Data · dataset · 2026
G²LM|LIC - Occupational Segregation and Gender Gaps in Nairobi: Disentangling Supply from Demand and Preferences and Beliefs Using Worker and Employer Surveys
Listed in IDSC Dataverse
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.
Description
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.
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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.
Links
Where it is published
- Dataverse dataset page dataverse.iza.org/dataset.xhtml?persistentId=doi%3A10.15185%2Fglmlic.845.1 ↗
landing page · from dataverse iza org
- DOI doi.org/10.15185/glmlic.845.1 ↗
DOI / persistent id · from dataverse iza org
Catalogue records · 1
- Dataverse API dataverse.iza.org/api/datasets/:persistentId/?persistentId=doi%3A10.15185%2Fglml… ↗
metadata API · from dataverse iza org
Topics
- Stated by source
- Social Sciences
- From keywords
- Economics & Finance · Social Science
- Inferred from text
- Employment equity and diversity 81%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| IDSC Dataverse | doi:10.15185/glmlic.845.1 | 4 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:field:350502 | enrichment · dataverse iza org | taxonomy-embedding@1.0.0 | title+keywords+description (81%) |
| concepts[field].dataverse_subject:social-sciences | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /subjects |
| concepts[field].local:field:economics-finance | mapping · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /subjects |
| created_date | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | |
| description | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /description |
| publication_date | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | |
| title | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /name |
| updated_date | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | |
| version_label | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 |