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.

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.

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.

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. 

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.

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.

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.