Gender discrimination in hiring in poor countries: the role of trust

Last registered on June 25, 2024

Pre-Trial

Trial Information

General Information

Title
Gender discrimination in hiring in poor countries: the role of trust
RCT ID
AEARCTR-0013698
Initial registration date
June 19, 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
June 25, 2024, 10:45 AM EDT

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

Locations

Region

Primary Investigator

Affiliation
BROWN UNIVERSITY

Other Primary Investigator(s)

PI Affiliation
Geneva Graduate Institute

Additional Trial Information

Status
In development
Start date
2024-06-10
End date
2024-07-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Gender segregation in labor markets is a prevalent issue in poor countries, leading to significant wage gaps and talent misallocation. Efforts to address this segregation by promoting female labor supply depend on the level of discrimination women face upon entering the labor market. Our study tests for gender discrimination in Uganda, characterized by severe asymmetric information problems. Partnering with a vocational training center, we conduct an experiment with employers to examine the effect of gender on hiring decisions for trainees.
Our key intuition is that, in contexts characterized by severe asymmetric information, trustworthiness is a key determinant of hiring decisions. Given the evidence that women are generally perceived as more prosocial/trustworthy, we investigate whether this perception induces a comparative advantage for women in the labor market. We conduct two primary analyses: first, we assess gender differences in hiring outcomes; second, we examine how these gender differences evolve as the relevance of asymmetric information (moral hazard) in hiring decreases. We also examine the interplay with ability, gender preferences, and the drivers of women/men perceived differences in trustworthiness. We compare managers' beliefs about gender differences in behavior with data on actual behavior of job seekers.



External Link(s)

Registration Citation

Citation
Macchi, Elisa and Claude Raisaro. 2024. "Gender discrimination in hiring in poor countries: the role of trust." AEA RCT Registry. June 25. https://doi.org/10.1257/rct.13698-1.0
Experimental Details

Interventions

Intervention(s)
Our study investigates gender discrimination in hiring within male-dominated sectors in Uganda, focusing on the roles of trustworthiness and ability. We partner with vocational training centers to conduct an experiment with hiring managers. Hiring managers are presented with example CVs of vocationally trained workers. These CVs are designed to represent potential candidates they might consider hiring, and are randomly assigned to be either male or female workers. This randomization allows us to examine gender-based differences in hiring preferences. Managers indicate their hiring preferences based on the provided CVs, knowing that we will refer workers with characteristics they favor. To test the effect of asymmetric information (moral hazard) on gender differences in hiring, we randomize the provision of monitoring support to the managers. We have a pure control arm with no monitoring support, one treatment arm where monitoring support focuses on stealing and other common misbehavior practices, and one active control arm where the monitoring support focuses on workers' safety and wellbeing.
Intervention (Hidden)
Hiring managers are presented with example CVs of vocationally trained workers. The CV content is randomized from workers' registration files and GPA data from from the partner vocational training centers. Each CV has both a male and female version, and a low and high GPA version, resulting in 24 unique CVs with 96 combinations. Profiles are presented using the Incentivized Resume Rating Paradigm (Kessler et al. 2019).

Each manager evaluates 24 randomly selected profiles, which are stratified by gender, and ability. We display the CVs in random order and in blocks of 8 with breaks in-between. For each profile, the manager decides whether they want to be matched with a similar worker to start a probation period at the firm. Firms are incentivized to hire the workers with an amount of money that covers transport, food and other worker-related costs. Moreover, firms are randomized to receive or not monitoring support from the experimenters.

Audit visits performed by local team members. Both managers and workers are informed of the visits, but they are not announced.

There are two types of visits that we provide, and the type of visit is randomized at the firm level. One third of the sample is randomized to monitoring support that aims at reducing workers' stealing and other common misbehaviors via monitoring. One third of the sample is randomized to monitoring support that aims at preventing harassment and promoting safety of the workers. The last third of the sample is assigned to a pure control, and receives no visits.
Intervention Start Date
2024-06-10
Intervention End Date
2024-07-31

Primary Outcomes

Primary Outcomes (end points)
OFFER: Beliefs about hiring worker after the probation period (0-10)
MEET: choice of receiving the referral of a person like the respondent (yes/no).
Primary Outcomes (explanation)
- Offer: main outcome measure of hiring;
- Meet: measure of interest in the candidate -- which may include the interest in meeting profiles which are rare/uncommon (e.g., women mechanics).

Secondary Outcomes

Secondary Outcomes (end points)
- Quality: beliefs about workers worker's skills on a 0-10 scale
- Behavior: beliefs about workers behavior (trustworthiness, honesty, skills) on a 0-10 scale
- Effort: beliefs about workers effort (hardworking, not lazy, focused, punctual) on a 0-10 scale
- Earnings: beliefs about workers' earnings a year from the experiment (UGX)
Secondary Outcomes (explanation)
- Quality: measure of workers' skills
- Behavior: measure of workers' moral hazard (misbehavior)
- Effort: measure of workers' moral hazard (productivity)
- Earnings: measure of workers' outside options

Experimental Design

Experimental Design
Each CV is randomly assigned to a combination of gender (female/male) and ability (GPA 5 out 5 / GPA 3 out of 5).

Monitoring support randomization at the manager level:

T0) Pure Control Arm: Receives no monitoring support.
T1) No Harassment Monitoring: Focuses on monitoring workers' safety and wellbeing.
T2) Moral Hazard Monitoring: Focuses on monitoring moral hazard, specifically misbehavior (stealing, disrespect etc).
Experimental Design Details
We incentivize the exercise by matching employers and workers. We track whether the matching works by recording if the worker is contacted by the manager (viceversa) and if the worker ends up starting a probation period at the firm. If a matching occurs, we provide audit visits irrespective of the treatment.

Additional data cleaning and analysis points:

- We drop observations where the respondent refused to answer to the question (-88) .

- We exclude from our analysis observations for which there is no variation in the primary outcomes across a block of 8 CVs.

- We exclude from our analysis observations for which the respondent did not pass the understanding checks. We drop observations where respondents assigned to T1 do not select safety as the purpose of the visits, and respondents assigned to T2 do not select no stealing and misbehavior checks as the purpose of the visits.

- We cross-randomize ability and gender in the CVs to be able to establish the interaction between gender and ability on gender differences in hiring (statistical discrimination test).

- We plan to run the following heterogeneity analysis by managers' characteristics at baseline: 1) optimal gender composition in firm (median); 2) whether they normally hire from vocational training centers and 3) hiring manager's gender.

- In our main regression we control for CV fixed effects and manager fixed effects. We cluster standard errors at the manager level.
Randomization Method
Randomization done in office by a computer.
Randomization Unit
CV level randomization for gender; Manager level randomization for monitoring.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
300 hiring managers from sector "mechanics". We will expand to other male-dominated sectors if we do not reach the target because of lack of firms within the Kampala metropolitan area.
Sample size: planned number of observations
7200 CVs
Sample size (or number of clusters) by treatment arms
Gender treatment: 3600 male CV and 3600 female CV.
Monitoring treatment: 100 managers (2400 CVs) in each arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Uganda National Council for Science and Technology
IRB Approval Date
2024-06-06
IRB Approval Number
SS2574ES
IRB Name
Mildmay Uganda
IRB Approval Date
2024-04-12
IRB Approval Number
REF04082023

Post-Trial

Post Trial Information

Study Withdrawal

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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

Relevant Paper(s)

Reports & Other Materials