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Second emission trading market is not active in China so far, and the reason mainly lies in that enterprises do not have strong initiative for transaction. Thus it's meaningful to study related guiding mechanisms from the perspective of enterprises behavior. In this paper, an evolutionary game model and a small-world network model considering stock heterogeneity are constructed based on four given guiding mechanisms, and a simulation study is conducted through China Zhejiang emission trading market. The result shows that: (1) the optimal guiding mechanism is dynamic and changes from reward-punishment for both enterprises with surplus stock and enterprises with insufficient stock to reward-punishment for enterprises with insufficient stock when trading preferential profit coefficient increases to 1. (2) when penalty coefficient changes, the optimal guiding mechanism is the reward-punishment for both enterprises with surplus stock and enterprises with insufficient stock and keeps unchanged. (3) the enterprises with insufficient stock are more sensitive to penalty coefficient and trading preferential profit coefficient, especially to the latter, so it's better to stimulate the emission rights purchasing side and formulate positive reinforcement methods. The study of this paper can provide decision-making suggestions for Chinese government to stimulate the activity of second emission trading market. [Display omitted] • Four guiding mechanisms are given based on implementation objects. • An evolutionary game model is constructed. • A complex network model is constructed considering stock heterogeneity. • The optimal guiding mechanism is simulated and dynamically analyzed. • The policy recommendations are highlighted. [ABSTRACT FROM AUTHOR]

Despite the important policy and welfare implications of China's energy issues, to date there has been little investigation from a micro-level perspective of the misallocation of resources in manufacturing enterprises. To fill this gap, this paper deals with resource misallocations in China with special reference to energy and labor inputs. Using a large, novel dataset of manufacturing enterprises from Zhejiang province, we employ a simultaneous system of equations for (gross) industrial output value, wage bill, energy expenditure and carbon emissions. The explanatory variables include labor, educational attainment of employees, capital value, materials, and a list of energy-related variables. Our results show that, for the same energy content, non-coal energy inputs are more productive than coal and coal-related fuels. Non-coal energy is more environmentally friendly but more expensive than coal-related fuels. Using the model estimates, we conduct Wald tests on whether the marginal productivity of labor and energy significantly differ from their respective factor costs. The main findings are that there is substantial resource misallocation in manufacturing enterprises, with labor being underpaid and energy overpaid, on average, in comparison to their marginal productivity. For energy misallocation, however, the pattern varies considerably among the various subsectors. Specifically, energy is over-used in sectors such as Textile , Paper , Chemical , Plastics , Non-metallic , Ferrous metals and Non-ferrous metal . By contrast, energy is under-used in sectors such as Beverages , Textile-wearing apparel , Leather , Metal , Transport equipment , Electrical machinery and Communication equipment . These findings can assist decision-makers in targeting the sectors where there is the most misallocation, identifying which input factors are inappropriately used, improving economic efficiency and lowering overall production costs by reducing allocative inefficiency. [ABSTRACT FROM AUTHOR]

Abstract: China is currently facing the threat of serious air pollution and has adopted a series of governance policies. However, the fact that PM 2.5 indicator in some regions often reached far higher than the official threshold since 2015 has reflected that China's current Air Quality Index system for measuring and evaluating air quality is still not perfect. Therefore, this paper extended the current air quality indicator system officially used by China. Using improved Entropy-weighted Factor Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Method, we calculated the air quality scores of 26 cities in China's most economically developed region - the Yangtze River Delta region based on their daily average concentration numbers of main air pollutants from February 2015 to January 2018. Based on the air quality calculation result, we further studied the effectiveness of air pollution control policies of this region by using the Box-Jenkins Model with fuzzy strategy parameter adjustment. Our findings are: the pollution control policy is more effective to Shanghai, Jiangsu and Zhejiang. The air quality score of Shanghai has improved by 51.07% compared with its level before the policy. Meanwhile, the air quality improvement in Zhejiang province has shown the characteristics of "Campaign-style Governance" right before the G20 Summit, especially that in Hangzhou, the host city of the Summit. On the other hand, maybe due to late start of air pollution control programs, the cities of Anhui province haven't shown obvious improvements in air quality, and some cities have even seen deterioration in air quality scores during our study period. Graphical abstract Image 1 Highlights • We extended the current air quality indicator system officially used by China. • We used the Entropy-weighted Factor Method and TOPSIS Method for assessing. • We studied the control policies by Box-Jenkins Model with fuzzy strategy parameter. • Results and corresponding reasons were analyzed according to provinces and cities. • Policy recommendations for air pollution control in YRD were proposed. [ABSTRACT FROM AUTHOR]