Competition and Hiring Discrimination: Experimental Evidence from Egypt

Last registered on June 16, 2025

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Pre-Trial

Trial Information

General Information

Title

Competition and Hiring Discrimination: Experimental Evidence from Egypt

RCT ID

AEARCTR-0016104

Initial registration date

June 13, 2025

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 16, 2025, 7:33 AM EDT

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

Locations

Country

Egypt

Region

Greater Cairo

Primary Investigator

Name

Andreas Menzel

Affiliation

University of Padova

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Paolo Falco

PI Affiliation

University of Copenhagen

Contact Investigator

PI Name

Roberta Gatti

PI Affiliation

World Bank Group

Contact Investigator

PI Name

Asif Islam

PI Affiliation

World Bank Group

Contact Investigator

Additional Trial Information

Status

In development

Start date

2025-06-15

End date

2025-09-30

Keywords

Firms & Productivity, Gender, Labor

Additional Keywords

Competition, Gender, Discrimination, Lab-in-the-field experiment

JEL code(s)

J16, J71, M51, O12, O17

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

We study the relationship between the degree of competition firms face on the market for their output goods and hiring discrimination, in particular against women. We do so using a lab-in-the-field experiment with (planned) 500 SME owners or managers (employers) from the Greater Cairo area in Egypt.

For the purpose of this experiment, we create a temporary firm in the data processing sector offering real temporary jobs advertised broadly on local social media sites. We survey around 100 applicants, and based on a suitable subset, we create profiles. We show subsets of these profiles to the SME employers during the survey for them to select prospective employees among the candidates who will be offered the real jobs in the firm. Employers receive a payoff based on the productivity of the worker they select for the job.
We vary the degree of competition between employers by pairing employers in the survey with each other (without revealing their identities to one another), and paying the final payoff only to the employer who selects the worker that turns out to be most productive on the job. The degree of competition is varied by changing the group size of matched employers between one (no competition), two (some competition), and five (stronger competition).

We also randomly vary across employers whether the worker profiles contain a signal of the workers' productivity. The signal is based on a test run of the data task that workers undergo at the recruitment interview. This variation will be used to test for the effects of competition on taste-based versus statistical discrimination.

External Link(s)

Registration Citation

Citation

Falco, Paolo et al. 2025. "Competition and Hiring Discrimination: Experimental Evidence from Egypt." AEA RCT Registry. June 16. https://doi.org/10.1257/rct.16104-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

The experiment is based on a survey of SME owners/managers ("employers"). During the survey, respondents are asked to select workers for a real, paid, temporary job in a data management company the PIs are setting up for this study. The employers chose from sets of worker profiles shown to them during the surveys. The candidates are applicants who responded to an advertisement we posted online prior to the survey. They have been interviewed and are deemed suitable for the task. Employers receive experimental payoffs based on the productivity of the selected workers in the real job later on. Each employer makes six decisions over six different sets of workers.

The key experimental manipulations are:

(1) Differing sets of workers between choices within employer

(2) Whether the worker profiles contain a productivity signal based on a test performed during the recruitment interview.

(3) Degree of competition: employers are paired with none, one, or four (possibly more) other employers who are also taking part in the survey. In cases where employers have competitors, the productivity-based payoff is only paid to the employer who selects the most productive worker.

(4) Whether the job is a common employee position or a supervisory role.

(5) The rate at which an employer's productivity-based payoff is linked to the productivity of the selected worker.

Intervention (Hidden)

Intervention Start Date

2025-06-15

Intervention End Date

2025-08-31

Primary Outcomes

Primary Outcomes (end points)

Gender of the worker profile selected by the employer in each decision during the survey.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

We will aim to survey 500 SME owners/managers ("employers"). During the survey, participants will make six decisions, each time selecting one worker out of a set of profiles of candidates. One of the six decisions of each employer will be randomly selected, and the candidate chosen in that decision will be offered a real temporary (one-week) job at a survey data firm set up by the researchers for this experiment. The employer will receive a bonus based on the productivity of the chosen worker in the real job. The profiles are based on real applicants who applied for the job, which we advertised on social media.

Three of the decisions will be for an ordinary employee role in the firm, while the other three will be for a supervisor role.

The degree of competition will vary between decisions within employers. Competition will be simulated by randomly pairing an employer with other employers participating in the survey, and paying the worker-productivity-based bonus only to the employer in the pairings that selects the worker who turns out to be most productive later on in the job. One-third of the decisions will be in a setting where the employer is not paired with any other employer (no competition), one-third with the employer being paired with one other employer, and one with the employer being paired with four (possibly more) other employers. We will randomize the order of these three types of decisions.

Employers will be randomized into whether or not they will see a signal of the productivity of all candidates in all decisions. This signal is the productivity score the candidates achieved in a 30-minute test run of the data entry work conducted at the time of the recruitment interview.

Finally, employers will be randomized into three groups across which we vary the piece rate at which the average productivity of the selected worker is translated into the bonus payment for the employer (low, medium, high).

We will do the following heterogeneity analysis:
- Productivity information on candidates provided on profiles
- Employer being male or female
- Employer being above/below median educated in sample
- Employer being above/below median age in sample
- Employer running a business in a sector with low female labor worker share (according to representative Egyptian labor force surveys)
- Employer identifies as a religious person
- Employer has daughters as first child (conditional on having children)
- Most productive female worker has children
- Most productive female worker has at least some university education

Experimental Design Details

Randomization Method

Randomization done within the Survey, programmed in Survey CTO, and displayed on the tabs carried by the enumerators

Randomization Unit

Survey respondents (employers)

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

500 employers

Sample size: planned number of observations

3000 (500 employers times 6 decisions)

Sample size (or number of clusters) by treatment arms

(1) Degree of Competition: 1000 decisions under no competition, 1000 under some competition, 1000 under stronger competition

(2) Availability of Productivity Signals: 1500 decisions without signal, 1500 decisions with signal

(3) Piece rate for employer bonus: 1000 decisions low, 1000 decisions medium, 1000 decisions high.

Cross-randomization of (2) and (3).

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

IRB