China is a bank-dominated country; therefore, the sustainability of the Chinese banking industry is important for economic development. In this paper, data envelopment analysis (DEA) was combined with the Malmquist index, and we statically and dynamically analyzed the efficiency of listed banks during the period 2012–2017. The results showed that 12 of the 17 banks improved their technical efficiency. The technical efficiency of three banks remained the same, whilst that of two banks had dropped slightly by less than 1.0%. The Chinese government has learned from the lessons of past financial crises to find a way to forestall financial crisis, and implemented macroprudential policy, therefore the banking industry has actively served the real economy and promoted economic development while paying attention to the prevention of financial risks. According to the report of The Banker in 2018, for the first time, the four biggest banks in China topped the list of the Top 1000 World Banks. The research showed that, the Chinese government applied macroprudential framework in the banking supervision, and the listed banks effectively resisted financial risks and realized steady growth. We believe that the macroprudential framework plays a positive role in the economic development and financial stability in China.

We collected data pertaining to Chinese listed commercial banks from 2008 to 2016 and found that the competition between banks is becoming increasingly fierce. Commercial banks have actively carried out diversification strategies for greater returns, and the financial reports show that profits are increasingly coming from the non-interest income benefits of diversification strategies. However, diversification comes with risk. We built a panel threshold model and investigated the effect of income diversification on a bank’s profitability and risk. Diversification was first measured by the Herfindahl–Hirschman index (HHI), and the results show that there is a nonlinear relationship between diversification and profitability or risk does exist. We introduced an interesting index based on the entropy to test the robustness of our model and found that a threshold effect exists in both our models, which is statistically significant. We believe the combination of the entropy index (ENTI) and the HHI enables more efficient study of the relationship between diversification and profitability or risk more efficiently. Bankers and their customers have increasingly been interested in income diversification, and they value risk as well. We suggest that banks of different sizes should adopt the corresponding diversification strategy to achieve sustainable development.

As one of the important pillar industries in China, the automotive industry (i.e., the traditional vehicle and the new energy vehicle (NEV) sub-industries) plays a significant role in the national economy and social development. In this paper, by using the fixed assets, intangible assets, the operating expenses, and the number of employee as inputs and the operating income as output, we conduct efficiency evaluations based on data envelopment analysis (DEA) and Malmquist models, and measure the efficiency of listed automotive firms with the panel data of 77 listed A-share firms spanning from 2012 to 2016, statically and dynamically. The results show that the five-year average Malmquist indices of all the listed firms slightly decreased due to the decline of the technical change and the improvement of the efficiency change. We subdivide the automotive industry into the traditional vehicle and NEV industries, and find that the NEV industry performed better than the traditional one. We combine the industry development and efficiency evaluation, and believe that the NEV will be a new driving force of the economy.

The world has entered the digital economy era. As a developing country, China's banking industry plays an important role in the financial industry, and its size ranks first in the world. Therefore, it is of great significance to study the systemic risks of China's banks in the digital economy era. We first compare the traditional indicator approach and the market-based approach theoretically, and Conditional Value at Risk (CoVaR) model, a market-based approach, is considered to be an efficient way to discover systemic risk in different perspectives. Based on static and dynamic models, we evaluate the contributions of sixteen China's listed banks to the systemic risk. Furthermore, we model bank exposures, extend the models by considering extreme circumstance, and incorporate the effects of Fintech and non-bank financial institutions. The results show the levels of systemic risks and the corresponding systemic importance rankings vary in different time periods. We find that the contributions of some small banks to systemic risk are even higher than some big banks during the sample period. Moreover, the big banks face less risks than most of the small banks when the banking system is in distress. We make suggestions for improving financial supervision and maintaining financial stability.