Volume 9, Issue 6

This paper develops a simple trade model of heterogeneous firms, which incorporates the dual heterogeneity of credit constraints at the firm and industry levels and reveals the effects of the interaction mechanisms of trade policy uncertainty and credit constraint heterogeneity on exporters’ behaviour. The model confirms that the higher the level of industrial credit constraints, the greater the interaction of trade policy uncertainty and credit constraint heterogeneity, but firms with lower levels of credit constraints within a specific industry are more affected by this interaction. Then, based on the highly dis-aggregated trade data of China’s firms from 2000 to 2013, this paper provides empirical evidence for the main predictions and mechanisms of the theoretical model.

The economy of China has turned to the stage of high-quality development. In this sense, the connotation of regional innovation capacity should reflect more aspects, such as better economic effectiveness, people-centered philosophy of development and better living conditions. This study aims at establishing the evaluation index system of regional innovation capacity under high-quality perspective. Then the dynamic evaluation method based on gray correlation degree and TOPSIS is improved. And the improved method is applied to evaluate the regional innovation capacity under high-quality development perspective. The results show that: 1) The regional innovation capacity of Jiangsu, Zhejiang, Shanghai and Guangdong under high-quality development perspective is better than other regions, while the regional innovation capacity of Beijing-Tianjin-Hebei is imbalanced. Regional innovation capability of Fujian, Shandong, and Hainan from a high-quality perspective is at the middle and lower levels. 2) From the perspective of development trends, the gap of regional innovation capacity between Beijing, Jiangsu, Zhejiang, Shanghai, Guangdong and Fujian, Hebei, Shandong is gradually narrowing. 3) An in-depth analysis of the regional innovation capability of the eastern provinces and cities from the perspective of high-quality development through different dimensions shows that Beijing, Guang-dong, Jiangsu perform well in all dimensions, while Fujian and Hainan need to pay more attention to innovation input and the creation of a better innovation environment to enhance innovation output and promote innovation effectiveness. At last, based on above analysis, relevant policy recommendations are proposed.

Mergers and acquisitions (M&A) are important parts of banking reform, which can increase the synergies and reduce the costs of the banks. To analyze the effect and importance of the M&A in the reform period, we measure the productivity change of China’s banks who completed M&A during 2004– 2018, by using a two-stage data envelopment analysis (DEA) method. First, we incorporate the process of deposits producing and the process of profit earning as a two-stage structure of bank’s system. Then, we construct a slacks-based measure (SBM) model considering the weak disposability of undesirable outputs to measure the productivity of 14 M&A banks in China. Particularly, we adopt the global Malmquist index (GMI) to evaluate the productivity change of the banks, and analyze the efficiency change (EC) and technical change (TC) for the whole system and individual stages. Additionally, to facilitate making M&A plans, we classify the M&A banks to obtain the process they need to improve and the trend they could adopted: (i) We classify them into four categories by the productivity of two individual stages; (ii) We also classify them into four categories by EC and TC. Finally, the policy recommendations for M&A banks are given.

China is a country with the most water consumption, so it is lack of water resources. Industry has brought serious water pollution while driving economic development, which leads to the destruction of ecological environment. With the improvement of environmental awareness, many scholars have shifted their research direction to how to improve the ecological environment. Most studies consider the whole system as a “black box”, regardless of its internal structure. Therefore, a method to identify inefficiency is necessary and some suggestions for optimization are given. In this paper, a two-stage undesirable fixed-sum output data envelopment analysis (DEA) model is proposed. The industrial chemical oxygen demand (COD) emission during 2011–2015 are adjusted, and the efficiency values are calculated by heuristic search algorithm. The efficiency of 30 provinces and cities is divided into eastern, central and western regions. The model can identify the inefficient stage in industrial system, and find the source of low efficiency in the system. The analysis shows that the efficiency of eastern region is the highest, while the overall efficiency is inclined to the pollutant treatment stage. Finally, the paper puts forward some suggestions for the low efficiency areas, which can save water while ensuring economic benefits, and provide new direction for water pollution reduction and improve the ecological environment.

In recent years, China’s industrialization and urbanization have deepened, and the economy has grown considerably. But at the same time, they have also brought about many environmental problems. As a pillar of the national economy, the iron and steel (IS) industry is one of the most emitting and energy-consuming sub-sectors of the industrial sector. It is also one of the industries with the most severe overcapacity problem in China. In this paper, we explore the impact of capacity utilization on carbon dioxide emission based on panel data of China’s iron and steel industry from 2005 to 2014. We also tested the heterogeneity in different regions and different sub-samples. Results show that capacity utilization and carbon dioxide emission are positively correlated. However, the impact of capacity utilization on carbon dioxide emission differs when considering regional heterogeneity. Results in all three regions show a positive relationship between capacity utilization and carbon dioxide emission, but the impact intensity is strongest in the western region, followed by the eastern and central regions. Moreover, capacity utilization impacts carbon dioxide emission by influencing firm numbers in the iron and steel industry and energy consumption. Further analysis shows that there exists a threshold effect in different stages of energy consumption and energy structure. Finally, some findings and practical policy recommendations are provided.

Based on China’s real estate investment (REI), commercial housing sales (CHS), and GDP data from 2001 to 2020, we studied the dependence, asymmetry, and transmission direction of China’s real estate and economy. Their cross-correlation is demonstrated through the deep cross-correlation analysis (DCCA) algorithm, multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) algorithm and DCCA algorithm based on a time delay. Both REI and CHS have persistence with GDP. The real estate industry and economy have asymmetric multifractal characteristics. Meanwhile, real estate and the economy have different trends, and they can affect each other with the same length of time delay. This effect diminishes in a short period of time, and there are unsteady fluctuations in cross-correlation persistence in the long term.

The article selects the panel data of 289 prefecture-level and above cities in China from 2003 to 2017, establishes simultaneous equations and uses the 3SLS estimation method to study the relationship between air pollution and economic growth. On the whole, industrial sulfur dioxide and soot emissions have an inverted U-shaped relationship with per capita GDP, and the increase in sulfur dioxide emissions has played a significant role in hindering economic growth. From a regional perspective, the sulfur dioxide emissions in the eastern and western regions conform to the environmental Kuznets curve, and the per capita GDP at the turning point in the western region is significantly lower than the overall national level. The smoke and dust emissions in the eastern, central and western regions all conform to the environmental Kuznets curve, while the per capita GDP at the turning point in the western region is significantly lower than that in the eastern and central regions. In the eastern region, both sulfur dioxide and smoke and dust emissions significantly hinder economic growth, and this hindrance is mainly caused by the spatial transfer of labor. Through further analysis, it is found that environmental regulations can significantly suppress the negative impact of air pollution on economic growth. Finally, the article puts forward some suggestions, such as environmental governance according to local conditions and strengthening environmental regulations.