The question of how to achieve the sustainable development of resource-based cities has been a major concern for the whole world. In response, the Chinese government has introduced the National Sustainable Development Planning of Resource-Based Cities Policy (SDPRP) to address sustainable development issues in resource-based cities. However, few studies have evaluated the environmental effects of the implementation of the SDPRP. Therefore, difference-in-differences (DID) and mediation effect models were applied to investigate the impact of the SDPRP on pollution emission intensity using balanced panel data for 270 prefecture-level cities in China from 2003 to 2018. The statistical results reveal that the SDPRP significantly reduced pollution emission intensity. Robustness test results showed that the conclusions are robust. Furthermore, the inhibitory effect of the SDPRP on pollution emission intensity increased year after year. We also found that the SDPRP can reduce pollution emission intensity by facilitating technological innovation, accelerating digital transformation, and improving human capital level, in which the role of human capital is stronger, while the role of digital transformation is weaker. The heterogeneity results suggest that compared with mature resource-based cities, the SDPRP had a stronger inhibitory effect on the pollution emission intensity in declining resource-based cities. However, the impact of the SDPRP on pollution emission intensities in growing resource-based cities was significant, while it was not significant in regenerative resource-based cities. Similarly, the SDPRP had a significantly greater inhibitory effect on pollution emission intensity in megacities than in large cities, while it increased the pollution emission intensity in small- and medium-sized cities.
This study conducted quasi-natural experiments based on the panel data of 239 prefecture-level cities in China from 2005 to 2017. The difference-in-difference (DID) and mediation effect model are used to test the impact and mechanism of the construction of national eco-industrial demonstration parks (NEDP) on green total factor productivity (GTFP). The results show that: (1) The construction of NEDP has significantly improved the urban GTFP, and the conclusion is still valid after running the robustness test. (2) Mechanism analysis shows that the construction of NEDP has improved GTFP through technological innovation and industrial structure upgrading. (3) The heterogeneity results reveal that NEDP has a significant positive effect on GTFP in the central and western regions, while the effect was insignificant in the eastern region. Moreover, NEDP significantly contributes to GTFP in resource-based and non-resource-based cities, while the contribution of resource-based cities is greater than that of non-resource-based cities. This study provides a reference for China to further promote the construction quality of NEDP and green development.
Green biased technological progress takes into account the influence of energy input and pollution emission, which is of great significance to China's green development. This paper decomposes technological progress into green input biased technological progress (IBTC) and green output biased technological progress (OBTC) using the Slacks-based measure integrating (SBM) model. Factor bias in technological progress is determined based on data from 34 industries in China from 2000 to 2015. The results show that the green biased technology progress exists significantly in the industry, and most of them promote the growth of green total factor productivity. IBTC first tends to consume energy to pursue capital between capital input and energy input, while it tends to save energy after the Eleventh Five-Year Plan. Between labor input and energy input, it is biased towards saving labor and consume resources. OBTC is biased towards promoting industrial growth and curbing pollution emissions. Medium and light polluting industries are biased towards promoting industrial growth and curbing pollution emissions, while heavy polluting industries are biased towards emitting more pollution.
The urban green transformation is the basis for the green development of China’s economy, and the reduction of income inequality between urban and rural areas is necessary to ensure stable economic growth. Therefore, ensuring green and sustainable economic development, while taking into account social equity, is of practical importance for China to achieve comprehensive high-quality development. This paper constructs a spatial Durbin model and a mediating-effects model to examine the spatial effect of urban green transformation on the urban-rural income gap (URG) and its mechanism of action based on panel data of 265 cities in China from 2006 to 2018. It also divides cities by geographical location and urban population size to further investigate the heterogeneity of the impact of the urban green transition on URG. The study found that (1) there is a significant positive spatial correlation for the URG in China, and the urban green transition can reduce the URG, and the results of the study remain reliable after a series of robustness tests. (2) Urban green transformation can reduce the URG through technological innovation effects and digital effects. (3) Urban green transformation significantly reduced the URG in eastern regions and cities of considerable size and above and had no significant impact on the URG in other cities. The study results demonstrate the possibility of reconciling urban and rural economic development and environmental friendliness at the same time.
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