Technology innovation has become the main driving force of China’s economic growth. Sustainable development highlights the harmonious symbiosis of the economy and the ecological environment. Renewable energy companies characterized by technology-intensive and environmental friendliness are playing an increasingly important role in achieving economic development while alleviating environmental pressure. Therefore, this paper selects the A-share renewable energy listed companies in China between 2014 and 2019 as samples, using the fixed-effect model and the logit model to explore the effect of technology innovation on corporate sustainability. We find that technology innovation has a positive effect on both financial sustainability (FS) and social and environmental sustainability (SES). Due to the imbalance of regional social and environmental development and different degrees of emphasis placed on environmental and social responsibility, the positive impact of technology innovation on SES is heterogeneous between the east and the central and west regions. Moreover, as the strategic emerging industry, although the renewable energy industry is granted lots of subsidies from the government, the results show that when government subsidies exceed the threshold, the effect of technology innovation on FS is weakened. Government subsidies have a negative moderating effect on the relationship between innovation and SES. Furthermore, we subdivide government subsidies into government subsidies beforehand (GSB) and government subsidies afterwards (GSA). We reveal that the threshold effect of government subsidies mainly comes from GSA, while the moderating effect of government subsidies is caused by GSA and GSB. This paper is an expansion and enrichment of current studies on sustainable development and also puts forward feasible suggestions for the government to formulate precise and effective subsidy policies to stimulate technology innovation.

Purpose: In this paper, the authors use the balance sheet data to investigate the interconnectedness and risk contagion effects in China's banking sector. They firstly study the network structure and centrality of the interbank network. Then, they investigate how and to what extent the credit shock and liquidity shock can lead to the risk propagation in the banking network.Design/methodology/approach: Referring to the theoretical framework by Haldane and May (2011), this paper uses the network topology theory to analyze the contagion mechanism of credit shock and liquidity shock. Centrality measures and log-log plot are used to evaluate the interconnectedness of China's banking network.Findings: The network topology has shown clustering effects of large banks in China's financial network. If the Industrial and Commercial Bank of China (ICBC) is in distress, the credit shock has little impact on the Chinese banking sector. However, the liquidity shock has shown more substantial effects than that of the credit shock. The discount rate and the rollover ratio play significant roles in determining the contagion effects. If the credit shock and liquidity shock coincide, the contagion effects will be amplified.Research limitations/implications: The results of this paper reveal the network structure of China's interbank market and the resilience of banking system to the adverse shock. The findings are valuable for regulators to make policies and supervise the systemic important banks.Originality/value: The balance sheet data of different types of banks are used to construct a bilateral exposure matrix. Based on the matrix, this paper investigates the knock-on effects of credit shock triggered by the debt default in the interbank market, the knock-on effects of liquidity effects, which is featured by “fire sale” of bank assets, and the contagion effects of combined shocks.

Purpose: In this paper the interconnectedness among financial institutions and the level of systemic risks of four types of Chinese financial institutions are investigated.Design/methodology/approach: By the means of RAS algorithm, the interconnection among financial institutions are illustrated. Different methods, including Linear Granger, Systemic impact index (SII), vulnerability index (VI), CoVaR, and MES are used to measure the systemic risk exposures across different institutions.Findings: The results illustrate that big banks are more interconnected and hold the biggest scales of inter-bank transactions in the financial network. The institutions which have larger size tend to have more connection with others. Insurance and security companies contribute more to the systemic risk where as other institutions, such as trusts, financial companies, etc. may bring about severe loss and endanger the financial system as a whole.Practical implications: Since other institutions with low levels of regulation may bring about higher extreme loss and suffer the whole system, it deserves more attention by regulators considering the contagion of potential risks in the financial system.Originality/value: This study builds a valuable contribution by examine the systemic risks from the perspectives of both interconnection and tail risk measures. Furthermore; Four types financial institutions are investigated in this paper.

This paper investigates the influence of tax avoidance on capital structure based on share ownership under China’s economic system. Previous research has indicated that tax avoidance exits and has a potential effect on firms’ capital structure, but there is little literature focusing on this influence based on China’s economic system. In light of that, this paper uses A-share data of the Shanghai and Shenzhen stock exchange from 2007 to 2016 as samples to study the impact of tax avoidance on the capital structure based on China’s economic system. The results suggest that, firstly, there is a significant negative correlation between tax avoidance and the debt ratio of the listed companies; secondly, there is a significant difference in the effect of corporate tax avoidance on the debt ratio of different industries and different equity ownership. Besides, by regrouping the samples according to the share ownership and the degree of tax avoidance, it is revealed that China’s unique economic system would lead to an impact of tax avoidance on the capital structure that differs from other countries. Finally, it is found that there is a negative correlation between the degree of tax avoidance of the listed companies and the dynamic adjustment of assets-liability ratio through the extended study, further verifying that there is a substitution relationship between tax avoidance of the listed companies and their debt financing.

In this paper, a risk optimization model is proposed to minimize the oil supply risk from the perspective of diversification. The results show that there is large room for both China and India to improve the oil supply security. China should reduce oil imports from Saudi Arabia and Russia while increasing oil imports from the United States and Kazakhstan. India should import more oil from America and Russia while substantially reducing imports from Iraq and Saudi Arabia. In terms of the regional analysis, the Middle East plays a crucial role in the oil import strategies. They account for almost half of the total oil imports to China and India. African countries provide an alternative choice to diversify their energy supply risks. Based on forecasts of oil demand, we investigate the optimal oil import strategies for both countries until 2030 and 2040. China’s imports from the United States and Kazakhstan are forecasted to increase by more than ten times by 2030. India should import four times as much oil from the United States as it does now and import 10 times more crude oil from Russia. Africa and North America will play a more important role in India’s oil supply security.