Wealth Distribution

Wealth distribution research investigates the unequal allocation of resources within societies, aiming to understand its drivers and consequences. Current studies employ diverse approaches, including machine learning algorithms (like boosting models) to predict poverty and econophysical models to simulate the effects of different economic systems and social behaviors on wealth inequality. These analyses reveal the significant impact of factors such as time preference, information exchange, and social mechanisms (like mutual aid) on wealth distribution, offering valuable insights for policymakers and economists seeking to design more equitable systems. The findings highlight the limitations of traditional metrics like the Gini coefficient and the need for more nuanced measures of well-being.