A new coworker: better a male, a female or a friend?

Last registered on November 17, 2021

Pre-Trial

Trial Information

General Information

Title
A new coworker: better a male, a female or a friend?
RCT ID
AEARCTR-0008036
Initial registration date
August 30, 2021
Last updated
November 17, 2021, 5:59 PM EST

Locations

There are documents in this trial unavailable to the public. Use the button below to request access to this information.

Request Information

Primary Investigator

Affiliation
Bocconi University

Other Primary Investigator(s)

PI Affiliation
University of California Berkeley

Additional Trial Information

Status
In development
Start date
2021-08-26
End date
2022-09-30
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
In Uganda, the persistence of gender segregated labor markets results in the clustering of women within the least lucrative sectors, a trend that is generally observed in developed and developing countries (World Bank, 2011; Campos et al, 2015; Das; Kotikula, 2019). The proposed project examines the extent of gender bias perpetuated by employees through the referral system, which is a significant driver behind hiring decisions within informal labor markets. We present employees of businesses operating in highly segregated occupations with profiles of potential candidates to investigate their gender preferences as well as how these preferences interplay with personal connection to the candidate. On a small subsample we use monetary incentives to gain insight into the range of the value that respondents place upon upholding this form of discrimination. We also assess whether information shocks and changes in confidentiality can change the referring preferences of employees over candidates.
External Link(s)

Registration Citation

Citation
Alfonsi, Livia and Pedro de Souza Ferreira. 2021. "A new coworker: better a male, a female or a friend?." AEA RCT Registry. November 17. https://doi.org/10.1257/rct.8036-1.1
Sponsors & Partners

There are documents in this trial unavailable to the public. Use the button below to request access to this information.

Request Information
Experimental Details

Interventions

Intervention(s)
The experiment will offer to successful alumni of VT institutions in Uganda the opportunity of referring someone to a 1-month subsidized internship at their company. We will show to each of them a pair of profiles that match their respective trainings but that differ in quality. Respondents will also have the chance to refer a person they know. We will cross-randomize the sample in three ways. First:

- High quality male: the high-quality profile will bear a male name and the low-quality profile will bear a female name;
- High quality female: the high-quality profile will bear a female name and the low-quality profile will bear a male name;

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;

We also assess the impact of money incentives and information shocks in nudging respondents to pick a candidate whose gender does not match the dominance of the respondent’s training area. We randomize those who pick a candidate whose gender matches the dominance of the sector into three types of nudges to evaluate the extent to which we can shift such preferences. The first nudge is offering increased monetary incentives in case of retention for the candidates whose gender does not match the dominance of the sector. The second nudge is reading a text describing empirical evidence about the benefits of diversity in the work environment. The third nudge is a combination of the previous two incentives.
Intervention Start Date
2021-08-26
Intervention End Date
2021-10-31

Primary Outcomes

Primary Outcomes (end points)
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-conforming candidates, which we define as candidates whose gender does not match the gender that prevails in the sector. We identify three primary outcomes of interest:

Outcome 1: choice_hq
First, we look at the probability that the respondent picks the high-quality candidate. For each respondent, the outcome of interest takes value one if the high-quality candidate was selected for referral or zero otherwise. Assuming that respondents are quality-seeking in their referrals, we expect the high-quality candidate to always be picked and that any deviation is due to the gender randomly allocated to the unknown high-quality candidate. We strengthen the assumption of quality-seeking behavior by offering a monetary reward for the respondent in case the unknown candidate is retained. In this part, we are interested in the average discrimination against women.

Outcome 2: choice_nonconforming
Second, we consider the probability that the respondent picks the candidate whose gender does not match the dominance of the sector. For each respondent, this second outcome of interest takes value one if the gender of the referred candidate does not match the gender-dominance of the trade.

Outcome 3: selected_prob
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. This primary outcome might be explained by the candidate’s quality, the candidate’s gender, the respondent’s gender, whether he/she is a known or unknown candidate, and whether the gender of the candidate matches the dominance of the sector.

The main outcomes are analyzed both for the choice the respondent makes between the two known candidates as well as for the choice between the unknown candidates. We will also assess whether private referrals increase the probability of referring a female and a non-conforming candidate.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
- Decision to change the referral after treatment
- Ranking of candidates
- Rating of the quality of unknown candidates
- Rating of the likability of unknown candidates
- Rating of the quality of network candidates
- Rating of the likability of network candidates
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This study is 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 2 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 pre-made profiles based on real-life candidates and ask for respondents to refer one of the candidates for a 1-month 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 unknown 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. At the end, if the respondent picks a candidate whose gender matches the dominance of the sector, we will test whether they would change their choice according to certain incentives.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer on a statistical software (STATA).
Randomization Unit
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 at least one of the previous 3 survey rounds).
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
700 VTI alumni.
Sample size: planned number of observations
700 VTI alumni.
Sample size (or number of clusters) by treatment arms
First: Gender of high-quality candidate. Out of the 700 VTI alumni, 350 will be shown a high-quality male and a low-quality female. The other 350 alumni will be shown a high-quality female and a low-quality male.

Second: Publicity of referral. Out of the 700 VTI alumni, 350 will be said that the referrals will be public and that the business owner will know that they referred that candidate. The other 350 will be said that the referrals will be PRIVATE and that the business owner will NOT know that they referred that candidate.

Third: Incentive to pick a non-conforming candidate. The 700 VTI alumni will be randomly assigned to three groups:

- Nudge 1 (money incentive): 235 alumni.
- Nudge 2 (information shock): 235 alumni.
- Nudge 3 (money incentive + information shock): 230 alumni.

However, the money incentive will not exist if the respondent said they were NOT wage-employed in August. We do not expect money incentives to have a bite on non-wage-employed candidates, for which the questions will be only hypothetical. For this reason, we keep the variation in money incentive only for wage-employed respondents. We expect 65% of the VTI alumni to be wage employed in August, as predicted by the last end line.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number