The Factors determining female unemployment in South Africa: Evidence from the 2021 Labour Force Survey.

The persistent high unemployment confronting South Africa, in particular among women continues to be a cause of concern. The study set out to look at the factors driving female unemployment in South Africa in an attempt to contribute to efforts to find a solution to the problem of female unemployment. This study estimated the prevalence of female unemployment and identified its predictors in South Africa. Quarterly Labour Force Survey covering the fourth quarter of 2021 and a weighted sample of 13322 women aged 15-64 years were used. The dependent variable of interest was unemployment, while the independent variables were the age, population group, marital status, level of education, province of residence and geographic type. The analysis was conducted at bivariate and multivariate levels. It was found that female unemployment rates are significantly influenced by factors that include level of education, women in youth age category, differed among population group and marital status. The female unemployment varied significantly among provinces of residence and geographic type, with the highest prevalence rates observed in Eastern Cape, KwaZulu Natal, Gauteng and Limpopo. The study further found high unemployment rate in urban areas while traditional areas had high rates of discouraged job seekers.

Authors

Institutions

Publication Details

Journal
Journal of African Population Studies
Published
2024-10-02
DOI
https://doi.org/10.59147/japs_d8tz7upv
Citations
1
Primary Topic
Labor market dynamics and wage inequality
Type
article
Field-Weighted Citation Impact
1.13
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Factors determining female unemployment in South Africa: Evidence from the 2021 Labour Force Survey.

Anele, Philomene
1 citations
Journal of African Population Studies
Labor market dynamics and wage inequality
1.13
article

The Factors determining female unemployment in South Africa: Evidence from the 2021 Labour Force Survey.

Anele, Philomene
article en
1 citations

Abstract

The persistent high unemployment confronting South Africa, in particular among women continues to be a cause of concern. The study set out to look at the factors driving female unemployment in South Africa in an attempt to contribute to efforts to find a solution to the problem of female unemployment. This study estimated the prevalence of female unemployment and identified its predictors in South Africa. Quarterly Labour Force Survey covering the fourth quarter of 2021 and a weighted sample of 13322 women aged 15-64 years were used. The dependent variable of interest was unemployment, while the independent variables were the age, population group, marital status, level of education, province of residence and geographic type. The analysis was conducted at bivariate and multivariate levels. It was found that female unemployment rates are significantly influenced by factors that include level of education, women in youth age category, differed among population group and marital status. The female unemployment varied significantly among provinces of residence and geographic type, with the highest prevalence rates observed in Eastern Cape, KwaZulu Natal, Gauteng and Limpopo. The study further found high unemployment rate in urban areas while traditional areas had high rates of discouraged job seekers.

Journal of African Population StudiesVol. 37(1)
University of the Western Cape (ZA)
Openalex Percentile: Top 10%
Labor market dynamics and wage inequality
1.13
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.