Analysing Economic Convergence Across the America: A Survival Analysis Approach to Gross Domestic Product Per Capita Trajectories

Abstract

Machine learning algorithms, and economic interpretation, integrated with survival analysis, are used to examine the temporal dynamics associated with achieving a 5% increase in purchasing power parity-adjusted GDP per capita over a period of 120 months (2013-2022). The comparative investigation reveals that DeepSurv effectively captures non-linear interactions, though standard models exhibit comparable performance under certain conditions. The weight matrix evaluates the economic implications of vulnerabilities, risks, and capacities. To meet the GDP per capita objective, the findings emphasize the necessity of a balanced approach to risk-taking, strategic vulnerability reduction, and investment in governmental capacities and social cohesiveness. The policy guidelines advocate for individualized approaches that account for the complex dynamics at play in decision-making processes.