We explore how water pollution policy reforms in China could reduce industrial wastewater pollution with minimum adverse impact on GDP growth. We use a multi-sector dynamic Computable General Equilibrium (CGE) model, jointly developed by Harvard University and Tsinghua University, to examine the long-term impact of pollution taxes. A firm-level dataset of wastewater and COD discharge is compiled and aggregated to provide COD-intensities for 22 industrial sectors. We simulated the impact of 4 different sets of Pigovian taxes on the output of these industrial sectors, where the tax rate depends on the COD-output intensity. In the baseline low rate of COD tax, COD discharge is projected to rise from 36 million tons in 2018 to 48 million in 2030, while GDP grows at 6.9% per year. We find that raising the COD tax by 8 times will lower COD discharge by 1.6% by 2030, while a high 20-times tax will cut it by 4.0%. The most COD-intensive sectors—textile goods, apparel, and food products—have the biggest reduction in output and emissions. The additional tax revenue is recycled by cutting existing taxes, including taxes on profits, leading to higher investment. This shift from consumption to investment leads to a slightly higher GDP over time.

Objective: The objective of this paper is to predict the possible trajectory of coronavirus spread in the US. Prediction and severity ratings of COVID-19 are essential for pandemic control and economic reopening in the US. Method: In this paper, we apply the Logistic and Gompertz model to evaluate possible turning points of COVID-19 pandemic in different regions of the US. By combining uncertainty and severity factors, this paper constructed an indicator to assess the severity of the coronavirus outbreak in various states of the US. Results: Based on the index of severity ratings, different regions of the US are classified into four categories. The result shows that it is possible to identify the first turning point in Montana and Hawaii. It is unclear when the rest of the states in the US will reach the first peak. However, it can be inferred that 75% of regions in the US won’t reach the first peak of coronavirus before August 2, 2020. Conclusion: It is still essential for the majority of states in the US to take proactive steps to fight against COVID-19 before August 2, 2020.

Major changes have taken place in the structure of agricultural input factors in China, which will inevitably affect fertilizer input in agriculture. However, there is no consistent conclusion on the impact of capital and labor input on chemical fertilizer input. This paper applies directed acyclic graphs (DAGs) to clarify the backdoor path of capital and labor affecting fertilizer input. Using inter-provincial panel data, the dynamic panel system GMM method was adopted to examine the mechanism of factor substitution elasticity in determining the impact of agricultural capital-labor input on chemical fertilizer input. Results showed that agricultural labor and capital input are positively correlated with chemical fertilizer input, and the factor substitution elasticity has a negative regulatory effect in the progress of labor and capital input impact fertilizer input. From 1996 to 2018, the trend of capital replacing labor was obvious, and the growth ratio of capital input was much greater than the decrease ratio of labor input. Therefore, the increase in capital input and its substitution for labor is the main driver of the increase in fertilizer input. Meanwhile, the fertilizer-capital substitution elasticity decreased during the period 1996–2018, thus reinforcing the rise in fertilizer input caused by the increase in capital input. To reduce the agricultural pollution caused by the increase in chemical fertilizer input, it is very important to reverse the declining trend of fertilizer-capital substitution elasticity.