Search Results (750)

Regional economic inequality remains a persistent challenge in developing economies, particularly in peripheral regions characterized by fragmented geography and uneven development. This study examines spatial spillovers in regional economic inequality by integrating spatial econometric analysis with remote sensing-based indicators. Using district-level data from Eastern Indonesia, the analysis captures how inequality is shaped by spatial interdependence and localized development patterns rather than isolated regional characteristics. Regional economic inequality is measured using a district-level relative Williamson-type index, allowing inequality to vary across space within provincial contexts. To account for spatial dependence, the study employs a spatial econometric framework and evaluates alternative model specifications. In addition to conventional economic indicators, the analysis incorporates satellite-derived measures of economic activity, urbanization, and energy potential to capture spatially observable dimensions of regional development. The results reveal pronounced spatial clustering of regional economic inequality, indicating that disparities are structured by localized spatial interactions. Economic development and spatially distributed urbanization are closely associated with inequality patterns, while the dispersion of economic activity appears to be linked to more balanced regional outcomes. In contrast, natural resource potential alone does not systematically explain spatial inequality, highlighting the importance of complementary institutional and spatial factors. This study contributes to the regional economics literature by demonstrating the value of integrating remote sensing-based indicators into spatial inequality analysis. The findings underscore the need for spatially explicit, place-based development strategies to address persistent regional disparities in peripheral regions of developing economies. Full article

With the continuous advancement of industrialization in China, industrial wastewater discharge has become a critical factor influencing water environmental quality, public health, and the long-term sustainability of regional development. This study systematically examines both the direct and spatial spillover effects of industrial wastewater on disease incidence. Based on panel data from 30 provincial-level regions in China over the period 2011–2020, a composite incidence index of four waterborne infectious diseases is constructed using the entropy weight method, and the Spatial Durbin Model (SDM) is employed to capture both local and cross-regional effects. The results show that industrial wastewater discharge significantly increases disease incidence and exhibits clear spatial spillover effects, suggesting that the associated health risks may extend beyond local boundaries. Moreover, the analysis suggests that the “Water Ten Plan” reduced both local effects and regional spillovers, highlighting the value of stricter discharge control and coordinated basin-level governance for sustainable regional development. Overall, this study uncovers the spatial health externalities of industrial pollution and provides empirical support for integrated policy approaches linking environmental governance with public health protection. Full article

In the context of increasingly frequent and severe natural disasters, scientifically measuring and analyzing the efficiency of natural disaster emergency management in China is of great practical significance for enhancing the performance of the emergency management system and promoting its systematic and high-quality development. This study first applies a super-efficiency SBM-DEA model with undesirable outputs to systematically measure the efficiency of China’s natural disaster emergency management system during the period 2019–2023. Subsequently, the Dagum Gini coefficient and Kernel Density estimation are employed to examine regional disparities and dynamic evolution across eastern, central, western, and northeastern China. Finally, the coefficient of variation and spatial econometric models are applied to test the spatial convergence characteristics of emergency management efficiency. The results indicate that: (1) China’s overall disaster emergency management efficiency remains at a relatively low level and exhibits a fluctuating trend characterized by an initial increase followed by a decline. The regional distribution pattern of emergency efficiency is ranked as “Northeast > Central > West > East”. (2) The average annual contributions of intra-regional disparities, inter-regional disparities, and transvariation density to the overall variation in national emergency management efficiency are 27.58%, 39.90%, and 32.53%, respectively, indicating that inter-regional disparities and transvariation density are the dominant sources of systemic differences among regional subsystems. (3) The national distribution of emergency management efficiency displays a bimodal pattern, indicating polarization; however, the secondary peak is relatively flat, suggesting a weakening trend of provincial-level polarization and a gradual narrowing gap with high-efficiency regions. (4) σ-divergence is observed at the national level and in the central region, while both absolute and conditional β-convergence exist to varying degrees at the national level and across all four regions. Nevertheless, the enhancement of natural disaster emergency management efficiency has not yet realized a system-level transition from convergence in growth rates to convergence in efficiency gaps. In addition, economic development, technological progress, urbanization, and industrial structure exert significantly heterogeneous effects on disaster emergency management efficiency across different regions. Full article

Although digital economic development is often viewed as a catalyst for green transformation, the causal implications of policy-driven AI deployment for low-carbon logistics development remain unclear. To address this gap, this study leverages China’s National New Generation Artificial Intelligence Innovation Development Pilot Zones (AIIDPZs) as a quasi-natural experiment. Using panel data from 30 provincial regions from 2012 to 2022, this research employs a double machine learning framework to rigorously quantify the AIIDPZ policy’s causal effects on the logistics industry’s green total factor productivity (GTFP). We further examine underlying transmission mechanisms and spatial spillover effects. Results show that the AIIDPZ policy significantly enhances logistics GTFP, a finding robust to parallel trend tests, sample adjustments, and algorithm substitutions. Mechanism analysis reveals that the AIIDPZ policy promotes logistics GTFP by alleviating manufacturing agglomeration and collaborative agglomeration. This occurs mainly through the mitigation of environmental externalities and the easing of inter-sectoral resource competition. Heterogeneity analysis highlights substantial regional variation: the policy impact is strongest in East China, Central China, and Southwest China; positive but weaker in Northeast and Northwest China; and statistically insignificant in North and South China. Spatial econometric results confirm significant positive spillovers to neighboring regions. Temporally, the logistics industry’s GTFP shows a sustained upward trajectory, while spatially it follows a spatial pattern of “Eastern leadership, Central rise, and Western catch-up.” Robust empirical evidence is presented to evaluate the environmental outcomes of AI policy implementation, alongside policy-relevant insights for advancing coordinated and spatially differentiated regional development. Full article

The coordinated improvement of urban–rural integrated development (URID) and eco-environmental quality (EEQ) is a core strategic objective for pursuing sustainable development. However, existing studies have predominantly relied on qualitative discussions or single-region analyses, with insufficient empirical attention to multi-pathway mechanisms and spatial spillover effects. This study aims to examine the direct and heterogeneous effects of URID on EEQ, identify the dual mediating pathways, and quantify the spatial spillover effects across regions. Using panel data from 284 prefecture-level cities in China (2011–2023), this study employs panel regression, mediation analysis, and spatial econometric methods to investigate how URID affects EEQ. The results indicate that URID significantly promotes EEQ, with resource allocation efficiency and environmental regulation intensity serving as dual mediating pathways. This promoting effect varies across regions and policy stages. Moreover, URID exerts positive spatial spillover effects on neighboring regions. By providing national-scale evidence on mediating mechanisms and spatial externalities, this study extends prior research and offers implications for policy-making aimed at advancing the Sustainable Development Goals. The findings should be interpreted in light of the macro-level indicators employed and the observational research design. Full article

Amid the accelerating global pursuit of carbon neutrality, the regulatory role of forest ecological security in carbon sink function has emerged as a critical issue in achieving climate goals. This study developed a forest ecological security evaluation index system based on the Driving Force–Pressure–State–Impact–Response–Management (DPSIRM) framework. The forest ecological security comprehensive index for 31 Chinese provinces from 2007 to 2022 was calculated using the entropy weight method, and forest carbon sinks were estimated through the volume expansion method. Spatial econometric models and a mediation effect model were employed to empirically examine the impact of forest ecological security on forest carbon sinks and their underlying mechanisms. The results indicated the following: (1) Improvements in forest ecological security exerted significant positive direct and spatial spillover effects on forest carbon sinks. (2) The enhancing effect of forest ecological security on carbon sinks was significant in western regions, resource-based provinces, and economically underdeveloped areas. (3) Forest area transition and forest age structure transition served as key mediators in the relationship between forest ecological security and carbon sinks. In contrast, the mediating effects of forest species structure transition and forest origin structure transition were not significant, likely constrained by long-term ecological thresholds and socioeconomic inertia. Full article

In the spirit of the recent debate on the 15-minute city, two concepts are central: urban proximity and resilience. They became cornerstones of new urban planning perspectives on sustainability, livability, and inclusiveness in cities and metropolitan areas. Very recently, the notion of ‘proxilience’ has been introduced as an integration of urban planning views on the drivers of citizens’ wellbeing. The present study seeks to conceptualize and operationalize the proxilience concept for the case of metropolitan agglomerations, in which the core is termed here ‘Superbowl Economy’. Consequently, the paper presents a data-driven analytical approach that uses detailed empirical data on spatial density patterns, demographic factors, socioeconomic indicators, environmental quality attributes, infrastructure accessibility, and access to services and amenities. The empirical part of the study is based on a blend of geostatistical and econometric models (correlation and regression analysis, AHP modelling, and Random Forest model). The analysis framework and the underlying propositions on the proxilience impacts on spatial patterns of disparities in wellbeing are applied and tested for the greater Iași Metropolitan Area, which is one of the largest urban poles in Romania. The findings confirm proxilience as a novel, multidimensional tool that advances spatial (urban–regional) livability in a polarized yet fragmented urban system. Full article

Against the backdrop of coordinated advancement in new urbanization and rural revitalization strategies, the integration of urban and rural areas serves as a core approach to dismantling the urban–rural dichotomy and driving high-quality regional development. The enabling effects of its policy implementation on regional sustainable development have garnered significant attention. As pivotal conduits where urban and rural elements converge, peri-urban fringe zones have emerged as the primary arena for policy implementation and impact realization. Using panel data from 268 prefecture-level and above cities in China from 2015 to 2024 as the sample, this study treats the establishment of urban–rural integration pilot zones as a quasi-natural experiment. Employing a multi-period Difference-in-Differences model, instrumental variables method, and spatial econometric model, it systematically investigates the impact effects, operational mechanisms, heterogeneous characteristics, and spatial spillover effects of urban–rural integration policies on regional sustainable development. Findings reveal that urban–rural integration policies significantly promote regional sustainable development. This conclusion remains robust after endogeneity treatment and stability tests, with policies demonstrating stronger enabling effects on ecological sustainability than on economic and social sustainability, forming a development pattern characterized by “ecological priority and multidimensional coordination”. Policies achieve synergistic enhancement of regional economic, ecological, and social sustainability through three pathways: optimizing urban–rural factor allocation, establishing ecological co-governance systems, and advancing equitable public services. Policy effects exhibit significant heterogeneity: the stronger the urban baseline conditions, the more pronounced the policy’s enabling effect, while excessive population concentration exerts a marginal negative impact on ecological sustainability. Urban–rural integration policies generate a significant positive spatial spillover effect, accounting for 38.9% of the total effect. This spillover gradually diminishes with increasing distance within a 120 km radius, with geographic distance and administrative barriers serving as core constraints. This study provides empirical insights and practical pathways for optimizing urban–rural integration policy design and advancing regional sustainable development. Full article

Understanding the spatial mismatch between population distribution and economic activities is central to regional development, particularly in large river basins experiencing rapid demographic change. Existing studies often rely on slow-moving structural variables and give limited attention to dynamic population processes. This study examines the spatiotemporal patterns, demographic mechanisms, and regional heterogeneity of population–economy mismatch in the Yellow River Basin from 2000 to 2020. We hypothesize that population–economy mismatch exhibits pronounced spatial heterogeneity across the upper, middle, and lower reaches of the basin, and that demographic structure and migration dynamics play a decisive role in shaping these patterns. Using county-level data, we construct a Population–Economy Distribution Disparity Ratio R, apply decomposable Theil indices, and estimate two-way fixed-effects panel models incorporating demographic and migration indicators. Spatial econometric models are further employed as robustness checks. The results show that intra-regional disparities account for more than 97% of total population–economy mismatch, while inter-regional differences remain limited. Population migration intensity and age structure significantly influence mismatch dynamics, with effects varying systematically along the basin gradient. These findings underscore the importance of integrating dynamic demographic processes into spatial mismatch analysis and support regionally differentiated and systemically coordinated policy interventions for high-quality development in the Yellow River Basin. 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

As the global urban economy accelerates its transition from an “industrial economy” to a “service economy”, consumption has replaced investment as the core engine driving economic development. Commercial land serves as the physical foundation for consumer activities and plays a vital role in boosting urban economic vitality, enhancing residents’ quality of life, and promoting regional sustainable development when appropriately allocated. This study constructs a technical framework for analyzing the mismatch between commercial land supply and residential consumption demand, along with its impact mechanism, based on the integrated application of the multidisciplinary quantitative models such as the Boston Consulting Group Matrix (BCGM), Exploratory Spatial Data Analysis (ESDA), Decoupling Model (DM), and Explainable Machine Learning (EML). It conducts empirical research across 87 county-level cities in Gansu Province. The findings reveal that commercial land supply and consumption demand exhibit dynamic diversification, with prominent regional disparities and spatial autocorrelation characteristics. Commercial land in Gansu faces a severe mismatch, with demand exceeding supply and supply exceeding demand occurring simultaneously, and the former holding absolute dominance. The formation of mismatched relationships is influenced by many factors, exhibiting significant path nonlinearity, spatial non-stationarity, and relational interactivity. It is suggested that strategies of planning zoning and regional coordination be developed for mismatch governance, and differentiated management measures be implemented based on local conditions. This will provide a scientific basis for commercial territorial space planning and consumption policy design. Full article

Cassava mosaic disease (CMD) is a major constraint to cassava production in sub-Saharan Africa, particularly in Burkina Faso, where it poses a serious threat to rural food security. This study examined the impact of adopting innovative cassava mosaic disease management practices on cassava yields in the Guiriko and Nando regions of Burkina Faso. To address potential biases arising from differences in characteristics between adopters and non-adopters, an econometric approach based on the instrumental variables (IV) method within a counterfactual framework was employed to estimate the local average treatment effect (LATE). The data were drawn from a survey conducted in September 2023 among 511 cassava producers. The results indicate that the adoption of innovative cassava mosaic disease management practices had a positive and statistically significant effect on agricultural yields. Productivity gains were estimated at 29% in the Guiriko region and 41% in the Nando region, highlighting spatial heterogeneity in impacts. These findings suggest that promoting the diffusion of such practices can substantially improve cassava productivity and reduce the vulnerability of rural households. In addition, the analysis showed that socioeconomic and technical factors, including farmers’ age, membership in cassava producer organizations, household income levels, and the use of chemical fertilizers, also influence productivity outcomes. Overall, the study underscores the importance of strengthening agricultural extension services, supporting producer organizations, and promoting appropriate technologies to maximize the benefits of cassava mosaic disease management practices for food security and rural development. 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

This paper employs a top-down methodological approach to identify the most relevant contributions in the literature on the impact of European Cohesion Policy and European Structural and Investment Funds (ESIFs) on regional development. After a broad-spectrum bibliometric review, identifying the overall structure of research in this field, we systematically narrow its focus to quantitative studies and, ultimately, to econometric analyses of ESIF effectiveness. The results indicate that empirical research on ESIFs has grown in complexity, with increasing reliance on advanced econometric techniques such as spatial econometrics, difference-in-differences, and regression discontinuity designs. While a large portion of the literature finds positive effects on economic growth, employment, and regional convergence, these effects are frequently conditional on governance quality, institutional frameworks, and regional characteristics. In contrast, some studies report insignificant or even negative impacts, highlighting inefficiencies in fund allocation and policy implementation. The findings emphasize the necessity for context-specific policy adaptations, ensuring that ESIFs continue to support the evolving needs of regional economies in the European Union. Full article