G²LM|LIC - Occupational Segregation and Gender Gaps in Nairobi: Disentangling Supply from Demand and Preferences and Beliefs Using Worker and Employer Surveys

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Orkin, Kate; Alison, Andrew; Inbar, Amit; Barker, Nathan; Garlick, Robert; Nekesa, Carol, 2026, "G²LM|LIC - Occupational Segregation and Gender Gaps in Nairobi: Disentangling Supply from Demand and Preferences and Beliefs Using Worker and Employer Surveys", https://doi.org/10.15185/glmlic.845.1, Research Data Center of IZA (IDSC), V1

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Description	This dataset accompanies the project Occupational Segregation and Gender Gaps in Nairobi: Disentangling Supply from Demand and Preferences and Beliefs Using Worker and Employer Surveys. The study investigates how worker preferences, employer preferences, beliefs, and job search strategies jointly contribute to occupational segregation and gender wage gaps in Nairobi, Kenya. The dataset contains employer survey data collected from 601 firms across Western and Central Nairobi between March and May 2024. It provides detailed information on firms’ hiring practices, employee characteristics and wages, and employer evaluations of hypothetical job applicants presented through randomized CV vignettes. The survey measures hiring behaviour, labour demand, employer beliefs about worker productivity, expected job acceptance, and anticipated worker retention. The data include information on firms’ most recent hires, permanent employees, and short-term or on-demand workers, enabling analyses of hiring decisions, workforce composition, and gender differences across sectors. The vignette experiment randomly varies applicant characteristics—including gender, age, work experience, residential location, and referral status—to identify employer preferences and potential discrimination during recruitment. Together, the datasets provide a comprehensive resource for studying occupational segregation, employer behaviour, hiring discrimination, labour demand, and gender inequality in urban labour markets in Kenya.
Subject	Social Sciences
Keyword	employer survey, gender, hiring, labour markets, occupational segregation, recruitment, survey experiment, wages, worker survey, workplace discrimination
License/Data Use Agreement	IIL-1.0

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Citation Metadata

Persistent Identifier	doi:10.15185/glmlic.845.1
Publication Date	2026-08-02
Title	G²LM\|LIC - Occupational Segregation and Gender Gaps in Nairobi: Disentangling Supply from Demand and Preferences and Beliefs Using Worker and Employer Surveys
Author	Orkin, Kate (University of Oxford) Alison, Andrew (University of Oxford; Institute for Fiscal Studies) Inbar, Amit (University of Oxford) Barker, Nathan (Northwestern University) Garlick, Robert (Duke University) Nekesa, Carol (REMIT Kenya)
Point of Contact	Use email button above to contact. Admin, Dataverse (IZA)
Description	This dataset accompanies the project Occupational Segregation and Gender Gaps in Nairobi: Disentangling Supply from Demand and Preferences and Beliefs Using Worker and Employer Surveys. The study investigates how worker preferences, employer preferences, beliefs, and job search strategies jointly contribute to occupational segregation and gender wage gaps in Nairobi, Kenya. The dataset contains employer survey data collected from 601 firms across Western and Central Nairobi between March and May 2024. It provides detailed information on firms’ hiring practices, employee characteristics and wages, and employer evaluations of hypothetical job applicants presented through randomized CV vignettes. The survey measures hiring behaviour, labour demand, employer beliefs about worker productivity, expected job acceptance, and anticipated worker retention. The data include information on firms’ most recent hires, permanent employees, and short-term or on-demand workers, enabling analyses of hiring decisions, workforce composition, and gender differences across sectors. The vignette experiment randomly varies applicant characteristics—including gender, age, work experience, residential location, and referral status—to identify employer preferences and potential discrimination during recruitment. Together, the datasets provide a comprehensive resource for studying occupational segregation, employer behaviour, hiring discrimination, labour demand, and gender inequality in urban labour markets in Kenya.
Subject	Social Sciences
Keyword	employer survey gender hiring labour markets occupational segregation recruitment survey experiment wages worker survey workplace discrimination
Language	English
Funding Information	Gender, Growth and Labour Markets in Low Income Countries (G²LM\|LIC) Global Challenges Research Fund (UKRI Accelerating Adolescent Achievement Hub)
Depositor	Admin, Dataverse
Deposit Date	2026-07-31
Time Period	Start Date: 2024
Date of Collection	Start Date: 2024-03 ; End Date: 2024-05
Data Type	Survey data, Experimental data

Geospatial Metadata

Geographic Coverage	Kenya, Nairobi
Geographic Unit	Enumeration Areas (EAs) within Western and Central Nairobi

Social Science and Humanities Metadata

Unit of Analysis	Firms, Hiring managers, Individual workers, Individual hiring events, Hypothetical job applicants (CV vignettes)
Universe	Businesses with at least three employees operating in eight selected sectors in Western and Central Nairobi, Kenya. Survey respondents were the individuals responsible for hiring and staffing decisions within participating firms. Worker-level datasets additionally include information on permanent and short-term employees employed by sampled firms.
Time Method	Cross-sectional
Data Collector	University of Oxford research team in collaboration with REMIT Kenya.
Frequency	One-time survey
Sampling Procedure	Multi-stage sampling. Business corridors were identified using surveys of young adults, consultations with Nairobi residents, and Google Maps. Enumeration Areas (EAs) were constructed and verified through field visits. Businesses were enumerated through a census, after which eligible firms with at least three employees operating in eight target sectors were selected for the main employer survey. Of 1,624 listed businesses, 703 were eligible, and 601 completed the survey.
Target Sample Size	703
Collection Mode	Computer-assisted personal interviewing (CAPI)
Type of Research Instrument	Structured employer questionnaire including: firm characteristics, hiring history, employee roster, wages, randomized CV vignette experiment.
Characteristics of Data Collection Situation	Face-to-face interviews conducted with the individual responsible for hiring and staffing decisions within each participating firm.
Actions to Minimize Losses	Appointment scheduling with hiring managers following the business census.
Control Operations	Questionnaires administered using SurveyCTO with standardized electronic instruments. Randomization of vignette characteristics was embedded within the survey instrument.
Cleaning Operations	SurveyCTO-generated datasets were processed into four analytical datasets corresponding to firms, hiring events, permanent workers, and short-term workers.

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