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.

This study was conducted to understand better how rules influence China's energy performance; this research on these policies' efficacy that facilitating the transition to sustainable energy sources is of tremendous significance, particularly in light of the severe problems climate change poses. To determine whether or not strict regulations are beneficial to China's energy transition efforts, this research makes use of a substantial amount of data about China's environmental laws and environmental transition policies. This paper thoroughly analyses the impact of strict environmental regulations on various energy transition measures. These metrics include the availability of green energy, carbon emissions, and energy efficiency. The results provide insights into how environmental restrictions have affected China's transition to a different energy source. Policymakers and stakeholders may use this information to build efficient plans to expedite the transition to a low-carbon, renewable energy system in China and abroad.

Copper resources are widely used in power networks and clean - energy tech like PV panels, wind turbines, and NEVs. Restricted by domestic resources, China's copper supply chain is vulnerable with risks. Based on six supply - chain stages, this paper builds an assessment system for China's copper supply - chain risks. By adopting an improved Benefit of Doubt (BOD) model, this paper has systematically evaluated the risks in the whole copper supply chain, revealing the trends and deep-rooted causes of these risks. The findings of this study reveal that: (1) The supply chain risk of China's copper resources presents a significant upward trend over the past 15 years; (2) The current supply chain risks in copper are mainly concentrated at the stages of import, production, and application; and the recycling risk has a great potential for reducing the copper supply chain risks in the future. Based on these findings, this paper proposes two policy recommendations: (1) Develop diversified channels for importing copper resources and optimize overseas investment patterns and; (2) Improve the domestic supply capacity of secondary copper resources and reduce the risks at the recycling stage.

How enterprises can leverage frontier technologies to achieve synergy between environmental governance and high-quality development has become a critical issue amid the deepening global push for sustainable development and the green economic transition. Based on micro-level data of Chinese enterprises from 2009 to 2023, this study systematically examines the impact of artificial intelligence (AI) on corporate green governance performance and explores the underlying mechanisms. The findings reveal that AI significantly enhances green governance performance at the enterprise level, and this effect remains robust after accounting for potential endogeneity. Mechanism analysis shows that AI empowers green transformation through a dual-path mechanism of “cognition–behavior,” by strengthening environmental tendency and increasing environmental investment. Further heterogeneity analysis indicates that the positive effects are more pronounced in nonheavy polluting industries and state-owned enterprises, suggesting that industry characteristics and ownership structure moderate the green governance impact of AI. This study contributes to the theoretical foundation of research at the intersection of digital technology and green governance, and provides empirical evidence and policy insights to support AI-driven green transformation in practice.

The disparities in green transition have led to the call for a ‘just transition’. However, the large differences in energy efficiency across different regions have been identified as a primary hazard to the just transition. This study examines whether transferring low-carbon technology can improve the efficiency of energy, enhancing the overall energy efficiency, and marketing a sustainable and equitable energy future. In this paper, we utilize the Undesirable-SE-SBM model to estimate the energy efficiency of China's 30 provinces during 2012 to 2022, and empirically tested the impact of low-carbon technology transfer on the convergence of total-factor energy efficiency by convergence analysis. The results showed that: (1) There is evidence of σ convergence and absolute β convergence in the eastern and western regions, but not in the central region. (2) Low-carbon technology transfer can accelerate the convergence of total factor energy efficiency. Lagging regions that adopt low-carbon technologies can catch up with the advanced regions' level of total-factor energy efficiency. (3) There is regional heterogeneity in the effect of low-carbon technology transfer on the accelerating convergence of total factor energy efficiency. The western region experiences the most significant acceleration, followed by the eastern and central regions.

This paper examines the impact of green mergers and acquisitions (M&As) on firms’ transition to green exports. We develop a “Technology-Qualification” theoretical framework and conduct the empirical analysis using a matched dataset of Chinese listed manufacturing firms and customs records. The findings show that green M&As significantly promote firms’ green exports, and this effect remains consistent across a series of robustness test. Mechanism analysis reveals that green M&As promote green exports through two key channels: green innovation spillovers and green qualification spillovers. Further heterogeneity analysis indicates that the positive impact of green M&As on green exports is more pronounced among firms with stronger operational performance, weaker green foundations, and those involved in processing trade. In addition, green M&As not only stimulate green exports but also prevent the entry of polluting products and reduce the exit of green product, thereby driving a green-oriented dynamic restructuring of firms’ export structure. This paper offers micro-level insights into how firms can navigate the dual challenges of enhancing green production capabilities and overcoming barriers to green trade during their transition to green exports.

This paper examines the impact of asset bubbles on innovation and long-run economic growth within a semi-endogenous growth framework, incorporating idiosyncratic productivity shocks and endogenous credit constraints in the R&D sector. It demonstrates that pure bubbles tied to intrinsically useless assets and equity bubbles linked to intermediate goods firms can coexist, relaxing credit constraints and boosting entrepreneurs’ total factor productivity (TFP), which stimulates R&D and enhances growth along the transitional path. However, these bubbles generally do not influence the long-run economic growth rate. The model’s mechanisms and predictions are supported by aggregate and firm-level evidence, showing a positive correlation between equity bubbles and R&D investment, with stronger effects during periods of tightened financial constraints.

This study highlights asymmetries in liquidity risk pricing from the perspective of heterogeneously informed traders facing changing levels of preference uncertainty. We hypothesize that higher illiquidity premium and liquidity risk betas may arise simultaneously in circumstances where investors are asymmetrically informed about their trading counterparts’ preferences and their financial firms’ timely valuations of assets . We first test the time-varying state transition patterns of IML, a traded liquidity factor of the return premium on illiquid-minus-liquid stocks, using a Markov regime-switching framework. We then investigate how the conditional price of the systematic risk of the IML fluctuate over time subject to changing levels of preference uncertainty. Empirical results from the Chinese stock market support our hypotheses that investors’ sensitivity to the IML systematic risk conditionally increase in times of higher preference uncertainty as proxied by the stock turnover and order imbalance. Further policy impact analyses suggest that China’s market liberalization efforts, contingent upon its recent stock connect and margin trading programs, reduce the conditional price of liquidity risk for affected stocks by helping the incorporation of information into stock prices more efficiently. Tighter macroeconomic funding conditions, on the contrary, conditionally increase the price of liquidity that investors require.

The scale expansion of low-carbon industries and the green transformation of carbon-intensive industries are two sides of the same coin in achieving the “dual carbon” goals. However, research on transition finance supporting the upgrading of traditional existing carbon-intensive industries remains insufficient. The key to examining the effectiveness of transition finance lies in distinguishing whether the supported enterprises are engaging in greenwashing or green evolution. Based on data of Chinese A-share listed companies in the carbon-intensive industries, an empirical study is conducted and offers the following findings: (1) Transition finance not only does not increase greenwashing but also promotes comprehensive green innovation in carbon-intensive enterprises. (2) In terms of the influencing mechanism, transition finance exerts “resource effects” and “signaling effects,” promoting green innovation by improving debt maturity mismatch and attracting green institutional investors. (3) Heterogeneity analysis shows that the positive impact of transition finance on green innovation is particularly pronounced among enterprises in the eastern region, state-owned enterprises, and those with lower levels of managerial myopia. (4) Further industry spillover effects analysis reveals that transition finance empowers green innovation within industries though peer effects and competitive effects. The findings are essential for understanding the effectiveness of transition finance and offer valuable insights for policymakers.