Study on the Emission Reduction Effect of Environmental Protection Tax—An Empirical Study Based on the Change of Pollution Charge Standard in China?

This paper reflects the actual effect of China’s environmental protection tax by empirically analyzing the environmental effect of the emission fee, in order to provide reference for China’s environmental tax reform. Based on the traditional environmental “Kuznets” model, the factor of environmental tax is added to verify the effect of environmental governance of environmental tax. The results show that: 1) the improvement of sulfur dioxide emission charge standard can effectively inhibit industrial sulfur dioxide emission, which verifies the existence of environmental effect of pollution levy policies. 2) The improvement of sewage charge standard has better inhibitory effect on sulfur dioxide emission per unit GDP than on sulfur dioxide emission. 3) There is regional heterogeneity in the “emission reduction” effect of sulfur dioxide emission charges in the eastern, central and western regions of China. Pollutants should be taxed differently according to regional differences. 4) Economic growth and sulfur dioxide emission show an inverted “U” shape, China is still in the stage before the inflection point of EKC. Economic growth still takes environmental damage as the cost, and the “emission reduction” effect of technological progress is not ideal, which reveals the urgency of increasing technological development in the field of green environmental protection under the current situation.

Regional inequality, spatial spillover effects, and the factors influencing city-level energy-related carbon emissions in China

Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.