Fuzzy classification of countries by sustainable economic potential: application of the Solow–Swan and Green Solow models

Cross-national pollution and the intensifying use of natural resources constitute global challenges whose solutions are shaped by the sociopolitical and economic conditions of individual countries. This study develops a methodology leveraging Solow–Swan and Green Solow growth model parameters to classify countries by productive capacity and compare associated emission patterns, identifying transfer opportunities between economies with structurally similar sustainable development profiles. We analysed 185 countries from 2000 to 2023, constructing the full taxonomy for the 120 economies with all four structural parameters recoverable. Parameters were estimated via the Levenberg–Marquardt algorithm with sigmoidal reparameterization under economically feasible constraints; reliability was assessed through residual-based bootstrap confidence intervals and unit-root tests. Fuzzy c-means clustering in the four-dimensional feature space yielded six robust country profiles, ranging from developed nations with absolute or minimal capital–emissions coupling to developing nations with tightly coupled output–emissions trajectories, demonstrating that development need not follow high-carbon pathways.