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