Abstract
<p class="MsoNormal" style="margin-top: 12pt; text-align: justify;"><span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;">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.</span></p>