Dynamic Evolution and Driving Mechanisms of Green GDP: Provincial Evidence from China
DOI:
https://doi.org/10.54097/yxxt3n57Keywords:
Green GDP, Entropy Weight Method, Environmental Benefits, Regional Heterogeneity, Fixed-Effects Model.Abstract
This study constructs a comprehensive Green GDP accounting framework encompassing economic, resource, and environmental dimensions. Based on data from 2010–2022 for 31 provinces in mainland China and using an entropy weighting method to determine indicator weights, provincial Green GDP values are calculated. The results indicate that Green GDP and conventional GDP rise in tandem, with the former expanding at a marginally faster rate; meanwhile, the environmental-cost component exhibits a gradual decline over time. A structural inflection is observed around 2015–2016, after which growth patterns shift, and significant regional disparities in Green GDP are apparent. An ARIMA model forecast shows the gap between Green GDP and conventional GDP narrowing gradually from 17.4% in 2022 to 12.9% in 2028. Panel fixed-effects analysis reveals that economic scale is the primary driver of Green GDP growth; industrial structure upgrading exhibits a short-term “decline-then-rise” effect on Green GDP, and rapid urbanisation exerts additional environmental pressure. By integrating economic, resource, and environmental factors, this research offers a holistic and innovative approach to evaluating sustainable development. The entropy-based weighting and the combination of time-series forecasting with panel analysis represent methodological advances, and the findings not only enrich the theoretical understanding of Green GDP dynamics but also carry practical implications.
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