Analysis of job vacancies and skills mismatch in Rwanda using data mining techniques, (2019-2021)

Abstract

The current study aims at identifying skills mismatch and skills needed in the labour market in Rwanda in the year 2021-2022 which is a result of declining labour productivity. The researcher used both qualitative and quantitative data to describe skills mismatch in Rwanda. Primary data were used using web-scraping to obtain advertised jobs in Job in Rwanda or on MIFOTRA Portal. Machine learning algorithms were used to predict skills mismatch and the best models to estimate skills mismatch were both Decision Tree and Random Forest with an overall precision of 79 percent, according to the accuracy and degree of precision of the machine learning technique that was used to make this choice. The place of residence (Urban/Rural), economic activity, the age of the employee, and the type of education pursued by the employee were found to be factors associated with skills mismatch. Employed persons with high education are more inclined to do any job or occupation for low-skill employment, which could impede output and employee happiness in a particular organization. There was a sizeable fraction of the employed population part-time in low-skill jobs even if they would prefer to work full-time in an occupation that matched their skill set. Forty-two per cent of the employed population declared themselves as having occupations that match with the level of education required (self-declaration). The incidence of skills mismatch by occupation level has shown that persons employed in Service and sales workers are relatively under-skilled (60 percent) as vii compared with other main occupation groups. The incidence of skills mismatch was 37 percent in the agriculture sector and 29 percent craft and related. The mismatch among unemployed was 7.9% meaning that they lack the skills necessary for work given the amount of education they have acquired and the positions they are qualified for. The population of the Labour force was another part that is match affected by skills mismatch and this has an impact on the production of the country. When workers lack the necessary abilities to do their jobs more effectively and profitably, it has been discovered that the skills mismatch affects output among them as well.