Analyzing Economic Convergence Across the Americas: A Survival Analysis Approach to GDP per Capita Trajectories
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Abstract (arXiv)
By integrating survival analysis, machine learning algorithms, and economic interpretation, this research examines the temporal dynamics associated with attaining a 5 percent rise in purchasing power parity-adjusted GDP per capita over a period of 120 months (2013-2022). A comparative investigation reveals that DeepSurv is proficient at capturing non-linear interactions, although standard models exhibit comparable performance under certain circumstances. The weight matrix evaluates the economic ramifications of vulnerabilities, risks, and capacities. In order to meet the GDPpc objective, the findings emphasize the need of a balanced approach to risk-taking, strategic vulnerability reduction, and investment in governmental capacities and social cohesiveness. Policy guidelines promote individualized approaches that take into account the complex dynamics at play while making decisions.
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References · 5
- 2017Machine Learning for Survival Analysis: A Surveycited by 112
- 2020Survival regression with accelerated failure time model in XGBoostcited by 37
- 2021AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events datacited by 7
- 2022Shared Frailty Methods for Complex Survival Data: A Review of Recent Advancescited by 1
- 2023Buy when? Survival machine learning model comparison for purchase timingcited by 1
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