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