Socioeconomic Determinants of Youth Unemployment in Ethiopia, the Case of Wolaita Sodo Town, Southern Ethiopia

Tsegaw Kebede Tegegne


According to UN Secretariat, UNESCO,UNICEF, WHO, UNFPA and ILO youth are defined these individuals whose age is in between 15-24years, while for UN Habitat (Youth Fund) and the African youth charter, the age range is from 15-32 and 15-35, respectively. For others like organization for Economic Co-operation and Development (OECD) defines youth as those men and women in between 15 and 29 years of age.. To achieve the objective of this paper is to examine the socio-economic determinants of urban youth unemployment logistic model was used. A simple random sampling technique employed to select 395 youth were used. Both quantitative and qualitative data were collected from sampled youth unemployed persons through questionnaire and interview. Both descriptive and econometric data analyses techniques were applied. From the econometrics result revealed that confidence ,education status , access to information human related factor, institutional factors ,socioeconomic and demographic factors were significantly affect the youth unemployment status in the study area . The result also indicates that the higher months spent on searching, the higher the probability of getting job. This shows the cost of job search is positively related with employment status of the youth, as cost of search increases the higher the probability of being employed. The result also indicates that educational level of the youth’s household head has a negative and statistically significant effect on employment status of the youth at 10 percent level of significance. This finding is inconsistent with the general fact and the hypotheses of this study. Since confidence level of the youth matters for employment status of the youth, the concerned bodies should develop the confidence level of the youth by providing different trainings for the youth. The concerned body, especially the government should provide facilities related with information access like mass media and magazines in the study area.

Keywords: employment, Youth unemployment Binary logistic regression.

DOI: 10.7176/JESD/10-23-05

Publication date: December 31st 2019

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