Search Results (1,101)

This study examines Poland’s agricultural land market between 2009 and 2023 through fixed effects and spatial econometric models, highlighting economic and spatial determinants of land prices. Key results show that GDP per capita strongly increases land values (β = +0.699, p < 0.001), while agricultural gross value added (–2.698, p = 0.009), soil quality (–6.241, p < 0.001), and land turnover (–0.395, p < 0.001) are associated with lower prices. Spatial dependence is confirmed (λ = 0.74), revealing strong regional spillovers. The volume of state-owned WRSP land sales declined from 37.4 thousand hectares in 2015 to 3.1 thousand hectares in 2023, while non-market transfers, such as donations, exceeded 49,000 annually. Although these trends support farmland protection and family farms, they also reduce market mobility and hinder generational renewal. The findings call for more flexible, sustainability-oriented land governance that combines ecological performance, regional equity, and improved access for young farmers. Full article

Upgrading the industrial structure is an essential step for economic growth and the transformation of old and new development drivers. Counties situated at the rural–urban interface hold a comparative advantage in industrial upgrading compared to cities, converting agricultural resource dividends into economic value. However, whether agricultural innovation talent can facilitate this process requires further investigation. Based on a sample of 1771 Chinese counties, this study employs a quasi-natural experiment using China’s “World-Class Disciplines” construction program in agriculture and establishes a difference-in-differences (DID) model to examine the impact of agricultural innovation talent on county-level industrial structure upgrading. The results show that agricultural innovation talent significantly promotes industrial upgrading, with this effect being more pronounced in counties with smaller urban–rural income gaps, greater household savings, and higher levels of industrial sophistication. Spatial spillover effects are also evident, indicating regional knowledge diffusion. Knowledge empowerment emerges as the core mechanism: agricultural innovation talent drives industrial convergence, responds to supply–demand dynamics, and integrates digital and intelligent elements through knowledge creation, dissemination, and application, thereby supporting county-level industrial upgrading. The findings highlight the necessity of establishing world-class agricultural research and talent incubation platforms, particularly emphasizing the supportive role of universities and the knowledge-driven contributions of agricultural innovation talents to county development. Full article

Urban–rural integration (URI) plays a crucial role in advancing rural revitalization and the modernization of agriculture. Nevertheless, numerous nations encounter persistent obstacles, including inefficient resource mobility across urban–rural divides and uneven industrial distribution, while striving to foster such integration. Agricultural new quality productive forces (ANPFs) offer an innovation-led production framework fueled by advances in agricultural technology, allowing urban–rural integration (URI) through improved resource mobility between cities and rural regions. Utilizing panel data from 30 Chinese provinces (2013–2022), this study employs a two-way fixed effects model, mediation analysis model, threshold regression model, and the spatial Durbin model to investigate the transmission mechanism and spatial spillover effect of agricultural new quality productive forces (ANPFs) on urban–rural integration (URI). The findings show the following: (1) Agricultural new quality productive forces (ANPFs) significantly influence urban–rural integration (URI). (2) The influence is significantly stronger in western China than in the eastern and central regions. (3) Industrial restructuring and upgrading (IND) function as a mediating influence in this connection. (4) The role of informatization (INF) has a dual-threshold effect. (5) Geographically, while these forces promote local integration, they may impede progress in nearby regions. This study provides new empirical insights into the factors that influence urban–rural integration (URI) and proposes policy solutions to promote sustainable regional development. Full article

As the mainstream financial modality in the digital economy era, digital finance drives industrial digitization and green transformation through capital and technological support, enabling governments to advance environmental governance with greater precision, efficiency, and sustainability. Utilizing 2012–2023 panel data from 31 Chinese provinces, this study innovatively constructs a multidimensional panel data model for the quantitative analysis of the overall impact, heterogeneous effects, and spatial spillover effects of digital finance on government environmental governance. It further examines the mediating effect and the threshold effects of new quality productive forces, and the moderated mediation effects of green technological innovation and industrial collaborative agglomeration. In this study, (1) digital finance significantly drives government environmental governance, and this finding exhibits robustness; (2) digital finance exerts heterogeneous impact on government environmental governance, with more pronounced effects in eastern and sub-developed regions; (3) digital finance generates positive spatial spillover effects on government environmental governance; (4) new quality productive forces positively mediate the relationship between digital finance and government environmental governance; (5) green technological innovation exhibits dual moderation characteristics, moderating both “digital finance → new quality productive forces” and “new quality productive forces → government environmental governance,” while industrial collaborative agglomeration shows single moderation, specifically moderating “new quality productive forces → government environmental governance”; (6) the impact of digital finance on government environmental governance presents a nonlinear feature of “increasing marginal returns.” On these accounts, this study proposes targeted recommendations from six dimensions. Full article

This study aims to reveal the influence mechanism of innovation competition on the high-quality development of the manufacturing industry in Chinese local governments. Additionally, the study provides a theoretical basis for understanding how governments’ investment in science and technology breaks through key technological bottlenecks, enhances the innovation ability of enterprises, and promotes the high-quality development of the manufacturing industry. Based on balanced panel data of 269 prefecture-level and above cities in China from 2008 to 2021, the entropy value method is used to construct a comprehensive evaluation index of manufacturing development quality, and a two-way fixed-effect panel model is employed for the empirical analysis. The findings reveal that (1) for every 1% increase in local government investment in science and technology, the manufacturing high-quality development index will increase by 0.261%, indicating that local governments’ innovation competition significantly promotes the quality of manufacturing development; (2) enterprise innovation capacity plays a mediating role between government competition and manufacturing quality improvement; (3) the combined mechanism of innovation drive and promotion tournament results in a significant spatial strategic interaction of local governments’ innovation competition and a positive spillover effect on neighboring regions. Therefore, this study suggests that local governments implement different science and technology innovation investment strategies to optimize the allocation of innovation resources according to the regional manufacturing technology level. Full article

Amidst the dual challenges of escalating ecological environmental pressures and economic transformation globally, green innovation emerges as a pivotal pathway toward achieving high-quality sustainable development. To elucidate how digitalization and novel productive forces synergistically drive the green transition, the research utilizes panel data from 30 provincial-level administrative regions in China spanning 2009 to 2022, constructing a green innovation efficiency measurement frame-work grounded in the Super Slack-Based Measure (Super-SBM)model, alongside a novel productive forces evaluation system based on the triad of laborers, labor objects, and means of production. Employing spatial difference-in-differences and double machine learning methodologies within a quasi-natural experimental design, the research investigates the causal mechanisms through which digital empowerment and novel productive forces influence regional green innovation efficiency. The findings reveal that both digital empowerment and novel productive forces significantly enhance regional green innovation efficiency, exhibiting pronounced positive spatial spillover effects on neighboring regions. Heterogeneity analyses demonstrate that the promotive impacts are more pronounced in eastern provinces compared to central and western counterparts, in provinces participating in carbon trading relative to those that do not, and in innovation-driven provinces versus non-innovative ones. Mediation analysis indicates that digital empowerment operates by fostering the aggregation of innovative talent and elevating governmental ecological attentiveness, whereas new-type productivity exerts its influence primarily through intellectual property protection and the clustering of high-technology industries. The results offer empirical foundations for policymakers to devise coordinated regional green development strategies, refine digital transformation policies, and promote industrial structural optimization. Furthermore, this research provides valuable data-driven insights and theoretical guidance for local governments and enterprises in cultivating green innovation and new-type productivity. Full article

Between 2013 and 2020, China had implemented a pilot cap-and-trade carbon emissions trading system (ETS) in some cities. Previous research has reported that this policy significantly reduces air pollution in the policy-implementing districts. However, whether and to what extent there are spatial spillover effects of this policy on air pollution in other regions has not been sufficiently analyzed. The research objective of this study is to quantitatively assess the spatial spillover effects of China’s carbon ETS on air pollution. Based on data from 288 Chinese cities between 2005 and 2020, this study employs a multiple linear regression approach to estimate the policy effects. Our study finds that the policy significantly reduces the concentrations of black carbon (BC), nitrogen dioxide (NO₂), organic carbon (OC), particulate matter less than 1 micron in size (PM₁), fine particulate matter (PM_2.5), and particulate matter less than 10 microns in size (PM₁₀) in non-ETS regions. This indicates that the carbon ETS has beneficial impacts on air quality beyond the areas where the policy was implemented. The heterogeneity tests reveal that the beneficial spatial spillover effects of the ETS can be observed across cities with different levels of industrialization, population density, economic development, resource endowments, and geographical locations. Further mechanism analyses show that although the policy does not affect the degree of environmental regulation in other regions, it promotes green innovation, low-carbon energy transition, and industrial structure upgrading there, which explains the observed spatial spillover effects. Full article

In light of increasing environmental issues, green and environmentally friendly growth has emerged as a global consensus., making the progression of a low-carbon and eco-friendly new energy vehicle (NEV) industry essential for countries globally. This study focuses on the 26 provinces of China, employing benchmark regression, mediation analysis, spatial econometrics, and difference-in-differences models to comprehensively investigate the impact and underlying mechanisms of NEV industry agglomeration on high-quality green development, using a unified framework to measure both agglomeration and development standards, which enhances the accuracy of previous measurements using a single indicator. The findings show that NEV industry agglomeration directly promotes high-quality green development, mediated significantly by green technological innovation and public environmental awareness. Analysis reveals significant regional heterogeneity, with stronger NEV industry agglomeration in midwestern regions, areas prioritizing sustainable and low-carbon policies, and regions with advanced economic and financial systems, leading to a greater positive impact on high-quality green development. NEV industry agglomeration influences high-quality green development in neighboring regions through spatial spillover effects. The results remain robust when using instrumental variables and treating NEV-related policy formulation as a quasi-natural experiment. This study provides theoretical guidance and policy recommendations to encourage high-quality green development through NEV industry agglomeration. Full article

Focusing on the dynamic change process of urban ecology and economy, this paper explores the spatial correlation pattern of cities in the Yangtze River Delta (YRD) region for sustainable development from 2012 to 2023 based on the coupled coordination model, gravitational model, and social network analysis (SNA). First, the sustainable development level of the city shows a certain upward trend in the time dimension. In the spatial dimension, there is significant regional differentiation, which roughly shows the development characteristics of gradual increase from the interior to the coast. Second, cities with lower-level sustainable development and higher-level sustainable development always maintain their own stability, but being adjacent to a city with lower-level sustainable development increases the probability of an improvement. Third, cities that play an important role in driving the level of spatial correlation for sustainable development are mainly concentrated in the central and eastern parts of the YRD, with Shanghai, Suzhou, Nanjing, and Hangzhou being the most important radiation centers in the pattern of spatial correlation. Fourth, the affiliation system of sustainable development gradually changes from the double core system of Shanghai–Suzhou to the triple core system of Shanghai–Suzhou–Hangzhou to drive and lead the development of the subordinate cities. Fifth, the spatial network can be categorized into four plates: benefit, overflow, bilateral spillover, and broker, with obvious linkage effects between plates. Full article

Utilizing data from 282 prefecture-level cities in China from 2005 to 2021, this study constructs an evaluation index system for high-quality economic development across the following five dimensions: innovation, coordination, green, openness, and sharing. A continuous difference-in-differences approach is employed for regression analysis to empirically examine the impact of high-speed rail on high-quality economic development, further exploring its mechanisms and spatial spillover effects. The findings reveal that (1) HSR significantly promotes high-quality economic development; (2) with the development of HSR, from 2005 to 2021, China’s high-quality economic development showed an evolutionary trend of overall improvement, with a gradual optimization of spatial patterns; (3) it facilitates high-quality economic development by enhancing capital and labor mobility, strengthening industrial chain resilience, and advancing industrial structure upgrading; (4) high-speed rail development in neighboring regions generates positive spatial spillover effects on local urban economic quality; and (5) the impact of high-speed rail on high-quality economic development exhibits significant heterogeneity across cities with different regions, tiers, scales, and resource endowments. These results confirm the positive role of high-speed rail in fostering high-quality economic development. Full article

Under the collaborative framework of sustainable development and environmental pollution control in China, there is an urgent need to break the governance dilemma of traditional environmental regulations and explore innovative paths for sustainability. This paper empirically tests the direct impact, spatial spillover effects, and mechanisms of free trade zones (FTZs) in China in reducing water pollution. Using a spatial Durbin model (SDM) combined with the staggered difference-in-differences (STA-DID) method on a dataset of 266 Chinese cities encompassing eastern, central, and western regions with diverse economic and environmental baselines from 2003 to 2023, the study finds that FTZs significantly reduce local water pollution by 9.17 million tons of untreated sewage discharge (β = −916.6, p < 0.01), with a spatial spillover effect that decreases pollution in surrounding cities by 12.33 million tons (β = −1232.9, p < 0.01). Upgrading industrial structure, accelerating technological innovation, and strengthening government environmental governance constitute the core mediating channels. This study provides theoretical support for institutional innovation in environmental governance and empirical evidence to address the trade-off between economic growth and environmental protection in China, contributing to the understanding of how context-specific institutional innovations can advance regional sustainability, aligning with the United Nations Sustainable Development Goals (SDGs). Full article

As the relationship between cryptocurrency mining activities and electricity consumption becomes increasingly close, the risk spillover effect is steadily drawing a lot of attention to the energy and cryptocurrency markets. For the purpose of studying the risk contagion between the cryptocurrency and energy market, this paper constructs a risk contagion network between cryptocurrency and China’s energy market using complex network methods. The tail risk spillover effects under various time and frequency domains were captured by the spillover index, which was assessed by the leptokurtic quantile vector autoregression (QVAR) model. Considering the spatial heterogeneity of energy companies, the spatial Durbin model was used to explore the impact mechanism of risk spillovers. The research showed that the framework of this paper more accurately reflects the tail risk spillover effect between China’s energy market and cryptocurrency market under various shock scales, with the extreme state experiencing a much higher spillover effect than the normal state. Furthermore, this study found that the tail risk contagion between cryptocurrency and China’s energy market exhibits notable dynamic variation and cyclical features, and the long-term risk spillover effect is primarily responsible for the total spillover. At the same time, the study found that the company with the most significant spillover effect does not necessarily have the largest company size, and other factors, such as geographical location and business composition, need to be considered. Moreover, there are spatial spillover effects among listed energy companies, and the connectedness between cryptocurrency and the energy market network generates an obvious impact on risk spillover effects. The research conclusions have an important role in preventing cross-contagion of risks between cryptocurrency and the energy market. Full article

Facilitating industrial restructuring and modernization plays a pivotal role in realizing China’s dual-carbon objectives (carbon peaking and carbon neutrality) and advancing sustainable socioeconomic progress. Leveraging panel data from 30 provincial-level administrative units (2005–2022) and adopting the Spatial Durbin Model, this research investigates how industrial structure upgrading influences carbon emission intensity within the framework of a unified national market, while elucidating its operational mechanisms. The key findings include the following: (1) Provincial carbon emission intensity demonstrates pronounced “high-high” and “low-low” spatial agglomeration during the study period. Industrial restructuring exhibits marked carbon abatement effects, accompanied by discernible cross-regional spillover benefits. (2) Industrial structure upgrading can reduce carbon emission levels by promoting the technology diffusion effect, while the competitive demonstration effect of digitalization has not yet manifested. (3) The establishment of an integrated national market enhances the capacity of industrial upgrading to suppress carbon emission intensity. (4) The emission-reducing impacts of industrial restructuring manifest heterogeneous patterns across regions and temporal phases: In Eastern China, industrial upgrading paradoxically elevates emission intensity. Central-western regions experience significant emission reductions. Temporally, the relationship follows an inverted U-shaped trajectory. These insights underscore the necessity for policymakers to refine industrial modernization strategies, expedite nationwide market integration mechanisms, and cultivate region-specific green transition roadmaps. Full article

This study investigates the coupling coordination between carbon emission efficiency (CEE) and carbon balance (CB) in the Yellow River Basin (YRB), aiming to support high-quality regional development and the realization of China’s “dual carbon” goals. Based on panel data from 74 cities in the YRB between 2006 and 2022, the Super-SBM model, Ecological Support Coefficient (ESC), and coupling coordination degree (CCD) model are applied to evaluate the synergy between CEE and CB. Spatiotemporal patterns and driving mechanisms are analyzed using kernel density estimation, Moran’s I index, the Dagum Gini coefficient, Markov chains, and the XGBoost algorithm. The results reveal a generally low and declining level of CCD, with the upstream and midstream regions performing better than the downstream. Spatial clustering is evident, characterized by significant positive autocorrelation and high-high or low-low clusters. Although regional disparities in CCD have narrowed slightly over time, interregional differences remain the primary source of variation. The likelihood of leapfrog development in CCD is limited, and high-CCD regions exhibit weak spillover effects. Forest coverage is identified as the most critical driver, significantly promoting CCD. Conversely, population density, urbanization, energy structure, and energy intensity negatively affect coordination. Economic development demonstrates a U-shaped relationship with CCD. Moreover, nonlinear interactions among forest coverage, population density, energy structure, and industrial enterprise scale further intensify the complexity of CCD. These findings provide important implications for enhancing regional carbon governance and achieving balanced ecological-economic development in the YRB. Full article

The driving mechanism of new qualitative productivity forces for coordinated development, which constitutes an inherent requirement of high-quality development, requires creative factor allocation through spatial flows, and the same is true for new maritime qualitative productivity forces. In this study, we constructed an evaluation indicator system to assess the impact of spatial flows of marine new qualitative productivity force factors on economic coordinated development in China’s coastal regions. Using panel data from 11 coastal provinces (2003–2022), we quantified new qualitative productivity force factor spatial flows and marine economic coordinated development levels, visualized their spatial–temporal patterns, and empirically examined their interaction mechanisms. The key findings include the following: (1) From 2013 to 2022, marine new qualitative productivity force factor spatial flows in coastal China transitioned from clustered “block-style” to scattered “multi-point” distribution patterns, with marine economic coordination exhibiting steady growth alongside pronounced spatial polarization. (2) Marine new qualitative productivity force factor spatial flows demonstrate significant positive direct effects on local marine economic coordination. (3) The notable spatial spillover effects of marine new qualitative productivity force factor spatial flows enhance coordinated development in neighboring regions. (4) Heterogeneous impacts emerge across marine new qualitative productivity force factor dimensions, where the spatial flows of new-type marine objects of labor and means of labor exert particularly significant influences. These findings provide policy insights for optimizing the spatial allocation of marine new qualitative productivity force factors to advance China’s marine economic coordination. Full article