American Journal of Theoretical and Applied Statistics
Volume 9, Issue 5, September 2020, Pages: 228-237
Received: Aug. 28, 2020;
Accepted: Sep. 22, 2020;
Published: Oct. 12, 2020
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Loice Yoda, Department of Mathematics, Multimedia University of Kenya, Nairobi, Kenya
Karanja Anthony, Department of Mathematics, School of Science, Multimedia University of Kenya, Nairobi, Kenya
Pius Kihara, Department of Financial and Actuarial Mathematics, Technical University of Kenya, Nairobi, Kenya
Turkana County experiences re-occurring drought and conflict leading to an increased dependency ratio, injuries, both physical and emotional as well as displacement. This study, using Resilience Index Measurement, Analysis is to determine which factors have the capability to maximize resilience in livelihoods by minimizing the effect of the shock by looking at different ways of how livelihood contributes to household’s coping strategies and capacity during the calamity. Data used in this study was obtained through quantitative method where a sample (n≥384) was drawn from the target population by random sampling from the data collected between 2015 and 2016. Factor loading analysis was done to establish the weights of each resilience component. RIMA model has shown the ability to be an appropriate tool that can deal with both linear and nonlinear regression concepts. The overall Resilience Index of Turkana county was 0.0457 and that gender to some extent is contributing factor in determining the resilience index. The household head for Pastoral category were between 24-41 years, which is young with 28 years as the average age. Access to market facility determines the kind of what livelihood activity individual engages in at 79%. Access to credit significantly affects Resilience of an individual (p < 0.1) thus contributing to diversity in choosing livelihood negatively. Remittances have a negative effect on the fishery and farming livelihoods by 7%.
Strategies of Households Resilience in Adapting to Challenges in Turkana County, American Journal of Theoretical and Applied Statistics.
Vol. 9, No. 5,
2020, pp. 228-237.
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