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This paper examined the economic impacts of China's emissions trading system (ETS), implemented in 2013, in terms of gross domestic product (GDP) and per capita GDP. The methodology drew on a difference-in-differences (DID) method using dynamic panel data for 30 provincial regions. The estimation results show that implementing an ETS policy has statistically significant negative effects on economic growth. When considering the additional control variables, these effects are still statistically significant. Furthermore, these negative impacts increase over time with respect to both GDP and per capita GDP. The counterfactual tests confirm the robustness of our DID estimation results. The specific influence mechanism of China's ETS policy was finally discussed. Our findings provide a quantitative decision-making support for popularizing ETS policy in China. Based on our DID model, empirical investigations of the ETS policy, especially concerning economic growth in other regions would produce prolific contributions to the literature. [ABSTRACT FROM AUTHOR]

Transportation investment has served as one of the most promising economic instruments to lower transportation costs and promote economic growth. To enhance the effectiveness and efficiency of such kind of capital investments, one critical issue is to gain a better understanding of the pathways that transportation investment would have to influence economic growth. By using a provincial panel data in China, this study attempts to investigate how transportation investments impact economic growth through a variety of pathways. Structural equation modeling (SEM) is applied to understand the relationship between transportation investment, investment in relevant sectors, industrial structure, employment growth, and economic development. It finds that investment in transportation sectors can promote economic growth through direct and multiple indirect pathways. The indirect pathways can improve economic performance through the investments in relevant sectors, growth of industry and employment growth. These impacts would be significantly changed under diverse spatial and temporal conditions. [ABSTRACT FROM AUTHOR]