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Advancing data factor marketization can fully unlock its value,crucially enhancing manufacturing supply chain resilience.Based on data of A-share manufacturing listed companies from 2011 to 2021,this study systematically examines the impact mechanisms and effects of data factor marketization on supply chain resilience through dual perspectives of market operations and policy guidance.The results show that data factor marketization significantly strengthens supply chain resilience,and this conclusion remains robust across a series of robustness tests.From the market perspective,the effect is more pronounced for firms with lower market positions,non-stateowned enterprises,and firms in technologyintensive industries,highlighting the inclusiveness and technological attributes of data factor marketization.Mechanism analysis shows that,at the firm level,data factor marketization enhances manufacturing supply chain resilience by reducing transaction costs and facilitating digital transformation.From the policy perspective,at the city level,the establishment of data trading platforms improves manufacturing supply chain resilience by stimulating digital innovation.Moreover,stronger regional intellectual property protection further strengthens the positive effect of data factor marketization on manufacturing supply chain resilience.These findings provide important policy implications for realizing the potential value of data factors and synergistically enhancing manufacturing supply chain resilience through the coordinated roles of market mechanisms and policy guidance.
Green innovation is crucial for balancing economic performance with environmental sustainability.Using data from China's A-share listed companies between 2003 and 2023,the study investigates how climate risk perception influences corporate green innovation.The results indicate that,overall,climate risk perception significantly enhances green innovation activities.Mechanism tests reveal that the promoting effect operates through two distinct channels:first,by strengthening firms' willingness to pursue green transformation and stimulating their motivation for green innovation;and second,by increasing firm-specific risks and thereby reducing financial support available for such innovation.Furthermore,the promoting effect of climate risk perception is more pronounced in non-state-owned enterprises and in firms operating in industries with higher exposure to climate risks.Further analysis shows that the driving force behind this effect stems primarily from transition risks rather than physical risks.Additionally,the signing of the Paris Agreement has amplified the positive influence of climate risk perception on green innovation.Based on the above conclusions,the study derives the following implications.First,in response to climate risks and the pressures of economic green transformation,the government needs to strengthen policy guidance and build a systematic policy support framework.This will facilitate a shift for enterprises from passive adaptation to proactive transformation.Second,it is essential to establish and improve corporate climate risk information disclosure systems to enhance transparency.This involves developing systematic and scientific disclosure standards and implementation guidelines,and promoting the establishment of a disclosure regime that integrates both mandatory and standardized elements.Third,a market-driven external governance ecosystem should be constructed to stimulate endogenous motivation for corporate green transformation through diversified oversight and incentive-compatible mechanisms.On the one hand,the incentivizing and constraining roles of stakeholders,such as investors and consumers,should be fully leveraged in corporate climate risk management.On the other hand,the supervisory and interpretive functions of securities analysts,rating agencies,and media regarding corporate green innovation activities need to be strengthened.Compared with the existing literature,the main contributions of the study are threefold.First,it enriches the literature on the drivers of corporate green innovation by introducing the perspective of climate risk perception.While prior studies have primarily focused on factors such as environmental regulations,social credit system reforms,and corporate governance,the study examines how the subjective construct of climate risk perception influences corporate green innovation and its underlying pathways,thereby deepening the theoretical understanding of corporate green innovation behavior.Second,the study expands the literature on the microeconomic consequences of climate risk—particularly climate risk perception—by focusing on green innovation.Existing researchs have largely investigated outcomes such as stock returns,financing costs,and earnings management in the context of climate risk,yet has overlooked the relationship between climate risk perception and green innovation.As green innovation serves as a critical means for firms to enhance green competitiveness and strengthen organizational environmental legitimacy,examining its link with climate risk perception contributes to a more comprehensive understanding of the microeconomic effects of climate risks and offers important insights into how such risks influence corporate performance.Third,in terms of mechanism analysis,the study investigates how climate risk perception affects green innovation through two channels:green transition willingness and idiosyncratic risk.The findings provide new empirical evidence to unravel the “black box” of the impact pathways of climate risk perception.
The global economic environment has become increasingly complex and volatile,with trade policy uncertainty(TPU)emerging as a fundamental factor shaping fluctuations in industrial chains worldwide.Escalating trade frictions,intensifying geopolitical tensions,and the restructuring of supply chains amid the aftermath of the global public health emergency have generated persistent external shocks that threaten the stability of international production networks.For China,which holds a pivotal position within the global manufacturing and trade system,the evolution of TPU exerts a profound and lasting influence on industrial performance and structural interdependence.Examining how TPU affects long-term volatility and dynamic correlations within China's industrial chain is essential for understanding industrial resilience and sustainable economic development.To quantify these effects,the Generalized Autoregressive Conditional Heteroskedasticity Mixed Data Sampling(GARCH-MIDAS) model and the Dynamic Conditional Correlation Mixed Data Sampling(DCC-MIDAS)model are employed.Monthly TPU indices are integrated with daily return data from the upstream,midstream,and downstream sectors of China's industrial chain from 2014 to 2024.The mixed-frequency econometric approach enables the simultaneous capture of high-frequency financial market dynamics and low-frequency macro-policy influences,allowing for a more comprehensive assessment of volatility behavior and intersectoral linkages under policy uncertainty.By bridging heterogeneous data frequencies,the models effectively overcome the limitations of traditional single-frequency volatility frameworks and provide richer insights into the transmission mechanisms of trade uncertainty.Empirical evidence indicates that TPU has a statistically significant and negative effect on long-term volatility across China's industrial chain.The impact is most pronounced in upstream resource-based industries,which are more exposed to global commodity and trade disruptions,while the effects on midstream manufacturing and downstream consumer sectors are relatively weaker.Moreover,TPU significantly reduces the long-term correlations between upstream-midstream and midstream-downstream sectors,implying that elevated uncertainty weakens industrial coordination and integration.However,the correlation between upstream and downstream sectors remains statistically insignificant,suggesting that uncertainty primarily transmits through adjacent stages rather than across the entire value chain.Robustness analyses using alternative measures such as the Economic Policy Uncertainty(EPU)index and comparative evidence from the United States confirm the stability and general applicability of the findings.Consistent results across indicators and countries reinforce the conclusion that trade policy uncertainty constitutes a key determinant of long-term industrial volatility and structural correlation.Methodologically,the integration of GARCH-MIDAS and DCC-MIDAS models introduces a novel mixed-frequency perspective into industrial chain analysis,allowing for the separation of short-term financial fluctuations from long-term policy effects and enriching the empirical understanding of volatility persistence within production networks.From a policy perspective,the results offer both theoretical and practical implications.Investors are advised to diversify portfolios across industrial segments and employ volatility-based hedging strategies to mitigate risks arising from policy uncertainty.Policymakers are encouraged to enhance transparency,predictability,and international coordination in trade policy to stabilize long-term industrial linkages.Strengthening supply chain resilience is also essential:upstream industries should prioritize resource security and technological upgrading;midstream sectors should accelerate digital transformation and industrial collaboration to reduce vulnerability to supply disruptions;and downstream industries should expand market diversification and regional trade partnerships to offset demand-side volatility.Understanding how TPU influences long-term volatility and intersectoral correlations provides valuable insights for safeguarding industrial stability and promoting sustainable economic growth in an era of persistent global uncertainty.
The rural circulation system is the only bridge between rural production and consumption,and is also an important starting point for the priority development of agriculture and rural areas.By constructing a theoretical model for the development of rural circulation system empowered by digital economy,using the dynamic QCA research method,the multiple configuration paths of various dimensions of digital economy are examined in the process of improving the development of rural circulation system from time and space dimensions.The research finds are as follows.The high-quality development path of the rural circulation system is diversified,and there are three configuration paths,the configuration of digital investment-scale-driven resource coordination type(a1),digital talent-infrastructure-driven technological innovation type(a2)and digital industry-investment-driven factor sharing type(a3).To achieve the development level of high-quality rural circulation system requires the synergistic effect of multiple digital conditions,and single condition variable cannot directly contribute to the development of high-quality rural circulation system.Digital investment and digital scale as the core missing conditions will lead to the development of non-high-quality rural circulation system.The development of high-quality rural circulation system has a significant temporal effect,and there are multiple paths for each province to realize the development of high-quality rural circulation system.The development of digital economy has brought new opportunities for the development of rural circulation system,and it is necessary to adapt to local conditions to explore the high-quality development path of rural circulation system.From a theoretical perspective,the high-quality development of rural circulation is an expansion and elevation of the theory of high-quality economic development in the fields of logistics and rural development.From a practical perspective,the exploration of the digital development path of rural circulation helps to further improve the modern circulation system and promote the integrated development of urban and rural areas.
The digitization of tax administration marks a major transformation in China's tax governance model,yet its differential effects on corporate strategic versus substantive innovation remain underexplored.This paper treats the phased implementation of the “Golden Tax Phase Ⅲ” project as a quasi-natural experiment and examines data from Chinese A-share non-financial listed firms over the period2009-2023.The results show that tax administration digitization has no significant impact on strategic innovation but significantly promotes substantive innovation,with the positive effect being more pronounced in non-state-owned and high-tech firms.Mechanism tests reveal that this differentiated impact is primarily driven by the alleviation of external liquidity constraints.Further analysis indicates that while tax administration digitization significantly enhances firms' overall innovation,it also significantly inhibits equity financing.These findings suggest that to strengthen firms' substantive innovation capabilities,efforts should focus on improving the informatization level of tax administration,standardizing tax enforcement,and innovating fiscal and tax support instruments.
Clarifying the interplay between new quality productive forces and economic resilience,and capturing their coupling coordination dynamics,is essential for promoting the development of new quality productive forces and advancing China's high-quality economic growth.Based on an integrated evaluation framework,a coupling coordination degree model,kernel density estimation,spatial correlation analysis,and spatial econometric models are employed to examine the spatiotemporal evolution and determinants of their coupling coordination degree in China from 2014 to 2023.Results show that:both systems exhibit steady upward trends,while the coupling coordination degree evolves toward a bipolar pattern,with increasing regional dispersion and widening absolute disparities;Spatial heterogeneity is observed,characterized by a“high in the east and low in the west” pattern,with stable spatial dependence reflected in “H-H” clusters in the eastern coastal region centered on the Yangtze River Delta and “L-L” clusters in the western and northeastern regions centered on Inner Mongolia,Xinjiang,and Jilin;A significant mutually reinforcing effect exists between the two systems,with new quality productive forces exerting a stronger positive impact.Specifically,new quality productive forces contribute most to the transformation and development capability subsystem,while economic resilience has the strongest marginal effect on the new quality meansof-labor subsystem.Furthermore,virtual agglomeration,government intervention,urban economic development,market scale,and teaching and research significantly enhance local coupling coordination,whereas foreign direct investment exerts an inhibitory effect.Government intervention,market scale,and education and research produce positive spatial spillovers,whereas virtual agglomeration and foreign direct investment generate negative spatial spillovers.
Local debt risks and real estate risks represent two critical areas in the prevention of systemic financial risks.Addressing these risks in a steady and orderly manner is essential for safeguarding financial stability and fostering high-quality development.Based on hand-collected comprehensive data on local government debt,this study employs a panel fixed-effects model at the firm level to empirically examine how local government debt affects the leverage ratio of listed real estate enterprises.The findings reveal that whether local government debt leads to higher leverage in real estate firms depends on the region's reliance on land finance.In areas with high land finance dependency,local government debt significantly increases the leverage of listed real estate companies.This effect is particularly pronounced in regions with lower levels of economic development,greater fiscal pressure,and weaker market institutions,as well as for real estate firms with abundant internal financing and slower accounts payable turnover.Further analysis indicates that local governments primarily transfer debt pressure to real estate enterprises through the land scale-price effect and the credit constraint alleviation effect,which drive up short-term leverage and encourage inventory accumulation.However,when credit policies for the real estate sector are tightened,the risk transmission channel from local government debt to the real estate sector is disrupted,resulting in a “debt dam” phenomenon.Accordingly,this paper proposes that fiscal and tax system reforms should be deepened to enhance the sustainability of local public finances,steadily and orderly weaken the risk linkage between local government debt and the real estate sector,and accelerate the establishment of a new model for real estate development.
With the rapid advancement of digital technology,the variety of digital products has expanded significantly,playing a vital role in promoting economic and social development.Research on the statistical classification and accounting treatment of digital products is essential for compiling Supply-Use Tables for the Digital Economy(Digital SUTs),improving the digital economy's statistical measurement system,and accurately reflecting the impact of digital products on economic and social development.Firstly,a review is carried out of the development history from “ICT products” to “content and media products” and further to “digital products”.With reference to the latest international standard for national accounting,the System of National Accounts 2025(SNA 2025),the definitions and classifications of digital products are elaborated,and their key characteristics sorted out,including non-rivalry,network effects,rapid iteration,and spatial transcendence.Secondly,it summarizes the important role of digital product statistical accounting in the measurement of macroeconomic statistical indicators,the monitoring of the development level of digital economy and the improvement of enterprise production efficiency and market adaptability.Thirdly,international and domestic research progress on specific types of digital products such as cloud computing,data and databases,artificial intelligence,free digital products,and non-fungible tokens is systematically reviewed.By aligning digital products with the officially issued Statistical Classification Catalogue of Products in China,this study attempts to identify relevant product categories that correspond to or are widely penetrated by digital products,and further explores appropriate valuation methods.Finally,the challenges and future directions for the statistical accounting of digital products are outlined,with corresponding policies and suggestions proposed.A reference is provided for improving the statistical accounting system of digital products and the digital economy,and theoretical and methodological support is offered for promoting the high-quality development of the digital economy.
Green development refers economic growth and social development that aims at efficiency,harmony and sustainability,with its core being the achievement of harmonious coexistence between environmental protection and economic development,thereby realizing a win-win outcome.Currently,Chinese enterprises still face two major challenges in their green transformation proess:insuffieient transformation momentum and inadequate transformation capabilities.As a core element in the era of digital economy,can data elements drive the green transformation of enterprises?What are the paths of corporate green transformation?Does significant heterogeneity exist in this driving effect?Answering the above questions is not only crucial for enterprises to innovate their production and operation methods and advance their green,high-quality and sustainable development,but also of great significance for promoting China's economic transition to green development,achieving the“Dual Carbon” goals,and realizing high-quality and sustainable economic development.Therefore,this study addresses the above issues through theoretical analysis and empirical verification.This paper selects all A-share non-financial listed companies in China from 2011 to 2023 as the research samples,and employs a two-way fixed-effects regression model,to empirically examine the impact of micro data elements on corporate green transformation in China and its underlying mechanisms from a micro-level perspective.The study finds that:First,data elements can effectively drive the green transformation of Chinese enterprises.Second,data elements can effectively alleviate the information asymmetry faced by enterprises,promote green technological innovation,and thereby drive corporate green transformation.Third,government subsidies play apositive moderating role in the process of data-driven corporate green transformation.Moreover,the driving effect of data elements on corporate green transformation is more significant in the central and western regions,non-heavily polluted enterprises,and state-owned enterprises than in the eastern regions,heavily polluted enterprises,and non-state-owned enterprises.Based on the above findings,this study constructs a systematic solution from the three dimensions:institutional innovation,subject empowerment,and policy synergy,to provide a multi-dimensional practical path for fully releasing the multiplier effect of data elements in green transformation.This study not only provides theoretical insights and practical decision-making reference for corporate green transformation in the digital economy era,but also aligns with the requirements of the “dual carbon” strategy and highquality development.It further provides a way to crack the structural contradiction in the “transition pain period”,and supports China in building a modernized industrial system and a green development model.
Robust domestic demand generated by China's new urbanization has positioned it as a critical nexus linking the supply and demand sides within the new development paradigm.Against the evolving backdrop of institutional opening-up,understanding how new urbanization shapes banks 'risk-taking behavior is essential for safeguarding economic and financial stability during the transition to high-quality development.Using an annual panel dataset of 273 regional banks in China from 2011 to 2022,an empirical analysis is conducted to evaluate the impact of new urbanization on banks 'risk-taking,to identify the underlying transmission mechanisms,and to examine the moderating role of institutional opening-up.The empirical evidence yields four main findings.First,new urbanization exerts a significant inhibitory effect on banks' risk-taking.This result remains robust after addressing potential endogeneity concerns via instrumental variable estimation,lagged dependent variable specifications,omitted variable tests,dynamic panel models,and alternative clustered robust standard errors specifications.The conclusion is further supported by a series of robustness checks,including alternative measures of core explanatory variables and maximum likelihood estimation.Heterogeneity analysis reveals pronounced regional differences:the riskmitigating effect of new urbanization is stronger for banks located in central and western regions,smallersized cities,and areas with relatively underdeveloped economic and financial systems.Second,mechanism analysis indicates that new urbanization reduces banks' risk-taking through three distinct channels:enhanced off-balance-sheet profitability,improved credit quality of loan portfolios,and reduced credit concentration.The transmission pathways of "new urbanization—off-balance-sheet profitability/loan credit rating/credit concentration—banks' risk-taking" are all empirically validated.Third,moderating effect analysis highlights the amplifying role of institutional opening-up.Higher levels of institutional opening-up strengthen the effectiveness of new urbanization in curbing banks' risk-taking.This effect is particularly pronounced in the investment and information dimensions of institutional opening-up,underscoring the importance of improved cross-border information flows and investment liberalization in enhancing risk governance within the banking sector.Moreover,financial opening-up weakens the inhibitory effect of new urbanization on regional banks' risk-taking only in the central and western regions.Institutional openingup strengthens the risk-mitigating effect of new urbanization exclusively in non-resource-based cities.Finally,an extended analysis of risk-taking types shows that new urbanization exerts a stronger inhibitory effect on banks' active risk-taking than on passive risk-taking.Overall,these findings deepen the understanding of the economic and financial consequences of new urbanization and contribute to the literature on the interaction between institutional opening-up and financial stability.The results also provide policy-relevant implications for improving the governance efficiency of institutional opening-up,strengthening financial system stability,advancing high-quality economic development,and promoting Chinese-style modernization.