Search Results (579)

With rapid urbanization, improving school quality in compulsory education is critical for optimal educational resource allocation. This study integrates a random forest machine learning model, GIS spatial analysis, and a spatial econometric model to examine the spatiotemporal differentiation of school quality in Dalian, China, in 2016 and 2020, as well as its relationships with the construction land development cycle, population density, and housing prices. The findings reveal a core–periphery structure, with overall school quality on the rise and basic facility configuration exerting a stronger impact than teacher strength. Among internal resources, per capita sports venue area (PCSFA) and per capita teaching equipment value (PCTRE) contribute most significantly to school quality, while high-quality clusters in traditional educational hubs, university-covered areas, and transitional zones spur improvements in surrounding schools. The population density, housing prices, and the construction land development cycle all positively correlate with school quality, highlighting the need for coordinated action among urban planners, education authorities, and housing regulators to ensure that land development, housing affordability, and school facility investments advance equitable access to quality education. These results provide a novel perspective on compulsory education quality assessment and offer a valuable foundation for guiding education policies and urban development strategies. Full article

Effectively controlling the carbon emissions intensity of the transportation sector (TSCEI) is essential to promote the sustainable development of the transportation industry in China. This study, which builds upon trend analysis, the Dagum Gini coefficient, and spatial autocorrelation analysis to reveal the spatiotemporal differentiation of TSCEI, employs both traditional and spatial Markov chain to analyze the dynamic evolution of TSCEI and forecast its future development trend. Furthermore, econometric models are constructed to examine the convergence characteristics of TSCEI. The empirical results reveal the following key findings: (1) TSCEI in China has significantly declined, exhibiting a spatial distribution pattern of “higher in the north, lower in the south; higher in the west, lower in the east”. (2) Inter-regional differences are the main contributors to overall TSCEI disparities, with provincial TSCEI exhibiting positive spatial autocorrelation, primarily characterized by high–high and low–low agglomeration. (3) TSCEI tends to gradually shift from high- to low-intensity states over time, with an equilibrium probability of 90.98% for transferring to lower intensity state. Provincial TSCEI shows significant spatial spillover effects, influenced by neighboring provinces’ states. (4) TSCEI demonstrates convergence characteristics at national and regional levels, including σ convergence, absolute and conditional β convergence, with the transportation energy structure and technological progress playing a particularly prominent role in facilitating the convergence of TSCEI towards lower values. The policy implications of promoting TSCEI convergence and reducing spatial inequality are discussed. Full article

The digital economy offers new solutions for reconciling the growth of the non-timber forest-based economy (NTFBE) with ecological and environmental protection. Utilizing panel data from China’s provinces between 2011 and 2020, this study constructed a comprehensive indicator system for the purpose of examining the coordinated development of the NTFBE and the ecological environment. The employment of a panel of econometric methods, including Tobit models, mediated effects models, spatial Durbin models and threshold regression models, has enabled us to ascertain that the digital economy can effectively drive this coordinated development. The digital economy has a positive spillover effect in neighboring regions, although there is no discernible impact in central and northeastern China. Improvements in human capital and digital infrastructure reinforce this effect. Furthermore, the empowerment of green technology and industrial transformation, as well as the adoption of differentiated development strategies across distinct forest economic models, would be of paramount importance. These findings indicate a necessity for the standardization of the NTFBE. In conclusion, these implications offer novel solutions from China’s forested regions that reconcile socioeconomic growth and environmental protection, thereby fostering the sustainable development of forests. Full article

Achieving sustainable rural development in China requires effectively integrating agricultural growth with ecological balance. However, existing research on the coordination between agricultural economy and ecosystems has often focused on isolated aspects, such as economic growth or ecological sustainability, or has been limited to specific provinces or regions, lacking a comprehensive nationwide analysis. To address this gap, this study uses spatial data from 31 provincial-level regions in China from 2008 to 2022, developing a multidimensional framework that encompasses economic input, structure, efficiency, benefits, vitality, ecological conditions, and pressure. Using multi-factor econometric methods, we comprehensively evaluate the coordination between China’s agricultural economy and ecosystems, revealing regional disparities and spatiotemporal variations in their coupling coordination, and analyzing the barriers affecting this coordination. Our findings show that: First, coupling coordination has steadily improved, narrowing regional disparities. Second, regional differences are primarily driven by variations between the eastern, central, and western regions, with structural disparities shifting from interregional to hyper-variable density. Third, development exhibits a “club convergence” pattern, where upward transitions are difficult and downward mobility is a risk. Key barriers include farmland scale, land efficiency, afforestation area, and soil erosion control. Based on these findings, we recommend regional development strategies, dynamic monitoring mechanisms, optimized land use, and enhanced ecological protection. This study provides valuable insights for policymakers and practitioners to promote the coordinated and sustainable development of agricultural economies and ecosystems in China. Full article

New quality productivity (NQP) has the possibility to enhance carbon emission performance which will fortify the groundwork for long-term economic expansion even further. The research examines the panel data of 30 provinces spanning the years 2012 to 2022 for an evaluation framework for NQP and carbon emission performance at the provincial level. Employing fixed effect models, mediation effect analysis, and spatial econometrics, the study explores the effect of NQP on carbon emission performance, its mediating mechanisms, and the spatial spillover effects. The findings indicate that (1) NQP significantly lowers carbon emissions for every unit of GDP and enhances carbon emission performance, and the result holds up when the instrumental variable methods are used. (2) The NQP had a significant contribution to improving carbon emission performance via advancements in green innovation. (3) The NQP does more than directly enhance the regional carbon emission performance; in contrast, it additionally positively influences the carbon emission performance level of the adjacent regions by the spatial spillover effect. (4) The impact of NQP on carbon emission performance is particularly pronounced in eastern and innovative regions. On this basis, we should vigorously develop the NQP, strengthen cross-regional policy coordination, and promote green and sustainable development. Full article

Venture capital is vital for developing capital markets and the low-carbon transformation of the economy. We used panel data from 27 cities in the Yangtze River Delta urban agglomeration from 2011 to 2022 to investigate how the scale and structure of venture capital influence the intensity of urban carbon emissions using spatial econometric models. We show that an increase in the scale of venture capital can inhibit the increase in the intensity of urban carbon emissions, and the effect is more pronounced in cities with higher pollution and better geographical location. Heterogeneity exists in the carbon-reduction effects of venture capital across industries. The direct carbon reduction effect of venture capital flowing to mid- and low-end industries is stronger and more prominent in cities with higher pollution and less favourable geographical locations. The long-term carbon reduction effect of venture capital flowing to high-end industries is stronger. The mediating effect of technological innovation is prominent, while the effect of industrial structure upgrade is not prominent. The enterprises’ willingness and ability to engage in green transformation acts as a positive moderator, whereas the positive moderating effect of the government in that respect is insufficient. This study clarifies the mechanism of venture capital on urban carbon emissions and offers valuable insights for optimising the structure and system of venture capital. Full article

With the advent of the information age, the digital economy has become an important force in promoting economic and social development; however, its impact on urban–rural relations remains controversial. The primary objective of this paper is to conduct a comparative analysis of the spatiotemporal evolution trends of both the digital economy and urban–rural integration in China. It focuses on exploring the spatial spillover effects and dual effects of the digital economy on urban–rural integration. Utilizing comprehensive data from 31 provinces spanning from 2000 to 2021, this paper employs multiple econometric models to analyze the intricate relationship between these two phenomena. The key findings indicate that, in the short term, the digital economy has a dampening effect on urban–rural integration, with an estimated total short-term impact of −4.21. Conversely, in the long run, the digital economy significantly fosters urban–rural integration, exhibiting a long-term effect of 0.47. Moreover, the digital economy exhibits notable spatial spillover effects, influencing adjacent areas through mechanisms such as technology diffusion and knowledge dissemination. This spatial spillover effect is pronounced within a radius of one to two provinces or approximately 540 km and gradually diminishes as the distance increases. This paper provides a new perspective for understanding the complex relationship between the digital economy and urban–rural integration with an important reference value for promoting coordinated urban–rural development in China. Full article

Digitization plays a vital role in fostering economic and social development. This study empirically investigates the impact of digitization on urban industrial structures, technological innovation, public service levels, and social–ecological resilience. Various approaches, including the two-tier stochastic, spatial econometric, and panel threshold models, have been employed to analyze panel data from 287 cities from 2008 to 2023. These data are examined through a quasi-natural experiment analyzing the evolution of urban social–ecological resilience following China’s promotion of the national comprehensive pilot zone for big data. The findings are as follows. (1) The positive effects of digitization on urban social and ecological resilience substantially outweigh the negative effects, with an overall increasing trend in the positive net effect, albeit with significant regional differences. (2) Digitalization exhibits a significant spatial spillover effect, enhancing local social–ecological resilience while inhibiting improvements in neighboring cities. (3) Technological innovation and public service levels positively affect social–ecological resilience, whereas industrial structure upgrading has a negative indirect effect. Both industrial structure upgrading and public service levels demonstrate nonlinear effects under the threshold constraints of the intermediary mechanism. (4) In terms of policy mechanisms, regional differences in the urban industrial structure, innovation capacity, and public service levels must be considered. This approach is essential for promoting the organic integration of digitization across regions, mitigating the polarization effect, and enhancing the diffusion effect. Full article

The realization of intelligent transformation is an important path for the industry to move towards low-carbon development. Based on panel data from 30 provinces in China, this study utilizes the intermediate effect model and spatial econometric model to analyze the influence of industrial intelligence on carbon emissions. The research reveals that industrial intelligence helps with carbon reduction, and the result is still valid after undergoing various tests. Industrial intelligence relies on green technological innovation, industrial structure upgrading, and energy intensity to realize carbon reduction. There is a spatial spillover role of industrial intelligence on carbon emissions, which has a positive influence on carbon reduction in local and adjoining regions. The influence of industrial intelligence on carbon emissions exhibits heterogeneity in the regional dimension, time dimension, and industrial intelligence level dimension. The research provides empirical evidence and implications for using artificial intelligence to achieve carbon reduction. Full article

Non-point source pollution from agricultural land use is a significant contributor to environmental pollution, causing serious threats to water, air, and soil quality. Environmental regulations have been shown to have a significant negative effect on pollutant emissions. However, empirical studies examining the impact of agricultural environmental regulations on cultivated land non-point source pollution are limited. To explore the effects of environmental regulations on cultivated land non-point source pollution, this study focuses on the Dongting Lake Plain. Using statistical data from 2010 to 2020, we analyze the temporal and spatial changes in cultivated land non-point source pollution before and after the implementation of the “Zero Growth of Fertilizer and Pesticide Use Action Plan”. A spatial econometric model is used to assess the impact of environmental regulations on pollution. The results indicate that non-point source pollution in the Dongting Lake Plain shows positive global spatial autocorrelation. Locally, in 2010 and 2015, high-high clusters were dominant, while low-low clusters were less common. By 2020, low-low clusters became the main pattern of pollution. The introduction of the Zero Growth Action Plan had a negative impact on pollution intensity within the region and positive spillover effects on neighboring areas. In terms of emission structure, the plan significantly reduced nitrogen emission intensity and pesticide loss, but had a positive impact on phosphorus emissions. The level of regional economic development had a significant negative effect on pollution intensity, while urbanization had a positive effect. Agricultural technological progress showed a negative spatial spillover effect on phosphorus emissions, and regional economic development had a negative spatial spillover effect on nitrogen and pesticide emissions. This study provides evidence of the impact of environmental regulations on cultivated land non-point source pollution and offers valuable insights for the development of future pollution control policies. Full article

Under the continuous innovation and widespread application of digital technology, accelerating the formation of new-quality productive forces is an unavoidable theme of the times. Based on a systematic analysis of the logical relationships between the digital economy, industry–academia–research collaborative innovation, and new-quality productive forces, this article constructs a theoretical analysis framework for the impact of the digital economy on new-quality productive forces. This article also employs spatial econometric techniques and panel threshold models to empirically test the relationships among the three. This study finds that spatial correlation is a significant factor that cannot be ignored in the process of the digital economy and industry–academia–research collaborative innovation empowering the formation of new-quality productive forces. The empowering effects of the digital economy and industry–academia–research collaborative innovation on new-quality productive forces differ, with the former’s effect significantly higher than the latter. The combined effect of both shows a strong synergistic impact on accelerating the formation of new-quality productive forces. Further threshold model tests reveal that both the digital economy and industry–academia–research collaborative innovation have certain thresholds in promoting the development of new productive forces. Only when they achieve synergy and progress together can they maximize their respective roles in driving the development of new productive forces. This research is of great significance for fully leveraging the digital economy to empower the formation of new-quality productive forces, thereby promoting high-quality economic development in China. Full article

With the rapid economic growth in China, the years from 2012 to 2017 witnessed a severe outbreak of haze pollution. In response, numerous enterprises were shut down or forced to reduce production, leading to significant negative impacts on the economy and society. Consequently, the scientific management of haze pollution has become a focal point of China’s environmental research. This paper explores the influence of green finance and environmental regulations on haze pollution, employing spatial autoregressive and spatial Durbin models to conduct an empirical analysis based on panel data from 30 Chinese provinces spanning 2000 to 2017. The following conclusions were thus drawn: from 2010 to 2017, the green finance index of the Beijing–Tianjin–Hebei region and Liaoning Province, which suffered severe haze pollution, showed an overall downward trend; efforts to strengthen environmental regulations played an important role in reducing air pollution, especially the PM2.5 level; the improvement in the green finance level can help reduce haze pollution; and green finance has an obvious spatial spillover effect. A number of policy recommendations were proposed on this basis, including strengthening inter-regional cooperation and exchanges in green finance, promoting the scientific application of environmental regulations in areas with serious haze pollution, strengthening the implementation of green finance strategies in areas with serious haze pollution, and establishing regional green finance demonstration zones. The purpose of this study is to provide meaningful support for China’s scientific management of haze pollution through an analysis of the impact of green finance and policy optimization. The innovative aspects of this research lie in its pioneering use of spatial econometric models to investigate the role of green finance and environmental regulations in controlling haze pollution. The findings reveal that advancements in green finance can significantly alleviate haze pollution. Full article

The labour supply has historically been subject to influence from the economic cycle. On the other hand, there is a paucity of research in the Latin American region examining the impact of social factors on labour participation in diverse contexts. This study examines the spatial dependence of the cyclical sensitivity of labour supply in 23 provinces of Ecuador. A time series analysis was conducted to calculate the cyclical sensitivities of labour supply, and spatial econometric techniques were applied to assess spatial dependence using monthly data for the period 2021 to 2024. We found evidence of a positive and significant spatial dependence in the cyclical sensitivity of labour supply. Our findings suggest that labour decisions in one province are influenced by those in neighbouring provinces, thereby providing a framework for the design of public policies that take into account these interdependencies. Full article

Urban spatial structure, shaped by human intervention in the natural environment, impacts the functional space and socioeconomic efficiency of cities. Against this backdrop, this study investigates the linkage between urban spatial structure (USS) and carbon emission efficiency (CEE) in China from 2012 to 2020. This paper employs a nine-year dataset and spatial econometric models involving 279 prefectural cities in China. The study innovatively employs the Herfindahl index and the super-efficiency SBM model to evaluate the level of polycentric urban structure and CEE in these cities. It further explores the trends in spatial evolution and relevant characteristics of these factors. Additionally, the study applies the SDM to explore the spillover effect of urban polycentric structure on CEE. The study makes innovative use of the Herfindahl index and the super-efficiency SBM model to evaluate the level of polycentric urban structure and CEE in these cities, further exploring the trends in spatial evolution and relevant characteristics of these factors. Additionally, it applies the SDM to explore the spillover effect of urban polycentric structure on CEE. Robustness tests are carried out to confirm the findings. The results confirm that a polycentric structure significantly enhances carbon emission efficiency within a city. However, it adversely affects neighboring cities by reducing their carbon emission efficiency through negative spatial spillover effects. The results verify that a polycentric structure significantly enhances carbon emission efficiency within a city. However, it has an adverse impact on neighboring cities by reducing their carbon emission efficiency through negative spatial spillover effects. Full article

With the spread of the concept of sustainable development, the quality of development of the construction industry has begun to receive attention. Compared with speed, the quality of the development of the construction industry is not only reflected in its output, but also its impact on socio-economic development factors, which should be emphasized, and the comprehensiveness of its measurement is more difficult to ensure. However, theoretical and practical research on construction development in developing countries has been limited, mainly in terms of the semantic foundations and quantitative methods of the subject. Therefore, this paper focuses on China, the largest developing country, defines the concept and connotation of high-quality development of the construction industry (HQDCI), and constructs a set of tools for evaluating and analyzing HQDCI based on the theory of mutation and the relevant theories of spatial econometrics. In case studies, we also found that the key role of innovation drive and social contribution in HQDCI has been highlighted, and the balance of development has constrained HQDCI in some regions. In terms of spatial analysis, we find that the role of economic circles and city clusters in promoting HQDCI deserves attention, mainly because economic circles and city clusters can drive regional coordination, resource integration, and innovation diffusion. This paper expects to provide some insights into the transformation and sustainable development of other developing countries through this evaluation and analysis system based on the transformation of China’s construction industry. Full article