The Impact of Wealth Inequality on Economic Growth: A Machine Learning Approach

Abstract In recent years, the issue of increasing economic inequality in both advanced and emerging economies has garnered considerable focus, sparking numerous debates in economic and political circles. At the heart of social science inquiries is the critical question of whether economic inequality acts as a catalyst for or an obstacle to economic growth. This study explores the impact of wealth inequality on economic growth considering heterogeneity of the countries. Utilizing advanced datasets and cutting-edge machine learning techniques to address the nonlinear dynamics of this relationship, our analysis provides a nuanced departure from traditional panel data models. Our findings indicate that the impact of wealth inequality on economic growth is heterogeneous, contingent upon a country’s economic structure and existing level of inequality. Specifically, while a moderate level of inequality may stimulate growth in developed and pre-communist countries, it tends to impede growth in developing and underdeveloped countries with higher degrees of economic inequality. Our research further elucidates the presence of an inverted U-shaped relationship between wealth inequality and growth, identifying an optimal inequality threshold beyond which the adverse effects—such as diminished access to education and increased social unrest—surpass the potential benefits.