Abstract

Economic stress endured by countries globally can be due to numerous socioeconomic factors, including unemployment, measured by the unemployment rate expressed in percentage (%). Various micro and macro socioeconomic variables, including the quality of education and vocational training in the countries and the availability of it, cause high unemployment rates. This study assesses the impact education has on unemployment rates and focuses on youths in emerging market countries to determine the nature of the relationship between the two variables. In addition, the study aims to predict which continents will have increasing unemployment rates for youths in the next five years across the Americas (including South and North American countries), Africa, Asia, and Europe. CRISP-DM framework will be followed by a methodology that includes data mining techniques such as correlation analysis, regression analysis, decision tree, k-means cluster analysis, and time series forecasting analysis, all enabled by R studio, and using Tableau for geographic visualizations. Using the data sourced from theglobaleconomy.com, the data mining techniques were applied to achieve the study goals. The findings concluded that the relationship between education level and unemployment rate for youths in emerging market countries is inverse. Generally, higher education levels, especially secondary education, led to lower unemployment rates due to better employment prospects. However, due to the considerable variation in the results of the findings, the relationship could be more significant, meaning education level does not significantly impact unemployment rates, and many other factors come into play.

Publication Date

5-2024

Document Type

Thesis

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research

Advisor

Sanjay Modak

Advisor/Committee Member

Khalil Al Hussaeni

Campus

RIT Dubai

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