Adverse selection remains a significant challenge in the insurance industry, often resulting in substantial financial losses for insurers. The primary hurdle in addressing the issue lies in accurately identifying and quantifying adverse selection. Traditional methods often fail to adequately account for the heterogeneity of insurance purchasers and the endogenous nature of their insurance decisions. This study introduces an innovative approach that integrates the Gaussian Mixture Model and the regression-based model from Dionne et al. (2001) to assess adverse selection, addressing the limitations of previous methods. Through comprehensive simulations, we demonstrate that our method yields unbiased estimates, outperforming existing approaches. Applied to China’s automobile insurance market, leveraging IoT devices to track telematics data, this method captures risk heterogeneity among the insured. The results offer robust evidence of adverse selection, in contrast to conventional methods that fail to detect this phenomenon due to their inability to capture the underlying relationship between customer risk and claim behavior. Our approach offers insurers a robust framework for identifying information asymmetries in the market, thereby enabling the development of more targeted policy interventions and risk management strategies.

The relationship between ESG factors and corporate performance is contentious, partly due to the literature's neglect of organizational demographic differences. Using data from 5,127 Chinese companies (2009-2022), we empirically analyze ESG's impact on corporate performance, factoring in the demographic heterogeneity of executive teams. Our findings indicate that although ESG indeed enhances corporate performance, its conversion effect is significantly influenced by the vertical dyads of gender and education within the top management teams (TMT). Additionally, our extended analysis reveals that these two types of vertical dyads exhibit distinct structural characteristics.

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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 study examines how full-time external supervisors affect corporate irregularities using listed Chinese state-owned enterprises (SOEs) as a research sample. We find that full-time external supervisors restrain corporate irregularities. This outcome continues to hold after accounting for potential endogeneity concerns. Further mediating effect analysis shows that full-time external supervisors mitigate corporate irregularities by curbing managers' opportunistic behavior. Additionally, the heterogeneity analysis demonstrates that the impact of full-time external supervisors on corporate irregularities varies significantly across different types of SOEs and internal control environments. Overall, this paper enriches and expands the literature on the effectiveness of full-time external supervisors in emerging economies and provides new insights for dealing with corporate irregularities.

This paper investigates how institutional investors’ site visits affect firm productivity by using a dataset of China’s A-share listed firms. The findings reveal that site visits have a constructive effect on firm productivity. Moreover, mechanism analysis indicates that reducing information asymmetry and improving stock price informativeness are two channels through which site visits influence firm productivity. Heterogeneity analysis demonstrates that the nexus between site visits and firm productivity is more pronounced for non-state-owned firms and firms with intenser product market competition. Overall, this study brings new insights into the benefits of site visits and highlights the importance of investor activism.

Enterprise digital transformation has become an inevitable trend in the digital economy era that can significantly impact enterprises. This paper takes the data of A-share listed companies from 2006 to 2022 as a sample to explore the effect of enterprise digital transformation on listed companies' corporate social responsibility and the mechanism of its role. It was found that corporate digital transformation can significantly enhance Csr(Corporate social responsibility), and enterprise digital transformation has a noticeable enabling effect on Csr, which can dramatically improve Csr. The relationship between the two still holds after the robustness test. It has been found that digital transformation can affect Csr by enhancing the green innovation capability of enterprises, the fairness of internal compensation distribution, and the sustainable development capability of enterprises. Heterogeneity analysis reveals that corporate digital transformation's impact on Csr fulfillment performance is more significant for non-state-owned firms and firms in the central and eastern regions. In addition, corporate financing constraints and government innovation subsidies influence Csr.

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.

As China’s Zero-COVID policy has come to an end and travel restrictions have been removed, the country’s mobility patterns are very likely to become more heterogeneous than during the pandemic. Human mobility is a key mechanism through which economic activities emerge and viruses spread. It can bring both advantages and challenges to cities with different characteristics. This paper investigates intra-city mobility trajectories of 368 Chinese cities within a non-linear time-varying latent factor framework to uncover the evolution of heterogeneity in local travel behavior amidst that China has been approaching the turning point of the post-pandemic new normal. To this end, we compiled a novel panel on a weekly basis, using the latest Baidu Mobility Data and the risk-level data released by the State Council of the People’s Republic of China. We further examine the effects of exposure to high COVID-19 risk in the city on commuting behavior between May 17, 2021 and June 26, 2022. Our results provide stylized facts on stratified local travel across China: first, the 368 cities can be categorized into six clusters based on their mobility dynamics, and second, the gaps in intra-city mobility tend to narrow within each cluster but widen between different clusters. Moreover, exposure to high COVID-19 risk has a stronger impact on home-workplace commuting rates than on dining-, leisure, and recreational travel rates, persistently dampening commuting behavior. In addition, divisions in intra-city travel strength and commuting behavior between western regions and the rest of China are evident. In sum, this paper suggests that the daily life and economic activities which depend heavily on human mobility are recovering at different rates across China.