This paper investigates the impact of FinTech on corporate inefficient investment, exploring whether FinTech can enhance the quality and efficiency of corporate investment.The findings reveal that FinTech development significantly mitigates underinvestment and curbs overinvestment, with a more pronounced governance effect on overinvestment, thereby demonstrating a remarkable role in improving investment quality and efficiency.Mechanism analysis shows that FinTech enhances corporate investment efficiency by promoting uncertainty governance.Further research indicates that FinTech not only alleviates financing constraints but also optimizes resource allocation to support high-quality enterprises, fostering a market environment of survival of the fittest.Moreover, high-quality information disclosure and a high level of corporate governance play a positive moderating role, helping to better leverage the governance effect of FinTech development on corporate investment efficiency.Furthermore, the improvement in corporate investment efficiency brought about by FinTech development contributes to enhancing production efficiency, fostering new quality productive forces, and improving enterprises' product market performance.The conclusions provide a deeper understanding of the consequences of FinTech development on corporate investment behavior, offering theoretical basis and policy recommendations for governments to guide FinTech development, address corporate investment issues, and achieve healthy and sustainable economic development.

Digital transformation enables enterprises to turn digitalization into environmental benefits. However, whether environmental policies can reverse this process turning environmental benefits into digital dividends, and whether heterogeneous policy tools can work synergistically remain underexplored. Using a quasi-natural experiment of demonstration cities for energy-saving and emission reduction fiscal policies, we find that combining fiscal subsidies(incentive-based)with command-and-control regulations promotes enterprise digital transformation.Incentive tools ease financial burdens but may distort environmental incentives and induce strategic innovation.Regulatory tools impose rigid constraints on substantive technological progress but yield no additional revenue, risking cost burdens if overused.Moreover, business uncertainty dampens policy effects, excluding“three high”industries from benefiting.The policy effect is stronger for enterprises in low-fiscal-dependence regions, while in low-marketization regions it concentrates in state-owned enterprises.This study offers new insights into synergizing environmental policy tools to balance transformation benefits with market burdens.

Enhancing the innovation capability of state-owned enterprises is essential for achieving high-level technological self-reliance and self-strengthening, promoting the deep integration of technological innovation and industrial innovation, and developing new quality productive forces.Based on a theoretical analysis of the innovation function of state-owned enterprises, this paper combines the entire process of innovation to construct an evaluation index system for the comprehensive innovation capability of state-owned enterprises.The system encompasses five elements:innovation input capability, technological innovation capability, non-technological innovation capability, collaborative innovation capability, and innovation output capability.We further measure the comprehensive innovation capability of state-owned enterprises using data of Chinese listed companies from 2015 to 2024.The results show that the comprehensive innovation capability of state-owned enterprises shows a fluctuating upward trend.This improvement is primarily attributed to the enhancement of non-technological innovation capacity brought about by reforms in management mechanisms.However, contributions from innovation output capabilities, such as the marketization of innovation achievements, are insufficient.Further study also found that the inter-regional gap in the comprehensive innovation capability of state-owned enterprises has narrowed, whereas the inter-industry gap has widened.The comprehensive innovation capability of state-owned enterprises has surpassed that of non-state-owned enterprises, and state-owned enterprises have distinct advantages in non-technological innovation and collaborative innovation.To enhance the comprehensive innovation capability of state-owned enterprises, it is necessary to strengthen institutional and management innovation, build a collaborative innovation ecosystem, and promote the commercialization of innovationachievements.

Optimizing the efficiency of resource allocation is an important path to enhance total factor productivity and achieve high-quality economic development.Finance is the core hub that influences resource allocation.With the continuous integration of digital technology and traditional finance, inclusive finance digitalization has become an important factor affecting the efficiency of resource allocation.Using data from Chinese A-share listed enterprises, this study empirically examines the impact of inclusive finance digitalization on resource allocation efficiency and its underlying mechanisms from the perspective of spillover effects.We find that inclusive finance digitalization significantly reduces the dispersion of total factor productivity(TFP)among enterprises within regions and industries.A 10-unit increase in the level of inclusive finance digitalization lowers the standard deviation of inter-firm TFP by 0.060, thereby enhancing resource allocation efficiency.The mechanisms include reducing supply chain risks, diminishing market power, digital spillovers, increasing R&D investment, and human capital effects.Heterogeneity analysis reveals that the positive impact of inclusive finance digitalization on resource allocation efficiency exhibits spatial, industry and ownership heterogeneity.The effect on eastern regions, the manufacturing sector and non-state-owned enterprises are more pronounced.This study provides implications for empowering the real economy through digital financial innovation, thereby promoting the integration of the digital and real economies to advance high-quality development.

This paper evaluates the impact of policy-based agricultural credit guarantees, a key fiscal-financial innovation, on county-level industrial upgrading in China.Using county-level panel data from 2009 to 2023 and a staggered difference-in-differences design, we find that these guarantees significantly foster industrial structural transformation, with stronger effects in counties characterized by greater fiscal capacity, higher degrees of marketization, and more developed credit infrastructures.Mechanism analysis identifies two primary channels:a credit transmission effect that scales up loan volumes and improves allocative efficiency, and a real-sector cultivation effect that strengthens the growth capacity of micro-level firms.Importantly, the realization of the credit transmission effect relies heavily on partner banks possessing sufficiently advanced FinTech capabilities.In addition, we document that the policy has a larger marginal impact in counties with lower initial levels of industrial development, suggesting a role in promoting regional convergence, and that its effects are more pronounced when guarantees are partnered with national banks, whose hard-information-based risk management systems are highly complementary to external credit enhancement and therefore respond more strongly to such policy incentives.

In the context of widening income inequality, low-income groups have limited consumption capacity while high-income groups exhibit low marginal propensity to consume, potentially weakening economic growth.Thus, leveraging monetary policy's income distribution effect to narrow the income gap is crucial.This paper employs income quantile data from the World Inequality Database and constructs a Proxy-SVAR model to address endogeneity issues and recognition deficiencies in traditional SVAR models.Findings show:(1)Under expansionary monetary policy shocks, middle and low-income groups' incomes rise, primarily through wage income channels.High-income groups' incomes decline, affected via investment income channels, owing to weak transmission caused by factors such as the“housing not speculation”policy and sluggish stock markets.(2)Compared to traditional SVAR, the Proxy-SVAR overcomes attenuation bias in monetary shocks and identifies larger shocks.(3)Structural monetary policies benefit low-income groups more, yielding stronger distributional effects.China's monetary policy has curbed income inequality and supportsed common prosperity.In the future, we can actively use structural monetary policy tools to help low-income groups and help Chinese path to modernization.

It is of great theoretical and practical significance to study the impact of innovative city pilot policy on employment.Under the framework of an exogenous growth theory, this paper deconstructs how the innovative city pilot policy affects employment, and uses the innovative city pilot policy as a quasi-natural experiment to establish a multi-period Difference-in-Differences model for empirical analysis. The study found that the national innovative city pilot policy promoted the employment growth of related enterprises by about 7.43%, and various robustness analysis results showed that this effect was significant. The theoretical and empirical results of its mechanism path show that the pilot policy of national innovative cities promotes employment growth through innovation effect, scale differentiation effect and industry differentiation effect.The employment promotion effect of the pilot policy of national innovative cities is heterogeneous, which mainly promotes the employment growth in the central and western regions, the Yangtze River Economic Belt and the regions with better institutional environment.This paper affirms the positive employment effect of innovative cities, which is helpful to further deepen the pilot policy of national innovative cities and provide theoretical and empirical reference for promoting employment growth.

The escalation of Sino-US trade frictions has extended the focus of contention to the high-technology sector.Facing severe constraints imposed by external technological blockades on China's technological advancement, the vigorous development of artificial intelligence(AI)has become a core engine for breaking through containment and achieving high-quality technological development.Using a sample of A-share listed companies from 2007 to 2023, we employ textual analysis to construct a technological blockade index and examine the impact of external technological blockades on the development of AI in Chinese enterprises.The findings reveal that the“forcing effect”of external technological blockade significantly drives Chinese enterprises to enhance their AI technological capabilities. Mechanism analysis suggests that under the shock of technological blockade, a concentrated supply chain configuration contributes to enhanced supply chain resilience, thereby promoting the level of AI technology.Simultaneously, technological blockade can compel enterprises to increase R&D investment, thereby improving their AI capabilities.Heterogeneity analysis indicates that high financing constraints, inefficient investment, managerial short-termism, and industry concentration weaken the“forcing effect”of technological blockade.In further analysis, we find there is a positive effect of AI development on corporate production efficiency and value creation.This research enriches the field of AI-related studies and provides valuable insights for enterprises seeking to overcome external technological barriers, promote the integration of AI with the real economy, and achieve breakthroughs in AI application.

Business-to-government(B2G)data sharing represents a critical intersection between digital government development and the cultivation of data factor markets.However, in practice, it is often constrained by firms' reluctance characterized as“unwillingness, inability, and uncertainty”to share data. Drawing on structuration theory of technology, this study develops a dynamic analytical framework of“situated motivations-sharing rules”and conducts a longitudinal single-case study of the“City Brain”initiative in Haidian District, to systematically uncover the implementation mechanism of B2G data sharing.The findings reveal that B2G data sharing evolves through a spiral mechanism of“situated motivations-sharing rules-value creation,”progressing across three stages:point-to-point connection, systematic sharing, and platform-based operation.During this process, governmental motivations shift from peer competition pressure to service empowerment and ecosystem building, while enterprise motivations evolve from risk avoidance to opportunity seeking and value realization.Sharing rules shape these motivations through two key pathways:organizational restructuring and technological enablement. Furthermore, the creation of governance, market, and social value serves as the core driving force that reinforces motivations and drives the iterative evolution of sharing rules.This study extends the analytical boundaries of structuration theory of technology to cross-sector data collaboration and provides both theoretical insights and practical implications for promoting government-enterprise data integration and fostering a sustainable data ecosystem.