This paper develops a network to analyze inter-industry risk spillovers during high and low volatility periods. Our findings indicate that China's Industrials and Consumer Discretionary exhibit the greatest levels of spillovers in both high and low volatility states. Notably, our results demonstrate the "event-driven" character of structural changes to the network during periods of pronounced risk events. At the same time, the economic and financial network exhibits clear "small world" characteristics. Additionally, in the high volatility stage, the inter-industry risk contagion network becomes more complex, featuring greater connectivity and direct contagion paths. Furthermore, concerning the spillover connection between finance and the real sector, the real economy serves as a net exporter of risk. The study's findings can assist government agencies in preventing risk contagion between the financial market and the real economy. The empirical evidence and policy lessons provide valuable insights for effective risk management.

This paper examines the spillover effect of environmental regulations on firms’ green technological innovation, from the perspective of supply chain relationships. Analyzing data from Chinese listed companies, we find that the average environmental regulatory pressure faced by the client firms of a supplier firm enhances the green patent applications filed by the supplier firm, indicating that environmental regulatory pressure from clients spills over to suppliers. When the industries of suppliers are more competitive or the proportion of their sales from the largest client is higher, suppliers feel more pressured to engage in green innovation, resulting in more green patent applications. Thus, via their negotiation power, client firms can prompt supplier firms to innovate to meet their demand for green technologies. Finally, we show that this effect is particularly pronounced when supplier firms are located in highly marketized regions, receive low R&D government subsidies, or have high ESG ratings.

Local financial development is crucial for advancing regional financial supply side structural reform, enabling local governments to leverage financial instruments to effectively mobilize land resources and foster competitive growth. The introduction of numerous financial products linked to land-related rights and interests has resulted in a pronounced transmission and interconnection of fiscal and financial risks across regions. This study examines the impact of local financial development on land financialization in China using panel data from prefecture-level cities and detailed information on land mortgages. The findings indicate that the establishment of city commercial banks (CCBs) contributes to the progress of land financialization by incentivizing local government financing vehicles to participate in land mortgage financing, increasing the transfer of debt risks to the financial sector. Notably, the impact of CCBs on land financialization is more pronounced in regions with urban agglomeration, high GDP manipulation, inadequate local financial regulation, and robust implicit government guarantees. Further analysis reveals that CCB establishment has negative spillover effects on land financialization in neighboring areas, while expansion strategies such as establishing intercity branches, engaging in cross-regional mergers, and relaxing regulations have mitigated the rise of land financialization at the regional level. This study provides policy recommendations that focus on reducing local governments’ reliance on land financing and enhancing the prevention and management of financial risks.

This research study primarily examines the digital transformation’s internal mechanism promoting enterprises’ total factor productivity (TFP) based on the matching and learning mechanism. Afterward, this research article empirically examines the digital transformation’s influential mechanism on enterprises’ TFP, using the Chinese listed companies’ data on the “A” stock market for the time period ranging from 2007 to 2019. The major study findings are as follows: (1) the improvement of the digital transformation significantly increases enterprises’ TFP. The proposed conclusion remains robust after a series of robustness- and the endogeneity test. (2) Furthermore, mechanism analysis reveals that digital transformation effectively enhances enterprises’ TFP by eliminating resource misallocation in the industry. In addition to this, digital transformation relies on the mechanism of “learning by doing” to promote the technological innovation’s spillover effect; hence, effectively enhancing enterprises’ TFP. (3) Heterogeneity analysis demonstrates that the digital transformation’s impact on enterprises’ TFP is heterogeneous in the context of enterprise size, enterprise type, and enterprise ownership. Lastly, this study puts forward that government bodies should intensify the construction and investment in digital infrastructure, promote a series of institutional reforms, and support digital technological R&D practices.

Based on 31 provinces, municipalities, and autonomous regions in mainland China, this paper explores the temporal and spillover effects of the provincial COVID19 pandemic on stock returns. The results show that stock returns are significantly and negatively correlated both with the pandemic in the firm’s headquartered province (referred to as, local province), and the pandemics in other provinces (referred to as, non-local provinces). By multiple time dimensions analysis, we find that at the weekly (monthly) level, the impact of the pandemic in local province on stock returns is larger (weaker) than the pandemics in non-local provinces, showing the temporal (spillover) effects. Mechanism analysis shows that COVID-19 can quickly reduce investors’ attention to stock market. The heterogeneity analysis shows that firms owned by state, with bad CSR, or a higher proportion of shares held by the largest shareholder are more affected by COVID-19. After replacing samples and time intervals, the results remain robust.

This paper employs a difference-in-differences approach to study whether a Chinese audit firm improves its competencies through organizational learning after one of its audit teams has a client cross-listed in the US. Among a group of companies that are listed only in China, we define those audited by firms that have cross-listed clients as the treatment group, and companies audited by other firms as the control group. We find an improvement in audit quality for the treatment group after their audit firms have cross-listed client experience in the US. A large-scale survey of auditors corroborates these findings and sheds light on specific actions undertaken by audit firms to facilitate learning. Both the empirical and survey results highlight the benefits of auditing crosslisted clients in the US and its positive externality on improving the audit quality of non-US-listed companies.

As the world’s two largest economies, China and the US are currently experiencing political and economic friction. This conflict brings high uncertainty to financial markets. Assessing risk spillover effects in a sector level will help us to characterize international risk contagions. We construct a multilayer network to examine tail risk spillovers between China and the US and find that (1) the value of total connectedness rises amidst tensions but declines during reconciliations; (2) interlayer spillovers mainly manifest as extreme pulses instead of steady outflows, which implies a significant increase in the frequency and magnitude of interlayer spillovers requires vigilant monitoring; and (3) compared with the in-strength, the out-strength is more concentrated, which represents that some sectors may play the role of major interlayer transmitter in tail risk spillovers. Monitoring interlayer spillovers helps policymakers and investors respond to emerging systemic threats.

This paper employs a difference-in-differences approach to study whether a Chinese audit firm improves its competencies through organizational learning after one of its audit teams has a client cross-listed in the US. Among a group of companies that are only listed in China, we define those audited by Chinese audit firms that are not international Big 4 affiliates and have cross-listed clients as the treatment group, and companies audited by other audit firms as the control group. We find an improvement in audit quality for the treatment group after their audit firms have cross-listed client experience in the US, and this improvement is not attributable to the effect of joining an international accounting firm network, registration with the PCAOB, or the consolidation in the audit market. A survey of auditors corroborates these findings and provides evidence on audit firms’ specific actions to facilitate learning. Our findings shed light on the benefits of auditing cross-listed clients in the US and its positive externality on improving the audit quality of non-US-listed companies in China.

The study of interconnections between various sectors of the national economy is crucial for understanding the pattern and pace of macroeconomic growth. This paper analyzes the macroeconomic impact of shocks occurring in specific sectors through both supply and demand perspectives and proposes a combination of bottom-up and top-down structural path analysis approaches to trace the transmission path of network spillover effects, where shocks in this paper refer to microeconomic productivity changes and network spillover is defined as the effect on GDP due to the propagation of shocks to other sectors. The research results found that the total spillover effect of primary and secondary industry sectors in China shows an inverted U-shape, and the total spillover effect of tertiary industry sectors shows an upward trend. A large total spillover effect of a sector does not mean that both upward and downward spillover effects are large; for example, the construction industry has high upward spillover effects and low downward spillover effects. The spillover effect of each production layer decreases as the path lengthens, and the distribution is Lshaped.In addition, by identifying the critical paths of spillover effects, we find that the spillover effects of labor-intensive industries, such as wholesale and retail, are decreasing year by year, and the spillover effects of the paths related to the information technology industry are gradually occupying an important position.

In the international context of the surging tide of anti-globalization, China will raise the establishment of pilot free trade zone as a national strategy, and achieve the goal of promoting highquality economic growth through a series of reform measures, such as promoting investment liberalization and facilitation, improving investment promotion and protection mechanisms, and improving the level of overseas investment cooperation. To study the role of the pilot free trade zones on investment, the panel data of 46 cities from 2005 to 2018 are used to empirically test the investment growth effect and investment spillover effect of the pilot free trade zones by using the Difference-in-Differences Spatial Dubin Model. The results show that the pilot free trade zones can significantly promote investment growth and have a spillover effect on investment in surrounding areas. Through the grouping regression of the eastern, central, and western regions, it is found that the eastern pilot free trade zones have the most obvious investment spillover effect on the surrounding areas, and the central pilot free trade zones have a siphon effect on the investment in the surrounding areas. In addition, different batches of pilot free trade zones or the same batch of pilot free trade zones have different investment spillover effects on surrounding areas at different time points. Finally, policy suggestions are put forward: strengthen the strategic implementation of the pilot free trade zones, improve the spatial radiation mechanism, promote linkage development and differentiated development, and make the pilot free trade zones better promote investment growth and investment spillover.