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Temporal Dynamics of Countries' Journey to Cluster-Specific GDP per Capita: A Comprehensive Survival Study

Author

Listed:
  • Diego Vallarino

    (Independent Researcher, Madrid, Spain)

Abstract

This research delves into the temporal dynamics of a nation's pursuit of a targeted GDP per capita level, employing five different survival machine learning models, remarkably Deep Learning algorithm (DeepSurv) and Survival Random Forest. This nuanced perspective moves beyond static evaluations, providing a comprehensive understanding of the developmental processes shaping economic trajectories over time. The economic implications underscore the intricate balance required between calculated risk-taking and strategic vulnerability mitigation. These findings guide policymakers in formulating resilient economic strategies for sustained development and growth amid the complexities inherent in contemporary economic landscapes.

Suggested Citation

  • Diego Vallarino, 2024. "Temporal Dynamics of Countries' Journey to Cluster-Specific GDP per Capita: A Comprehensive Survival Study," Review of Economic Assessment, Anser Press, vol. 3(1), pages 1-19, February.
    • Handle: RePEc:bba:j00010:v:3:y:2024:i:1:p:1-19:d:301
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    References listed on IDEAS

    as
    1. Zhou, Fanyin & Fu, Lijun & Li, Zhiyong & Xu, Jiawei, 2022. "The recurrence of financial distress: A survival analysis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1100-1115.
    2. Joseph F. Hair Jr. & Luiz Paulo Fávero, 2019. "Multilevel modeling for longitudinal data: concepts and applications," RAUSP Management Journal, Emerald Group Publishing Limited, vol. 54(4), pages 459-489, October.
    Full references (including those not matched with items on IDEAS)

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