Modeling the effect of devolution on youth unemployment rates in Kenya using autoregressive integrated moving average - intervention model
Palavras-chave:
ARIMA-Intervention Model, Devolution, Kenya, Time Series, Youth UnemploymentResumo
Youth unemployment remains a major concern, particularly in African countries with the youngest population globally. In Kenya, youth unemployment rate has shown fluctuations despite several government efforts such as the Youth Enterprise Development Fund (YEDF), Kenya Youth Empowerment Project (KYEP) and the Youth Employment Scheme Abroad (YESA). The impact of devolution on youth unemployment in Kenya has had little investigation on, which is the reason for this study. The study aims to assess the effect of devolution on youth unemployment rates in Kenya, utilizing Autoregressive Integrated Moving Average-Intervention model. This research was informed by the Keynesian and Decentralization theories of employment, which collectively illustrate how government efforts, like introduction of devolution, are anticipated to influence labor market results. This study used the yearly secondary data on youth unemployment rates from the World Bank covering the period from 1991 to 2022. Computational analysis was done using Python programming. An ARIMA (0, 0, 0)(0,0,1)[4] was selected as the most suitable model for the youth unemployment rates prior to devolution (noise model) due to its lowest Akaike Information Criterion (AIC) value of 234.746 in comparison to other identified candidate models. By including devolution as an intervention in the selected noise model, its statistical significance was established at the 0.05 level of significance. Comparative analysis findings revealed that the average youth unemployment rate increased from 6.67% prior to devolution to 10.19% during the devolution period. The projected counterfactual rate during devolution was approximated to be 8.583%, which confirmed the observed increase as statistically significant. In conclusion, the effect of devolution was found to be statistically significant, implying that youth unemployment rates increased during devolution, as confirmed by the fitted ARIMA - Intervention model. Based on the upward trend in youth unemployment rates, the study recommended that policymakers prioritize other context specific and targeted interventions to address structural barriers in the youth labour markets. These should include expanding access to skills training and vocational education, fostering youth entrepreneurship through financing and mentorship programs, and aligning education curriculum with labour market needs.
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Direitos de Autor (c) 2025 Samuel Wesonga Usolo, Dr. Okoth Annette, Dr. David Angwenyi

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