Provincial Level In China Research Articles (Page 1)

This paper examines the impact of the digital economy on service consumption using provincial panel data from China (2014–2022) via fixed effects models. The empirical results indicate that the digital economy has a significant positive impact on the growth of service consumption in China. In further heterogeneity analysis, we provide evidence that the digital economy has a significant positive impact on service consumption in eastern China, whereas the positive effect lacks statistical significance in the central and western regions. Notably, the positive effect of the digital economy on service consumption is statistically significant in both rural and urban areas, with the magnitude of the effect being greater in rural areas than in urban areas. Specifically, the digital economy exerts a positive and statistically significant impact on transportation, communication, and healthcare consumption; in contrast, its impact on education, culture, and entertainment consumption is positive yet statistically insignificant. In terms of policy implications, we propose strengthening regional coordination to narrow the digital economy gap, providing preferential allocation of special bonds to the central and western regions, and launching “AI + Education” initiative to develop personalized learning platforms.

In the context of China's goal of achieving carbon neutrality by 2060， an accurate assessment of the degree and spatial spillovers of provincial agricultural carbon neutrality has great significance for formulating effective mitigation strategies and promoting regional and national carbon emission management. This study precisely defined the systematic boundary of agricultural carbon emission and carbon sink and then constructed an agricultural carbon neutral evaluation model from the two dimensions of carbon source and carbon sink. The entropy weight TOPSIS method was adopted to evaluate the degree of agricultural carbon neutrality at the provincial level in China empirically and explore the spatial correlation characteristics. The results showed that the agricultural carbon neutrality is highest in the northeast， followed by the west， central， and east regions. The agricultural carbon neutrality exhibits clear and consistent spatial dependence， as well as local spatial agglomeration. Rural income， agricultural technology， financial investment， and industrial structure can significantly promote agricultural carbon neutrality. However， these factors have the potential to exert a negative spatial spillover effect. Consequently， it is imperative to employ a multitude of strategies in these regions to promote agricultural carbon neutrality.

BackgroundRapid urbanization in China has significantly reshaped the human settlement environment (HSE), bringing opportunities and challenges for public health. While existing studies have explored environmental-health relationships, most are confined to micro-level contexts, focus on single environmental dimensions, or assess specific diseases, thus lacking a comprehensive, macro-level understanding.ObjectiveThis study aims to assess the associations between population health level and multidimensional HSE features at the provincial level in China and uncover nonlinear relationships and interaction effects underlying the association between HSE and population health level.MethodsUsing panel data from 31 Chinese provinces spanning 2012 to 2022, a composite Health Level Index (HLI) was constructed based on four core health indicators using the Entropy-TOPSIS method. 19 HSE indicators covering five dimensions—ecological environment, living environment, infrastructure, public services, and sustainable environment—were selected as explanatory variables. The study employed the XGBoost machine learning algorithm to model the relationship between HSE and HLI. SHAP values and Partial Dependence Plots (PDPs) were used to interpret feature importance, nonlinear relationships, threshold values, and interaction effects.ResultsXGBoost outperformed all benchmark models, confirming its strong predictive capacity. SHAP analysis identified six key features—number of medical institution beds (NMIB), urbanization rate (UR), mobile phone penetration rate (MPPR), road area per capita (RAPC), population density (PD), and urban gas penetration rate (UGPR)—as the most influential factors. Nonlinear relationships and threshold effects were observed between key features and population health level. PDP plots further revealed that optimal health levels are typically associated with high UR, high MPPR, high RAPC, and moderate NMIB, underscoring the importance of structural synergy over isolated infrastructure expansion.ConclusionThis study provides robust evidence that the relationship between HSE and health is nonlinear, multidimensional, and highly interactive. Effective urban health governance requires coordinated development of urbanization, digital infrastructure, and public services, along with rational healthcare resource allocation. The findings offer actionable insights for health-oriented urban planning and policy formulation in rapidly urbanizing regions.

Agriculture is a major contributor to global greenhouse gas emissions. Consequently, studying the sustainable development of agricultural activities is crucial for achieving the United Nations’ Sustainable Development Goals. Utilizing panel data from 30 Chinese provinces from 2012 to 2022, this study measured the environmental, economic, and social dimensions of sustainable agricultural development (SAD) at the provincial level in China. Employing two-way fixed-effects and mediated effects models, the study empirically examined the driving effect of digital village construction (DVC) on SAD, along with the underlying mechanisms. The results reveal that the overall level of SAD in China has shown a gradual upward trend, although a pattern of higher SAD levels in the eastern regions compared to the west remains evident. DVC was found to exert a significant positive effect on SAD. Crucially, the market-based allocation of factors and agricultural product circulation were identified as significant mediating variables in this relationship. Heterogeneity analysis showed that the promoting effect of DVC is more significant in major grain-producing areas and in regions exhibiting higher SAD levels. Based on these findings, the study proposes targeted policy recommendations to provide practical strategies for different regions to advance DVC, narrow regional disparities, and enhance SAD levels.

The improvement of GTFP has become an important guarantee to change China’s development mode and achieve long-term stable economic growth, while the development of AI is of great significance to the development of GTFP. This paper adopts the SBM-GML method to calculate the GTFP of 30 regions in China from 2011 to 2020, and manually collects AI data to study the impact of AI on GTFP, and systematically analyze the relationship between AI and GTFP using a panel double-fixed model with a faceted threshold model. The experimental results show that: (1) There is a positive and significant effect of AI on GTFP, which increases GTFP productivity by 0.3654% for every 1% increase in AI, which still holds after a robust type test. (2) The development of AI in China’s eastern region has a greater promoting effect on GTFP. (3) Further mechanism analysis reveals that RIS and ER are two important channels through which AI influences the improvement of GTFP. (4) Threshold regression shows that AI has a single threshold effect on GTFP based on TI and LNPGDP. The promotion of GTFP by AI is higher when technological innovation is less than the threshold value of 29.95, and the promotion of GTFP by AI is insignificant when the level of economic development is less than the threshold value of 85.45. This paper deepens the knowledge and understanding of the role played in the development of AI at the macro level and provides suggestions for improving GTFP at the provincial level in China.

The new energy vehicle (NEV) industry has become one of the most important industries in China’s economic development. Based on the panel data of 27 provincial administrative regions in China from 2011 to 2022, combined with the random effect panel of the Tobit model and the Bootstrap method to test the multiple intermediary paths, this paper studies the impact of new energy vehicle promotion (NEVP) in China on regional green development, taking into account the intermediary effect and regional heterogeneity of NEVP on the green development level (GDL). The results show that NEVP significantly promotes the GDL. The mediating effect of NEVP to improve local-level green development through the digital economy level is significant in the eastern region, while in the central and western regions, it is not significant. NEVP can significantly promote the upgrading of regional industrial structure and the construction of transportation infrastructure in the eastern, central, and western regions so as to improve the local GDL.

As a core strategy in China’s modernization process during the new era, urban-rural integration development is imperative for expanding the development space of Chinese-style modernization and advancing high-quality growth. This paper uses the panel data of provincial levels in China from 2012 to 2023 to construct a three-level indicator system to measure the level of urban-rural integration and rural land utilization efficiency in China’s provinces, and explores the impact mechanism of China’s urban-rural integration on rural land utilization efficiency. Findings include: (1) Urban-rural integration significantly enhances rural land use efficiency; (2) Mechanism analysis demonstrates that urban-rural integration boosts land transfer rates and labor mobility between urban and rural areas, thereby improving land use efficiency; (3) Regional heterogeneity analysis reveals stronger promoting effects in eastern and western regions, with statistically insignificant impacts in central China. Policy recommendations are proposed, focusing on establishing market-driven resource allocation mechanisms, implementing region-specific policies, and improving collaborative governance of land transfer and labor mobility. This research provides empirical support for deepening the theory of urban-rural integration, optimizing the allocation of land resources, formulating differentiated policies, and resolving regional development imbalances.

The trend in pancreatic cancer incidence from 2009 to 2019 and the prediction from 2020 to 2030: An analysis of provincial data in China.

Carbon quota allocation and emission reduction responsibility sharing at provincial level in China from transport industry

Developing new-quality productivity in water conservancy (NQPWC) is vital for advancing economic and social development, with a focus on sustainability. An evaluation of NQPWC and the identification of key barriers can help define the challenges and guide the development of targeted solutions. This study established an evaluation indicators system for NQPWC through four dimensions (3H1G): High-technology, High-efficiency, High-quality, and Green. Utilizing a multi-attribute decision approach based on the Real-Code Accelerated Genetic Algorithm Projection Pursuit model (RAGA-PP model), an evaluation of NQPWC at the provincial level in China from 2011 to 2022 was conducted. The results revealed a curvilinear upward trend in NQPWC in most regions, with southeastern coastal provinces (cities) outperforming those in the northwest. Further, the major obstacles affecting NQPWC’s development were identified through an Obstacle Degree Model (ODM), with High-technology being the most significant dimension, followed by High-quality, Green, and High-efficiency.

The Economic Impact of Carbon Tax on the Provincial Level in China: Based on the Multi-Regional CGE Model of 31 Provinces

China has less than 10% of the world’s arable land but must feed more than 20% of the global population. Both climate change and farmland degradation pose significant challenges to China’s food security. In 2009, Chinese government launched a nationwide, well-facilitated farmland (WFF) construction strategy to improve food production. The ultimate goal is to create 80 million hectare (1.2 billion mu) of WFF by 2030. Timely monitoring and generation of a public WFF dataset are critical for assessing China’s food production and security. However, such data are not currently available for research community or industrial sector. By compiling and synthesizing 377 reports and documents released by local authorities, this study created WFF dataset for 2020, covering both prefecture and provincial levels in China. Additionally, the provincial 2030 WFF targets and the current completion rates are included. This dataset has wide range of applications in food security, as well as agricultural water and nutrition managements for researchers and policymakers.

In the wave of global digitalization, regional digital transformation has become the core force in promoting economic development and social change in various countries. Based on the grouping perspective, this study aims to explore the mechanism of institutions and markets linkages on regional digital transformation. Using the fuzzy-set qualitative comparative analysis (fsQCA) method, this study begins with the statistical data at the provincial level in China in 2023. In this model, regional digital transformation is the outcome variable, while institutions (fiscal expenditure intensity, intellectual property intensity, human resource allocation) and the markets (product market, capital market, labor market) serve as the antecedent variables. The research findings demonstrate that:(1) No single condition can determine regional digital transformation. (2) High intellectual property intensity is a core condition for achieving high regional digital transformation in all configurations. (3) There are five linkage pathways between institutions and markets, and different pathways are applicable to regions with different resource allocation and development conditions. The research results are reliable after the robustness test. This study's configuration model enhances theoretical insights into regional digital transformation mechanisms, offering practical guidance for government policy and strategic business adjustments.

Over the past three decades, China’s rapid economic development, social transformation, and the COVID-19 pandemic, have reshaped the landscape of mental disorders and self-harm burden. The raw data were sourced from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021. Our study presented the burden by disability-adjusted life-years (DALY) of mental disorders and self-harm at both national and provincial levels in China from 1990 to 2021, by age and sex. We also analysed the association between economic situation and disease burden by Pearson’s correlation. While the overall age-standardised DALY rates of mental disorders exhibited minimal change (-0.3%) over this period, that of self-harm declined dramatically (-69.8%). From 1990 to 2019, both depressive and anxiety disorders saw significant reductions, particularly among working-age adults. However, depression disorders increased significantly among the elderly. The pandemic reversed the gains in anxiety disorders burden, especially in young adults, but only transiently increased depressive disorders burden. With increasing economic development, eating disorders burden rose substantially (+70.4%). These findings underscore the necessity for tailored interventions targeting high-risk groups, including addressing depression among the elderly, anxiety in young adults following the pandemic, and eating disorders in economically prosperous regions.

Based on the panel data of 30 provinces in China from 2007 to 2017 and the theory of feasible ability, this paper uses the principal component method to measure the social welfare level at the provincial level in China, and observes its spatial distribution by Moran index and spatial panel. The paper analyzes the influence of financial decentralization, environmental decentralization, and local environmental protection fiscal expenditure on the social welfare level by using system GMM and differential GMM and through threshold model analysis the threshold effect of decentralization on the social welfare level by threshold model analysis. The results show that: The social welfare level in China presents the characteristics of spatial aggregation, and the imbalance still exists. Fiscal decentralization, environmental fiscal expenditure, and technological innovation have significantly improved the social welfare level, while environmental decentralization weakens the level of social welfare, and there is an inverse curve characteristic between environmental fiscal expenditure and foreign investment projects. Therefore, we need to optimize the structure of fiscal expenditure, improve the performance of fiscal expenditure, and improve the incentive mechanism of environmental fiscal expenditure. According to the concept of green development, the Pareto improvement of economic and non-economic welfare can be realized in different regions.

National and provincial burden of disease attributable to fine particulate matter air pollution in China, 1990-2021: an analysis of data from the Global Burden of Disease Study 2021.

Drivers of civil aviation emissions in China: Considering spatial heterogeneity and interdependence.

The relationship between environmental regulation and regional innovation has been disputed. This paper analyzes data at the provincial level in China between 2009 and 2020 using a fixed-effects model to investigate the relationship between environmental regulation and innovation. The baseline regression results suggest that market-based environmental regulatory instruments effectively promote regional innovation, while command-and-control environmental regulatory instruments hinder regional innovation. However, the impact of environmental regulation exhibits heterogeneity and non-linearity. The implementation of overly strict command-and-control environmental regulatory instruments hinders innovation, while the implementation of low-intensity command-and-control environmental regulatory instruments instead promotes innovation. In economically developed provinces, market-based environmental regulation promotes innovation, while in less economically developed provinces, market-based environmental regulation inhibits innovation instead. Further analysis from a pollution reduction perspective shows that environmental regulations that mitigate air pollution significantly promote regional innovation levels. This study not only enriches theoretical discourse but also offers practical policy recommendations for balancing environmental governance and innovation development in China.

Characteristics identification and mitigating potentials of provincial gaseous reactive nitrogen emissions from livestock and poultry breeding systems in China.

Depressive and anxiety disorders constitute a major component of the disease burden of mental disorders in China. To comprehensively evaluate the disease burden of depressive and anxiety disorders in China. The raw data is sourced from the Global Burden of Disease, Injuries, and Risk Factors Study (GBD) 2021. This study presented the disease burden by prevalence and disability-adjusted life years (DALYs) of depressive and anxiety disorders at both the national and provincial levels in China from 1990 to 2021, and by gender (referred to as 'sex' in the GBD 2021) and age. From 1990 to 2021, the number of depressive disorder cases (from 34.4 to 53.1 million) and anxiety disorders (from 40.5 to 53.1 million) increased by 54% (95% uncertainty intervals: 43.9, 65.3) and 31.2% (19.9, 43.8), respectively. The age-standardised prevalence rate of depressive disorders decreased by 6.4% (2.9, 10.4), from 3071.8 to 2875.7 per 100 000 persons, while the prevalence of anxiety disorders remained stable. COVID-19 had a significant adverse impact on both conditions. There was considerable variability in the disease burden across genders, age groups, provinces and temporal trends. DALYs showed similar patterns. The burden of depressive and anxiety disorders in China has been rising over the past three decades, with a larger increase during COVID-19. There is notable variability in disease burden across genders, age groups and provinces, which are important factors for the government and policymakers when developing intervention strategies. Additionally, the government and health authorities should consider the potential impact of public health emergencies on the burden of depressive and anxiety disorders in future efforts.