Abstract
The present study seeks to find out how gender, age, area of living, parent background in terms of educational level and occupation determine the probability of youth to be out of the labour market in six Sub-Saharan Africa countries. We utilize data from the school-to-work transition surveys from 2014 and 2015 from the ILO. For each country, we first calculate a revised version of the Human Opportunity Index developed by the World Bank. Second, we compute the contribution of each factor to that index. The results show that dissimilarity has a marked influence in Madagascar and to some extent Malawi and Uganda, while the major challenges with getting the youth onto the labour market are still in Liberia even after taking dissimilarity of unchangeable background into account.
Highlights
Africa is a continent with the youngest population whereby 70% of its population is below 30 years old (Awad 2019)
For Madagascar, we can conclude that factors beyond the control of individuals cause a large chunk of inactivity disparity
A particular policy focus must be on ensuring that youth with the disadvantaged unchangeable background are given extra support to provide them with equal chances of being on the labour market as their peers who were fortunate to be born into better circumstances
Summary
Africa is a continent with the youngest population whereby 70% of its population is below 30 years old (Awad 2019). According to the International Labour Organization (2008) the unemployment rate among the youth in Sub Saharan Africa (SSA) remains below 7% during 1997–2007, while the inactive rate (people who are neither employed or unemployed, e.g., students, retirees, housewives, etc.) during the same period remained high (increased slightly from 42% to 44%). We seek to find out how gender, age, area of living, parent background in terms of educational level and occupation determine the probability of youth to be out of the labour market in these countries. The selection of these variables is based on the preceding and recent empirical literature (Dimova and Stephan 2019; Brunori et al 2019; Assaad et al 2019).
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