As geopolitical tensions intensify, unilateral sanctions have become an important“strategic weapon”through which the United States (U.S.) exerts external economic coercion. As a third-party country and a key node in the continued deepening of global supply chains, whether China can stabilize global production networks constitutes critical evidence of its role in promoting the building of a community with a shared future for mankind. Using firm-level supply-chain relationships between sanctioned-country firms and Chinese listed companies from 2009 to 2023, this study finds that U.S. sanctions shocks significantly promote the formation of cross-border supply chains between sanctioned-country firms and Chinese firms, highlighting China’s important third-party role within the sanction’s regime. Mechanism analyses based on institutional coordination and market coordination indicate that U.S. sanctions induce sanctioned countries to deepen free trade agreements with China and to increase their trade dependence on China, thereby facilitating the establishment of cross-border supply chains between the two sides. The third-party effects of U.S. sanctions on cross-border supply chains are more pronounced when sanctions take the form of trade sanctions, when bilateral political relations between the sanctioned country and China are relatively weak, or when cultural distance is smaller. Further analysis shows that U.S. sanctions not only significantly strengthen the maintenance of existing supply-chain relationships between sanctioned-country firms and Chinese firms, but also foster the formation of new supply-chain ties. In addition, the structural power analysis indicates that the production power and knowledge power of sanctioned countries strengthen the third-party effects of U.S. sanctions on cross-border supply chains, whereas market power weakens this effect.

External demand is crucial to a country’s economic growth. This is especially true at a time when China is comprehensively advancing high-standard opening-up, which makes it all the more necessary to study how macroeconomic policies can effectively mitigate the adverse effects of external demand shocks. By constructing a two-sector open-economy dynamic stochastic general equilibrium model, the effects of negative external demand shocks on the macroeconomy are analyzed, and on this basis the short-run and long-run effectiveness of fiscal policy as well as its welfare effects are further examined. The results show that, first, in the short run, a contraction in external demand exerts negative shocks on major economic variables such as employment, output, interest rates, and inflation, after which the economy gradually returns to its steady state. Meanwhile, consumption subsidies, tax cuts in the tradable sector, and tax cuts in the non-tradable sector can all effectively promote overall economic growth in the short run. Second, in the long run, fiscal policies can all effectively increase key macroeconomic variables: consumption subsidies are more effective in boosting employment, tax cuts in the non-tradable sector are more suitable for stimulating consumption, and tax cuts in the tradable sector can effectively raise aggregate output. Third, in the short run, consumption subsidies, tradable-sector tax cuts, and non-tradable-sector tax cuts all increase social welfare. Therefore, the key to comprehensively deepening fiscal reform lies in building a fiscal policy toolbox that combines short- and long-term measures and delivers precisely targeted interventions. Through cross-cycle and structure-optimizing policy design, this approach aims to achieve the strategic objectives of promoting development through reform and advancing opening-up through reform.

Promoting the intelligent transformation of the manufacturing sector is a critical pathway to mitigate demographic aging constraints and to foster high-quality manufacturing development. The reform of social insurance premium collection may serve as an institutional impetus for firms’ intelligent upgrading by inducing changes in factor prices. Using a panel of A-share listed manufacturing firms in China from 2013 to 2023, this study treats the 2018 reform plan on social insurance premium collection as a quasi-natural experiment and empirically examines its effects and mechanisms on firms’“machine replacement”. The results indicate that the reform significantly accelerates firms’ adoption of industrial robots. Heterogeneity analyses further show that the effect is more pronounced among firms facing greater difficulty in cost adjustments, firms with a lighter tax burden, and firms located in regions with stronger tax enforcement. Mechanism tests suggest that the reform promotes labor-capital substitution by increasing labor costs and enhances capital-technology complementarity by raising demand for high-skilled labor, thereby improving firms’ industrial robot intensity. Accordingly, policy efforts should further advance the reform by strengthening its legal foundations and technological support, leverage the induced factor substitution and skill-complementarity effects to facilitate robot adoption, and implement targeted measures for firms and regions under the greatest transformation pressure to guide intelligent manufacturing upgrading effectively.

How upgrades in the technology of tax enforcement affect corporate VAT declaration behavior is a key question for understanding the governance effects of digital tax enforcement. Employing the phased rollout of Golden Tax III as a quasi-natural experiment, and using data from the National Tax Survey of Enterprises from 2011 to 2019, this paper identifies corporate tax manipulation from the perspective of the VAT input-output tax ratio. The empirical results show that: First, after the implementation of Golden Tax III, the number of firms located to the left of the zero-tax-burden point and suspected of relatively high levels of tax manipulation decreased significantly. Second, from the perspective of firms’ declaration behavior, the upgrade in information technology for tax enforcement reduced the VAT input-output tax ratio of such firms by approximately 1.5% on average, indicating that the room for firms to maintain low tax burdens by adjusting input and output declarations has been compressed, and tax compliance has markedly improved. Third, this governance effect is more pronounced among firms with stronger incentives for tax manipulation, mainly reflected in larger reductions in the input-output ratio for small and medium-sized enterprises, non-state-owned firms, and those with higher pre-existing VAT credit balances. Fourth, further analysis shows that the constraining effect of the tax-enforcement technology upgrade on VAT manipulation is primarily exerted on the input side, with deductible input VAT declining significantly, while no significant change is observed on the output side. This suggests that Golden Tax III mainly compresses firms’ room for manipulation by strengthening the identification of abnormal credits and the verification of upstream-downstream matching. These findings provide new micro-level evidence for understanding how digital tax enforcement reforms reshape corporate tax declaration behavior, and offer empirical support for advancing precision-based regulation and optimizing tax governance in the context of data-driven tax governance.

Promoting the deep integration of the digital and real economies is a strategic priority for building a modern industrial system anchored in the real sector. Under fiscal constraints, optimizing fiscal and tax policy mixes to improve incentive effectiveness has become an important policy issue. Using panel data on Chinese A-share listed firms from 2010 to 2024, this study examines the effects of fiscal and tax policy mixes on digital-real technology integration and explores the underlying mechanisms. The results show that supply-side policy instruments, including tax incentives and fiscal subsidies, promote digital-real technology integration through an R&D incentive mechanism, while the demand-side instrument of government procurement operates through a commercial credit channel. Combining supply-side and demand-side policy instruments overcomes the limitations of single-policy interventions and generates significant synergistic effects. Heterogeneity analysis indicates that the effectiveness of different policy mixes varies with regional digital infrastructure and the business environment, as well as firms’ supply chain structure and life-cycle stage. Further analysis shows that policy sequencing plays an important role in determining policy effectiveness. A“supply first, demand later”sequence significantly promotes digital-real technology integration, whereas a“demand first, supply later”sequence and simultaneous implementation are less effective. These findings suggest strengthening cross-departmental policy coordination to improve the overall effectiveness of fiscal and tax policies, establishing a tiered and differentiated policy support system to achieve more precise policy targeting, adopting a gradual“supply first, demand later”implementation strategy to optimize policy sequencing, and enhancing firms’ capacity to respond to policy incentives, thereby facilitating the transformation of external policy support into endogenous innovation momentum.

e-CNY is an important product driving the high-quality development of China’s digital economy. Its characteristics, such as substituting cash in circulation and offering secure and convenient payment functions, create an innovative impact on traditional deposit-lending business of commercial banks. Based on the Neomonetarist Model, we analyze cash-like Digital RMB, bank competition, and interbank business within a unified analytical framework, using data from 2016-2023 of Chinese commercial banks to apply a multi-period difference-in-differences model. Results indicate that the issuance of e-CNY exerts a“crowding-out effect”on bank deposits, which will reduce the liquidity creation of commercial banks. This effect is realized through two channels: bank competition and participation in interbank business. Further research reveals that the issuance of the e-CNY primarily affects commercial banks' liquidity creation on the liability side. Therefore, while actively promoting the issuance and implementation of e-CNY, the central bank should dynamically adjust capital allocation within the banking system and the real economy. Additionally, it’s advisable for commercial banks to promote the development of hybrid digital financial products and flexibly integrate with e-CNY application scenarios, thereby balancing the shock of innovation with business stability. Finally, regulatory authorities should improve the corresponding regulatory framework and prioritize information security in the digital currency context.

The intelligent economy represents an advanced economic form emerging from the evolution of the information economy and the digital economy. It is fundamentally characterized by the deep integration of data, algorithms, and computing power. Through the systematic coupling of intelligent factor endowments, intelligent industrial development, intelligent application integration, and an intelligent collaborative ecosystem, it reshapes the entire processes of production, distribution, exchange, and consumption. Based on the evolutionary logic, connotations, and characteristics of the intelligent economy, this study constructs an evaluation index system comprising four dimensions: intelligent factor endowments, intelligent industrial development, intelligent application integration, and Intelligent collaborative ecosystem. Using the improved entropy-weighted TOPSIS method, the all-permutation polygon method, the Dagum Gini coefficient, kernel density estimation, and the spatiotemporal Markov chain method, this study measures the level of intelligent economy development in 284 prefecture-level cities in China from 2013 to 2023. The findings indicate that: First, China’s intelligent economy has continuously improved overall, evolving from initial accumulation to accelerated development and subsequently to quality-oriented optimization; second, regionally, the eastern region remains the leader, while the central and western regions continue to catch up, and the northeastern region has improved overall but exhibits insufficient stability. Regional disparities have widened, primarily owing to interregional differences; third, the development of the intelligent economy displays clear upward mobility and path dependence. Low-level regions tend to transition to adjacent levels, whereas high-level regions exhibit a strong locking effect. Moreover, the development level of neighboring regions affects local state transitions. Accordingly, differentiated policies, multidimensional coordination, and cross-regional linkage should be advanced to promote the coordinated development of the intelligent economy across regions.

The development of the intellectual property judiciary, as a core pillar of property rights protection, has a significant impact on regulating corporate data asset disclosure practices. Using listed companies from 2007 to 2023 as the research sample, this study empirically examines the impact of intellectual property courts on corporate data asset disclosure practices. The study finds that intellectual property courts can curb firms' strategic disclosure of data asset information. Mechanism tests indicate that intellectual property courts exert a deterrent effect and optimize the financing environment, thereby curbing firms' strategic disclosure of data asset information. Heterogeneity tests reveal that this deterrent effect is more pronounced among firms audited by non-big-10 accounting firms and those located in regions with high internet penetration rates. Consequently, firms should establish a systematic data asset management framework, while the government should build a legal system to prevent firms from engaging in strategic disclosure of data asset information.

As a new engine driving China's economic growth, the digital economy plays a crucial role in stabilizing trade. This paper utilizes product-level trade data from China’s Customs Database and the CEPII-BACI Database from 2015 to 2021 to measure the extensive and intensive margins of provincial exports and empirically examines the impact and underlying mechanisms of the digital economy on these margins. The findings indicate that the digital economy significantly promotes the extensive margin of provincial exports, while its impact on the intensive margin is not statistically significant. This effect varies across industries, regions, and importing countries. Specifically, the digital economy exerts a stronger promoting effect on the extensive margin in data-intensive and technology-intensive industries. However, in sectors characterized by high information transparency and intense competition, the digital economy may suppress the intensive margin of exports. Moreover, the higher the digital economy development levels of both trading partners, the more pronounced the expansion of the extensive margin. The signing of Free Trade Agreements (FTAs) can further enhance the digital economy’s effect on expanding the extensive margin. Further analysis reveals that trade costs, intermediate goods imports, and international innovation cooperation are key channels through which the digital economy influences the extensive margin expansion of exports. Based on these findings, the government should strengthen digital infrastructure and international cooperation, promote enterprise innovation and the digital transformation of traditional industries. At the same time, it is essential to actively participate in the formulation of international digital trade rules and deepen economic and trade cooperation with developed countries to comprehensively enhance the supportive role of the digital economy in export development.

Against the backdrop of building a nationally integrated market for technology factors, promoting the diffusion and application of green technologies through market mechanisms has become a critical pathway for strengthening regional environmental pollution control and advancing the green transition. Using green patent transfer data for Chinese prefecture-level cities from 2006 to 2022, this study systematically examines the impact of green technology transfer on regional environmental pollution control and its underlying mechanisms through two-way fixed-effects models, instrumental-variable methods, and word-frequency analysis. It further proposes pathways for overcoming bottlenecks in green technology transfer from a full-cycle perspective. The results show that green technology transfer significantly improves regional environmental pollution control, and this finding remains robust after a series of robustness checks. Mechanism analysis indicates that green technology transfer improves regional environmental pollution control through two channels. The resource allocation effect is reflected in the optimized allocation and restructuring of green technological resources, while the indigenous innovation effect is reflected in the enhancement of local green innovation capacity. A full-cycle analysis of green technology transfer covering demand, process, and application further shows that its positive effect on environmental pollution control becomes significantly stronger as regional emphasis on environmental protection increases, social support conditions improve, and technological absorptive capacity strengthens. Accordingly, efforts should be made to improve market mechanisms for green technology transactions, strengthen regional innovation capacity, and establish a full-cycle support system, thereby effectively fostering a virtuous cycle of technology transfer, environmental pollution control, and green development.

Corporate AI washing, a decoupling between AI-related talk and action, has become an important issue threatening innovation ecosystems, yet its performance-feedback drivers remain underexplored. Integrating performance feedback theory and impression management theory, this study examines how dual performance aspiration gaps affect corporate AI washing and identifies their boundary conditions. Using a sample of Chinese A-share listed firms from 2011 to 2023, we test the hypotheses with two-way fixed-effects regressions. The results show that historical aspiration surplus and industry aspiration shortfall significantly increase corporate AI washing, whereas historical aspiration shortfall and industry aspiration surplus significantly inhibit it. When board independence or regional AI attention is high, firms that meet industry aspirations show a weaker positive effect of historical aspiration surplus on AI washing and a stronger negative effect of historical aspiration shortfall. Heterogeneity analysis further shows that these relationships are particularly pronounced among high-tech enterprises and non-digital enterprises. Based on these findings, governments should establish a dual institutional-cognitive regulatory system to supervise and standardize corporate AI-related technology disclosures. Stakeholders should strengthen their ability to identify AI washing and pay particular attention to firms with historical aspiration surpluses and industry aspiration shortfalls. Firms, in turn, should optimize executive incentive mechanisms and strengthen the internal monitoring role of independent directors. A tripartite governance mechanism involving governments, stakeholders, and firms can effectively curb corporate AI washing.

While acting-in-concert entities can more accurately reflect the substantive control of shareholders over listed companies, existing research has predominantly focused on their governance advantages, paying insufficient attention to their negative effects. Based on a study of data from A-share listed companies in the Shanghai and Shenzhen stock markets from 2015 to 2024, it is found that an increase in the degree of control by concerted actors significantly raises the probability of corporate misconduct, the severity of violations, and the amount of penalties imposed. Corporate digital transformation and technology-driven regulation serve as endogenous corrective and exogenous constraint mechanisms, respectively, mitigating the relationship between acting-in-concert entities and corporate violations. Mechanism tests confirm that acting-in-concert entities elevate the probability of violations by intensifying violation pressure, creating opportunities for misconduct, and fostering self-justifying cognitions. Further analysis shows that, by type of violation, compared to operational violations, acting-in-concert entities have a more pronounced impact on information disclosure violations and leaders’ misconduct. By degree of control, the likelihood of corporate violations is highest when acting-in-concert entities possess absolute control. Based on these findings, regulatory authorities should establish a differentiated supervision system for acting-in-concert entities and strengthen penetration-style oversight. Companies should actively promote digital transformation to build a solid compliance foundation, while minority investors need to develop risk identification mechanisms. These measures can collectively optimize the corporate governance structure and enhance the operational order of capital markets.