DATA-DRIVEN INSIGHTS INTO MIGRATION: IDENTIFYING KEY DRIVERS OF POPULATION DECLINE IN NORTH MACEDONIA
Shpresa SALI, Shkurte LUMA-OSMANI, Florinda IMERI, Ermira MEMETI
Abstract
This project addresses the issue of population leaving the country, using advanced Data Mining techniques to identify the main factors that have a great impact on this worrying phenomenon. Mass migration, especially of young people and skilled labor, has become a serious challenge for economic and social development in the Balkan countries, particularly in the Republic of North Macedonia. By analyzing statistical data from sources such as state institutions like MakStat and international agencies like the World Bank, this study aims to reveal the connection between economic (unemployment, low wages) and social (education, quality of life) factors with the decision to emigrate. The methodology used in this project requires the application of advanced machine learning techniques, such as algorithms for classification, clustering, and regression analysis, to analyze behaviors that influence these migratory changes. Through these approaches, the main goal is to identify the population groups that are most at risk of leaving the country, as well as the main factors that influence this big decision. Mass migration of population has affected a lot, various sectors of North Macedonia, including the labor market, public services, the education system, and the domestic economy, making this phenomenon a serious challenge to the sustainable development of the country.
Pages: 401 - 405