Recently, the Chinese Government has strengthened the enforcement of bankruptcy laws to protect creditors’ rights. This study shed light on the effect of creditor protection on asset-debt maturity mismatch by employing a quasi-natural experiment in China. The results show that creditor protection mitigates maturity mismatch, and the effect is more pronounced among financially constrained firms. Results remain robust after the dynamic effects test, placebo test, propensity score matching approach, entropy balancing method, and controlling for COVID-19 shocks. Mechanism tests show that creditor protection decreases the cost of debt and reduces over-investment. The effect of creditor protection is pronounced in private companies, financially independent companies, and companies with secured loans. Creditor rights can alleviate maturity mismatch in firms with medium ownership concentration and managerial ownership levels. Economic consequences studies suggest that creditor protection reduces corporate default risk. This study reveals the mechanism and effect of creditor protection on asset-debt maturity mismatch in emerging markets, providing recommendations to policymakers for assessing and improving bankruptcy law regimes.

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.

Since the global financial crisis of 2007–2009, preventing financial crises has become one of the most important objectives of regulators and banks. Although previous studies have identified the phenomenon of risk contagion in the banking system, the underlying mechanisms of risk contagion are still unclear. This study delves into the multi-stage contagion mechanism of liquidity risk based on interbank lending linkages and clearing rules and introduces a new index to quantify bank liquidity risk. We find that the contagion of liquidity risk is primarily determined by the network structure of risk exposures between banks in default and is not significantly influenced by the lending relationships of banks that remain solvent. The empirical results suggest that banks with high risk should be prioritized for cash injections to improve system liquidity. These findings offer new insights into financial risk contagion and practical recommendations for regulatory authorities formulating intervention strategies and for banks conducting risk management.

The use of green finance to slow down global warming in support of sustainable development remains widely discussed. This study examines whether investment structure moderates the impact of green finance on the environment in China, one of the top carbon-emitting nations and the second-largest economy in the world. We primarily used the moments-quantile regression approach with fixed-effect models on panel data from 1992Q1 to 2020Q4. First, the results confirmed that green finance and public and private investments worked synergistically to lower CO2 emissions, especially in Central and Western China. However, there was no proof that green finance and foreign direct investment were complementary in reducing CO2 emissions in China, unlike the Central region. Second, green finance marginally lowered CO2 emissions in all provinces, mainly in Eastern and Western China; this reduction was largely dependent on private investment in the Western region’s most polluting areas and foreign direct investment in Eastern and Western China’s least polluting provinces. Third, the beneficial effect of green finance occurred at varying optimal thresholds and investment-related conditions across Chinese regions at different quantiles. Lastly, we showed that in contrast to the variable impacts of urbanization, oil prices, and economic growth across Chinese regions at different quantiles, renewable energy, and trade openness reduced CO2 emissions. In conclusion, the study makes some policy recommendations for China’s sustainable economic development, an important model from which other countries can tailor their investment strategies and environmentally friendly policies.

Emissions data collection and management are crucial to operationalizing an emissions trading scheme (ETS). Regulators need high-quality data to allocate emissions allowances and monitor compliance. However, collecting such data can be costly, challenging various actors. Emitters may misreport data, weighing the cost against their interest, while governments may struggle with limited resources in managing compliance. Third-party verification is a solution but tends to be ineffectual and causes new problems unless with sufficient oversight and support. This quality-cost dilemma becomes even more complex in multi-level ETSs, as in China’s national ETS (NETS). Despite increased regulatory efforts to address data challenges, there remains a lack of in-depth legal analysis on the relationship between data quality and cost. This Article establishes a three-element analytical framework—data quality, cost concerns, and intergovernmental relations in data management—to shed light on the nuances of data regulation. Using China’s NETS as a case study, we gain a deeper understanding of the three elements in a specific jurisdiction and the legal institutions, practices, and challenges involved. Governments, emitters, and third-party verifiers each have unique roles and limitations in this process. We suggest legal and regulatory strategies for finding solutions. Our actor-centered analytical model and practical recommendations for the NETS can serve as a valuable guide for jurisdictions facing similar data challenges.

Chinese enterprises are currently facing unprecedented economic transformations accompanied by a diverse array of challenges. This article delves into these challenges and provides management recommendations to assist companies in addressing these pressing issues. First, China's economic growth is gradually slowing, prompting companies to explore new avenues for growth, such as diversifying their products and markets, enhancing research and development, and expanding into emerging markets. Second, the uncertain global trade landscape has impacted exports and supply chains, necessitating diversified supply chains, new trade partnerships, and proactive strategies to navigate potential trade policy changes. Additionally, the pressure of technological innovation cannot be underestimated, urging companies to increase R&D investment, collaborate with other enterprises on research, and recruit and nurture high-quality tech talent. Furthermore, with the Chinese government's growing focus on environmental concerns, companies need to invest in clean production technologies, build sustainable supply chains, and actively fulfill their social responsibilities. Other challenges including rising labor costs, intellectual property protection, financial risks, regulatory compliance, talent recruitment and retention, and digital transformation all require proactive responses. By adopting proactive management strategies, Chinese enterprises can thrive in this era filled with both opportunities and risks, achieving sustainable growth and enhanced competitiveness.

Fighting global warming has become a vital requirement for environmental sustainability. Green finance has gained popularity as a promising mechanism for transitioning to a lowcarbon economy. Thus, this paper investigates whether excess green financing increases renewable energy capacities and enhances environmental quality from 1992Q1 to 2020Q4 in China, one of the major CO2 emitters. We primarily used the method of moments-quantile regression with fixed-effect models. First, we found nonlinear U-shaped impacts of green finance on wind power capacities in all Chinese regions, thermal power capacities in the Western and Central areas, and hydropower capacities in Eastern China, respectively. Second, we confirmed an inverted U-shaped impact of green finance on CO2 emissions in the Eastern region but U-shaped effects in the Western and Central regions. The impacts of green finance were asymmetrical due to the heterogeneous distributions of renewable energy sources and environmental quality within and between regions. Green finance mostly improved environmental quality when certain conditions and thresholds were met. Third, green finance had substantial marginal effects on environmental quality in the least polluted provinces (Q.20) in Western China and the most polluted provinces (Q.80) in Eastern China. Finally, there were heterogeneous effects of oil prices, urbanization, foreign direct investments, and trade openness on renewable energy consumption and environmental quality across Chinese provinces. Accordingly, this study provides some policy recommendations for China’s sustainable development, a key example from which the international community can adjust its green policies.

Macro-prudential policy plays a crucial role in stabilizing the financial system and influencing banks' risk preferences and willingness to take risks. This study examines the influence of macro-prudential policies on bank risk-taking using unbalanced panel data from 126 commercial banks in China between 2010 and 2021. The difference-in-differences model is employed to analyze the data. The empirical findings demonstrate that implementing macro-prudential policies in China effectively enhances bank risk prevention measures. In other words, macro-prudential policy implementation facilitates the digital transformation of banks and subsequently reduces risk-taking behaviors. Moreover, the heterogeneity test reveals that macro-prudential policies have a more significant impact on the risk-taking behavior of commercial banks with higher capital adequacy ratios compared to those with lower ratios. Additionally, commercial banks with strong interbank dependence exhibit more pronounced effects on their risk profiles when subjected to macroprudential policies with stricter capital supervision requirements. Therefore, this study proposes policy recommendations for strengthening bank capital supervision through differentiated approaches, serving as a valuable reference for the regulatory authorities.

Evidence from the U.S. and Europe suggests that current risk assessment tools used by researchers and financial professionals to determine individuals’ risk tolerance and provide suitable portfolio recommendations may be flawed due to “mis”perceptions of risk. Limited research has examined the reliability of these tools as measures of relative risk tolerance for households in emerging economies like China. This study develops a multidimensional index of risk tolerance specifically tailored for Chinese households using a psychometric approach. The effectiveness of this multidimensional index in predicting individuals’ financial decisions is tested and compared to traditional unidimensional measures of risk tolerance commonly used in developed countries. The findings indicate that multidimensional measures are more consistent and significant predictors of Chinese households’ investment decisions. Additionally, the study uncovers evidence that cultural differences, related to market expectations and social networks, which are often overlooked in U.S. and European models, play a crucial role in shaping individuals' risk perceptions and investment choices in China. Robustness checks were conducted to account for potential endogeneity between risk tolerance and investment decisions. The findings provide valuable insights for researchers and financial professionals seeking to develop more accurate risk assessment tools that capture risk attitudes and perceptions in China and other developing countries. By adopting a multidimensional approach that accounts for cultural and psychosocial factors, these improved tools can enhance the precision of risk evaluation and facilitate more appropriate investment recommendations.

This study examines whether sell-side analysts have the ability to disseminate information consistent with anomaly prescriptions in China. I adopt 192 trading-based and accounting-based anomaly signals to identify undervalued and overvalued stocks. Analysts tend to give more (less) favorable recommendations and earnings forecasts to undervalued (overvalued) stocks. On analyzing the information content, I find that analyst recommendations and earnings forecasts are consistent with accounting-based information rather than trading-based information. Analysts make recommendations and earnings forecasts consistent with anomalies, especially when firms experience relatively bad firm-level information. Additionally, undervalued (overvalued) stocks are associated with high (low) analyst coverage. The results indicate that analysts may contribute to mitigating anomaly mispricing and improving market efficiency in China.