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Analyzing Economic Convergence Across the Americas: A Survival Analysis Approach to GDP per Capita Trajectories

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  • Diego Vallarino

Abstract

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.

Suggested Citation

  • Diego Vallarino, 2024. "Analyzing Economic Convergence Across the Americas: A Survival Analysis Approach to GDP per Capita Trajectories," Papers 2404.04282, arXiv.org.
    • Handle: RePEc:arx:papers:2404.04282
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    References listed on IDEAS

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    1. Renyan Jiang, 2022. "A novel parameter estimation method for the Weibull distribution on heavily censored data," Journal of Risk and Reliability, , vol. 236(2), pages 307-316, April.
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