Determining Countries' Key Factors of Competitiveness Based on Machine Learning Methods

Abstract

Amidst the prevailing consensus within the scientific community on the pivotal role of institutions in shaping economic growth, there exists a subset of indicators, including education, healthcare, and infrastructure, whose impact remains comparatively underexplored. The overarching research objective of this study is to meticulously examine the influence of key determinants on the development of economic competitiveness. The research methodology is firmly anchored in a comparative analysis of the Global Competitiveness Index across two editions, employing machine learning techniques, specifically Principal Component Analysis. This analytical approach facilitates the identification of the most salient factors contributing to a country's competitiveness. The distinctive contribution of this study lies in its rigorous and comprehensive exploration of factors influencing economic growth through the innovative lens of machine learning methodologies. The findings underscore the imperative for nations to accord priority to institutional development and foster a conducive business environment as essential precursors to achieving heightened competitiveness. Subsequently, efforts should be directed towards initiatives that elevate the quality of life for the populace. Moreover, the study underscores the pivotal role of education as one of the primary catalysts for fostering economic growth.