This study aims to examine the causal effect of carbon regulatory risk on corporate bond yield spreads in emerging markets through empirical analysis. Exploiting China's commitment to peak CO2 emissions before 2030 and achieve carbon neutrality before 2060 as an exogenous shock to an unexpected increase in carbon regulatory risk, we perform a difference-in-difference-in-differences (DDD) strategy. We find that exposure to carbon regulatory risk leads to an increase in bond yield spreads for carbon-intensive firms located in regions with stricter regulatory enforcement. This positive relationship is more pronounced for firms with financing constraints, belonging to more competitive industries, and located in regions with a high marketization process. We further identify that higher earnings uncertainty and increased investor attention serve as two mechanisms by which carbon regulatory risk influences the yield spreads of corporate bonds. Moreover, the spread decomposition reveals that the rise in bond yield spreads after an increase in carbon regulatory risk is primarily driven by the rise in default risk rather than the rise in liquidity risk. Overall, our findings highlight the importance of considering carbon regulatory risk exposure in financial markets, especially in developing economies like China.

This paper investigates the causal impact of pre-trade transparency on the market liquidity of an over-the-counter-style market by leveraging a natural experiment in China’s interbank corporate bond market. We find that turnover, market liquidity, and aggregate bond returns significantly declined when the regulators unexpectedly suspended real-time quote dissemination in March 2023. Consistent with our expectation, these effects were mainly focused on interbank bonds, not exchange bonds, and bonds with lower credit ratings and longer maturities. This study contributes novel evidence to the transparency literature and provides insights for policymakers in emerging markets weighing the trade-offs between data governance and market efficiency.

The Central Environmental Protection Inspector (CEPI) is a critical regulatory measure in China aimed at improving ecological quality. From a compliance cost perspective, we examine the impact of the CEPI on corporate environmental governance. The findings reveal an asymmetry in the CEPI's influence: it significantly promotes environmental governance efforts on the non-production side of enterprises, while having no substantial effect on the production side. Additionally, government environmental subsidies do not provide a resource incentive in the process of the CEPI influencing corporate environmental governance. However, local environmental governance pressure mitigates this asymmetry, leading the CEPI to significantly enhance environmental governance on both the production and non-production sides. Further analysis shows that under the synergistic effect of local environmental governance pressure, the CEPI encourages state-owned enterprises to focus on environmental governance on the production side, while non-state-owned enterprises tend to focus on the non-production side. Moreover, political connections reduce the positive impact of the CEPI on production costs under local environmental governance pressure. Finally, the CEPI also significantly encourages enterprises to expand their production scale. These findings offer valuable insights for refining the CEPI system to better promote corporate environmental governance.

To address the challenges posed by renewable energy integration in power systems, China is advancing the development of Pumped Hydro Storage (PHS). However, the rapid growth of PHS installations, coupled with strict regulations and a high reliance on capacity compensation, has led to increasing financial burdens on other utilities. One solution is to reallocate the capacity compensation through market-based approaches to implement the “beneficiary-pays” principle. To achieve this goal, an operational policy named ’partial-regulated dispatch’ is proposed in this study. The analysis of this policy encompasses two crucial dimensions: the dispatch mechanism and business models. The dispatch mechanism evaluates PHS’s capacity contribution to grid stability, while the business models focus on enhancing PHS profitability to reduce dependency on capacity compensation while ensuring long-term economic sustainability. Furthermore, the flexibility of PHS is introduced as a criterion for assessing system security contributions, considering both individual unit vibration characteristics and multi-unit commitment strategies. The case study shows that through partial-regulated dispatch, PHS can reduce its reliance on capacity compensation by nearly 50% while ensuring its regulation service via flexibility compensation. This policy effectively balances economic viability with system support capabilities. Moreover, flexibility compensation provides PHS operators with a risk mitigation strategy in the complex power market environment. Under an appropriate operational strategy and policy incentives, the flexibility can be enhanced by nearly 30% in a fully marketized scenario, contributing to both system stability and operational efficiency.

The high-penetration integration of renewable energy requires huge demand for reliable capacity resources, and the coal-fired units are the main providers of the reliable capacity in China. This study proposes a future-oriented approach to facilitate coal-fired power’ transition through capacity market development. Focusing on China’s power market reform context, we propose a two-stage capacity market mechanism integrating annual capacity auctions and monthly capacity bidding, and design the procedural and transactional framework for coal-fired power participation. We further outline three market strategies including energy market trading, centralized capacity market trading, and renewable energy alliance leasing. Environmental costs are incorporated to construct revenue models and derive boundary conditions for coal-fired units’ decision-making. Research results reveal that current capacity prices fail to cover costs, requiring substantial market-driven price increases to achieve profitability. While stable capacity revenue can reduce medium-to-long-term and spot market prices, fostering competition between coal-fired power and renewable energy resources. However, coal-fired power remains highly sensitive to price volatility, demanding robust resilience to fluctuations. Carbon prices significantly influence capacity prices, yet excessive free carbon quota allocations weaken carbon price transmission effects, necessitating optimized quota ratios to enhance market responsiveness. Finally, policy implications are proposed according to the research results.

Prefabricated buildings(PBs) have significant advantages in improving construction efficiency, saving resources, and reducing environmental pollution. They have become an important direction for transforming and upgrading the global construction industry. However, the high construction costs have severely restricted their large-scale adoption. To systematically explore the key influencing factors and the mechanism of the construction cost of PBs, this study uses the method of combining interpretative structural model (ISM) and structural equation model (SEM), identifies the main influencing factors by synthesizing literature and data analysis, analyze hierarchical relationships between these factors via ISM, and quantifies the influence intensity and mechanism of the construction cost by SEM method. The results show that the driving factors of the construction cost of PBs can be divided into several levels. The core factors, such as the assembly rate, the production scale of prefabricated components, the integration of design management, the technical level of designers, and the specialization of prefabricated components in the factory, play a crucial role in cost optimization. In conclusion, this study deeply reveals the impact mechanism of the construction cost of PBs, offers practical guidance for reducing construction costs and optimizing resource allocation, and provides a scientific basis for government policy-making and enterprise strategic decision-making.

This study identifies a significant settlement effect in China’s equity options market, where price decline and pre-settlement return momentum exists on the settlement Friday (T+2) due to a temporal misalignment between option expiration (T) and the T+1 trading rule for the underlying asset. We attribute this phenomenon to three distinct behavioral channels: closing pressure from put option unwinding, momentum-generating predatory trading by futures-spot arbitrageurs exploiting liquidity fragility, and an announcement effect that attenuates the anomaly by adjusting spot speculators' expectations. Robust empirical analysis identifies predatory trading as the primary driver of the settlement effect.These findings offer critical insights for market microstructure theory and the design of physically-delivered derivatives.

We examine how social networks shaped by high-speed rail connections influence investor attention and market reactions to earnings announcements in China. Firms in high-centrality cities exhibit stronger immediate and subsequent responses in investor attention, stock price, and trading volume to earnings news. Further analysis shows that earnings-induced local attention predicts future attention spillovers to intercity investors, amplifying both price and volume reactions after announcements. Overall, these findings indicate that high-speed rail networks foster investor social networks that facilitate the dissemination of firm news and help explain predictable patterns in investor behavior and market pricing.

Climate change presents a global threat, prompting nations to adopt low-carbon development pathways to mitigate its potential impacts. However, current research lacks a comprehensive framework capable of integrating multiple variables and providing dynamic optimization capabilities. This article focuses on designing pathways for developing a low-carbon economy to tackle climate challenges. Specifically, we construct a low-carbon economy model that incorporates economic, environmental, social, energy, and policy factors to analyze the drivers of economic growth and carbon emissions. We utilize economic model predictive control and tracking model predictive control to optimize development pathways aligned with various low-carbon targets, creating and validating a comprehensive framework for low-carbon policy design using historical data from China. This study highlights significant advantages in analyzing low-carbon pathways through advanced techniques like hierarchical regression and model predictive control, providing a robust framework that enhances our understanding of causal relationships within the LCE system, captures system feedback, dynamically optimizes pathways, and accommodates diverse policies within a comprehensive low-carbon economy system.

This paper investigates the gambling preference of Chinese investors in the convertible bond (CB) market through a natural experiment—the 2018 amendment of Article 142 of the Company Law. Utilizing CB issuance data from 2016 to 2023, we employ a cohort difference-in-difference approach and find a 4% to 7% increase in IPO premiums for high-repurchase-expectation CBs across various measures. This significant increase indicates that the legal revision reshapes investors’ expectation and adjusts their valuation of CBs. Furthermore, the event-study analysis reveals the escalating impact of legal revision, driven by the herding behavior of gambling investors.