Statistical Modelling of Unemployment Rate in Kenya Using Logistic Regression

Abstract

Unemployment is one of the challenges that has kept majority of governments around the world scratching their heads. It is one of the crisis of the modern world which keeps growing every day. It is mainly affected by the economic growth of a given country. Majority of governments are ever in a hurry to put in place policies that will help tame this crisis. The goal of this project, is to investigate the relationship between individuals age, gender, marital status, education level, region of residence and the unemployment level in Kenya and determine to which extent each variable affect the unemployment level. Logistic regression will be used as the estimating technique. Secondary data from Kenya Continuous Household Survey Program by the Kenya National Bureau of Statistics is used to illustrate the relationship between the response variable and the predictors. As per the analysis, a conclusion is made that age, gender, location and education level are significant in determining unemployment in Kenya. It is noted that the higher the education level the less the risk of unemployment. It is also clear that the youth are the one mostly affected by unemployment. A recommendation is made to the government of Kenya to put in place immediate policies that will help tame the unemployment menace among its citizens. Also a suggestion is made to carry out a research on the duration an individual takes between seeking for a job and finding one.