This study theoretically and empirically examines the impact of intangible capital on firm markups. The current research follows Altomonte et al. (2021) and first establishes a theoretical framework of intangible capital affecting firm markups. Accordingly, this study finds that an increase in intangible capital results in an increase in firm markups via the “production efficiency” channel but a decrease in firm markups via the “market-based pricing” channel. We use the data of Chinese manufacturing firms to further empirically study the influence of intangible capital on firm markups and its influencing mechanism. After a series of robustness and endogeneity tests, this research finds that intangible capital is conducive to increasing firm markups. Results of the empirical analysis also reveal that the positive impact of an increase in intangible capital on the markups of Chinese manufacturing firms via the “production efficiency” channel are higher than the negative impact of an increase in intangible capital via the “market-based pricing” channel. Moreover, the impact on the markups of different types of firms are not the same, with significant heterogeneity characteristics. This study provides micro evidence from a large developing country on how intangible capital affects the change in firm markups, thereby providing a new perspective on the economic effects of intangible capital.

Purpose: High investment efficiency is a key dimension of high-quality enterprise development. As critical nodes embedded in supply chain networks, corporate investment behaviors are profoundly shaped by the structural characteristics of their supply chains. Concentrated supply chain configuration, as one of the core structural features, has not yet been systematically examined in terms of its impact on corporate investment efficiency and the underlying mechanisms, leaving an important research gap. Design/methodology/approach: Based on a sample of China’s A-share listed enterprises from 2007 to 2023, this study empirically examines the effect of concentrated supply chain configuration on corporate investment efficiency. Findings: First, concentrated supply chain configuration exerts a significant inhibitory effect on corporate investment efficiency, a conclusion that remains robust after a series of tests. Second, mechanism tests indicate that this influence operates primarily through three channels: exacerbating financing constraints, crowding out working capital, and deteriorating the information environment. Third, heterogeneity analysis shows that both supplier concentration and customer concentration inhibit investment efficiency, with the latter having a slightly stronger negative effect. The adverse impact is more pronounced in over-investing enterprises, non-state-owned enterprises, smaller firms, and those in growth or decline stages. Furthermore, regional factor market development, external market power, and internal control quality are found to effectively mitigate the negative effect of concentrated supply chain configuration on corporate investment efficiency. Originality: This study extends the research on determinants of corporate investment efficiency from a supply chain structure perspective, providing new theoretical insights and empirical evidence for understanding corporate investment behavior in China.

The governmental governance environment significantly influences real corporate investment. Based on the data of listed A-share enterprises from 2010-2020,we adopt a heterogeneous timing difference-in-differences method to examine the impact of Open government data (OGD) on real corporate investment by leveraging the launch of OGD platforms. It is found that OGD significantly promotes real corporate investment. This conclusion remains robust after a series of tests for robustness and endogeneity, including parallel trend, placebo, heterogeneity treatment effect, and replacing variable. The analysis of the impact mechanism reveals that OGD influences real corporate investment by reducing enterprise uncertainty and alleviating financing constraint. The heterogeneity analysis indicates that OGD exerts a more pronounced investment promotion effect on non-state-owned enterprises, without political affiliations, regions characterized by intense government intervention, and areas exhibiting low social trust. This study contributes both conceptual insights for advancing the real economy with higher quality and practical recommendations to support the modernization of national governance structures and administrative effectiveness.

This paper examines biodiversity risk transmission to US agricultural futures markets. We find: (1) all futures exhibit moderate-to-high biodiversity sensitivity, with coffee showing highest response through transparent price transmission mechanisms; (2) wavelet analysis reveals time-frequency heterogeneity, where tropical crops maintain strong long-term synchronization with biodiversity risk, intensified during COVID-19; (3) frequency-dependent asymmetric correlations emerge, with grains shifting from positive long-cycle to negative short-cycle correlations; (4) systemic spillover analysis indicates moderate interdependence, with soybeans as primary risk receiver and sugar as dominant transmitter, revealing differentiated transmission roles.

This study employs a Triple-Difference (Triple-DID) model, utilizing balanced panel data at the district level from Beijing, Shanghai, Shenzhen, and Hangzhou between 2018 and 2024, to critically evaluate the effectiveness of the Multi-School Zoning Policy (MSZP) in suppressing the capitalization of educational resources into housing prices and promoting educational equity. The research explicitly accounts for spatial and institutional heterogeneity as well as household strategic behavior.The results indicate that: (1) MSZP significantly reduced the average housing price premium associated with elite school districts by 15.2%, with the strongest effect observed in Beijing and the weakest in Hangzhou; (2) The policy's effectiveness diminishes as the spatial concentration of high-quality educational resources increases, highlighting persistent structural inequalities; (3) In areas characterized by resource monopolization and strong institutional inertia, the policy's suppressive effect on educational capitalization and its gains in educational equity are both constrained.The findings suggest that MSZP alone cannot fully overcome the "spatial lock-in" effect of high-quality educational resources. Achieving lasting equity requires complementary deeper institutional innovations, such as robust cross-district teacher rotation, transparent resource allocation mechanisms, and adaptive zoning algorithms. This research offers quantitative evidence for optimizing policy and institutional tools in the pursuit of comprehensive urban education reform.

This study investigates the impact of Total Factor Productivity(TFP) growth in China's high-tech industry on household consumption, examining the distinct roles of labor and capital factor productivity from the perspective of biased technological progress. We innovatively construct a sequential proportional NDDF-Luenberger index. This index not only provides a theoretically consistent measure of TFP but also enables its precise decomposition into labor factor productivity and capital factor productivity, allowing for the quantitative identification of the degree and direction of technological bias. Our analysis yields three key findings. First, China's high-tech industry TFP evolved through a three-phase pattern of "surge–retreat–recovery," characterized by persistent capital-biased technological progress. Second, at the national level, improvements in overall TFP, labor factor productivity, and capital factor productivity all significantly promote household consumption, validating the theoretical pathway where supply-side efficiency gains stimulate demand. Third, significant regional heterogeneity exists: the Eastern region exhibits a "capital-led" growth pattern with weaker consumption effects from labor productivity; the Central and Western regions show "factor synergy," where both productivities contribute to consumption; whereas the Northeastern region suffers from a blocked transmission mechanism, where technological progress fails to significantly boost local consumption due to insufficient integration with the regional economy. By integrating supply-side TFP with demand-side consumption through the lens of biased technological progress, this research provides critical insights for fostering a virtuous cycle between innovation and domestic demand, offering valuable implications for industrial and regional policy design aimed at sustainable and inclusive growth.

Utilizing microevaluation data on the extent to which firms advance the achievement of the UN’s Sustainable Development Goals (SDGs) provided by Robeco, this paper examines the influence of corporate sustainability on stock price performance and its underlying economic mechanisms. The empirical results suggest that firms’ sustainability has a significant negative effect on excess returns, particularly the contribution of firms to the social dimension of sustainability. Firms’ SDG performance can alleviate financing constraints and reduce financial risk, but it does not significantly enhance financial performance, leading to market capital outflows from high SDG-performing firms, especially from individual investors. Furthermore, our results suggest that high SDG-performing firms are undervalued and do not increase the information content in their stock prices, which may be the main reason for the negative effect of SDG performance. We also conduct a series of heterogeneity tests, which show that firms from regions with high environmental regulatory intensity and less economic development, as well as heavily polluting firms and firms with poorer information environments, experience greater negative effects. These findings have implications for investors to properly understand corporate sustainability and for regulators to promote the development of a low-carbon economy.

We revisit cross-asset time-series momentum (XTSM) and single-asset time-series momentum (TSM) in China's stock and bond markets. With a fixed-effects model, we find a positive momentum from bonds to stocks and a negative momentum from stocks to bonds, with both momentum persisting for no more than six months. By employing a cross-grouping method, we find that the choice of lookback periods and asset signals impacts the performance of XTSM and TSM. A comparison between XTSM, TSM, and time-series historical (TSH) portfolios reveals that XTSM outperforms in small/midcap stocks and government bonds, while its performance is weak in large-cap stocks and corporate bonds. A spanning test confirms that XTSM generates excess returns that other pricing factors can not explain. XTSM is more prone to momentum crashes. Increased market stress has similarly adverse effects on XTSM and TSM. Furthermore, Market illiquidity, IPO counts, new investor accounts, and consumer confidence index positively correlate with the returns of XTSM and TSM portfolios, while IPO first-day return and turnover rate correlate negatively. The effects of these sentiment indicators exhibit heterogeneity.

We empirically examine how institutional investors react to adjustments in environmental policies in China. We observe a seemingly counterintuitive phenomenon: when environmental policies intensify, fund managers do not increase their holdings in high ESG-rated firms as might typically be expected; instead, they significantly divest from these firms. This behavior stems from the fact that, under stringent environmental policies, maintaining a high level of ESG investing leads to financial losses and fund outflows, especially in the short term, which impair fund managers’ compensation and raise career concerns. Further, within the context of environmental policy adjustments, our heterogeneity analysis tries to disentangle the true motivations behind institutional investors' ESG adoptions. We demonstrate that both pro-social preferences and financial incentives play pivotal roles, and that fund managers do not tolerate unlimited financial losses when ESG investing underperform. Our findings reveal the economic impact of environmental policies on institutional investors and shed light on the contentious and complex nature of the ESG concepts.

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.