dc.identifier.citation |
hmad , Z., & Khan , J. (2016). An Analysis of the Causes and Consequences of Unemployment in District Peshawar. SUIT Journal of Social Sciences and Humanities, 1(1), 114-127. Ayieko, Z. O. (2011). Rural electrification programme in Kenya: AEI practitioners workshopl. Nairobi, Kenya: Rural Electrification Authority. Bashir, F., Ahmad, T. I., & Hidayat, T. (2013). Causes of highly educated females' unemployment in Pakistan: A case study of Bahawalnagar district. Pakistan Journal of Humanities and Social Sciences, 1(1), 1-10. Burger, R., & Fintel, D. V. (2009). Determining the Causes of the Rising South African Unemployment Rate: An age, period and generational analysis. Matieland, South Africa : University of Stellenbosch Economic Working Papers: 24/09 . Dagume , M. A., & Gyekye, A. (2016). Determinants of youth unemployment in South Africa: Evidence from the Vhembe district of Limpopo province. Environmental Economics, 7(4), 59-67. Dessie , W. A. (2015). Women and Unemployment in Bahir Dar City, |
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dc.description.abstract |
In 2018, women unemployment globally remained higher in comparison to men at the rate of 6.1 % in relation to 5.1 % for men. To reduce women unemployment, the government of Kenya introduced various policies and programmes to promote women in terms of securing employment. This includes the reservation of 30% of all Government procurement opportunities for women, youth and persons with disabilities and establishment of women fund to increase access to credit to encourage startups among women. In spite of the numerous programs, women unemployment in Kenya has remained above the country’s rate of 7.4%. Several studies have examined the determinants of unemployment. However, there is scanty literature on women unemployment and none has examined the nexus between women unemployment and rural development justifying the study in Kenya. Specifically, the study examined the gender unemployment gap, detected unexpected change in women unemployment and established the effect of rural development on women unemployment in Kenya. Time series data spanning 23 years was analyzed using both descriptive and inferential statistics. Findings indicate that the gender unemployment gap has narrowed significantly to less than 1% from 2007 in relation to years before 2007. Unidirectional causality was established running from rural development to women unemployment with a percentage increase in rural development decreasing women unemployment by 0.2% based on OLS analysis. Thus rural development is a significant determinant of women unemployment. The study recommends that the government should increase its budgetary allocation to programs that can promote rural development such as rural electrification which will open up employment opportunities for majority of poor women living in rural areas. |
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