The Impacts of Technical Progress on Sulfur Dioxide Kuznets Curve in China: A Spatial Panel Data Approach
This paper aims to reveal the nexus for sulfur dioxide (SO 2 ) emission and income, as well as the effects of technical progress on SO 2 emission in China based on environment Kuznets curve (EKC) hypothesis. The spatial panel technique is used in case the coefficient estimates are biased due to the negligence of spatial dependence. With the provincial panel data of China from 2004 to 2014, this is the first research that finds an inverse N-trajectory of the relationship between SO 2 emission
... en SO 2 emission and economic growth and confirms the beneficial impacts of technical advancement on SO 2 emission abatement. The empirical results also suggest that the industrial structure change is an important driving force of the SO 2 EKC. In addition, the direct and spillover effects of determinants on sulfur emission are clarified and estimated by a correct approach. Finally, we check the stability of our conclusions on the EKC shape for SO 2 and technical progress effects when controlling for different variables and specifications, through which we find the turning points are sensitive to variables selections. Sustainability 2017, 9, 674 2 of 27 cutting the pollutants emission by 10% during the 11th Five-Year plans period. The total SO 2 emission deduced by 12.45% based on the 2005 emission level. However, the amount of SO 2 emission is still a heavy burden on the environment system: in 2010, 21.85 million tons of SO 2 were exhausted into the atmosphere  . On the other hand, China has increased investment in new energy industries and environmental technologies such as wind power, hydropower, solar power and end-of-pipe abatement technology that can largely reduce exhaust gas emission [3, 5] . Thus, except for the economic factors, the technical progress impacts on SO 2 emission in China are another issue worthy of discussion. In the past literature, multiple shaped environmental Kuznets curves such as U, inverse U-shaped, and N were found  . Zheng et al.  and Kang et al.  testified an inverse N-shaped EKC for carbon dioxide emission in China. Because an U/inverse U-shaped EKC is naturally nested in an N/inverted N-shaped EKC, in this study, we examine if there exists an N or inverse N-shaped EKC for SO 2 emission in China. To take the spatial dependent effects of variables into account, these two prior studies focused on CO 2 ECK in China and applied the spatial panel data models: Zheng et al.  applied the dynamic spatial panel model to explore the determinants and spatial relation of provincial carbon dioxide emission in China. They firstly found the inverted N-shaped relationship between carbon dioxide intensity and GDP in China, yet they failed to present the amount of direct and spillover effects of those determinants. After that, Kang et al.  further testified the inverse N-shaped relationship between carbon dioxide emission and GDP through the application of spatial panel data technique. Besides, they also reported two turning points of the inverted N-trajectory. However, they directly interpreted the coefficients estimates of independent variables in spatial Durbin model as the direct and spillover effects, which is invalid. LeSage and Pace  argued that the estimated coefficients of spatially lagged explanatory variables and its significant test should not be explained as the amount of spillovers and significance of spillover effects in spatial models. Instead, a partial derivative estimate of the impact of changes in the variables in spatial model specification offers a more valid way of estimation and interpretation of spillover effects and testing significance. Furthermore, Elhorst  pointed out that parameters estimated in the spatial Durbin model do not represent the direct marginal effects of a change in the explanatory variables on the dependent variable, since the feedback effects (Feedback effect = Direct effect − Coefficient) will lead to a impacts going through neighboring regions and then back to the local regions themselves. To the best of our knowledge, no one has studied the spillover effects in the EKC for SO 2 or examined the existence of the cubic term in the SO 2 EKC in the context of China. In addition, the technical progress impacts on the reduction of SO 2 emission remains uncertified. Therefore, this study contributes to the literature by overcoming these gaps. There are four unique contributions of this paper. First, we verified the existence of the inverse N-shaped EKC for SO 2 and its stability in the context of China. Second, we clarified the beneficial effects of technical progress on SO 2 emission reduction and its stability. Third, the industrial structure is confirmed to be a driving force of SO 2 EKC. Fourth, a valid estimation approach is applied for the direct and spillover effects of the determinants of SO 2 emission through spatial panel data model. The remainder of the paper is organized as follows: Section 2 gives a brief review of past literature. Section 3 describes the variable selection for the empirical analysis and methodologies of spatial econometrics. Section 4 describes the details and source of the data. Section 5 presents the estimation results and analysis. Section 6 conducts the robustness check to test the stability of estimation results in different situations. Section 7 concludes our findings, presents the limitations and offers implications for further studies.