Abstract
By promoting financial agglomerations to support green development in a region is a keyway for China to resolve the sharp contradiction between economic growth and environmental protection. However, existing research only considered the promotion effect of financial agglomerations on green development, but the spatio-temporal non-stationarity of that effect has been overlooked. Using a panel data of 285 prefecture-level cities in China and based on the evaluation of green development by a Driving-Pressure-State-Impact-Response (DPSIR) model, this paper analyzes the spatial correlation of financial agglomeration on green development. The paper also investigates the differences in the spatio-temporal influence of financial agglomeration on green development from both global and local perspectives by employing a Bivariate Local Indicators of Spatial Association (BLISA) model and a Geographically and Temporally Weighted Regression (GTWR) model. The results indicate that: (1) There exists significant spatial dependency between financial agglomeration and green development from 2003 to 2015, with Low-Low (L-L) and Low-High (L-H) spatial clusters as the main cluster types. (2) From the local perspective, the promoting effect of financial agglomerations on green development has showed significant spatial heterogeneity with a gradually decreasing trend from the southeast coast to the northwest inland of China. This work can help to develop policies for supporting green development by formulating differential strategies for financial agglomerations.
Highlights
How to improve human wellbeing, protect the environment, and promote sustainable development through green economic growth are key goals of the 2030 Global Sustainable Development
Since high-quality economic growth and environmental protection are at the core of green development, this paper focuses on the economic beneficial effects of agglomerated financial industries on green development as related to protecting China’s natural environment
In order to further test the spatial autocorrelation of financial agglomeration and green development, we adopt bivariate Moran’s I to measure the bivariate global Moran index of model variables and the associated statistical significance
Summary
How to improve human wellbeing, protect the environment, and promote sustainable development through green economic growth are key goals of the 2030 Global Sustainable Development. Since the international financial crisis in 2008, the environmental degradation caused by rapid economic growth has worsened the health and the wellbeing of humans. The consequence of fast-paced development of traditional industries has led many developing countries all over the world to search for a sustainable way to achieve the balance of economic growth and environmental protection. The resource consumption and environmental pollution resulted from the long-term extensive industrial development seems to have reached the limit of environmental carrying capacity [1]. This has caused China to suffer from a serious environmental crisis
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