Determinants of youth unemployment in Uganda: The role of gender, education, residence, and age

Abstract Youth unemployment in Uganda increased from 12.7% in 2012/13 to 13.3 in 2016/17, despite a decline in the overall national unemployment rate from 11.1% to 9.2%. This poses serious development challenges, particularly to the ongoing efforts to poverty reduction. The main objective of the current study is to examine the extent to which gender, education, residence, and age determine youth unemployment in Uganda. Using recent data from the Uganda National Household Survey 2016/17 collected by the Uganda National Bureau of Statistics, we obtained a sample of 5,912 respondents for the ages between 18 years and 30 years. The main findings based on a binary logistic regression approach, reveal that education, gender, residence, and age are all critical in driving youth unemployment. The Ugandan youth who has some level of education is more likely to be unemployed compared to those with no education. But the youth that attended post-secondary education is associated with the highest unemployment probability followed by those with secondary school education and finally by primary education. While an increase in age appears to increase youth unemployment for females, the married youth have less chances of being unemployed compared to the unmarried youth. Moreover, as the probability of being unemployed reduces for the married youth, being divorced increases that probability. Similarly, the male youth are found more likely to be unemployed than their female counterparts. Additionally, the urban youth increased their chances of unemployment compared to the rural ones. Likewise, males are far more likely to remain in unemployment relative to females, just as living in the northern, eastern, or western region as a youth is less risky in terms of unemployment compared to living in the central region. On the other hand, whereas the education level of the household head is not important for youth unemployment, the marital status and gender of the household head are critical. The indirect effects of education, gender, residence, and age are clearly notable. Implications for policy and research are drawn.