Search Results (1,396)

Breaking through the constraints of traditional agricultural resources and expanding food supply channels have become essential for safeguarding food security. The non-timber forest-based economy (NTFE), which integrates multiple understory production activities including planting, breeding, and foraging, expands the variety of food sources and provides a new pathway for enhancing regional diversified food supply capacity (DFSC). Based on this perspective, this study constructs evaluation indicator systems for both DFSC and NTFE development. The entropy-weighted TOPSIS method is employed to measure the levels of DFSC and NTFE development across 31 Chinese provinces from 2011 to 2022. A two-way fixed effects model and a spatial Durbin model are applied to empirically investigate the mechanisms through which the NTFE enhances DFSC. The results show the following: (1) Between 2011 and 2022, both the DFSC and the level of NTFE development in China exhibited a sustained upward trend. Specifically, the level of NTFE development grew rapidly before 2019, with a slowdown in growth in the later years, while DFSC maintained a steady increase throughout the study period. (2) NTFE development significantly promotes DFSC. (3) The NTFE enhances DFSC by facilitating the upgrading of the forestry industrial structure and improving forestland productivity. (4) The NTFE generates positive spatial spillover effects on DFSC, and these spillover effects are stronger than direct local effects. Full article

In the context of China’s pursuit of high-quality economic development, enhancing agricultural productivity is crucial for ensuring food security and promoting common prosperity. This paper constructs a systematic IV-LP-ACF-SAR econometric framework to analyze agricultural Total Factor Productivity (TFP) growth using panel data from 31 Chinese provinces spanning 2014 to 2023 (n = 341 observations). The framework employs the instrumental variable (IV)-based Levinsohn–Petrin (LP) proxy variable method under the Ackerberg–Caves–Frazer (ACF) system to estimate a Translog production function while addressing endogeneity using multiple spatial weight matrices. TFP growth is decomposed into technical change (TC), technical efficiency (EC), and scale efficiency (SC). A Spatial Autoregressive (SAR) model with Dynamic Common Correlated Effects (DCCE) explores spatial spillover effects and regional heterogeneity. Results show that China’s agricultural TFP remained largely stagnant from 2014 to 2023 with an average annual growth rate of −0.18%, where technical efficiency decline (−0.33% annually) was the main constraint. Technical change remained neutral, while scale efficiency contributed positively (+0.15% annually). Mechanization showed the highest output elasticity (0.99), while fertilizers, pesticides, and labor exhibited negative marginal returns. Spatial analysis revealed significant negative scale efficiency spillovers with regional patterns of “scale synergy in the Northeast/Northwest” and “efficiency synergy in East/North China.” These findings suggest that productivity policy should shift toward a dual-driver model combining efficiency enhancement and optimal scaling, with differentiated regional policies and inter-provincial coordination mechanisms necessary to mitigate negative spillovers and enhance sustainable agricultural growth quality. Full article

Assessing urban resilience under compound shocks requires observable and comparable process evidence that can inform resilient land governance and cross-jurisdiction planning. Using China’s Pilot Free Trade Zones (PFTZs) as a staged institutional setting, this research examines whether institutional exposure is associated with deviation–recovery trajectories of urban activity during the 2020 COVID-19 shock and whether these associations propagate through spatial spillovers with an identifiable scale profile. Institutional exposure is operationalized by the prefecture-level cities actually covered by PFTZ functional areas. With harmonized administrative boundaries, we construct an annual city-level VIIRS nighttime light (NTL) series for 2013–2024 and treat NTL as an activity-change signal rather than a direct proxy for output. We trace shock deviation in 2020 and subsequent recovery via staged differencing. Spatial interaction frictions are represented by least-cost path distance (LCPD) derived from a multi-source cost surface, which is used to build a gravity-based spatial weight matrix. Estimation relies on the Spatial Durbin Model (SDM), with LeSage–Pace impact decomposition to distinguish direct and spillover effects, complemented by distance-threshold diagnostics to map attenuation patterns. Results indicate persistent clustering within the PFTZ-related urban system. The shock year is characterized by compressed connectivity and fragmented brightening, whereas recovery proceeds in a layered manner with earlier core repair, partial corridor reconnection, and weaker adjustment at the periphery. Spatial dependence in activity change is statistically significant. Associations linked to institutional exposure are realized primarily locally, while structural and scale conditions more readily operate through spatial externalities. Spillovers are most detectable at meso-scales and attenuate gradually across distance thresholds. Overall, the integrated earth-observation and spatial-econometric framework provides replicable geospatial evidence to support resilient land governance and regional coordination under common shocks. Full article

Against the backdrop of global economic volatility, environmental pressures, and intensifying industry competition, tourism resilience has become a critical indicator for assessing the capacity of tourism systems to withstand external shocks and achieve sustainable development. As an important engine of high-quality economic growth, the digital economy provides new momentum for strengthening tourism economic resilience. Existing literature predominantly focuses on the direct impacts of the digital economy, with insufficient exploration of its mediating pathways and spatial effects. Based on panel data from 11 provinces in China’s Yangtze River Basin from 2011 to 2023, this study constructs comprehensive evaluation index systems for the digital economy and tourism economic resilience. A mediating effect model and a Spatial Durbin Model are employed to systematically examines the impact mechanisms and spatial spillover effects of the digital economy on tourism resilience. The results show that the digital economy significantly enhances tourism economic resilience, primarily by fostering openness and technological innovation. Heterogeneity analysis indicates that this effect is more pronounced in provinces located in the upper and lower reaches of the Yangtze River Basin. Spatial analysis further reveals a significant positive local effect, accompanied by a negative spillover—or ‘siphon’—effect on neighboring provinces. Building upon the verification of the fundamental relationship, this study further extends the theoretical analytical framework of tourism resilience from the dimensions of mechanism decomposition and spatial effects. It thereby offers new empirical evidence and policy insights for fostering regional tourism resilience in the era of the digital economy. Full article

Although numerous studies have examined the impact of high-speed rail (HSR) on regional economic development, few have explored this relationship from a network perspective—a research gap this paper seeks to fill. Specifically, this paper aims to clarify the theoretical mechanism through which the HSR network affects the spatial evolution of regional industries, focusing on the new industry entry. We improve the local spread model by incorporating the HSR network as a key component and perform empirical analyses using the Spatial Durbin Model (SDM) and spatial mediation effect model, drawing on data from Chinese A-share-listed companies. The findings indicate that China’s regional industries underwent spatial evolution characterized by “diffusive agglomeration”. In terms of direct effects, connectivity ranks as the most influential HSR network indicator; however, when both direct and spillover effects are taken into account, accessibility becomes the primary factor, underscoring its vital role in reshaping the spatial distribution of industries. Additionally, the HSR network exerts a slightly stronger impact on industrial spatial diffusion (fueled by knowledge spillovers) than on industrial agglomeration (driven by market size), and its attraction to new industry entry is notably greater in peripheral regions than in core regions. These results demonstrate that HSR, characterized by “transporting people rather than goods”, mainly facilitates the exchange of knowledge, technology and information instead of reducing freight costs, offering valuable insights for optimizing regional industrial layouts. Full article

Total factor productivity (TFP) serves as the primary driver of high-quality development and a key determinant for the sustainable growth of Japan’s beef cattle industry. This study analyzes panel data from nine agricultural regions in Japan, covering the period from 2004 to 2022, and applies the Malmquist-Luenberger index model to measure and decompose TFP in the sector. It utilizes various methods, including the Dagum Gini coefficient, kernel density estimation, and Markov chains, to examine regional disparities and dynamic changes. Additionally, the study applies the geographic detector and spatial Durbin model to explore the spatiotemporal evolution and influencing factors. The results show that: (1) From 2004 to 2022, TFP in Japan’s beef cattle industry steadily declined, accompanied by growing regional imbalances. The Tokai region was the only area to experience positive TFP growth, while other regions generally saw declines. (2) The spatial disparity in TFP growth has increased, with an intensified imbalance and a widening gap between regions. TFP distribution is becoming more “multipolar,” with considerable dynamic mobility. (3) TFP exhibits a general positive spatial correlation. Geographic detector analysis reveals that factors such as the number of agricultural research and development personnel, fiscal support, industrial agglomeration, feed production capacity, and labor productivity are the key drivers behind spatial TFP differentiation, reflecting a complex interplay of multidimensional factors. (4) Industrial agglomeration, fiscal support, and the number of agricultural R&D personnel exhibit significant spatial positive spillover effects, indicating that coordinated regional progress is essential for fostering the sustainable and healthy development of the beef cattle industry. This study provides theoretical and empirical support for the sustainable development of Japan’s beef cattle industry and offers policy recommendations to enhance the economic growth quality of the beef cattle industries in both Japan and China. Full article

National big data comprehensive pilot zones (BDCPZs) are key platforms for piloting and implementing big data policy. Additionally, the exploration of their impact on carbon unlocking efficiency and its mechanisms holds significant value. Here, using panel data of 281 prefecture-level cities from 2007 to 2023, we developed a staggered difference-in-differences (DID) model for the systematic investigation of the effects of big data policy on carbon unlocking efficiency and its mechanisms. Our findings demonstrate that BDCPZs significantly enhance carbon unlocking efficiency via four pathways: (1) the rationalization of industrial structure; (2) the optimization of energy structure; (3) the improvement of digital technological innovation; and (4) the application of artificial intelligence technology. On the other hand, heterogeneity testing revealed that the positive effect of the establishment of BDCPZs on carbon unlocking efficiency is more pronounced in cross-regional pilot zones and non-industrial tax-dominated areas. Finally, we also found that the establishment of BDCPZs has significant spatial spillover effects on the carbon unlocking efficiency of surrounding cities. It will be necessary to further strengthen the systematic planning of BDCPZs to enhance carbon unlocking efficiency. Full article

Investigating the relationship between digital innovation and carbon productivity, along with its underlying mechanisms, is important for advancing regional low-carbon, sustainable development. In this study, panel data spanning 2012 to 2022 from 30 provincial-level regions in China are analyzed utilizing mediation analysis and spatial Durbin models to systematically examine the transmission pathways, heterogeneous characteristics, and impact of digital innovation on carbon productivity. The findings reveal the following: (1) Digital innovation significantly enhances carbon productivity, exhibiting robust spatial spillover effects. (2) Spatial mediation analysis reveals that digital innovation enhances carbon productivity through three pathways—industrial structure upgrading, energy consumption efficiency, and technological progress—each exhibiting both local transmission and cross-regional spillover characteristics. (3) Regional heterogeneity analysis indicates that digital innovation exerts more substantial cross-regional spillover effects on carbon productivity in central and western regions than in eastern regions. Temporal heterogeneity analysis indicates that the effect of digital innovation on enhancing carbon productivity increased significantly after 2018. This study reveals the intrinsic logic and constraints governing digital innovation’s impact on carbon productivity, providing policymakers with a reference for formulating strategies to coordinate the development of digital and green economies. Full article

Neighborhood variations in depression, an important aspect of the overall mental health burden, have been linked both to environmental context (e.g., area crime, neighborhood cohesion), and to area socio-demographic composition. Previous models seeking to explain such spatial variations in mental health, such as those based on Bayesian disease mapping, follow a standard approach defined by: spatially stationary effects of area predictors; predictor effects neglecting potential spatial spillover; and a spatially structured residual to account for unmodelled spatial dependencies. In a study of depression incidence in England neighborhoods, we consider the gains from an alternative strategy, allowing nonstationary environmental impacts; spillover effects of environmental factors, and a non-stationary spatial intensity. We focus particularly on impacts of socio-behavioral environments, namely neighborhood cohesion and crime. We find these to be major influences on neighborhood depression incidence, and also find major gains in model performance by explicitly considering non-stationarity and spillovers. Allowing context heterogeneity, varying spatial intensity and spillover are shown to enhance the impacts of socio-behavioral environments on depression incidence, and such findings have broader relevance to disease mapping regression. Public health policy framing may therefore need to be tailored to locally specific environmental impacts, and to inter-agency collaboration across arbitrary boundaries. Full article

Given the increasing uncertainty in the global economy, enhancing urban economic resilience is now paramount to advancing coordinated regional development. As a key force reshaping factor allocation and economic structures, the digital economy’s role in empowering urban economic resilience holds significant theoretical and practical value, especially for closely linked riverine urban agglomeration. Using 2010–2022 panel data of 41 Yangtze River Delta cities, this paper constructs a multidimensional economic resilience evaluation system. Employing two-way fixed effects, instrumental variables, and Spatial Durbin Model, it systematically examines the impact mechanism, heterogeneity, and spatial spillover of the digital economy on urban economic resilience. The findings indicate the following: (1) The digital economy significantly enhances urban economic resilience. (2) Its empowering effect exhibits notable regional disparities, with metropolitan areas and core cities benefiting more substantially. (3) The digital economy strengthens surrounding cities through spatial spillovers, yet some peripheral cities remain trapped in “low–low” agglomeration. This paper offers important insights for global riverine urban agglomerations: promoting the digital economy should prioritize cross-regional governance, enhancing core cities’ leading role, and boosting targeted investment in digital infrastructure and innovation in peripheral areas. This approach is essential for narrowing regional differences and improving overall resilience and sustainability. Full article

This paper proposes a Bayesian estimation method for spatial lagged panel quantile models. The proposed model simultaneously considers spatial lag effects of the dependent variable and the quantile regression framework, enabling effective capture of spatial dependence and conditional distribution heterogeneity. The research constructs a Bayesian estimation framework based on the asymmetric Laplace distribution by decomposing the random disturbance term into a combination of normal and exponential distributions, successfully developing a probabilistic model with both thick tail robustness and computational efficiency. On this basis, the study derives the full conditional posterior probability distributions of model parameters and designs a hybrid Markov Chain Monte Carlo (MCMC) sampling algorithm integrating Gibbs sampling and Metropolis–Hastings algorithm for parameter estimation. Numerical simulation experiments demonstrate that, compared with traditional estimation methods, the proposed Bayesian estimation approach exhibits superior estimation accuracy and robustness across different quantiles, with particularly pronounced advantages in small sample and heavy-tailed distribution scenarios. This methodology provides a more reliable theoretical tool for analyzing panel data with spatial dependencies. This method can not only accurately quantify the spatial spillover effect, but also identify the different effects of the same influencing factor at different emission levels, which provides a strong methodological support for formulating differentiated and precise emission reduction policies. Full article

Agricultural development is vital to rural economies in developing countries. Rural e-commerce has emerged as an important instrument for promoting rural economic transformation, yet its impact on agricultural development remains underexplored. Using panel data for 1345 counties in China from 2010 to 2022, this study exploits a quasi-natural experiment created by the phased implementation of the Rural E-Commerce Demonstration County (REDC) program and applies a staggered difference-in-differences approach to identify its causal effects on agricultural development. The results show that the REDC program significantly promotes agricultural development, mainly through expanded consumer demand and greater social investment. Its effects are particularly evident in regions with balanced production and consumption and in economically developed counties. Moreover, the REDC program shows no evidence of a significant negative siphon effect within 50 km of pilot counties but generates strong positive spillovers in the 50–200 km surrounding range. Taken together, these findings provide empirical evidence supporting the advancement of rural e-commerce and agricultural scaling in China, while also offering policy implications for other developing countries seeking to promote rural e-commerce. Full article

This study draws on panel data from 31 Chinese provinces spanning 2012–2023 to develop a comprehensive indicator system capturing both the digital economy and agricultural product supply chain resilience. Anchored in the perspective of sustainable agricultural development, the analysis examines how the digital economy contributes to enhancing the resilience and long-term stability of agricultural product supply chains amid rising external uncertainties. The results show that the digital economy significantly improves supply chain resilience not only within a province but also across neighboring regions, indicating a clear digital empowerment effect with pronounced spatial spillovers. Further heterogeneity analysis reveals marked regional and urban–rural disparities: the estimated effects are substantially stronger in eastern China than in the central and western regions, and cities located within urban agglomerations experience more pronounced resilience gains than those outside such clusters. In addition, threshold analyses indicate that agricultural technological progress and industrial structure upgrading act as positive moderating factors, implying a nonlinear and stage-dependent relationship between the digital economy and agricultural product supply chain resilience. Overall, these findings underscore the role of digital development in fostering resilient and sustainable agricultural supply chains and provide insights relevant to coordinated regional development under the broader agenda of high-quality agricultural transformation. Full article

The present research examines the spatial dynamics and impact of Short-Term Rentals (STRs) in highly touristic and spatially constrained insular territories, using the island of Santorini (Thira), Greece, as a case study. Unlike large metropolitan areas, where tourism pressure can diffuse across space, islands present limited land availability and infrastructure capacity, thereby intensifying the potential externalities of uncontrolled STR expansion. The study examines how STRs are spatially distributed, their interactions with formal accommodation facilities, and the extent to which they have penetrated residential, rural, and other legally protected areas. The analysis integrates Airbnb listings with land use, regulatory, environmental, and other datasets, applying specific metrics, including the Average Nearest Neighbor Index, Kernel Density Estimation, Standard Deviation Ellipses, Global Bivariate Moran’s I, and Local Collocation Quotient. The results reveal increased spatial clustering in high-amenity areas, a high degree of professionalization, and increased presence of STRs outside formal settlements. STRs exhibit colocation with formal accommodation in high-tourism zones, as well as a spillover effect in areas where hotel activity is prohibited. This underscores the need for an island-specific spatial analysis to support integrated planning and regulatory approaches that address STR-related impacts on tourism-dependent islands. Full article

The conflict between the economy and the ecological environment is prominent in China’s coastal cities, and these cities contend with heightened uncertainty. Therefore, this study uses the econometric model to analyze the spatial–temporal pattern characteristics and affecting factors of the coupling coordination level between urban economic resilience (ER) and urban ecological resilience (EcR) in China’s coastal cities based on improvement of the evaluation index system, thus advancing policy suggestions. The main conclusions are as follows: (1) The coupling coordination degree (CCD) between ER and EcR across different types of coastal cities strongly correlates with their spatial distribution patterns of economic development. From the East China Sea to the South China Sea and Yellow and Bohai Sea Coast cities and from central cities to industrial cities, other types of cities, and resource-based cities, CCD exhibits an overall declining trajectory. (2) The gap in CCD in China’s coastal cities generally shows an expanding trend. (3) The spatial distribution pattern of the centrality of CCD in China’s coastal cities has a relatively high consistency. Urban spillover roles are highly consistent with levels of economic development. (4) The number and diversity of dominant influencing factors have steadily increased. Full article