Economic Globalization and Environmental Outcomes in Heterogeneous Panels: Composition, Technique, and Distributional Evidence from Shanghai Cooperation Organization Economies

Fudan Journal of the Humanities and Social Sciences. 2026.

This study reassesses whether economic globalization is compatible with carbon mitigation across nine Shanghai Cooperation Organization economies over 1997 to 2024. A sequenced panel design is applied: pre-estimation diagnostics establish cross-sectional dependence, slope heterogeneity, and mixed integration orders; fixed effects with Driscoll and Kraay standard errors provides the preferred conditional mean estimate; Hansen threshold regression, panel quantile regression, method of moments quantile regression, mean-group, common correlated effects, and augmented mean-group estimators, sectoral interaction models, and country specific regressions establish the shape, distribution, and dispersion of the response. The Environmental Kuznets Curve is not supported. The income locus is convex rather than concave once country effects are admitted, with a joint Wald statistic of 128.42 and a turning point of 464 USD lying at the extreme lower edge of the data. The inverted U appears only in pooled and random effects specifications, identifying it as an artefact of between country variation. Trade openness raises emissions with an elasticity near 0.22, and a significant interaction with industrial structure of 0.488 shows the effect is generated by productive composition rather than openness itself. Renewable energy is the sole determinant that is negative, significant, and stable across every estimator and every quantile. Policy should therefore target composition and technique channels directly rather than await income driven decoupling.

Keywords: foreign direct investment, Shanghai cooperation organization (SCO), Environmental Kuznets Curve, Renewable energy consumption, Panel quantile regression, International Economics and Trade​, Driscoll and Kraay standard errors, sectoral interaction models, Industry value added including construction, share of GDP, Agriculture, forestry and fishing value added, share of GDP, Services value added, share of GDP, reference sector