomly exposed to different narratives about a fictitious member of the out-group or in-group with identical or different labor characteristics.
Some respondents of the local host group will thus listen to a narrative about a fictitious individual of the host population and others to a narrative about a refugee. The same applies to respondents of the group of refugees. This fictitious character’s labor market characteristics, such as their occupation, are included in the vignette read to the respondent. Our experiment randomly varies this information across vignettes so that it either matches or is different from the respondent’s own job characteristics.
The study aims to analyze the interplay between perceived labor market competition and out-group discrimination. Using the results of our experiment, we will evaluate prevailing attitudes regarding out-group discrimination among hosts and refugees in Ethiopia and Uganda. Moreover, we will ask whether perceived labor market competition is an important driver of discriminatory attitudes towards the out-group.

Because the experiment is being executed in Uganda and Ethiopia, we can additionally compare the results from the two countries to descriptively analyze whether differential migration policies correlate with perceived labor market competition and discriminatory responses. In an attempt to capture additional effects and take advantage of using two identical designs in two countries sharing similar characteristics, we aim at doing a cross-country analysis, pooling the two sets of data together and measuring the same outcomes. Particular attention will be put on the use of sampling weights.
The intervention is planned to start on 29 January 2022 in Uganda and 20 February 2022 in Ethiopia and end on 28 February 2022 and 15 March 2022 in Uganda and Ethiopia, respectively.
Intervention Start Date
2022-01-29
Intervention End Date
2022-07-31

Primary Outcomes

Primary Outcomes (end points)
Our primary measures of interest are;
(1) Measures of discrimination towards the fictitious individual
(2) Measures of perceived labor market competition and labor market discrimination
Primary Outcomes (explanation)
Questions belonging to measure (1) capture discriminatory attitudes. They cover questions on whether the respondent would accept an out-group member in their community, family, or as a work colleague. We will use these questions to build an index of how welcoming the respondent is towards members of the out-group or in-group.

Moreover, the survey includes a set of questions aimed at gauging labor-market-related discrimination and perceptions of competition (measure (2)). For example, we ask whether respondents feel in competition for the same jobs with the fictitious character. We also include normative questions eliciting the desired degree of labor market integration for the fictitious individual.

Those three sets of questions will allow us to analyze
(1) The degree of perceived labor market competition when individuals are sharing or not the same labor market characteristics
(2) The amount of discrimination towards the out-group compared with the in-group
(3) The interplay between the two: Does discrimination increase in situations where perceived labor market competition is high?

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our experimental intervention is embedded in a survey questionnaire focused on labor market outcomes and interaction between refugees and host communities in Uganda and Ethiopia.

As part of this experiment, respondents are randomly assigned to four equally sized treatment groups. Each respondent will listen to a single narrative about a fictitious individual who is either from the in-group or the out-group and either sharing or not the respondent’s labor market characteristics.
T1: In-group; same labor market characteristics (25%)
T2: In-group; different labor market characteristics (25%)
T3: Out-group; same labor market characteristics (25%)
T4: Out-group; different labor market characteristics (25%)

Due to the matching process along with labor market characteristics, only those respondents who indicate being currently employed (including self-employed) or actively searching for work will administer the experimental module.

After the narrative is read out loud to the respondents, they are asked to respond to questions about the fictitious individual, notably concerning perceived labor market competition and general attitudes (prejudice, discrimination).
The purpose of our study is to better understand discriminatory attitudes towards the out- and in-group, and to gauge the extent to which negative/positive perceptions of refugees among host communities as well as obstacles/drivers to integration among refugees are driven by the perception that both groups are competing or not in the labor market.
Experimental Design Details
The experiment proceeds as follows:

(1) Respondents are randomly assigned to any of the four equally sized treatment groups (T1, T2, T3, and T4) as described above. Randomization is executed by a computer for the entire sample, which will be stratified based on group membership (refugee/ host) and location (Uganda: Isingiro District and Kampala; Ethiopia: Addis Ababa and Somali region).

(2) Within the detailed survey questionnaire, respondents are asked to report whether they are currently working or searching for work and which industry and occupation they are currently working in (or intending to turn to).

The experimental module can thus link back to the group membership of the respondent (refugee/ host), as known ex-ante from the listing, and the relevant occupation, determined by the answers in the respective survey module.

(3) In the experimental section, respondents will be randomly exposed to a standard narrative about a fictitious individual who belongs to group G and is exerting occupation O.

The random narratives stress the background of the fictitious character as a local or refugee as well as its occupational background. Narratives are only differing with respect to single words that are inserted for group G and occupation O.
G = {refugee; local host}
O = {respondent’s occupation; occupation differing from the respondent}

Single words for group G and occupation O will be auto-filled by a computer-based on survey response right before the experimental section.

T1: Respondent listens to a narrative about an in-group member who is working in the same occupation as himself.
T2: Respondent listens to a narrative about an in-group member who is working in a different occupation than himself.
T3: Respondent listens to a narrative about an out-group member who is working in the same occupation as himself.
T4: Respondent listens to a narrative about an out-group member who is working in a different occupation than himself.

The narratives (example for Uganda - symmetrically for Ethiopia) take the following form:

“[AIDA/ROBERT] is a [GROUP G: Ugandan/ refugee living in Uganda]. [She/He] (has lived in Uganda [her/his] entire life and) moved to [Isingiro district/ Kampala] five years ago. [She/He] has been working as a [OCCUPATION O: Same occupation as respondent/ different occupation] for a long time so [she/he] has a lot of experience in [her/ his] occupation. [She/He] also speaks many Ugandan local languages and English very well. [She/He] enjoys working in this profession and would recommend [her/his] friends to work in the same sector. But while being a [OCCUPATION O: Same occupation as respondent/ different occupation] fulfills [her/him], [she/he] is sometimes very tired after work. Due to difficult circumstances, [she/he] has to change jobs while keeping her/his current profession. So far, she/he has struggled finding a job.”

The narrative stresses competition on the local labor market by referring to the fictitious character as a local neighbor, living in the same district/ capital. Stories are comparable across all groups (refugees; hosts; different occupations): all four treatment groups’ narratives have the same length and are containing identical information (e.g. duration of stay in this district - thereby similar knowledge and networks).
The narrative is designed to be politically benign and to avoid raising positive or negative emotions. To make respondents relate with the narrative, the gender of the fictive character in the narrative is set to match that of the respondent.

While inserting a string for the group level G is straightforward, we are implementing one additional step when it comes to occupation group O in order to make narratives exactly comparable in their length (one to three words).

For individuals who have been randomly assigned to treatment groups T1 or T3 (same occupation), the enumerator will be asked to shorten the occupation string indicated by the respondent.
E.g.: If the respondent states he is an “undergraduate teacher for Maths and sports”, the enumerator is trained to shorten the string to “teacher”.
The narrative will then be based on the shortened version of the string.

For individuals who have been randomly assigned to treatment groups T2 or T4 (different occupation), we have prepared a list of different occupations that the computer will randomly draw from.
This list of occupations is split into “high skilled (above secondary degree)” and “low skilled (below secondary degree)” occupations so that respondents will be matched with a fictitious character of the same skill level. This step intends to avoid confounding effects based on hierarchical judgements.
For programming reasons, the enumerators have to confirm that the randomly drawn occupation is indeed different from the string variable that the respondent indicated as his own. If the enumerator denies, a second random draw happens and the procedure is repeated.

(4) After the fieldworker reads the narrative to the respondent, the respondent answers questions that
Make them relate to the story (“Should the character search for work? What would you recommend him/ her to do?”)
Elicit their willingness to interact with the fictitious individual.
Gauge their normative perception concerning labor market integration of the fictitious individual
Randomization Method
Computer-based
Randomization Unit
Individual. We stratify by refugee status (refugee or non-refugee), and location (Uganda: Kampala, Isingiro District; Ethiopia: Addis Ababa, Somali Region).
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
210 Clusters in Uganda (Enumeration areas from the Census of 2014 in Uganda)
210 Clusters in Ethiopia (Enumeration areas from a mapping planned for the upcoming Census)
Sample size: planned number of observations
Uganda: Isingiro District: 1200 Ugandan households and 1200 Refugee households Kampala District: 1200 Ugandan households and 1200 Refugee households Ethiopia: Addis Ababa region: 1200 Ethiopian households and 1200 Refugee households Somali region: 1200 Ethiopian households and 1200 Refugee households Note that we are expecting a certain attrition and non-response rate given the refugee-host context in both countries. We expect attrition to be at random, proportionally distributed across treatment groups. Another correction we will make to our sample for relevance is that we are administering the experiment exclusively to individuals who are currently working (employed, self-employed) or unemployed individuals actively looking for a job. That way, we are excluding out of the labor force individuals, who would struggle to relate to the narrative. Consequently, our sample size is likely to reduce, especially among the refugee population who is more likely to be out of the labor force. However, since randomization is stratified based on groups (refugees/hosts) and location (rural/urban), we expect this to be proportional across our four treatment groups. Besides testing our four hypotheses on the entire sample (refugees and hosts in urban and rural areas of Ethiopia and Uganda), we may do some heterogeneous analyses. Therefore we will divide the sample according to these characteristics to disentangle further between groups’ differences in attitudes. The experimental module is part of a large survey executed in the areas of interest. It consists of a household survey where all the members are asked a set of questions related to their socio-economic conditions. This survey lasts about 20 minutes and aims at drawing an extensive picture of the types of households we are interviewing. The household survey is followed by an RSI (Random Sample Individual) survey where one working-age individual is selected at random among all household members. The survey lasts one hour and extensively goes over the labor market history of the respondent. It also includes our experiment and sections related to integration, perception, and networks. Thus, our experiment is administered to one individual per household. Consequently, we do not have to cluster our standard errors at the household level and we are avoiding spillover effects.
Sample size (or number of clusters) by treatment arms
The whole sample is split into 4 treatment arms. When disregarding attrition, non-response, and out-of-the-labor-force individuals by whom the experiment will not be administered, we are left with 2,400 respondents per treatment arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
To detect a minimum effect of 2% of our outcome variable (translated into a 10% increase from our baseline value), we need a sample size of around 2,200 individuals per variation, with a 90% confidence level. We are confident that our sample size is sufficient to get meaningful and interpretable results (with enough power). Such an MDE is realistic given what we find broadly in the literature on these kinds of outcomes of attitudes and beliefs (see for instance Cattaneo and Grieco (2020)). Our randomization implies 2,400 individuals per treatment group (i.e. 1,200 individuals per treatment group and country), and some of our analysis will be based on comparing outcomes of two pooled treatment groups. Thus further power calculations need to be performed to account for these different sample divisions. REFERENCE: Cattaneo, C., & Grieco, D. (2021). Turning opposition into support to immigration: The role of narratives. Journal of Economic Behavior & Organization, 190, 785-801.
Supporting Documents and Materials

Documents

Document Name
IRB Research Approval
Document Type
irb_protocol
Document Description
This is the IRB research approval letter received from Uganda National Council for Science and Technology.

NB: We are not required to apply to an IRB in Ethiopia. The intervention is however fully identical to the one for Uganda.
File
IRB Research Approval

MD5: bb4e88ce4bbe40d6c67081a8fb239334

SHA1: 6d765a4346a6ac1ae9d70d3edb9602ad1ad8b8fa

Uploaded At: January 28, 2022

IRB

Institutional Review Boards (IRBs)

IRB Name
Uganda National Council for Science and Technology (UNCST)
IRB Approval Date
2021-10-11
IRB Approval Number
SS1039ES
Analysis Plan

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Post-Trial

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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

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Reports & Other Materials