Akademik Məlumat İdarəetmə Sistemi
Energy Strategy Reviews, vol.65, 2026 (SCI-Expanded, Scopus)
China's rapid industrialisation has generated unprecedented demand for natural resources, rendering its economic trajectory acutely sensitive to commodity price instability. This study investigates the dynamic relationships among natural resource volatility (NRV), green finance investment (GFI), energy transition intensity (ETI), green foreign direct investment (GFDI), and technology innovation (TI) on provincial economic performance across 30 Chinese provincial-level regions (provinces, municipalities, and autonomous regions) over the period 2001–2021. Employing a battery of second-generation panel econometric techniques—including the Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) model, the Panel Quantile Regression (PQR) framework, and the Panel Dynamic Ordinary Least Squares (PDOLS) estimator—this study accounts for cross-sectional dependence and slope heterogeneity inherent in province-level panel data. Empirical results reveal that NRV exerts a statistically significant negative effect on long-run GDP growth, with a one-unit increase in NRV reducing provincial output by 0.312%. Conversely, GFI and ETI exhibit positive and significant long-run effects of 0.487% and 0.538%, respectively. Quantile regression estimates indicate that the dampening effect of NRV on GDP is more pronounced in lower-income provinces, whereas green finance exerts stronger growth-enhancing effects in upper-quantile economies. The robustness of these findings is confirmed through PDOLS estimation. These findings call for differentiated policy designs: targeted green finance capacity building for lower-income provinces to mitigate the adverse growth effects of natural resource volatility, and accelerated renewable energy deployment nationwide to decouple economic growth from resource dependence.