Unemployment and underemployment in Kenya: a gender gap analysis

Abstract

This paper analyses the gender gaps in open unemployment and underemployment in Kenya, using data from the Kenya Integrated Household Budget Survey 2005/06. Unemployment and underemployment probability functions were estimated separately for men and women, using binary probit specification and the gender gap in each outcome was decomposed to determine what factors explain it. The probit estimates indicate that even after controlling for differences in personal and household characteristics, the women were still more likely than men to be unemployed or underemployed. Observable individual human capital characteristics, marital status, region of residence, non-labour income and individual’s age were significant determinants of unemployment and underemployment. Decomposition results show that most (88.8percent) of the total female-male unemployment probability gap is explained by female-male differences in individual and household characteristics and only 11.2percent is unexplained. In contrast, only 5.4percent of the female-male underemployment probability gap is explained by female-male differences in individual and household characteristics while 94.6percent is unexplained. The key characteristics generating female-male gaps in unemployment and underemployment probabilities in Kenya are region of residence, age, education level, marital status and adverse shocks. This implies that policy interventions that aim to lower gender gaps in unemployment and underemployment should target the most affected age cohorts and locations. Policy should also give priority to interventions that narrow disparities in access to education and those that reduce adverse shocks.