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Geographical variation and determinants of women unemployment status in Ethiopia; A multilevel and spatial analysis from 2016 Ethiopia Demographic and Health Survey data
Authors: Solomon Sisay Mulugeta, Shewayiref Geremew Gebremichael, Setegn Muche Fenta, and Berhanu Engidaw Getahun
Source: PLOS ONE , Volume 17, issue 7; DOI:10.1371/journal.pone.0270989.
Topic(s): Employment
Spatial analysis
Women's autonomy
Country: Africa
  Ethiopia
Published: JUL 2022
Abstract: Background: Unemployment is a major problem in both developed and developing countries. In Ethiopia, women unemployment is particularly high, and this makes it a grave socio-economic concern. The aim of this study is to assess the spatial distribution and identify the determinant factors of women unemployment in Ethiopia. Methods: The data used for the study is the Ethiopian Demographic and Health Surveys of 2016. A total of 15683 women are involved in the study. Global Moran's I statistic and Poisson-based purely spatial scan statistics are employed to explore spatial patterns and detect spatial clusters of women unemployment, respectively. To identify factors associated with women unemployment, multilevel logistic regression model is used. Results: A spatial analysis showed that there was a major spatial difference in women unemployment in Ethiopia with Global Moran's index value of 0.3 (p<0.001). The spatial distribution of women's unemployment varied significantly across the country. The major areas of unemployment were Afar and Somalia; southwest Tigray; North and west Oromia, and Eastern and southern parts of Amhara. Women with primary level of education(AOR = 0.88, 95%CI: 0.80, 0.98), secondary and above level of education (AOR = 0.71, 95%CI: 0.62, 0.82), women with rich wealth index (AOR = 0.79, 95% CI: 0.70, 0.90), pregnant women (AOR = 1.24, 95% CI: 1.06, 1.5), women with a male household head(AOR = 1.4, 95% CI: 1.28, 1.50), and urban women(AOR = 0.60, 95% CI: 0.50, 0.70) statistically associated with women unemployment. Conclusion: The unemployment rate of women in Ethiopia showed variation across different clusters. Improving entrepreneurship and women's education, sharing business experiences, supporting entrepreneurs are potential tools for reducing the unemployment women. Moreover, creating community-based programs that prioritize participation of poor households and rural women as well as improving their access to mass media and the labor market is crucial.
Web: https://pubmed.ncbi.nlm.nih.gov/35797384/