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Neutrosophic Sets and Systems

Abstract

This study examines the relationship between education and entrepreneur income in Ecuador, a prototypical small economy grappling with employment challenges. Utilizing quantile regression and neutrosophic statistical methods, the research uncovers varied impacts of education on earnings across different income levels. The findings reveal a decrease in indeterminacy as individuals ascend income quintiles, indicating that higher education levels yield more predictable and substantial economic returns at the upper end of the income spectrum. These insights are vital for policymakers to develop targeted educational interventions. The study’s methodological novelty lies in its adoption of neutrosophic statistics, which embraces the indeterminacy intrinsic to economic data, offering a refined lens for understanding the income-education interplay. Future research directions include longitudinal studies to trace the temporal effects of education and cross comparative analyses across economies. The potential integration of machine learning with neutrosophic statistics promises enhanced predictive models, contributing to data-driven economic policy formulation.

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