Abstract
This study examined the relationship between environmental regulations (ER) and green economic efficiency (GEE) based on the panel data of 30 provinces in China from 2008 to 2017. Firstly, GEE was calculated and evaluated using the super-efficiency SBM model with undesirable outputs. Secondly, the impact of ER on GEE was studied with the Tobit model. Finally, this article draws conclusions based on the above analysis and offers some suggestions for government and enterprise. The results show that the GEE of China is generally low. The GEE of the eastern region is much higher than that of the middle and western regions, with the western region performing slightly better than the middle. From west to east, there is a V shape, with high efficiency in the west and east and low efficiency in the middle. The impact of ER on GEE has the characteristics of nonlinearity and spatial heterogeneity. At the national level, as well as in the middle and western regions, the impact of ER on GEE shows an inverted U shape that first rises and then falls. ER are currently within the range conducive to the development of GEE. If the intensity of ER exceeds the critical value, they will have a negative impact on GEE. In the eastern region, the impact of ER on GEE is shown as a U shape that first falls and then rises. At present, the ER are not of sufficient intensity to contribute to the improvement of GEE. Only when the intensity of the ER exceeds the critical value will they have a positive influence on the GEE.
Highlights
The Paris Agreement signed by the 21st Conference of the Parties to the “UnitedNations Framework Convention on Climate Change” in 2015 stated that all parties would deal with the global threats of climate change and keep the global average temperature rise within 2 ◦ C compared with that before industrialization, striving to keep it within 1.5 ◦ C
Pollutants generated during processing are a crucial source of undesirable outputs, which usually inhibit the efficiency of the green economy
The constructed model is as follows: GEEi,t = α0 + β 1 ER2i,t + β 2 ERi,t + β 3 GDPi,t + β 4 INDi,t + β 5 FAi,t + β 6 OPENi,t + β 7 URBi,t + μi,t + ε i,t where i means a province (i = 1, 2,..., 30), t means time, GEE means the green economic efficiency, EG means environmental regulations, ER2 means the square term of environmental regulation, GDP means the development level of the economy, IND means the industrial structure, FA means the level of fixed assets across the whole of society, OPEN means the level of opening up, URB means the urbanization level, μ means the individual effect used to control individual effects, and ε is the error term
Summary
Nations Framework Convention on Climate Change” in 2015 stated that all parties would deal with the global threats of climate change and keep the global average temperature rise within 2 ◦ C compared with that before industrialization, striving to keep it within 1.5 ◦ C. Improving the efficiency and quality of economic development is a significant way to promote green development. In the process of economic development, China pays more attention to efficiency and quality, such as urban ecological efficiency, energy and resource allocation efficiency, and total factor productivity, which all reflect the concept of green economic efficiency to a certain extent. Domestic enterprises can gain a competitive advantage in the international market, thereby improving industrial efficiency and corporate performance, creating a “win–win” situation regarding environmental protection and economic growth [8,9,10]. Whether the influence of environmental regulations on green economic efficiency corresponds to the above hypothesis requires further studies. The impact of environmental regulations on green economic efficiency was studied with the Tobit model, followed by further studies to test whether the relationship between the two was nonlinear
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