Whom Would You Rather Work With?

The experiment will offer to successful alumni of VT institutions in Uganda the opportunity of referring someone to a 6-week subsidized internship at their company. We will show to each of them a pair of profiles that match their respective trainings. The pair of profiles will always have different gender. Respondents will also have the chance to refer a person they know. We will cross-randomize the sample in three ways. First:

- Group 1 (High quality male and High quality female): respondents are shown a randomly generated male profile with 11 months of work experience and a randomly generated female profile with 11 months of work experience;
- Group 2 (High quality male and Low quality female): respondents are shown a randomly generated male profile with 11 months of work experience and a randomly generated female profile with 6 months of work experience;
- Group 3 (Low quality male and High quality female): respondents are shown a randomly generated male profile with 6 months of work experience and a randomly generated female profile with 11 months of work experience;
- Group 4 (Low quality male and Low quality female): respondents are shown a randomly generated male profile with 6 months of work experience and a randomly generated female profile with 6 months of work experience.

When asked about these profiles, respondents will be told that they are willing to accept the internship if offered it.

Second:

- Public referral: the business owner will know who referred the candidate and the respondent will be warned that his/her referral will be PUBLIC;
- Private referral: the business owner will NOT know who referred the candidate and the respondent will be warned that his/her referral will be PRIVATE (i.e., we will tell the respondent that we are going to approach their employer saying that an ANONYMOUS WORKER in the firm chose to refer the chosen candidate to a subsidized internship position; in other words, the employer will NOT be told that the referral came from the research team/implementing partner, but from a worker within the firm);

Third, we also cross-randomize a vignette experiment to understand the mechanisms of referrals:

- Vignette group 1: we present two scenarios, one in which a man applies to a job by walking in and another in which a man applies to a job through a referral.
- Vignette group 2: we present two scenarios, one in which a woman applies to a job by walking in and another in which a woman applies to a job through a referral.
- Vignette group 3: we present two scenarios, one in which a woman applies to a job by walking in and another in which a man applies to a job through a referral.
- Vignette group 4: we present two scenarios, one in which a man applies to a job by walking in and another in which a woman applies to a job through a referral.

In the vignette experiment, the order of the scenarios shown is also randomized.

2023-06-20

2023-07-31

We want to assess to what extent gender biases exist in referrals performed by our respondents. Specifically, we are interested in measuring the existence and relevance of two potential biases: against females and against the non-stereotypical candidates, which we define as candidates whose gender does not match the gender that prevails in the sector. We identify the primary outcomes of interest:

Outcome 1: Probability of picking a female profile AND Difference in probability of picking the female profile and male profile (respondent-level)
First, we look at the probability that the respondent picks the female candidate for the 6-week internship. Similarly, we look at the gap in probabilities of choosing the profile of one gender or the other.

Outcome 2: Probability of picking a profile of a non-stereotypical gender (respondent-level)
Second, we consider the probability that the respondent picks the candidate whose gender does not match the dominance of the sector.

Outcome 3: Probability of being picked (profile-level)
Additionally, in line with other audit studies that analyze the success of candidates using callbacks (Bertrand and Mullainathan, 2004; Booth and Leight, 2010; Becker et al., 2019), we intend to analyze the performance of the fake candidates individually by looking at their probabilities of being selected by the respondent. For each candidate, the probability of being selected is one if the respondent refers him/her or zero otherwise. The dependent variables shall be the gender of the profile, the quality of the profile, and interaction term -- plus profile fixed effects.

Outcome 4: Probability of picking a network member (respondent-level)

Outcome 5 (vignettes): how happy the employer will be with the candidate, how much the coworkers will like to work with the candidate, how likely the candidate is to have all qualifications for the job, and how likely the candidate is to stay in the job for one year.

We will carry out heterogeneity analysis on the following variables: gender of respondent, gender dominance of the sector of training, sector of training, respondent IS wage-employed when interviewed, gender of employer, size of the business, share of male workers in the business (and dummy for above and below median), share of male customers in the business (and a dummy for above and below median), gender attitudes of the respondent, perceived gender attitudes in the training area, and perceived gender attitudes of customers and employer.

Gender attitudes of the respondent is an index of 8 components (2 questions on gender attitudes in the household, 6 questions on gender attitudes in the labor market). Gender attitudes in the sector is an index of 6 components (6 questions similar to those asked to the respondent). Gender attitudes of the employer is an index of 3 components (3 questions similar to those asked to the respondent -- but we ask what would the employer say) and a question from 0-10 on "How open is your employer to hiring workers from the non-stereotypical gender?". Gender attitudes of customers is a question from 0-10 on "How open are your customers to being served/handled by workers of the non-stereotypical gender?".

- Ranking of candidates
- Rating of the quality of anonymous candidates
- Rating of the likability of anonymous candidates
- (After asking to losen the assumption that profiles will accept the job) Rating of the probability of accepting the offer of anonymous candidates
- Rating of the quality of network candidates
- Rating of the likability of network candidates
- Rating of the probability of accepting the offer of network candidates

We will carry out heterogeneity analysis on the following variables: gender of respondent, gender dominance of the sector of training, sector of training, respondent IS wage-employed, gender of employer, size of the business, share of male workers in the business (and dummy for above and below median), share of male customers in the business (and a dummy for above and below median), gender attitudes of the respondent, perceived gender attitudes in the training area, and perceived gender attitudes of customers and employer.

Gender attitudes of the respondent is an index of 8 components (2 questions on gender attitudes in the household, 6 questions on gender attitudes in the labor market). Gender attitudes in the sector is an index of 6 components (6 questions similar to those asked to the respondent). Gender attitudes of the employer is an index of 3 components (3 questions similar to those asked to the respondent -- but we ask what would the employer say) and a question from 0-10 on "How open is your employer to hiring workers from the non-stereotypical gender?". Gender attitudes of customers is a question from 0-10 on "How open are your customers to being served/handled by workers of the non-stereotypical gender?".

This study is an extension of a previously registered trial (AEARCTR-0008036), that was a spin-off of the Meet Your Future Project (MYF), an RCT designed to analyze a career-coaching program for Ugandan vocational students aimed at reducing labor market access inequities for socioeconomically disadvantaged students. Both the main and the spin-off study are conducted in collaboration with the NGO BRAC, who implemented all data collections and interventions, and five reputable vocational training institutes (VTIs) in Central and Eastern Uganda. The experimental evidence from this study will come from a cohort of 700 successful alumni from vocational training institutes which the research team has been following for more than 4 years as part of the MYF Project. We will leverage a soon-to-be-launched survey and add an extra module to explore how gender preferences in segregated occupations interplay with a referral-based hiring system.

We will show to respondents pairs of randomly generated profiles based on real-life candidates and ask for respondents to refer one of the candidates for a 6-week subsidized internship program in the companies of respondents. Selected candidates will be called for the program based on a lottery system. Respondents will also have the chance to name up to two network members and select one of them instead of the anonymous candidates. To ensure all respondents have quality-seeking behaviors, we will offer to all of them a monetary reward if the candidate is retained. Non-wage-employed respondents will answer the survey only hypothetically, as their choices will not be part of the lottery and they will be offered no money.

Not available

Randomization done in office by a computer on a statistical software (STATA).

Individual-level randomization, stratified by gender, sectoral gender dominance (male/female dominated sector), wage employed in previous end line and hard to find dummy (which takes value one if the respondent was not found in the previous survey round).

No

600 VTI alumni.

600 VTI alumni.

Main randomization:

- Group 1 (High quality male and High quality female): 150
- Group 2 (High quality male and Low quality female): 150
- Group 3 (Low quality male and High quality female): 150
- Group 4 (Low quality male and Low quality female): 150

Cross-randomization:

- Public referral: 300
- Private referral: 300

Vignettes:
- Vignette group 1: 150
- Vignette group 2: 150
- Vignette group 3: 150
- Vignette group 4: 150