ABSTRACT This study investigates the spatial convergence dynamics of sustainable development using the Green Gross Domestic Product (Green GDP) indicator, which includes environmental costs. Based on panel data from 160 countries between 1970 and 2023, β ‐, σ ‐, and γ ‐convergence tests are conducted using spatial econometric methods (SEM, SAR, SDM) and different weight matrices (distance, neighborhood, threshold‐based). The findings indicate a strong spatial dependence in Green GDP levels, with high clusters in Western Europe, North America, and Northeast Asia, and low clusters in Sub‐Saharan Africa and South Asia. Furthermore, it has been determined that countries with high Green GDP levels but low neighborhood effects, such as Singapore, Luxembourg, and the UAE, are vulnerable to cross‐border environmental risks, whereas countries in low‐level clusters, such as Malawi, Niger, and Burundi, exhibit fragile sustainability structures. γ ‐convergence analyses reveal that there was a strong re‐ranking process until the 1990s, but that the pace slowed significantly after 2000, supporting the findings of σ ‐convergence. Although Western and Northern Europe and high‐income economies contribute significantly to the process, the contribution of resource‐dependent economies in Africa and Central Asia remains limited. The results of conditional spatial β ‐convergence show that per capita income accelerates the convergence process; emissions exert an inhibiting effect; urbanization and agriculture have a supporting effect; and dependence on natural resources imposes a limiting effect. Accordingly, carbon reduction and clean technologies should be prioritized in emission‐intensive countries, whereas diversification and resilience should be emphasized in natural resource‐dependent economies.
Bingöl et al. (2026) studied this question.