Developing new quality productivity forces is an inherent requirement and important focus for solidly promoting high-quality development. This article is based on the basic principles and methodology of Marxist political economics and follows the research approach of “raising problems, analyzing problems, and solving problems”. It analyzes that insufficient effective investment is an important factor restricting the development of China’s new quality productivity forces, explains the theoretical connotation of effective investment and accelerator, and combines Marx’s capital circulation theory to analyze the accelerator effect of effective investment in promoting the development of new quality productivity forces. Based on the new development stage, it proposes a practical path to play the accelerator effect of effective investment, and finally puts forward safeguard measures from the aspects of market, capital, evaluation mechanism, and government to play the accelerator effect of effective investment. Research has found that: 
First, in terms of theoretical connotation, the effective investment is evaluated based on its purpose or function. Investment that can achieve expected goals well is considered effective investment, while investment that deviates significantly from expected goals is not considered effective investment. The core essence of accelerator is to accelerate the development speed or process of something by taking effective measures (i.e. accelerator) to achieve a certain goal, shorten the completion time of the goal, and thus achieve the expected goal faster. 
Second, in terms of internal mechanisms, it is necessary to grasp the objective development laws of new quality productivity forces from Marx’s capital circulation theory, and grasp the key elements such as optimizing and upgrading the industrial chain and supply chain system, enhancing technological innovation capabilities, cultivating high-quality labor force, and upgrading the built environment, and effective investment should be increased according to the principle of adapting measures to local conditions. The position and role of the government and the market in increasing effective investment should be properly handled. 
Third, in terms of practical path, it is necessary to accelerate the enhancement of its independent technological innovation capabilities by building high-level innovation consortia, leveraging the leading and driving role of chain leaders and chain owners in accelerating the optimization and upgrading of the industrial chain and supply chain system, absorb more capital into the strategic emerging industries and future industries through diversified policies, cultivate more high-quality talents through innovating joint training models, and better leverage the joint efforts of the government and the market in creating a high-quality built environment. 
Fourth, in terms of safeguard measures, further strengthen the market adjustment mechanism and enhance the effective investment growth momentum led by the market. Further improve the capital market system and promote more patient capital investment in new quality productive forces industries. Establish and improve a dynamic evaluation mechanism for effective investment, and promote sustained investment in effective investment. Further enhance the government’s macroeconomic governance capabilities, strengthen the organization, coordination, and stability of effective investment.

The high-quality development of the domestic service industry plays a critical role in revitalizing household consumption and constructing the micro-foundations of a domestic demand-driven economic paradigm. In the context of China’s transition toward dual circulation and consumption-led growth, understanding how service sector expansion reshapes household economic behavior is both theoretically significant and policy-relevant. Despite increasing attention to the role of services, the specific pathways through which domestic service development influences consumption dynamics remain underexplored in existing literature.
This study employs multi-wave micro-level survey data and a difference-in-differences (DID) strategy based on policy shocks and regional pilot programs to identify the causal effects of domestic service development on household consumption. Leveraging plausibly exogenous variation across time and space, we find that the expansion of the domestic service sector significantly increases total household consumption expenditure. More importantly, this expansion also unlocks latent consumption potential among previously underserved populations. These effects remain robust across alternative model specifications, placebo tests, and sample restrictions, confirming the reliability of the empirical strategy.
Mechanism analyses reveal a dual-channel transmission structure that operates through both supply- and demand-side mechanisms. On the supply side, the outsourcing of time-intensive domestic labor alleviates household time constraints, facilitates labor force participation—especially among women—and increases household disposable income, thereby supporting immediate consumption. On the demand side, domestic services strengthen familial care structures, reduce uncertainty in daily life management, and improve expectations for future living standards. These changes enhance consumer confidence and raise the marginal propensity to consume, particularly for durable and long-term expenditure categories, thus stimulating sustained consumption momentum. Heterogeneity analyses further uncover meaningful spatial and demographic asymmetries. The consumption-promoting effects of domestic services are most pronounced in eastern provinces with more mature service markets and stronger digital infrastructure. At the household level, women and low-income families benefit disproportionately, suggesting that domestic service development contributes to both economic inclusion and gender-equitable growth. These findings underline the redistributive potential of the service sector and its capacity to support inclusive domestic demand expansion.
Finally, the study identifies a threshold-type moderating role of digital infrastructure. At low levels of digital penetration, service access barriers—such as information asymmetry, platform exclusion, and regional mismatch—constrain the availability and reliability of domestic services, thereby dampening their consumption effects. Conversely, once a critical digital threshold is crossed, the integration of digital platforms significantly amplifies the efficiency, accessibility, and trust in service provision, thereby enhancing its ability to unlock household consumption potential. This non-linear moderating pattern points to the necessity of complementing service sector development with inclusive digitalization policies.
Together, these findings provide micro-level evidence for the strategic role of domestic services in shaping household consumption behavior, reinforcing the theoretical linkage between service economy expansion and endogenous demand growth. The study not only contributes to a deeper understanding of the household-service nexus but also offers actionable policy insights for optimizing service sector governance under the digital economy, especially in the context of China’s ongoing consumption transition.

In recent years, local government financing vehicles have played an important role in promoting infrastructure construction and local economic development, but their accumulated hidden debt risks have become increasingly prominent. In order to resolve this risk, the central government has repeatedly stressed the need to gradually strip the government financing function of financing platforms and promote their market-oriented transformation by category. In this context, this paper deeply explores the impact of financing platform transformation on financing cost and local government implicit debt structure, aiming to understand the change of financing cost and how this change affects the structural risk of local government implicit debt during the transformation of financing platforms. Through in-depth analysis, this paper helps to provide theoretical support and practical guidance for local governments to formulate scientific debt management policies, optimize debt structure and reduce debt risks.
Firstly, this paper reviews the relevant research on local government financing vehicles, debt risk and marketization transformation at home and abroad. The existing research mainly focuses on how government credit affects the debt issuance of financing platforms, but how the interactive relationship between local government financing platforms (LGFVS) and market subjects affects the debt financing behavior has not been fully explored.
Secondly, this paper uses the bond issuance data of local government financing platform companies from 2013 to 2019, takes advantage of the policy impact of “Document No. 43” of The State Council in October 2014, which requires stripping off the financing function of local government financing platforms, and uses the DID model to analyze the impact of the transformation of financing platforms into the bond issuance cost of existing financing platforms. The results show that the “platform withdrawal” policy has significantly reduced the credit Spreads of the bonds issued by the existing financing platforms, indicating that the financing cost has decreased. This conclusion passed the parallel trend test and the robustness test of replacing explanatory variables with PSM-DID.
Finally, the mechanism analysis finds that the “platform withdrawal” policy optimizes the composition of existing local government financing platforms, strengthens the guarantee and bottom-supporting expectations of existing local government financing platforms, and leads to the reduction of financing costs of existing local government financing platforms. At the same time, the bond issuance Spreads of the platform companies that have withdrawn rise significantly, indicating that the decoupling signal of the “withdrawal platform” policy is effective. Further research shows that the bond debt ratio of local government financing vehicles has significantly increased, while the borrowing debt ratio has significantly decreased. The reduction of the financing cost of existing financing platform bonds makes financing platform companies more inclined to choose bond financing with lower cost compared with bank loans, thus optimizing the implicit debt structure of local governments. On this basis, this paper puts forward the following policy recommendations: first, firmly resolve the target of local government implicit debt risk, optimize the debt maturity structure and financing cost; Second, continue to promote the decoupling reform between financing platforms and local governments, standardize the financing behavior of local governments; Third, promote the market-oriented transformation of financing platforms by category and optimize the overall debt structure; Fourth, we will improve the construction of the bond market and promote market-oriented pricing of debt financing by financing platforms.
The innovation and contribution of this paper are mainly reflected in the following aspects: first, it examines for the first time the impact of the debt-transformation measure of local government financing platform companies being stripped of their government financing functions on the financing cost and debt structure of existing financing platform companies, filling the research gap in related fields. Second, this paper analyzes the influence mechanism of the transformation of financing platforms on the financing cost of the existing financing platform companies from the perspectives of the quality optimization of the existing local government platform companies and the strengthening of the guarantee expectation, which enriches the relevant research on the bond price formation of government financing platforms. Third, it is found that the implicit guarantee of local governments for withdrawing platform companies has been greatly weakened, but the implicit guarantee of existing financing platform companies has been strengthened, indicating that the decoupling signal of local governments is effective, but it also suggests that it is necessary to strengthen the control of new debt scale of existing platform companies while gradually promoting the transformation of platform companies.

Education, science and technology, and human resources are the basic and strategic support for comprehensively building a modern socialist country. Based on the new starting point of entering the ranks of innovative countries, we are faced with practical problems such as weak scientific and technological innovation ability, huge population size and demographic dividend decline. Summarizing the practical process of China’s “trinity” innovation system and quantifying the overall effectiveness of China’s “Trinity” innovation system are of important reference value for improving China’s international competitiveness in innovation, adapting to the transformation from demographic dividend to talent dividend, and accelerating Chinese-style modernization.
In this paper, education, science and technology, talent “Trinity” construction of China’s innovation system as a starting point. First of all, it systematically reviews the formation process of China’s innovation system since the founding of New China, the strategic measures of China’s innovation system since the 18th National Congress of the Communist Party of China, and the new momentum of China’s innovation system since the 20th National Congress of the Communist Party of China. Secondly, an innovation-driven production system including education, science and technology and talents is built around the “three firsts”, and the overall system efficiency is decomposed from the “Trinity” factor perspective and the contribution perspective of demographic dividend and talent dividend. Finally, it quantitatively analyzes the development law and internal structure of China’s innovation system, the main channels of education system enabling science and technology system and talent system, and the path mechanism of education enabling population dividend and talent dividend from the national scale and national strategic area level.
The research results show that the construction of China’s innovation system with the “Trinity” layout has achieved remarkable results, and the overall efficiency of the “Trinity” is higher than the overall efficiency of talent science and technology and education science and technology. The priority development of education brings new opportunities for the construction of China’s innovation system. The education system can simultaneously influence the talent dividend and the demographic dividend to empower the science and technology system and the talent system, and the enabling effect has a time superposition effect. Talent leadership and drive bring new vitality to the construction of China’s innovation system, China’s demographic dividend has not disappeared and talent dividend is taking shape, and the education system can accelerate the transformation of demographic dividend into talent dividend. The regional aspect shows that the innovation-driven development of the Yangtze River Economic Belt has reached a new level, the construction of a scientific and technological innovation community in the Yangtze River Delta region has been increasingly improved, scientific and technological innovation has achieved remarkable results in helping the ecological protection and high-quality development of the Yellow River Basin, and the Beijing-Tianjin-Hebei region has a long way to go in building a collaborative innovation community.
The research conclusion shows that the “Trinity” of education, science and technology and talents is a new path of innovation in China, and an important magic weapon to improve the overall efficiency of China’s innovation system in the new development stage. This study believes that, based on the new stage of Chinese-style modernization, it is necessary to adhere to the Party’s overall leadership of national innovation system construction, establish a “Trinity” operating mechanism of education, science and technology and talents, accelerate the transformation of demographic dividend to talent dividend, and integrate innovation system construction into the development of national strategic areas.

Currently, the world is undergoing a new round of technological revolution and industrial transformation, with technological innovation emerging as a pivotal force in reshaping the global economic landscape. The proposition of new-quality productivity provides a new theoretical guide for productivity in the context of Chinese-style modernization, marking a new phase in the development of productivity with innovation as its core. How to accurately grasp the scientific connotations of new-quality productivity, fully recognize its main characteristics, and enhance its ability to promote high-quality development are questions of the times that we must answer well in the new era and on the new journey. With the rapid development of new-generation digital technologies such as artificial intelligence, big data, and the Internet of Things, the digital economy has become a new driving force for China’s economic growth. The permeability of digital technologies facilitates the optimization of production factor allocation and the establishment of new production relationships, serving as a crucial support for advancing new-quality productivity. The import of digital products can inject new vitality into the economic system by promoting independent innovation, accelerating the digital transformation of enterprises, and enhancing the level of human capital, thereby driving the formation and development of new-quality productivity. This is highly important for enhancing the country’s overall competitiveness and achieving high-quality economic development.
This paper empirically examines the impact of digital product imports on new-quality productivity using data from A-share listed companies in Shanghai and Shenzhen from 2011 to 2016. After estimation via a two-way fixed effects model, we find that digital product imports have a significant positive effect on new-quality productivity levels. Subsequently, we address endogeneity by using the number of fixed-line telephone calls in 1984 and the Bartik Instrumental Variable. Robustness checks are conducted by replacing the explained and explanatory variables, adding joint fixed effects, changing clustering standards, and increasing control variables, all of which yield consistent and reliable results. Next, we perform heterogeneity analysis through grouped regressions based on firm ownership, geographical location, and factor intensity, revealing significant differences. Specifically, the positive impact of digital product imports on new-quality productivity is more pronounced for enterprises located in the eastern region and technology-intensive enterprises. Following this, we conduct mechanism tests and find that both the level of technological innovation and digital transformation are important channels through which digital product imports influence new-quality productivity. Finally, we use the Changes in Changes (CIC) model to investigate the differences in the promotional effects of digital product imports on new-quality productivity across different quantile levels, concluding that the more digital product imports increase, the greater the enhancement of new-quality productivity.
The main contributions of this paper are as follows: Firstly, this paper is the first to examine the impact of digital product imports on new-quality productivity in enterprises. The Third Plenary Session of the 20th Central Committee of the Communist Party of China emphasized the development of new-quality productivity according to local conditions. However, empirical research on the impact of digital product imports on new-quality productivity is quite limited, and few studies systematically review and empirically test the underlying mechanisms between them. Secondly, this paper focuses on analyzing the causal effects of digital product imports on new-quality productivity in enterprises. By comprehensively adopting methods such as adding control variables and using multiple exogenous instrumental variables to mitigate endogeneity issues, and by conducting a detailed analysis of the underlying impact mechanisms from the perspectives of digital transformation and upgrading effects and technological innovation effects, this paper provides a new theoretical analysis framework for subsequent research. Thirdly, this paper uses the Changes in Changes (CIC) model to estimate the differences in new-quality productivity across different quantile levels of enterprises, providing a unique research perspective. In the further analysis, we use the CIC model to estimate the differences in new-quality productivity across different quantile levels of enterprises and find that the impact of digital product imports on new-quality productivity is not significant at lower quantile levels but is significant at higher quantile levels. This leads to the conclusion that the more digital product imports increase, the better the enhancement of new-quality productivity.

With the accelerating process of population aging in China, many structural contradictions and practical problems have emerged behind it. Based on the current social and economic development level and institutional environment in China, the policy of delaying retirement has relatively become a more reasonable and feasible policy option to relieve the pressure on pension and optimize the allocation of labor force. Although delaying retirement is objectively necessary, it has triggered widespread attention and heated discussions from all sectors of society once it was proposed. Among them, the focus of the controversy lies in whether delaying retirement will crowd out employment. Therefore, a comprehensive examination of the impact of delaying retirement on the labor market has important theoretical and practical significance for promoting the smooth transition and implementation of China’s delaying retirement policy, which is also the core of this paper.
In view of this, further considering that the OECD countries, as economies that entered the aging society earlier, have carried out long term policy practices in coping with labor supply pressure and optimizing the pension system. Some countries have gradually raised the legal retirement age through legislation and established a flexible retirement mechanism, accumulating rich practical achievements in relieving the pressure of pension payment and maintaining the vitality of the labor market, which provides important precedents and references for China. At the same time, considering that China’s policy of gradually raising the retirement age has not been officially implemented, and due to the limitations of relevant data such as employment and labor participation rate in China, it is impossible to directly test the effect of the policy of delaying retirement with existing data. Therefore, this paper draws on the panel data of 35 OECD countries from 1995 to 2020, and uses the overlapping generations model and the difference-in-differences (DID) method to explore the possible impacts of delaying retirement on the labor market from both theoretical and empirical levels, so as to provide cross-national empirical evidence support for the smooth transition and implementation of China’s policy of progressively raising the retirement age.
The research finds that: First, from a theoretical perspective, the policy of delaying retirement can effectively alleviate the employment pressure in the labor market by reducing the pension contribution rate and amplifying the intergenerational effect. Second, empirical analysis shows that in the long run, the policy of delaying retirement can not only increase the overall labor-force participation rate but also significantly promote the labor participation of young and middle-aged groups. That is, delaying retirement will not crowd out youth employment, and this conclusion is robust under various econometric tests. In addition, the mechanism test further shows that the reduction of the social security contribution rate is indeed an important channel through which the policy of delaying retirement exerts its labor-participation effect. Third, there is significant heterogeneity in the labor-force participation rate effect of the policy of delaying retirement, and the exertion of this effect is jointly influenced by the gender of the labor force, the degree of regional aging, the industrial structure, and the level of digital application. However, it should be noted that although this paper provides an international experience reference for exploring the impact of delaying retirement on the labor market by drawing on the data of OECD countries, when transplanting and applying it to the Chinese context, the potential limitations brought about by the institutional differences in the labor market need to be fully considered.
At the end of this paper, corresponding suggestions are put forward to achieve the dual objectives of a smooth policy transition and employment stability through the incentive mechanism for flexible delaying retirement. First, in view of the fact that there are still public cognitive biases during the formulation process of the delaying retirement policy, it is necessary to consolidate the implementation foundation of the policy from the two dimensions of cognitive guidance and skill improvement. Second, there is significant heterogeneity in the labor participation effect of delaying retirement, and the policy design needs to be adjusted accordingly to improve the implementation efficiency. Third, although due to the limitations of the current data, this paper does not conduct an in-depth discussion on the labor-force participation status among different attribute positions and employment sectors, yet combined with the characteristics of China’s labor market, the delaying retirement policy needs to fully reserve differential adjustment spaces during the promotion process.

Under the policies background of innovation-driven and accelerated construction of manufacturing power, improving the technological innovation capability of enterprises is the key support for the transformation and upgrading of China’s manufacturing industry. With the intensification of global scientific and technological competition and the increase of research and development (R&D) costs, it is more difficult for enterprises to realize innovation only by relying on internal resources. It has become a realistic choice for many enterprises to actively obtain external innovation resources through cross-border mergers and acquisitions (M&A). With the continuous improvement of China’s outward foreign direct investment (OFDI) policies system, the overall scale of cross-border M&A of manufacturing enterprises has increased and become rational. In the context of the urgent need for the transformation and upgrading of the manufacturing industry and China’s commitment to promoting a high level of opening-up, it is of great practical significance to study the impact of cross-border M&A on enterprise innovation.
This paper focuses on the following questions: First, will cross-border M&A by Chinese manufacturing enterprises affect enterprise innovation? What kind of impact will it have? Second, are there any differences in the impact effects on different host country locations, enterprise entities, and M&A methods? Thirdly, through what mechanisms do cross-border M&A of Chinese manufacturing enterprises affect enterprise innovation? Does the influence effect of the mechanism vary depending on the location of the M&A?
To answer the above questions, the following research content is designed: First, construct a theoretical analysis framework for the impact of cross-border M&A on enterprise innovation, establish a mathematical model to reveal the mechanism of cross-border M&A and enterprise innovation, and explore the transmission mechanism of the impact of cross-border M&A on enterprise innovation. Second, based on the experimental data of cross-border M&A and innovative development of Chinese manufacturing enterprises, examine the direct impact of cross-border M&A on the quality and quantity of enterprise innovation. Third, examine the heterogeneous impacts of different M&A locations, enterprise entities, and M&A methods on the innovation effects of cross-border M&A enterprises. Fourth, examine the different intermediate path mechanisms by which cross-border M&A affect enterprise innovation, as well as the differences in the roles of individual mechanisms in different M&A locations.
In accordance with the corresponding paradigm of mutual confirmation of theories and empirical analysis, this paper takes China’s listed manufacturing enterprises as the research object, and based on the matching data of CSMAR listed companies database, the global M&A transaction database (Zephyr) and Chinese Research Data Services Platform (CNRDS) from 2009 to 2020. The fixed effect, propensity score matching and difference-in-differences (PSM-DID), parallel trend test, placebo test, mediating effect were comprehensively used in this study.
The following conclusions are drawn:
First, cross-border M&A have significantly promoted the improvement of both the quantity and quality of enterprise innovation, with the improvement effects on the quantity and quality of innovation being 3.3% and 2% respectively, and the promotion effect is sustainable. Second, cross-border M&A can enhance the level of innovation through the promotion effect of R&D efficiency and knowledge base. Third, the impact of cross-border M&A on enterprise innovation is heterogeneous. From the perspective of the location of M&A, M&A in non-OECD countries have a higher effect on enhancing the quantity and quality of innovation than those in OECD countries, and M&A in OECD countries are more conducive to promoting enterprise innovation by improving R&D efficiency. The innovative enhancement effect brought by M&A in countries with distant institutional distances is higher than that in countries with close institutional distances. The innovation enhancement effect brought by M&A in countries with a long cultural distance is higher than that in countries with a short cultural distance, especially reflected in the improvement of innovation quality. From the perspective of the enterprise entity, only those with a relatively high productivity level can effectively enhance the quantity and quality of their innovation through cross-border M&A. Both cross-border M&A of state-owned enterprises and non-state-owned enterprises can significantly increase the number of innovations of enterprises. Moreover, cross-border M&A of state-owned enterprises have a more significant effect on increasing the number of innovations, while non-state-owned enterprises can significantly improve the quality of innovation of enterprises. The effect of M&A of high-tech enterprises on improving the quantity and quality of innovation are more obvious than that of general technology enterprises. In terms of the effect of M&A on increasing the number of enterprise innovations, enterprises in the western region have the highest effect, followed by those in the central and eastern regions. Only M&A of enterprises in the western region can significantly promote the improvement of innovation quality. From the perspective of merger and acquisition methods, technology M&A can significantly enhance the quantity and quality of an enterprise’s innovation, while non-technology M&A have no obvious impact. The effect of controlling M&A on enhancing the quantity and quality of innovation is higher than that of non-controlling M&A. Vertical M&A have a higher effect on increasing the number of innovations. Horizontal M&A have a higher effect on improving the quality of innovation.
Based on this, this article puts forward the following countermeasures and suggestions. Manufacturing enterprises should actively carry out cross-border M&A and pay attention to the integration of resources and capabilities after the M&A. Enhance the R&D efficiency of manufacturing enterprises, encourage them to develop independent innovation capabilities and improve their knowledge base. Based on the actual situation and characteristics of the enterprise, flexibly formulate differentiated cross-border merger and acquisition decisions.
The possible marginal contribution of this paper lies in the following: First, it examines the specific effects of the amount and frequency of cross-border M&A on the quantity and quality of enterprise innovation, making up for the deficiency of previous studies that were not objective and comprehensive enough in measuring the indicators of enterprise cross-border M&A and innovation. Second, analyzing the heterogeneous impact of M&A in different locations, entities and methods on enterprise innovation has enriched the relevant research on cross-border M&A of heterogeneous enterprises. Third, revealing the mediating role of enterprise R&D efficiency and knowledge base in promoting enterprise innovation through cross-border M&A, as well as the differences in the mediating role of R&D efficiency in different merger and acquisition locations, enriches the relevant research on the mechanism of the impact of M&A on enterprise innovation.

In recent years, the global trade environment has become increasingly complex, marked by escalating protectionism and intensified competition for technological dominance. Chinese exporters face mounting challenges from rising domestic factor costs and the erosion of traditional comparative advantages. At the same time, structural overcapacity and weakening bargaining power expose the limitations of scale-driven growth. Within this context, enhancing technological innovation has become central to sustaining competitiveness and navigating global value chain restructuring.
This study investigates whether and how innovation-related provisions embedded within regional trade agreements (RTAs) can foster innovation among Chinese exporters. It proposes that “innovation rules”—including intellectual property rights, competition policies, technical standards, talent development, and technology cooperation—promote innovation by improving institutional frameworks, reducing uncertainty, and enhancing resource accessibility. To provide empirical validation, the paper constructs a firm-level composite index measuring the depth of integration into RTA innovation rules and assesses its impact on firm innovation performance.
Using firm-level data from customs trade flows and patent databases for Chinese A-share listed companies from 2002 to 2016, the research applies fixed-effects panel regressions to estimate the effect of RTA innovation rule depth on patent output. The core explanatory variable is the composite index weighted by trade values with partner countries. A rich set of controls—such as firm size, intangible assets, and regional indicators—is included to mitigate omitted variable bias.
Empirical findings show that the deepening of RTA innovation rules significantly boosts innovation outcomes among Chinese exporting firms. This supports the hypothesis that exporters—by virtue of their higher exposure to international regulatory standards and greater need for technological adaptation—benefit disproportionately from institutional innovations embedded in RTAs. Further heterogeneity analysis reveals that firms in central and western China, as well as state-owned enterprises (SOEs), experience more substantial innovation gains. These findings challenge the conventional view that innovation leadership is concentrated in the eastern private sector, suggesting a convergence effect and highlighting the institutional leverage enjoyed by SOEs in navigating RTA frameworks.
This study explores two mechanisms through which the deepening of RTA innovation rules fosters innovation among Chinese export firms. The first is a market-driven channel: by locking in tariff concessions, harmonizing technical standards, and strengthening intellectual property protection, RTAs reduce export market portfolio risks, thereby stimulating firms’ incentives to undertake high-risk, long-term innovation projects. The second is a resource-supply channel: enhanced institutional arrangements—such as stronger IP regimes, mutual recognition of conformity assessments, transparent government procurement, and anti-corruption provisions—alleviate financing constraints, improve the predictability of the policy environment, and expand both external and internal capital sources for R&D. This dual mechanism not only mitigates market uncertainty but also eases capital bottlenecks, jointly reinforcing firms’ innovation capacity. Empirical results confirm that both channels are statistically significant and economically meaningful, lending support to the proposition that RTA innovation rules can serve as effective catalysts for technological upgrading through institutional design.
To address potential endogeneity concerns, the study implements a series of robustness checks. First, an instrumental variable estimation is conducted using a recalculated RTA innovation rule depth index—constructed based on firms’ export values in the final sample year (2016)—as an instrument. This alternative specification confirms the causal impact of RTA innovation rules on firm-level innovation. Second, a staggered difference-in-differences (DID) approach strengthens the identification strategy by leveraging variation in the timing of firms’ initial exposure to RTA rules. Third, a propensity score matching (PSM) method is employed to mitigate potential sample selection bias, yielding consistent results. Finally, the robustness of the findings is further supported by alternative model specifications, including the Poisson Pseudo Maximum Likelihood (PPML) estimator and alternative dependent variables such as the number of invention patents.
This research makes several theoretical and practical contributions. Theoretically, it enriches the literature on trade policy and innovation by shifting the focus from aggregate-level analysis to firm-level behavioral responses. It also expands the conceptualization of RTA innovation rules by incorporating a multidimensional framework. Practically, the findings provide actionable insights for policymakers and firms alike. For policymakers, the results underscore the importance of embedding robust innovation provisions into future RTA negotiations and ensuring their effective domestic implementation. Creating centralized RTA databases, offering compliance guidance, and providing technical training can help reduce barriers to utilization. For firms, especially exporters, monitoring RTA developments and aligning internal innovation strategies with external regulatory frameworks will be critical for sustaining technological competitiveness.
In conclusion, this study presents compelling evidence that the deepening of innovation rules in RTAs can serve as a strategic lever for promoting firm-level innovation in China, particularly among exporting firms. By reducing institutional and market frictions, these rules enhance firms’ innovation capacity and position them to compete more effectively in global markets. As the landscape of international trade continues to evolve, leveraging institutional openness for innovation-driven growth will be essential to China’s long-term economic strategy.

As China’s population increasingly concentrates in economically developed regions, the dual challenges of high housing prices and elevated rental rents have become more intense, particularly for low-income households. These groups typically rely on shared rental arrangements to mitigate rental expenses. Nevertheless, their rental units tend to be substantially smaller than the city average, and they often endure lengthy commutes. This situation not only directly undermines their quality of life and diminishes their sense of belonging and social integration, but may also jeopardize the stable provision of labor and the sustainable development of cities. In this context, effectively expanding the availability of affordable housing, alleviating housing cost burdens for low-income groups, and ensuring their rental needs are adequately met have emerged as critical issues in achieving social equity. The third plenary session of the 20th Central Committee of the Communist Party of China in 2024 explicitly pointed out the need to “move faster to establish a housing system that supports both housing rentals and purchases” and to “scale up the construction and provision of government-subsidized housing to meet the essential need of salaried people for a home to live in”. Consequently, studying the rental housing security policies targeting low-income populations holds significant importance for mitigating residential conflicts, stabilizing labor supply, and promoting social integration.
Our paper primarily aims to assess the effectiveness of rental subsidy policies in enhancing rental housing services for low-and-middle-income households and to analyze the mechanisms through which these policies impact the rental and housing markets. We further seek to investigate how such interventions improve the welfare of targeted families, with consideration of overall social welfare. To achieve this goal, we develop a heterogeneous-agent overlapping generations (OLG) dynamic general equilibrium model incorporating the real estate market, endogenizing rent, housing prices, and interest rates. Accordingly，the model parameters are calibrated using empirical economic data, and a government-implemented monetary rental subsidy policy directed at low-income households is introduced. Within this framework, we investigate how adjustments to the subsidy policy affect asset prices and, consequently, influence the welfare and inequality in residential services among heterogeneous agents. In addition to conducting long-run steady-state analysis, we simulate short-term transitional dynamics to capture changes in household behavior and rental market prices along the transitional path. Furthermore, an extended version of the model incorporates a lottery-based subsidy allocation mechanism, allowing for a distinction between subsidy intensity and coverage.
Our research indicates several points. Firstly, an appropriate level of subsidy intensity can improve the rental services accessible to low-income families while simultaneously narrowing the gaps in living space and income within society. Secondly, the implementation of rental subsidy policies amplifies rental demand among low-income households, which in turn drives up market rents, and incentivizes high-income households to raise their investment properties for rent purpose, thereby contributing to rising housing prices. Thirdly, along the transitional path, the welfare of low-income families across different generations improves. However, market rents and housing prices experience significant short-term fluctuations, underscoring the importance of accounting for the dynamic effects on the rental market in the short run. Fourthly, under the lottery mechanism, maintaining a fixed subsidy ratio while increasing the probability of being selected results in a greater number of subsidized households. Nevertheless, attention must be given to the rising rental costs faced by non-subsidized low-income families due to increased market rents.
Our study has the following contributions. First, from a general equilibrium perspective, we theoretically analyze the impact of monetary rental subsidy policies targeted at low-income households on their housing decisions and asset allocation across heterogeneous agents. Furthermore, we thoroughly investigate the equilibrium spillover effects on both rental and purchase markets, and quantitatively analyze the welfare and distributional effects of varying subsidy levels. Second, in addition to analyzing long-run steady-state outcomes, we simulate the transition path between the initial and new steady states. Specifically, we examine fluctuations of rent and house prices during this dynamic process of transition, as well as the welfare effects on low-income families across different birth cohorts, thereby addressing the limitations of existing literature that primarily focuses on steady state analysis. Third, the model is further developed to assess the heterogeneous effects of implementing a lottery-based rental subsidy mechanism under a constrained government budget, considering impacts on both recipients and non-recipients. 

Achieving the dual objectives of reducing corporate tax burdens and maintaining fiscal stability is crucial for advancing high-quality economic development. Artificial intelligence (AI), embedded with the connotations of new quality productive forces, presents a promising opportunity to address this dual challenge. Existing literature shows that AI significantly affects taxation-related factors such as labor structures, asset investment patterns, and R&D expenditure, thereby creating the possibility of corporate tax reductions. At the same time, AI adoption improves firms’ productivity and business performance, offering a pathway to tax base expansion. However, few studies directly examine the impact of AI on both corporate tax burden and government tax revenue, as well as the interconnection between them. Therefore, this paper integrates artificial intelligence, corporate tax burdens, and government tax revenue into a unified analytical framework to systematically examine the impact of AI technology on both corporate tax burdens and government tax revenue, as well as the intrinsic connection between these two effects, all through the analytical lens of new quality productive forces.
Compared with prior research, this paper makes four main contributions. First, departing from single-perspective assessments of technological effects, this study integrates AI technology, corporate effective tax burden, and government tax revenue into a unified analytical framework based on theories such as developing new quality productive forces. This approach extends the analytical boundaries of AI’s economic implications from both macro and micro perspectives. Second, through theoretical analysis and empirical evidence, this research reveals the mechanisms through which AI technology generates a “tax-reduction dividend” for firms and a “revenue-enhancement dividend” for the government. It further uncovers the intrinsic linkage between these two fiscal dividends, characterized by the pathway of “corporate tax reduction → output expansion → industry spillover → tax base broadening → government revenue increase.” Third, this study validates, in the domain of technology and taxation, the scientific rationale and practical relevance of fully implementing The Thought on Socialism with Chinese Characteristics for a New Era, vigorously developing new quality productive forces, and advancing the “AI+” initiative. Empowering enterprises with AI technology to drive innovation aligns with the essence of new quality productive forces, facilitates the dual objectives of reducing corporate tax burdens and increasing government revenue, and holds significant implications for high-quality economic development. Fourth, this research also provides verification and extension of the theoretical expectations derived from the supply-side economics perspective on tax reduction incentives. The “Laffer curve” posits an inverted U-shaped relationship between tax rates and revenue. This study demonstrates that AI technology enables firms to better adapt to tax incentive policies, thereby generating tax reduction effects, which in turn incentivize improvements in production efficiency and operational performance.
Based on data from Chinese A-share listed firms and city-level panels from 2008-2023, we employ fixed-effects models to empirically test the impact of AI adoption on corporate effective tax burdens and government tax revenue, and further explore the relationship between the corporate “tax-reducing dividend” and the government “revenue-enhancing dividend.”At the corporate level, the study finds that AI technology significantly reduces the effective tax burden of firms. This conclusion remains robust after accounting for endogeneity and undergoing rigorous robustness checks. The identified mechanisms for this effect are “Salary Tax Deduction,” “Intelligent Investment,” and “R&D Incentive.” Analysis of economic consequences reveals that the tax reduction induced by AI technology subsequently incentivizes improvements in firms’ operational performance and production efficiency. Furthermore, this tax reduction effect and its positive economic consequences exhibit significant spillover effects across industries. At the city level, the study finds that despite the tax reduction observed at the firm level, AI technology significantly increases overall government tax revenue. This finding also holds after controlling for endogeneity and passing robustness tests. The underlying reason is that the positive economic consequences stemming from AI’s tax reduction effect are also present at the city level. AI technology promotes the expansion of urban output and increases in aggregate profits, creating a “tax base broadening” effect that ultimately leads to higher government tax revenue. 
In conclusion, this study provides theoretical and empirical evidence that AI adoption enables the coexistence of lower corporate tax burdens and stable government revenue. Based on the research findings, we propose the following policy recommendations: i. promoting the targeted implementation of the “AI Plus” initiative to strengthen the foundation for developing new quality productive forces within enterprises, which includes supporting firms in intelligent transformation and talent cultivation; ii. fostering an industrial ecosystem conducive to new quality productive forces by enhancing cross-sector collaboration in the application of AI technologies, facilitating technology spillovers and coordinated development across sectors; and iii. optimizing fiscal policies related to AI technology to precisely cultivate high-quality tax sources, thereby providing sustainable fiscal support for the development of new quality productive forces, such as through tax incentives and innovation subsidies.

As a core driver of the Fourth Industrial Revolution, intelligent manufacturing plays a critical role in addressing the survival challenges faced by Chinese manufacturing firms amid economic restructuring and global technological competition. Unlike traditional labor-intensive production models, intelligent manufacturing—represented by industrial robots—emphasizes automation, efficiency improvement, and technological upgrading, reducing firms’ reliance on labor and vulnerability to market fluctuations. This transformative technology enables enterprises to optimize production processes, develop new markets, and enhance competitiveness, thereby lowering exit risks in an increasingly dynamic business environment. By promoting resilient and sustainable growth, intelligent manufacturing helps build a healthier industrial ecosystem and aligns with China’s strategic goals of building a manufacturing powerhouse and advancing high-quality development. Given this, this paper investigates the impact of intelligent manufacturing on Chinese firms’ survival risks and its underlying mechanisms, aiming to provide new insights and evidence for promoting industrial upgrading and enterprise sustainability.
Theoretically, this paper elaborates on the logical foundation of intelligent manufacturing in enhancing firm survival. Characterized by its focus on cost reduction, efficiency gains, and market expansion, intelligent manufacturing offers enterprises a new pathway to competitive advantage. By replacing labor with industrial robots, firms can improve labor productivity and lower marginal production costs, all of which help strengthen their ability to withstand market competition pressures. In addition, the introduction of intelligent manufacturing technology will also drive innovation by promoting the development of new products and entry into high-value markets, reducing dependence on low-margin market segments. Overall, the theoretical framework highlights two key mechanisms: first, the cost-efficiency effect, where intelligent manufacturing increases productivity and reduces production costs; and second, the market expansion effect, where intelligent manufacturing helps develop new products and increase market share. Ultimately, intelligent manufacturing will enhance revenue space through these two channels and cultivate new competitive advantages.
Empirically, this study uses data from Chinese manufacturing enterprises between 2000 and 2013 to examine the impact of intelligent manufacturing (proxied by industrial robot imports) on firm survival risks. The results show that intelligent manufacturing significantly reduces the survival risks of firms exiting the market, and the results remain robust after multidimensional robustness tests. After distinguishing between levels of robot technology, firms importing high-end robots experience a greater reduction in survival risks than those importing low-end robots, highlighting that the survival risk effect of intelligent manufacturing is related to firms’ technological absorptive capacity. Mechanism tests find that, although the effect of increasing profit margins in the short term is limited, the adoption of intelligent manufacturing technology does indeed promote enterprise survival capabilities through improving production efficiency, reducing marginal costs, stimulating new product development, and increasing sales revenue, and cultivates new market competitive advantages.
Heterogeneity analysis finds that, in terms of technological factors, overall, the higher the industry Concentration, the more significant the effect of using robot technology to consolidate market position and improve survival capabilities. However, compared with industries with higher capital intensity and higher technological levels, firms in industries with lower capital intensity and lower technological levels, which are more labor-intensive, show a more significant effect of reducing market exit risks through intelligent manufacturing transformation, alleviating the pressure of rising labor costs. In terms of openness factors, export-oriented and processing trade firms, which have priority access to advanced foreign technologies, benefit more in terms of survival from intelligent manufacturing transformation and upgrading, with a greater effect on enhancing international competitive advantages.
This study makes a valuable addition to the literature on intelligent manufacturing and firm survival dynamics. First, it provides causal evidence of the impact of intelligent manufacturing on firm survival risks using detailed large-sample data. Second, it disentangles the underlying mechanisms linking intelligent manufacturing to firm survival risks, highlighting the survival-promoting effects of intelligent manufacturing on both the supply and demand sides. Third, the rich heterogeneity analysis contributes valuable empirical evidence for designing and optimizing intelligent manufacturing policy systems.

Promoting the cross-regional flow of production factors and deepening the construction of a unified national market are foundational requirements for building a powerful domestic market in China. The core objective of this national strategy is to break down administrative boundaries, geographical barriers, and institutional transaction costs to achieve the efficient cross-regional allocation of resources. Firm cross-regional investment, which expands a firm’s business operating space, is a critical channel for facilitating this factor mobility.
Geographic distance, however, imposes significant cost burdens, information asymmetries, and management challenges, thereby hindering cross-regional investment and impeding the formation of an integrated market. While the economic impacts of physical infrastructure, such as high-speed rail, on mitigating these distances have been extensively studied, empirical research on the influence of digital infrastructure on corporate spatial location decisions remains scarce. This study examines whether the development of digital infrastructure can effectively stimulate cross-regional investment by firms into demonstration cities, thereby expanding their business operating space and providing new micro-level evidence on the construction of a unified national market.
To answer this question, this study employs China’s “Broadband China” strategy as a quasi-natural experiment. This top-down national policy was launched in 2013, with cities designated as demonstration zones in three phased batches during 2014, 2015 and 2016. Based on a comprehensive panel dataset constructed from 2007 to 2023, the study integrates firm-level financial data from all A-share listed companies, manually collected and geolocated parent-subsidiary relationship data, and the officially published list of “Broadband China” demonstration cities. A Difference-in-Differences model with multi-period shocks is employed to compare the differences in cross-regional investment attractiveness between demonstration and non-demonstration cities. 
The benchmark regression results indicate that the “Broadband China” policy significantly expands a firm’s business operating space by enhancing cities’ attractiveness for cross-regional investment. This result remains robust after a series of tests, including parallel trends analysis, placebo tests, PSM-DID, and entropy balancing. Mechanism analysis reveals this effect operates primarily through two channels. First, an information effect is identified. The study constructs a novel “average weighted geographic distance” metric to capture the economic spatial distance between parent companies and their subsidiaries. This finding provides evidence that optimized digital infrastructure facilitates the cross-regional flow of information, reduces the perceived risks and costs of remote management, and thus encourages firms to expand business operating space. Second is the cost effect, specifically reducing internal communication costs and lowering external transaction costs. Further analysis reveals a network synergistic effect. The study found that when both the starting point and destination of an investment possess high-quality digital infrastructure, it generates stronger network connectivity that surpasses the reduction of single-point information friction, thereby amplifying the effects on cross-regional investment activities. Regarding heterogeneity analysis, the impact of digital infrastructure varies across geographic distances and regional, urban, and corporate characteristics. Specifically, digital infrastructure significantly influences firms’ location choices for cross-regional investments in adjacent versus remote areas, eastern regions, large cities, non-state-owned enterprises, and high-tech firms. 
The contributions of this study are as follows. This paper makes contributions in three key areas. First, by examining firm’s business operating space, it reveals pathways for achieving the integration of efficient markets and effective government, providing micro-level evidence on how digital infrastructure drives the formation of a unified national market. Second, it uncovers the spatial effects and dual mechanisms through which digital infrastructure reshapes economic geography, enriching the existing research on digital infrastructure. Third, this study innovatively constructs the “average weighted geographic distance” metric between parent companies and subsidiaries. It validates the mechanism through which digital infrastructure drives spatial expansion of business operations from both information and cost perspectives. Furthermore, the heterogeneity analysis results provide policy references for optimizing digital infrastructure deployment and better advancing the construction of a unified national market.
Based on these findings, this study proposes the following policy recommendations. First, reinforce the “digital corridor” positioning of digital infrastructure to alleviate information asymmetry in cross-regional investment. Second, establish high-quality datasets complementary to digital infrastructure to strengthen data support for cross-regional allocation of factors. Third, optimize the spatial layout of digital infrastructure to leverage network synergies. Fourth, organically integrate digital infrastructure development plans with investment promotion policies.

China’s economy is currently in a critical period of transition from high-speed growth to high-quality development, with consumption playing an increasingly prominent role in economic growth. In recent years, however, the contribution of consumption to economic growth has declined. At the same time, tensions in the international landscape and trade frictions with countries such as the United States and Australia have adversely affected exports, and the structural imbalance caused by long-term high investment has also highlighted the limitations of China’s economic growth model. As such, shifting the growth paradigm and stimulating domestic demand have become important directions of the national economic development strategy. Nevertheless, China’s household savings rate has remained persistently high since the reform and opening-up period—rising from less than 28% in 2000 to 39% in 2010, and slightly declining to 37% in 2015—and is among the highest in the world. Such high saving rates have, to some extent, constrained the expansion of domestic demand, making it of great practical significance to study the factors influencing household savings. The existing literature mainly attributes China’s high saving rates to long-term factors such as uncertainties brought by market-oriented reforms, demographic changes, and institutional or cultural characteristics, which are however difficult to adjust in the short run. In contrast, the social security system offers a more policy-relevant perspective. Previous studies have shown that pension and health insurance schemes can reduce household saving rates, yet the role of the Housing Provident Fund (HPF) in shaping household saving decisions remains underexplored.
Using data from the Urban Household Survey (UHS) covering 2002-2014, this paper finds that a one-percentage-point increase in the HPF contribution rate reduces the household saving rate by 0.923 percentage points. Further mechanism analysis indicates that this effect is more pronounced among households with stronger precautionary saving motives, such as those with a higher share of employment in non-state-owned enterprises, lower per capita housing values, and lower education levels of the household head. Moreover, from a lifecycle perspective, the suppressing effect is stronger for households facing higher opportunity costs of interest loss, tighter liquidity constraints, or weaker tax benefits associated with HPF contributions. To address potential endogeneity concerns, we adopt housing reform allocation status and geographical distance to early pilot cities as instrumental variables, employ propensity score matching to re-balance the sample, and apply alternative measures of saving rates. Across all specifications, the negative impact of HPF contributions on household saving remains robust.
Based on the findings, this paper proposes the following policy recommendations: On the one hand, when adjusting the contribution ratio of the HPF, attention should be paid to the fact that it not only has the function of housing security but also exerts an impact on household consumption and savings decisions. Therefore, its dual attributes should be taken into account in evaluating its broader effects. On the other hand, raising the HPF contribution rate can serve as a feasible approach to reducing China’s persistently high household saving rate. Yet differentiated policies should be adopted for households with varying characteristics. For example, contribution rates may be appropriately lowered for households currently repaying housing loans or those not subject to liquidity constraints, while for residents nearing retirement—who face higher tax-shield costs and weaker policy effects—withdrawal conditions and limits may be relaxed to minimize welfare losses from contributions. This research confirms that the housing provident fund not only serves as a housing security mechanism but also significantly influences household savings behavior, offering a new perspective for understanding China’s high savings rate. Furthermore, it provides valuable insights for improving housing security policies, boosting consumption, and promoting high-quality economic development.

Against the backdrop of intensifying global climate change, persistent ecological degradation, and increasingly scarce resources, the concept of green development has become a universal consensus and shared goal among nations pursuing sustainable economic growth. As the world’s largest developing country, China has actively integrated into the global trade division of labor system by leveraging its low-cost labor advantage. While generating substantial economic gains, it has inevitably borne the environmental pressures transferred from developed countries, resulting in severe environmental pollution. Resolving the tension between economic transformation and ecological conservation has become an urgent requirement inherent to China’s pursuit of high-quality economic development. Green economic efficiency, as a key indicator balancing economic, social, and environmental performance, provides a scientific measure of China’s high-quality economic development. It not only demands finding a balance between resource utilization and environmental protection but also emphasizes enhancing the green attributes of economic activities through innovation-driven approaches and technological progress, thereby achieving synergistic development of economic growth and ecological conservation. In recent years, with the vigorous development of the digital economy, data elements have emerged as one of the core drivers of economic growth. They continuously empower socioeconomic expansion, industrial structure upgrading, and technological innovation, while also offering valuable insights for enhancing regional green economic efficiency.
This study uses the implementation of pilot policies for big data trading platforms as a quasi-natural experiment. Based on panel data from 284 prefecture-level cities and above in China from 2011 to 2023, it employs a combination of multi-period difference-in-differences models and super-efficiency SBM models to empirically examine the impact effects and mechanisms of data element market development on urban green total factor productivity. The study finds that the development of data element markets significantly enhances the efficiency of urban green economies, and this conclusion remains valid after undergoing a series of parallel trend tests, dual machine learning methods, and heterogeneity treatment effect tests. In terms of mechanisms, the development of data element markets primarily enhances government environmental regulation effectiveness, optimizes regional digital development environments, and stimulates regional green technological innovation vitality, thereby effectively driving a significant improvement in the green total factor productivity levels of Chinese cities. Further analysis shows that the development of data element markets also has significant spatial spillover effects, promoting the coordinated improvement of green total factor productivity in geographically adjacent regions and enhancing regional green development connectivity. In summary, this study provides important theoretical references and policy implications for deepening the understanding of the economic and environmental synergistic benefits of data element marketization reforms, releasing their technological dividends, and promoting the green and low-carbon sustainable development of regional economies.
Based on the findings, this paper proposes the following policy recommendations: first, strengthen the development of data resource trading platforms, improve the data trading platform system, establish a multi-tiered data trading market, and propel the transformation of data as an information technology factor into a new phase of deepened application and standardized development. Second, seize new opportunities presented by digital transformation, focus on key areas for establishing big data trading platforms, explore differentiated development paths, and comprehensively elevate the level of high-quality regional economic development. Third, narrowing development gaps between regions and building a regionally interconnected green digital economic development model are crucial measures for achieving green, high-quality development across the entire region. This research provides a scientific basis for governments to formulate more precise and effective digital economy policies, helping cities optimize and upgrade their industrial structures to achieve high-quality regional economic development. Establish a national-level data trading platform, build a multi-tiered data sharing and trading system, explore the cultivation of regional data trading platforms, and develop industry-specific data trading platforms.

Maintaining sound mental health contributes to enhancing children’s cognitive abilities, non-cognitive skills, and overall accumulation of human capital. Since the 18th CPC National Congress, the state has prioritized mental health education for young people, emphasizing the need to promote their holistic physical and psychological development. This has been integrated into the broader framework of national human resource development and the strategy of revitalizing the nation through science and education. Relevant departments have issued and implemented multiple policy documents. In recent years, the increasing academic burden on students and the spread of educational anxiety have become significant factors affecting the mental well-being of both students and parents. Children in compulsory education warrant particular attention. Alleviating their academic pressures while concurrently enhancing their psychological well-being has emerged as a critical issue for optimizing human capital structures and bolstering the nation’s future competitiveness. Against this backdrop, conducting a multidimensional assessment of the effectiveness of the neighbourhood school policy holds significant importance. By optimizing resource allocation, promoting educational equity, alleviating educational anxiety, and fostering children’s holistic development, this policy provides institutional support for achieving the strategic goal of building China into a leading country in education.
This paper examines the impact of the nearby enrolment policy for primary-to-secondary transition in compulsory education. Utilizing panel data from the China Family Panel Studies and applying a difference-in-differences approach, it assesses the policy’s effects on children’s mental health and its underlying mechanisms. Findings indicate that the nearby enrolment policy significantly reduced children’s depression levels by 0.16 standard deviations, yielding positive mental health outcomes alongside notable improvements in cognitive abilities. Mechanism analysis indicates that regarding academic pressure, the policy effectively alleviates children’s subjective perception of learning stress. Concurrently, it reduces total household education expenditure by curbing school selection competition intensity. Concerning commuting distance, the policy markedly shortens both travel distance and duration to school. Heterogeneity analysis reveals that the proximity enrolment policy yields more pronounced improvements in mental health for children from rural and low-educated households. This paper provides theoretical foundations for the spatial optimization of educational resources during educational modernization, validating the crucial role of equity-oriented institutional design in promoting children’s holistic development.
This paper proposes the following policy recommendations. Firstly, the policy of zoned admission without entrance examinations should continue to be strictly enforced. This requires ensuring that school catchment areas are scientifically defined and transparent, safeguarding the effectiveness of policy implementation, and strengthening oversight of unauthorized cross-zone enrolment practices. In future, consideration may be given to expanding the scope of admission without examinations, extending reforms for equitable distribution of educational resources to higher levels of education. Furthermore, targeted support for disadvantaged groups is essential, such as establishing counselling rooms in rural and under-resourced schools and conducting regular mental health screenings for pupils. Second, policies should continuously optimize the allocation of basic education resources, increasing investment in teaching staff and curricula for rural and under-performing schools. Information technology should be leveraged to enhance classroom teaching quality, narrowing disparities between schools and reducing families’ pursuit of prestigious institutions. It is recommended to establish free or low-cost after-school tutoring programs within schools to replace reliance on market-based supplementary tuition. Thirdly, reforms should centre on the educational assessment system, exploring holistic evaluation methods to diminish families’ utilitarian demand for supplementary tutoring. Fourthly, establish a dynamic monitoring and early warning mechanism for the school-age population to anticipate and adjust for shortfalls in school places in advance, thereby mitigating the impact of educational demand arising from demographic shifts. In areas experiencing sustained population inflows, dynamically increase the number of school places to effectively expand the capacity of state-funded schools and tangibly raise enrolment rates for children of migrant workers. In regions experiencing population outflows, actively promote the development of small-scale schools, implement small-class teaching and personalized learning models, optimize teacher allocation, and improve the teacher-pupil ratio.

The synergistic progression of digital transformation and environm-ental sustainability represents a critical pathway for industrial modernization, a process significantly shaped by supply chain networks where one firm’s digitalization can generate externalities for its partners’ environmental performance. Although digital technologies are recognized for their green potential, the direction and mechanisms of such spillovers along the supply chain remain theoretically and empirically unclear—specifically, whether digitalization influences upstream suppliers or downstream customers more strongly. This paper addresses this gap by developing a formal model and conducting rigorous empirical analysis to identify the direction, channels, and boundary conditions of these green spillovers.
Our theoretical model features a two-tier supply chain with a supplier, a client firm, and end consumers under incomplete contracting. It incorporates consumer utility from both physical and green attributes of final goods, where greenness accumulates from investments across production stages. As the demand-side leader and contract proposer, the client’s digitalization improves information flows and mitigates contractual incompleteness. This asymmetrically alters green investment incentives: it strengthens the client’s ability to monitor and signal demand for greener inputs, creating a strong incentive for upstream suppliers to improve green performance. In contrast, the model implies a weaker direct incentive for downstream customers, whose green efforts are more substitutable and less monitored upstream. Thus, we hypothesize that corporate digitalization generates a positive green spillover directed primarily upstream, with a negligible downstream effect.
Our empirical strategy is designed to test this proposition using micro-level data from China. We construct a novel and comprehensive dataset by meticulously matching the disclosed lists of major suppliers and customers of Chinese listed firms (sourced from CNRDS) with the granular establishment-level information from the National Tax Survey (NTS) spanning 2007 to 2016. This matching process is crucial as it allows us to incorporate the vast majority of non-listed firms that constitute supply chain links, mitigating a severe sample selection bias prevalent in studies relying solely on listed firm data. We derive two distinct analysis samples: a client-supplier panel (7,618 observations) and a client-customer panel (14,367 observations). Enterprise digitalization (DIG) is measured via text analysis of digital keywords in annual reports. Green development (GDE) is a composite index using entropy weighting, integrating NTS indicators on energy use, emissions, and pollution abatement costs.
Using a fixed-effects framework, we find robust evidence supporting the upstream spillover hypothesis. Client digitalization shows a significant negative association with supplier GDE (where lower GDE indicates better performance), while its effect on downstream customer GDE is negligible. This asymmetric finding holds across extensive robustness tests. We examine two underlying mechanisms. First, client digitalization reduces supplier transaction costs, proxied by business entertainment expense ratios, freeing resources for green investment. Second, it stimulates supplier innovation, raising expenditures on both external R&D services and internal R&D activities, thus enhancing technical capacity for green transformation.
Heterogeneity analysis shows the spillover is stronger in supply chains with higher transparency, supplier stability, and concentration. The effect is also more pronounced when clients and suppliers are geographically dispersed, suggesting digital tools can substitute for proximity and mitigate localized pollution agglomeration. We further find that digitally-induced supplier greening increases the supplier’s own total factor productivity (TFP) and contributes to overall supply chain TFP, indicating a “double dividend” aligning environmental and economic gains.
In conclusion, this study makes several contributions. It resolves a key ambiguity in the literature by providing theoretical reasoning and robust empirical evidence for a dominant upstream direction in the green spillover of corporate digitalization. It advances methodological practice by constructing a matched dataset that incorporates critical non-listed entities. It elucidates the dual operational channels of transaction cost reduction and innovation stimulation. Furthermore, it identifies critical moderating factors related to supply chain structure, geography, and ownership, offering actionable insights for managers and policymakers. To harness the full synergistic potential of digitalization for sustainability, strategies should focus on enhancing supply chain transparency and stability, leveraging digital tools for cross-regional green collaboration, and fostering governance structures that amplify market-driven environmental incentives.

In the new stage of Chinese-style modernization, the 15th Five-Year Plan have listed leading the development new quality productive forces and developing patient capital as core strategic tasks. New quality productive forces, as a major original theoretical innovation in Xi Jinping Economic Thought, are advanced productivity led by scientific and technological innovation, featuring originality, factor integration, green and low-carbon development, and institutional innovation. Its formation requires long-term investment, high-risk exploration and systematic collaborative innovation, which is incompatible with the short-term profit-seeking logic of traditional capital. Patient capital refers to long-term holding, strategic oriented and risk tolerant capital, which is naturally compatible with the long-cycle and high-uncertainty development needs of new quality productive forces. The coordinated development of the two is crucial to implementing the innovation-driven development strategy, achieving high-level self-reliance in science and technology, and building a modern industrial system. Based on the strategic orientation of the Outline of the 15th Five-Year Plan for National Economic and Social Development, this paper explores the internal theoretical logic and practical policy paths for their coordinated development, providing theoretical support and operational references for cultivating new quality productive forces and improving the financial system supporting scientific and technological innovation in the 15th Five-Year Plan period.
This paper focuses on clarifying the interactive coupling mechanism between patient capital and new quality productive forces, building a systematic collaborative development framework and designing targeted policy paths. The research follows the logic from theoretical construction to practical application: defining the core connotations of patient capital and new quality productive forces, analyzing their internal interactive logic; constructing a three-dimensional collaborative framework of patient capital, innovation ecosystem and new quality productive forces, and revealing the triple coupling mechanism of capital, institution and innovation; proposing a three-dimensional practical system from institutional supply, financial support and policy incentives; summarizing key policy implications and putting forward feasible suggestions.
In terms of research methods, this paper adopts normative theoretical analysis, literature review and logical deduction. It systematically sorts out existing studies on patient capital and new quality productive forces, integrates the theoretical connotations of Marxist political economy and innovation economics, and constructs a theoretical analysis framework through logical deduction. Meanwhile, it carries out policy text analysis based on the 15th Five-Year Plan and the spirit of the Fourth Plenary Session of the 20th Central Committee, and designs practical policy paths combined with China’s national conditions and the development reality of technology and finance. The main conclusions are as follows. First, patient capital and new quality productive forces form a two-way empowering and circularly reinforcing relationship through capital coupling, institutional coupling and innovation coupling. Patient capital positively empowers the cultivation of new quality productive forces through long-term capital supply, corporate governance optimization and risk sharing. New quality productive forces reversely strengthen patient capital and attract long-term capital agglomeration through return appreciation, risk mitigation and scale expansion, forming a closed-loop growth mechanism. Second, the three-dimensional collaborative framework of patient capital, innovation ecosystem and new quality productive forces is the core theoretical support for their coordinated development. Third, their coordinated development needs to rely on a three-dimensional practical system of institutional supply, financial support and policy incentives. Fourth, four logical transformations are needed: shifting from short-term capital logic to long-term innovation logic, from fragmented support to systematic coordination, from capital supply-side to institutional supply-side, and from unilateral support to two-way empowerment.
Based on the conclusions, this paper puts forward three policy recommendations: improving the institutional supply system by strengthening intellectual property protection, implementing differentiated supervision for long-term capital and promoting patient-oriented reform of state-owned capital; optimizing the financial support system by expanding long-term capital sources, innovating special financial tools and building a capital patience index; strengthening the policy incentive system by giving play to the guiding role of fiscal investment, optimizing the innovation ecosystem and building a green patient capital system.

The rapid iteration and breakthrough of artificial intelligence (AI) technology have driven a wave of AI entrepreneurship, making AI an important force for promoting economic development and reshaping income distribution. Considering the potential applications of AI in a wider range of regions and more scenarios, more research has begun to focus on the economic consequences of AI. Among these consequences, the impact of AI on income inequality has become increasingly prominent. As an application of AI technology, AI entrepreneurship activities are characterized by features that have profoundly influenced the comparative advantages of core and peripheral regions, thereby challenging the applicability of the traditional core-periphery urban structure in studying the economic outcomes of such activities. As various AI startups engaged in the research and application of AI technology, their remote and virtual characteristics, as well as the use of emerging data elements as core production factors, have profoundly influenced the comparative advantages of central and peripheral regions, weakening the dependence of regional economies on central areas. Based on the new perspective of AI entrepreneurial activities, this paper uses data from 284 prefecture-level cities in China from 2011 to 2022 to study the impact of AI entrepreneurship on within-region income imbalance.
The results show that AI entrepreneurship can significantly reduce within-region income imbalance, and this impact has a lasting and scale effect. For every 1% increase in the number of newly registered artificial intelligence enterprises and the total number of artificial intelligence enterprises in the current year, the Gini coefficient of the city decreases by 1.3% and 2.4%, respectively. The core conclusion remains robust after a series of robustness checks. Heterogeneity analysis reveals that the role of AI entrepreneurship in reducing within-region income imbalance is more pronounced for regions that place greater importance on digital economic infrastructure, have higher levels of digital inclusive finance development, and have more advanced AI technologies. The potential mechanisms show that the channels through which AI entrepreneurship reduces within-region income imbalance stem from the fact that AI entrepreneurship has reduced the dependence of the traditional center-periphery urban structure on the central areas, which include both direct and indirect effects. For direct effects, AI entrepreneurship has narrowed the income disparity including promoting regional employment and narrowing the income gap between urban and rural areas. For indirect effects, AI entrepreneurship has forced regions to improve infrastructure construction, optimized the resources allocation, and improved the quality and structure of employment. This paper further discusses whether AI entrepreneurship has a spatial spillover effect on reducing within-region income imbalance. The results show that AI entrepreneurship has a significant spillover effect. It can not only reduce the income disparity in the local area, but also reduce the income disparity in the surrounding areas.
This paper has several potential contributions. From the perspective of research, this paper explores the economic consequences of developing AI based on entrepreneurship activities, which can more comprehensively analyze and evaluate the economic consequences resulting from the application and penetration of AI. It compensates for the current studies’ excessive focus on the technology itself and insufficient coverage of technology application and industrial distribution, enriching the related research on the application of AI and its economic consequences. From the perspective of research content, this paper starts from the center-periphery structure theory, analyzes the particularity of AI entrepreneurship, discovers that AI entrepreneurship reduces the dependence on urban central areas, and narrows the income imbalance within regions through direct and indirect effects. Thus, this paper analyzes the applicability and new changes of the center-periphery structure theory in the context of the rapid development of digital technology and AI, supplementing related research on technological innovation and income inequality as well as digital divide. 
To conclude, this paper expands the theories and application of the “core-periphery” in the era of the digital economy, breaks through the core assumptions of the traditional  “core-periphery” theory based on geographical agglomeration and one-way resource flow of the industrial economy era. Also, this article incorporates AI entrepreneurship activities into the analysis framework of common prosperity, which helps deepen the understanding of AI entrepreneurship activities and their economic consequences.

In the context of profound global economic restructuring and accelerating technological transformation, the interaction between artificial intelligence (AI) and global value chain (GVC) resilience has become a central issue in academic and policy discussions. This paper investigates how AI enhances firms’ ability to withstand, adapt to, and reconstruct from external shocks within the GVC system, emphasizing the asymmetric moderating effects of supply chain stability from both export and import perspectives. Building upon the “absorption-adaptation-creation” analytical framework, we construct a multidimensional index of firm-level GVC resilience and employ matched Chinese customs and industrial enterprise data from 2008 to 2014 to empirically assess the impact of AI on resilience.
The results demonstrate that AI significantly improves firms’ GVC resilience, a finding that remains robust across various specifications, instrumental variable estimations, and alternative measures of AI adoption. Specifically, AI enhances absorptive immunity by enabling real-time monitoring and predictive analytics that strengthen early warning and risk-buffering capabilities. It improves adaptive recovery through flexible manufacturing and dynamic supply chain reconfiguration, allowing firms to resume production quickly after disruptions. Moreover, AI promotes creative reconstruction by fostering product innovation, demand recognition, and value chain upgrading, thus facilitating long-term resilience through path creation rather than mere restoration.
However, the effects of AI are not uniform. When incorporating supply chain stability, we find clear asymmetries between the export-demand and import-supply dimensions. On the export side, declining demand-side stability—resulting from trade protectionism, tariff barriers, and declining foreign demand—reduces firms’ profit margins and cost mark-ups. Such conditions limit firms’ financial flexibility and investment in intelligent technologies, thereby weakening AI’s capacity to enhance GVC resilience. Furthermore, lower export stability disrupts the accuracy of AI-based demand forecasting and production scheduling, diminishing supply chain efficiency and eroding the efficiency-driven component of resilience.
Conversely, declining import stability arising from dependence on critical intermediate goods and high-end technologies amplifies the strategic value of AI in ensuring production continuity. Under increasing import risks, AI enables firms to strengthen their resource reallocation capacity—substituting capital and technology for scarce labor inputs—and to enhance their innovation capability through accelerated product development and knowledge recombination. These adjustments allow firms to transform supply interruptions into opportunities for structural upgrading and process innovation. Therefore, lower import stability, instead of constraining firms, motivates the deeper integration of AI into production systems, amplifying its positive effects on GVC resilience.
Further analysis shows that China’s influence within global trade networks moderates these relationships. By incorporating China’s outward foreign direct investment stock as a proxy for national influence, we find that a stronger presence in key partner countries dampens the positive moderating effect of lower import stability on the AI-resilience linkage. This suggests that while outward investment can reduce short-term supply risks through coordination channels, it may also increase long-term dependency on key nodes, introducing new systemic stability risks.
The heterogeneity analysis provides additional insights. The positive effect of AI on GVC resilience is stronger in labor-intensive industries, where technological upgrading potential is higher and transformation costs are lower, compared to capital-intensive sectors characterized by technological path dependence. Firms without prior trade experience benefit more from AI adoption, as intelligent technologies compensate for their lack of external market knowledge and enhance their integration into global production networks. Moreover, the impact of AI on GVC resilience is more pronounced in regions with stronger intellectual property protection, indicating that institutional quality reinforces the innovation-based resilience mechanism by safeguarding firms’ technological returns and encouraging sustained R&D investment.
This study makes two key contributions. First, it constructs a comprehensive and dynamic measurement framework for GVC resilience, capturing firms’ short-term defense, medium-term recovery, and long-term transformation capabilities through the three dimensions of absorptive immunity, adaptive repair, and creative destruction. This multidimensional design overcomes the limitations of previous single-indicator measures and offers an operational tool for assessing firm-level resilience within the global production system. Second, by integrating supply chain stability into the GVC resilience framework, this study systematically examines how external shocks interact with internal technological capacity. The identified asymmetry between export and import stability risk provides a new understanding of the complex mechanisms through which AI enhances resilience under uncertainty.
The findings offer important policy implications. Policymakers should leverage AI and digital technologies not only to optimize efficiency but also to enhance robustness and adaptability across supply chains. Strengthening digital infrastructure, promoting AI adoption in manufacturing, and improving the institutional environment for innovation can help Chinese firms transform supply chain risks into strategic opportunities for upgrading. In a world of increasing geopolitical tension and technological decoupling, AI-driven resilience is thus essential for maintaining China’s stable participation and upward mobility in global value chains.

Under the dual pressures of widening fiscal revenue-expenditure gaps and accumulating debt risks, how to enhance local fiscal sustainability has become a core issue in fiscal governance. Many studies have explored the determinants of fiscal sustainability from the perspectives of public debt dynamics, demographic structure, or intergovernmental transfer systems. However, the role of budgetary institution reform in shaping fiscal sustainability remains insufficiently examined. Zero-based budgeting (ZBB), as an institutional innovation designed to break expenditure rigidity and optimize fiscal resource allocation, represents a fundamental shift from the traditional incremental budgeting logic. In view of this, using panel data from 31 Chinese provinces over the period 2007 to 2023, this study employs a staggered difference-in-differences model to systematically examine the impact of ZBB reform on local fiscal sustainability, aiming to provide empirical evidence for deepening budgetary management reform and mitigating local fiscal risks.
First of all, this paper establishes the theoretical framework linking ZBB reform to local fiscal sustainability. Traditional incremental budgeting relies on historical expenditure as the base and applies fixed growth rates, encouraging budget-maximizing behavior among government departments. Expenditure allocations consequently become rigid and path-dependent, weakening the government’s capacity to respond to fiscal risks. ZBB reform addresses these institutional deficiencies by requiring all expenditure items to be justified from a zero base, establishing priority ranking and competitive resource allocation mechanisms. Drawing on public choice theory and budgetary incrementalism, three hypotheses are proposed. First, ZBB reform significantly enhances local fiscal sustainability. Second, ZBB reform improves fiscal sustainability by raising expenditure efficiency. Third, ZBB reform improves fiscal sustainability by optimizing expenditure structure, particularly through reducing the share of administrative costs.
Secondly, this paper constructs a staggered difference-in-differences model exploiting the cross-provincial variation in reform timing. Since 2021, provinces such as Anhui, Guangxi, Hunan, and Gansu have successively launched ZBB reform initiatives, with significant variation in implementation timing that provides an ideal quasi-natural experiment setting for causal identification. The dependent variable, local fiscal sustainability, is measured by a composite index encompassing three dimensions: economic development sustainability, fiscal operation soundness, and fiscal risk controllability. This multidimensional measurement framework is consistent with the analytical paradigm advocated by the International Monetary Fund for fiscal sustainability assessment. The index is constructed using the entropy weight method to ensure objectivity. Eleven provinces are identified as the treatment group based on official policy documents and government reports. The model controls for fiscal decentralization, government size, urbanization, trade openness, financial development, population density, and fixed asset investment intensity, with province and year fixed effects included.
Thirdly, this paper reports the empirical results and a series of robustness checks. Baseline regression results show that ZBB reform significantly improves local fiscal sustainability, with a coefficient of 0.042 significant at the 1% level, representing an 11.9% increase relative to the sample mean. The parallel trends assumption is validated through an event study approach, and placebo tests with 1,000 randomized iterations confirm that the estimated effect is not driven by random factors. Robustness checks include instrumental variable estimation, PSM-DID with multiple matching methods, heterogeneity-robust estimators proposed by Callaway and Sant’Anna (2021) and Sun and Abraham (2021), and controls for concurrent policy shocks, all yielding results consistent with the baseline findings. Mechanism analysis confirms both transmission channels: ZBB reform significantly raises fiscal expenditure efficiency as measured by DEA-BCC model estimates and significantly reduces the share of administrative costs in total expenditure.
Finally, this paper further conducts heterogeneity analysis and extended analysis. Heterogeneity analysis reveals that the reform effects are substantially larger in regions with stronger governance capacity and where local decision-makers possess finance-related professional backgrounds. This finding underscores the nature of ZBB reform as an institution-intensive reform whose effectiveness depends on governance foundations and professional execution capacity. Extended analysis demonstrates that improved fiscal sustainability generates meaningful economic and social spillover effects, including raising residents’ per capita disposable income, narrowing the urban-rural income gap, and promoting the growth of both private investment and foreign direct investment by stabilizing market expectations and improving the regional business environment.
This study provides new empirical evidence for understanding the fiscal effects of budgetary institution reform, and offers several policy implications. First, ZBB reform should be accelerated nationwide with gradual extension from provincial to county levels. Second, a performance-oriented project review and dynamic adjustment mechanism should be established to consolidate the efficiency gains from reform. Third, government governance capacity and professional talent development should be strengthened to support high-quality reform implementation. Fourth, the economic and social spillover effects of improved fiscal sustainability should be leveraged by channeling freed fiscal resources toward public services and by enhancing fiscal transparency to strengthen market confidence.

Against the backdrop of the global spread of the anti-globalization trend and the risks of decoupling and disconnection, expanding high-level opening-up has become a key path for China to smooth the domestic and international dual circulation and achieve sustainable economic development. The trade competitive advantage of enterprises, as the core foundation of international competitiveness, is an important cornerstone for China to achieve high-level opening-up, directly determining the country’s division of labor position and trade control rights in the global value chain. Improving the trade competitive advantage of enterprises and ensuring high-level opening-up, and facilitating high-quality economic development, cannot be achieved without the support of the financial market, especially patient capital that assumes long-term strategic risks and provides fundamental support to the real economy. Short-term capital is unable to meet the needs of enterprises in key areas such as technological research and development, industrial upgrading, and green transformation. Long-term capital can provide stable financial support and strategic synergy, optimize the internal resource allocation of enterprises, enhance core competitiveness, and elevate the position of enterprises in the global value chain. Therefore, cultivating and developing patient capital is of vital importance for enhancing the trade competitive advantage of enterprises.
Based on the data of A-share listed companies from 2009 to 2023, this paper examines the impact of patient capital on enterprises’ trade competitive advantages from both theoretical and empirical perspectives, as well as the mechanism of its effect. The empirical analysis shows that patient capital has a significant exogenous effect. Through the construction of a long-term collaborative network between the investment entity and the invested enterprise, a stable strategic cooperation system is formed. Continuous resource investment and risk sharing mechanisms reduce the volatility of enterprise operations, and dynamic capital allocation optimization improves the efficiency of factor utilization, thereby effectively empowering enterprises’ trade competitive advantages. The mechanism analysis indicates that patient capital mainly enhances enterprises’ trade competitive advantages through three paths: global innovation network effect, R&D innovation effect, and value chain upgrading effect. Heterogeneity analysis shows that the role of patient capital investment in enhancing enterprises’ trade competitive advantages is particularly prominent in non-state-owned enterprises, labor-intensive enterprises, non-high-tech enterprises, and enterprises with better financial development levels. This is because patient capital can broaden stable financing channels for these enterprises, create long-term investment opportunities, help them break through resource constraints and transformation bottlenecks, and guide enterprises to focus on core business development and international market layout, thereby significantly amplifying the enhancement effect of trade competitive advantages.
Based on the research conclusions, the following countermeasures and suggestions are proposed. First, cultivate and expand patient capital to help enhance the trade competitive advantage of enterprises. In response to the insufficient supply of patient capital in China, on the one hand, broaden the channels for social security and pension funds to enter the market, optimize the assessment mechanism, offer tax breaks for angel investment and national guiding funds, and encourage the supply of long-term capital. On the other hand, enhance investors’ financial literacy, correct short-term speculative psychology, and leverage the exemplary role of financial institutions to foster a long-term investment mindset and establish a virtuous cycle mechanism. Second, leverage the three major effects to promote the enhancement of enterprises’ trade competitive advantage. By taking advantage of the global innovation network effect, encourage enterprises to expand overseas business, provide policy guidance and tax incentives, and deepen the coordination of technology and markets at home and abroad; relying on the R&D and innovation effect, obtain external knowledge through overseas liaison institutions, optimize internal resource allocation, and improve the quality of innovation; relying on the effect of value chain upgrading, guide enterprises to accurately position themselves in the global value chain, take R&D and innovation as the core, and promote products to move towards high-value-added links. Third, formulate differentiated policies to achieve precise regulation. In light of the heterogeneity of the empowerment of patient capital, prioritize the allocation of patient capital to private enterprises to stimulate their vitality; provide tax and R&D subsidies to labor-intensive and non-high-tech enterprises; strengthen supervision in regions with better financial development to create a low-risk environment; and at the same time, optimize the assessment of state-owned enterprises and support technological breakthroughs to meet the needs of different property rights, industries, and levels of financial development.

As China’s level of domestic economic development rises and its participation in global economic governance deepens, an open-economy model that relies primarily on the cross-border movement of goods and production factors has become increasingly inadequate to meet the requirements of a high-standard open economic system. Promoting a transition from factor- and goods-based opening toward institutional opening has thus emerged as an inevitable strategic choice for China in responding to changes in both domestic and international environments and in cultivating new sources of international competitiveness. Within this context, the reform and diffusion of the negative list regime for foreign investment access provide a valuable policy setting for examining the microeconomic effects of institutional opening.
At the same time, capacity utilization, an important indicator of resource allocation efficiency and overall macroeconomic performance, plays a critical role in achieving high-quality development. Against the backdrop of persistent excess capacity in several Chinese industries, both supply-side structural reform and the “dual circulation” development strategy emphasize improving capacity utilization by optimizing the supply structure and enhancing the efficiency of supply-demand matching. Accordingly, using the foreign investment negative list regime as an entry point to investigate the impact of institutional opening on firms’ capacity utilization not only offers empirical evidence on how institutionalized negative list management can help alleviate excess capacity and promote high-quality development, but also provides valuable insights for other developing economies seeking to advance institutional opening.
Based on China’s experience with institutional opening through the foreign investment negative list regime, this study employs data on A-share listed manufacturing firms from 2008 to 2022 and adopts a staggered difference-in-differences design to systematically examine the impact of institutional opening on firm-level capacity utilization and the underlying mechanisms. The results indicate that institutional opening significantly increases capacity utilization among manufacturing firms. This effect operates primarily through accelerated foreign capital agglomeration and intensified competition, strengthened incentives for technological innovation, and improved allocation of capital factors. Heterogeneity analyses further reveal that the positive effect of institutional opening on capacity utilization is more pronounced among firms with higher levels of digitalization, firms operating in less competitive industries, small and medium-sized enterprises, firms facing lower financing constraints, and privately owned firms.
This paper makes three main contributions. First, it investigates the relationship between institutional opening and firm-level capacity utilization from the perspective of reforms to the foreign investment negative list regime, thereby extending the scope of research on institutional opening. Existing studies have largely focused on the effects of institutional opening on market vitality (Xie and Li 2025), labor income shares (Huang et al. 2023), wage dispersion (Kao and Xie 2024), and technological innovation (Liu et al. 2025), while offering limited and unsystematic discussion of how institutional opening advances supply-side structural reform to alleviate capacity underutilization. By using the rule-based changes embedded in the negative list management regime, a representative form of institutional opening, as the analytical entry point, this paper provides micro-level evidence on how high-standard opening contributes to high-quality development and offers a new perspective on how opening and reform jointly address the problem of excess capacity. Second, the paper systematically uncovers the multiple mechanisms through which institutional opening enhances firms’ capacity utilization. Specifically, it develops an integrated framework that examines three distinct yet interrelated channels: foreign capital agglomeration and competitive effects, firms’ incentives for technological innovation, and the optimization of capital allocation. This framework highlights the systemic and deep-seated nature of institutional opening and offers clear theoretical guidance for policymakers seeking to maximize the gains from opening through coordinated, multi-dimensional reforms. Third, the paper conducts a comprehensive analysis of heterogeneity in the effects of institutional opening on firm-level capacity utilization. By examining differences across firms’ digitalization levels, industry competition intensity, financing constraints, firm size, and ownership structure, the study reveals the context-dependent nature of institutional opening and identifies the critical moderating roles of internal firm capabilities and the external institutional environment. This multi-dimensional and dynamic heterogeneity analysis provides robust empirical evidence on the differentiated impacts of institutional opening across varying market structures and firm characteristics.
The findings offer important policy implications for alleviating excess capacity and promoting high-quality development through deeper free trade zone reforms and a strengthened negative-list-based foreign investment regime. Given its positive effect on firms’ capacity utilization, further streamlining of the negative list, especially in relatively restricted sectors such as services, should remain a reform priority. Enhancing policy stability, transparency, and predictability through stronger legal protections, property rights enforcement, and competitive neutrality can reduce transaction costs and redirect resources toward efficiency and innovation. Policy efforts should also reinforce key channels of institutional opening by promoting foreign capital agglomeration, strengthening innovation incentives and intellectual property protection, and improving capital allocation efficiency through corporate governance and financial reforms. Finally, heterogeneous effects call for differentiated policy guidance to ensure broader and more efficient sharing of opening gains.

Since the launch of reform and opening up, China’s economy has achieved rapid growth and made leaps and bounds. However, elevated inventory has emerged as a major problem affecting the competitiveness of micro-level enterprises and constraining the stable operation of the macroeconomy. At present, as China’s economy enters a new normal, the issue of excessive corporate inventory demands urgent resolution. To date, no literature has examined from a macro perspective the impact of market integration—particularly the development of a unified national market—on the adjustment of non-finished goods inventory in China’s manufacturing enterprises. The Fourth Plenary Session of the 20th CPC Central Committee proposed “building a strong domestic market and accelerating the formation of a new development paradigm” while “resolutely removing bottlenecks and obstacles hindering the construction of a unified national market.” Advancing the construction of a unified national market represents a strategic deployment in response to significantly heightened international uncertainties and the urgent need for domestic economic transformation. This initiative aims to dismantle market segmentation and local protectionism, promote the free flow of factors of production, and facilitate corporate resource reallocation—all profoundly influencing firms’ production expectations and operational decisions. Extensive research indicates that the development of a unified national market generates positive and significant economic effects for enterprises. Differing from such literature, this paper expands the study of how a unified national market influences enterprise resource allocation by adopting the novel perspective of inventory adjustment.
This study examines the impact of China’s long-term institutional reform—the establishment of a unified national market—on inventory adjustment behavior at the microfirm level, using A-share listed companies from 2007 to 2022 as the research sample. Findings reveal that the unified market significantly reduced firms’ non-finished goods inventory levels, with robustness and endogeneity tests confirming this conclusion. Mechanism analysis indicates that the national unified market reduces uncertainty in market operations by lowering commodity circulation costs and supply chain risks, thereby achieving a “de-stocking” effect. Heterogeneity analysis reveals that the “de-stocking” effect is stronger in firms with low non-finished goods inventory ratios and high inventory turnover rates. Economic consequence analysis indicates that the national unified market enhances business efficiency by lowering corporate inventory levels. These findings reveal the micro-level efficacy of the unified market within the context of supply-side structural reform, offering valuable insights for policies aimed at optimizing resource allocation and improving industrial chain and supply chain efficiency. First, with the reduction of distribution costs as the core focus, we will continue to optimize the modern distribution system. Second, with stabilizing the supply chain as a key focus, establish a nationwide risk early warning and coordination mechanism. Third, gradually guide enterprises to enhance their inventory management capabilities and turnover efficiency through differentiated policies.
This paper systematically evaluates the micro-level effectiveness of the national unified market within the context of supply-side structural reform. Compared with existing literature, its marginal contributions may be reflected in the following three aspects: First, this study systematically examines the impact of national unified market development on corporate inventory adjustment behavior, providing valuable additions to theoretical literature on how macroeconomic policies influence micro-level corporate resource allocation. It expands the research boundaries on how institutional environments affect corporate micro-level decision-making and contributes to studies on the economic effects of the national unified market. Second, this study reveals a key pathway through which the unified national market reduces corporate inventory levels by analyzing uncertainty. This provides empirical evidence from the perspective of inventory adjustment, shedding light on the microfoundations of how the unified market enhances the efficiency of national economic circulation. Third, this study identifies the heterogeneity of the “de-stocking” effect of the unified national market across firms with different inventory management levels. It further discusses how this effect promotes enhanced operational efficiency, providing empirical evidence for policy formulation aimed at optimizing corporate resource allocation and strengthening the resilience and competitiveness of industrial chains and supply chains.

The Fourth Plenary Session of the 20th Central Committee of the Communist Party of China (CPC) emphasizes the imperative to “consolidate and strengthen the foundations of the real economy, and keep the focus of economic development on the real economy,” and further calls for efforts to “advance the building of a manufacturing powerhouse along intelligent, green, and integrated pathways, maintain a reasonable share of manufacturing, and develop a modern industrial system with advanced manufacturing as its backbone.” At the micro level, firms’ real investment is shaped not only by demand fluctuations and profit expectations but also crucially by financing conditions and cash-flow constraints. Manufacturing upgrading typically requires equipment renewal, process improvement, and technology adoption that are capital intensive, long-horizon, and slow to pay off. When liquidity constraints become binding, firms are more likely to postpone or scale down capital expenditures, or to tilt their portfolios toward short-term and low-risk uses of funds, generating distortions in investment structure. Accordingly, a systematic assessment of whether and how institutional policies can improve firms’ financing conditions and financing capacity to redirect capital toward real investment is important for understanding investment dynamics and structural adjustment, and for informing the design of policy toolkits aimed at strengthening the real economy with micro-founded evidence. From a policy perspective, since 2018 China has rolled out a sequence of tax and fee reductions intended to lower firms’ burdens and costs, stimulate demand-side momentum, and enhance supply-side vitality. Within this policy package, VAT credit refunds constitute a prominent institutional arrangement that directly improves corporate cash-flow positions. Under the relevant rules, tax authorities may refund firms’ excess accumulated input VAT credits in advance, rather than requiring firms to wait until future output VAT liabilities arise to offset those credits. For eligible firms, the policy effectively releases funds previously tied up within the VAT chain, representing a sizable and salient concession. For real-sector firms with high shares of fixed-asset and intermediate-input spending, VAT credit refunds may therefore influence investment decisions and investment structure by changing the degree of liquidity lock-up and firms’ financing behavior, potentially promoting real investment. At the same time, however, the released liquidity could be diverted into financial asset holdings, short-term wealth-management products, or other non-productive uses. This concern is particularly salient amid China’s ongoing growth-model transition and deepening reforms, as pressures on the real economy have intensified while financial instruments and related products have proliferated, drawing attention to corporate financialization (the “shift from real to virtual”). Weak and slowing real investment undermines allocative efficiency and productivity growth and is unfavorable to structural upgrading, while excessive expansion of financial capital may crowd out real investment and heighten bubble risks. This raises a sharper, policy-relevant question: do VAT credit refunds steer capital toward real-sector investment, or—under certain conditions—do they end up reinforcing a “from real to virtual” allocation pattern?
To address this question, this paper leverages the 2018 expansion of VAT credit refunds across industries as a quasi-natural experiment. Using a sample of A-share listed firms over 2010-2021, we employ a difference-in-differences framework to evaluate the effects of VAT credit refunds on both the level and the structure of corporate investment from a financing perspective. The results indicate that the policy significantly increases firm investment; more importantly, the incremental investment is primarily driven by real (productive) investment, implying a structural shift toward the real sector and a corrective force against “from real to virtual” tendencies. Mechanism analyses suggest that improved financing capacity is the primary transmission channel. Specifically, VAT credit refunds strengthen internal financing by improving operating cash flows and reducing working-capital lock-up and cost pressure in input purchases; they also strengthen external financing by easing financing constraints and mitigating information asymmetry, thereby improving credit assessment and financing availability and enhancing firms’ debt-financing capacity. Heterogeneity analyses further show that the financing incentive is stronger for large firms, while non-state-owned firms exhibit a more pronounced response in both investment expansion and investment-structure upgrading. These findings provide micro-level evidence consistent with the policy objective that VAT credit refunds can stabilize firms, relieve pressures, facilitate capital renewal, and support upgrading of the real economy.
This paper makes three contributions. First, it provides quasi-experimental evidence on how China’s VAT input credit refund program affects corporate investment with an explicit focus on real (productive) investment and the composition of investment, thereby speaking directly to the policy objective of strengthening the real economy. Second, we open the black box of transmission by documenting a financing-channel mechanism: VAT credit refunds ease liquidity lock-up and improve internal funding capacity, and they also mitigate financing constraints and information frictions, enhancing access to external debt finance. Third, by linking a major tax-policy instrument to firms’ investment allocation and financialization tendencies, our findings offer policy-relevant insights on how tax administration and financial intermediation can jointly steer resources toward technology upgrading and capital formation in the real sector.
Based on the analysis in this article, the following policy recommendations are proposed. First, refine VAT credit refund design and implementation to strengthen timely, predictable liquidity support for the real sector by streamlining verification and shortening processing time, with more targeted, compliant fast-track arrangements for high-tech manufacturing, strategic emerging industries, and upgrading projects in traditional industries. Second, enhance the financial system’s responsiveness to tax-policy signals to unblock the “refund-financing-investment” channel by incorporating refund receipt/stability into credit assessment and risk pricing, leveraging tax data to reduce information frictions, and directing more medium- and long-term credit—via guarantees, risk-sharing, and relending tools—toward manufacturing, technological renovation, and equipment upgrading, especially for SMEs. Third, build a tax-finance coordination framework with an explicit real-investment orientation to deter diversion into short-term financial placements by strengthening disclosure and linking incentives/support to verifiable real-investment outcomes (e.g., equipment upgrading, R&D, green and digital transformation) through a closed loop of ex ante guidance, in-process monitoring, and ex post evaluation.

Regional development imbalance is a key challenge in China’s economic and social transformation, and administrative boundary areas have long faced constraints to regional integration due to institutional factors such as differentiated supervision and fiscal management systems. The Beijing-Tianjin-Hebei (BTH) Coordinated Development Strategy, officially launched with the approval of the Beijing-Tianjin-Hebei Coordinated Development Plan Outline in April 2015, is a national initiative aimed at optimizing core city functions, strengthening regional radiation capacity, and promoting balanced and high-quality development. Exploring the impact of this strategy on the land market of Beijing’s administrative boundary counties is of great practical significance: it not only verifies the effectiveness of the strategy in promoting regional coordination but also provides empirical references for optimizing land factor allocation and advancing integration in other urban agglomerations such as the Yangtze River Delta and the Guangdong-Hong Kong-Macao Greater Bay Area.
The core theme of this study is to examine how the BTH Coordinated Development Strategy affects land prices in the administrative boundary counties of Beijing (the core city) and to reveal the underlying mechanisms and heterogeneous effects of the policy. The research adopts a quasi-natural experiment framework, treating the approval of the Plan Outline as an exogenous policy shock. The analytical approach follows three key steps: first, using a Difference-in-Differences (DID) model to identify the net effect of the strategy on land prices, with boundary counties adjacent to Beijing as the treatment group and other BTH counties as the control group; second, conducting mechanism tests to explore the roles of industrial development, population agglomeration, and public resource allocation (infrastructure); third, analyzing heterogeneity based on administrative level, transportation accessibility, and economic foundation.
Methodologically, the study primarily employs the DID model to address endogeneity issues, supplemented by robustness tests including Propensity Score Matching-DID (PSM-DID) to mitigate sample selection bias, event study to verify the parallel trend assumption, and placebo tests to rule out random effects. Heterogeneity analysis is conducted by grouping samples according to administrative level (county-level cities vs. ordinary counties), transportation accessibility (with/without railway stations), and economic foundation (high/low GDP).
Data sources include: ⅰ. 2007-2022 land transaction data from China Land Market Network, covering residential, commercial, and industrial land, aggregated to the county-year level to calculate unit land prices; ⅱ. Landscan 1km resolution population grid data to measure population agglomeration, ensuring spatial accuracy; ⅲ. enterprise registration data from Qichacha to assess industrial scale and structure; ⅳ. POI data to measure infrastructure scale (e.g., transportation facilities); ⅴ. socioeconomic data from the China County Statistical Yearbook and local statistical bulletins, including GDP, fiscal revenue, and public service indicators. All continuous variables are winsorized at the 1% and 99% levels to reduce the impact of outliers.
Key findings are as follows: ⅰ. The BTH strategy significantly promotes the rational appreciation of land prices in Beijing’s administrative boundary counties, with an average premium of 36.7%; industrial land exhibits the most prominent value-added effect (46.4%), followed by commercial land (44.8%) and residential land (33.4%), reflecting the effective implementation of regional industrial collaboration and spatial optimization. ⅱ. Core driving mechanisms are industrial structure optimization (promoting a shift to the service sector) and infrastructure improvement (increasing transportation investment), while the population agglomeration effect is not yet statistically significant—attributed to the policy-guided population concentration in key areas such as Xiongan New Area and the ongoing improvement of public services in boundary counties. ⅲ. Heterogeneous effects are evident: county-level cities, counties with railway stations, and high-GDP counties demonstrate stronger responses to the policy, with coefficients 2.7, 4.3, and 3.1 times higher than their counterparts, respectively.
Policy recommendations include: ⅰ. Consolidate and expand the collaborative achievements in boundary areas by deepening industrial synergy and infrastructure interconnection, and building boundary zones into demonstration platforms for high-quality regional integration. ⅱ. Optimize the guarantee mechanism for cross-regional factor mobility: improve public services through joint school-running and hospital-cooperation to enhance population attractiveness, and simplify approval processes for industrial land to promote industrial scale expansion. ⅲ. Implement differentiated and targeted regional policies: leverage the advantages of county-level cities to gather high-end factors, strengthen transportation infrastructure in counties without railway stations, and support low-GDP counties through paired assistance and fiscal transfer payments.
This study makes four main contributions: ⅰ. It breaks the limitation of existing land price research focusing on urban core areas, filling the gap in studying land premium mechanisms at administrative boundaries—a “frontier of institutional-market interaction.” ⅱ. It clarifies the core transmission paths (industrial structure optimization and infrastructure improvement) of the strategy’s impact on land prices, distinguishing it from studies that only examine overall policy effects. ⅲ. It quantifies the land premium effect brought by regional coordinated development, providing quantitative evidence for understanding the strategic value of administrative boundaries. ⅳ. It details the heterogeneous regulatory effects of institutional (administrative level), geographical (transportation accessibility), and economic (economic foundation) factors, offering targeted insights for land management in boundary areas.