MODELING DETERMINANTS OF YOUTH UNEMPLOYMENT STATUS AT REGIONAL STATE, ETHIOPIA:APPLICATION OF MULTILEVEL ANALYSIS

Abstract

Unemployment is a serious socio-economic problem that affects people of all ages in both developing and developed countries. Ethiopia's labor market development is based on a rapid increase in labor supply. Thus, in order to reflect on the current employment situation and forecast future changes, it is necessary to analyze and identify the factors that contribute to the youth unemployment situation. The main objective of this research was to identify how socio-economic and demographic factors were contributing to unemployment in the regional areas of Ethiopia. To achieve this objective two-level logistic regression was employed. In this study, a total of 17,021 region youths nested within 68 enumeration areas were considered from the 2020 region Employment and Unemployment Survey (REUS) conducted by the Ethiopian Statistics Services (ESS) of Ethiopia. In this study, multilevel logistics regression model was better fitted to the data than single logistics regression model. The results of the intra-class correlation coefficient (ICC) confirmed that there is variation in region youth unemployment across the enumeration areas. The study revealed that region youth unemployment was significantly varied by factors such as gender, age, educational level, kinship, and marital status compared to 5% level significant. As a result, this study revealed that being male, 20-29 years age, being having of vocational and above educational level, being head of household kinship role, being single marital status are more significant factors for being an unemployed regional youth. Therefore, highlighting the need for intervention on identified socio-demographic factors will address these issues and reduce regional youth unemployment.