Factors Affecting Unemployment Duration of the Science and Arts Stream University Graduates in Sri Lanka
Sri Lanka has a significant youth unemployment problem. In the recent years, a more serious problem is graduate unemployment. Therefore, Sri Lanka needs to develop appropriate policies to decrease the duration of unemployment. In this regard, research is required to determine the factors that affect unemployment duration of graduates in order to provide the policy makers with solid foundations for their decision-making processes. Globally several studies have investigated unemployment duration of graduates. Up to date, no study has been done in Sri Lanka that thoroughly investigates the unemployment duration of graduates in Sri Lanka. Thus, the main aim of this research is to identify the factors that affect the duration of unemployment in the Science and Arts stream graduates in Sri Lanka. A survival analysis was conducted to determine how the considered factors affect the duration of unemployment among the Science stream graduates. Due to the nature of the information gathered in relation to the unemployment duration of the Arts stream graduates, an ordinal logistic regression was applied to identify the significant variables of unemployment duration of the Arts stream graduates among the variables considered. The findings of this study show that the Semi Parametric Cox Proportional model is appropriate to determine the relationship between graduates' time taken to obtain the first job and explanatory variables. According to the analysis, the gender, the type of the degree, the job category (private or government sector jobs) and the results of the GCE Advanced Level General English subject have a significant impact on unemployment duration of Science stream graduates. For the Arts stream graduates, the family income, the professional courses followed by graduates during their academic years at the university and the participation in extra-curricular activities while in the university were found to be significant.
Keywords:Graduate Unemployment, Survival Analysis, Ordinal Logistic Regression Model
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