A Bayesian Hierarchical Modelling of Small Area Variation in Youth Unemployment in Namibia

Linda Shitenga, Namibia Statistics Agency
Petrus Iiyambo, University of Namibia

The government frequently finds it difficult to implement employment creation measures despite Namibia's high youth unemployment rate because there is a lack of up-to-date small-area labour market statistics. Using the 2018 Namibia Labour Force Survey data, Bayesian hierarchical modelling was used to estimate the risk of youth unemployment in Namibia at the constituency level. The findings demonstrated that youth unemployment varies greatly across constituencies, and rural youths are more likely to be unemployed than those in urban areas. In urban constituencies, male youths had a much higher chance of unemployment than female youths. Furthermore, youth without formal education are more likely to be unemployed as compared to those with formal education. The study recommends that more priority be given to integrating the youth into the labour market by improving their educational levels and implementing labour market policies to facilitate entry into the labour market of rural youths. Keywords: Unemployment, youth, small area estimation, Hierarchical Bayesian, Namibia