Search Results (41)

To promote global sustainable development, this paper focuses on the identification of relative poverty. On the one hand, based on the sustainable livelihoods framework, a multi-dimensional relative poverty identification index system is constructed, covering six dimensions—human capital, financial capital, natural capital, physical capital, social capital, and livelihood environment—with a total of 18 indexes. On the other hand, addressing the limitations of traditional relative poverty identification methods in handling dynamic three-dimensional data, the multiway Mahalanobis–Taguchi system (MMTS) is proposed to identify dynamic relative poverty. This method first unfolds dynamic three-dimensional data into two-dimensional data along the sample direction through multiway statistical analysis techniques, then constructs multiway Mahalanobis distances to measure sample differences, and finally uses a Taguchi orthogonal experimental design for dimensionality reduction and noise reduction to optimize the model. Experiments using tracking survey data from 2020 to 2024 in three poverty-stricken counties in China’s Dabie Mountain area show that MMTS performs better than the Two-Way Fixed Effects (Two-way FE) model and Dynamic LSTM. MMTS shows a higher specificity, stronger noise resistance, smaller result fluctuations, better G-means performance, and a better balance between sensitivity and specificity. This proves its scientific validity and practical applicability. Full article

Common prosperity is the fundamental driving force of rural revitalization, as well as the foundation for achieving sustainable economic development. The e-commerce to the countryside policy has energized the rural economy, helping to improve household economic resilience and reduce income stratification, thereby promoting the inclusive and sustainable development of the digital economy. Drawing on panel data collected from rural fixed observation points in Henan Province during 2009–2022, this study employs a staggered difference-in-differences (DID) approach to evaluate the impact of China’s e-commerce to the countryside policy on farmers’ income and income inequality. The empirical results reveal that the rural e-commerce policy significantly increases farmers’ income while mitigating income inequality. The underlying mechanisms function through three synergistic pathways: industrial structural upgrading, manifested through tri-sector integration driven by rural enterprise development; factor allocation restructuring, evidenced by productivity gains from optimized labor–capital reallocation; and enhanced market inclusion through digital technology empowerment that lowers participation barriers. Heterogeneity analysis indicates that the e-commerce to the countryside policy exhibits pro-poor characteristics, with its income-enhancing and equalizing effects being particularly pronounced in agricultural areas, traditional villages, county-level civilized villages, underdeveloped regions, registered poverty-stricken villages, and households with low human, physical, and financial capital endowments. These findings confirm the inclusive development efficacy of rural e-commerce among vulnerable populations. Consequently, the study provides a replicable policy implementation framework for achieving common prosperity objectives. Full article

The coordination between poverty alleviation and ecological protection is both a crucial requirement and a long-standing challenge for sustainable development. China’s implementation of a targeted poverty alleviation strategy has completed the task of eliminating extreme poverty. However, the evaluation of the corresponding ecosystem changes in the entire poverty-alleviated areas is still insufficient. This study investigated the spatiotemporal changes in ecosystem vulnerability across China’s 832 national poverty-stricken counties from 2005 to 2020. A habitat–structure–function framework was applied to develop an evaluation index, along with a factor analysis of environmental and socio-economic indicators conducted through the Geodetector model. Finally, the implications of China’s practices to balance poverty alleviation and ecological protection were explored. The results show that ecosystem vulnerability decreased from 2005 to 2020, with an even greater decrease observed after 2013, which was twice the amount of the decrease seen before 2013. The post-2013 changes were mainly brought about by the enhancement of the ecosystem function in critical zones such as the Qinghai–Tibet Plateau Ecoregion, Yangtze River and Sichuan–Yunnan Key Ecoregion, and Yellow River Key Ecoregion. From 2013 to 2020, the influence of the gross domestic product (GDP) surpassed that of other factors, playing a significant positive role in diminishing ecosystem vulnerability in the three regions mentioned. The results suggest that China’s poverty-alleviated areas have found a “win–win” solution for poverty alleviation and ecological protection, that is, they have built a synergistic mechanism that combines government financial support with strict protection policies (e.g., more ecological compensation, eco-jobs, and ecological public welfare positions for poor areas or the poor). These findings elucidate the mechanisms behind China’s targeted poverty alleviation outcomes and their ecological implications, establishing a practical framework for coordinated development and environmental stewardship in comparable regions. Full article

The lower reaches of the Jinsha River, serving as a vital ecological barrier in southwestern China and playing a crucial role in advancing targeted poverty alleviation efforts, remain underexplored in terms of the coupling between ecological and economic development, creating a gap in understanding the region’s sustainable development potential. This study combines the remote sensing ecological index (RSEI) derived from MODIS data and the biodiversity richness index (BRI) based on land use data to create the ecological environment index (EEI) using a weighted approach. It also develops the economic development index (EDI) from economic data using the entropy weight method. By integrating the EEI and EDI, the study calculates key metrics, including the ecological–economic coupling degree (EECD), coupling coordination degree (EECCD), and relative development degree (EERDD), and examines their spatiotemporal changes from 2000 to 2020. Additionally, the study applies a geographic detector model to identify the spatial drivers of the EEI, an obstacle factor diagnosis model to pinpoint the main barriers to EDI, and a neural network model to uncover the underlying forces shaping EECCD. The results indicate that: (I) From 2000 to 2020, the overall improvement rate of the ecological and economic subsystems was greater than that of the ecological–economic coupling system. The entire region is still in the Running-In Stage, and the coordination level has been upgraded from near imbalance to marginal coordination. About 85% of the counties’ EERDDs are still in the EDI Behind EEI Stage. (II) The structural composition of the EEI shows a pattern of low Dry Hot Valley Area and high in other areas, mainly driven by natural factors, although human activities had a notable impact on these interactions. (III) Originating from an impact model primarily driven by economic factors and supplemented by ecological factors, both EDI and EECCD exhibit a pattern of high in the south and low in the north, with improvements spreading northward from the urban area of Kunming. The development gradient differences between 24 poverty-stricken counties and 16 non-poverty-stricken counties have been reduced. (IV) For the six types of ecological–economic coupling development zones, it is essential to adopt localized approaches tailored to the differences in resource and environmental characteristics and development stages. Key efforts should focus on enhancing ecological protection and restoration, increasing financial support, implementing ecological compensation mechanisms, and promoting innovative models for sustainable development. Full article

The coordination and stability of the regional economy (RE) and ecological quality (EQ) are essential for the synergistic development of the Beijing–Tianjin–Hebei urban agglomeration (BTH). In this paper, based on remote sensing data and economic statistics data, this paper analysed the current situation and evolution of the RE and EQ in the BTH region. Based on the coupled coordination degree (CCD) model, this paper has developed an evaluative framework and quantifies the spatiotemporal coupled coordination of the RE and EQ in the BTH region from 2000 to 2020. The results show that: (1) in 2020, the GDP of the poverty-stricken counties (PSCs) around BTH accounted for 4.57% of the total BTH region, and the area of high-quality ecosystems, Net Primary Productivity (NPP), soil conservation, water conservation, and sand fixation accounted for more than 40% of the total BTH region; (2) the GDP growth of the PSCs accounted for 4.45% of the total growth in BTH, the reduced area of high-quality ecosystems accounted for 21.04%, and the increase in NPP, soil conservation, water conservation, and sand fixation accounted for more than 40% of the total growth in the BTH region; (3) the CCD of the RE and EQ in the BTH region showed a tendency to increase, but the gap between the regions gradually expanded, and the development type changed from a lagging RE to a lagging EQ, in which the coupled coordination grade of the PSCs was in a dissonance stage for a long time, and the level of economic development had to improve. Deepening the understanding of the spatiotemporal coupling relationship between the RE and EQ and adopting appropriate development policies is of great significance for achieving the coordinated and integrated development of the BTH region. Full article

As a new product that combines finance and digital technology, digital finance is of great significance to the governance of the ecological environment. Based on the panel data of 2128 counties in China from 2014 to 2020, the fixed effect model and a panel threshold model are established, and the direct impact, heterogeneity, and transmission paths of digital finance development on ecological environment quality are empirically analyzed. The results demonstrate that the progress of digital finance has a significant negative effect on ecological environmental performance, and robustness tests support this conclusion. Additionally, industrial agglomeration and structural transformation are crucial mechanisms through which digital finance hinders ecological environmental performance. Moreover, the adverse influence of digital finance development on the ecological environment is particularly pronounced in densely populated areas, county-level cities, and non-poverty-stricken counties. Fourthly, based on the development level of digital finance itself, digital finance has a double threshold effect on the performance of county ecological environment. When digital finance is at a low level and a high level, its negative impact on eco-environmental performance is the greatest. Between the low level and the high level of digital finance, digital finance has the greatest negative impact on the performance of the ecological environment. Finally, suggestions are put forward to promote the green development of digital finance, foster balanced regional development, and expedite industrial transformation in underdeveloped regions. Full article

Against the backdrop of rapid urbanization, with the expansion of administrative boundaries, some former villages have been transformed from administrative to urban in the sense that they have become special “village-to-city areas”; in this context, the housing pattern, which was previously dominated by self-built houses, is facing many challenges. In particular, the frequent occurrence of safety accidents in self-built houses in the village conversion areas in recent years constitutes an important component of urban spatial vulnerability. However, the ensuing “one-size-fits-all” ban on self-built housing has also raised concerns among scholars. In order to better guide the planning and construction of self-built houses, official safety inspections, planning guidance, and institutional constraints are essential. However, the safety inspection of self-built houses across China is difficult. On the one hand, it is challenging to obtain data on individual buildings (e.g., age, use, building structure ratio, foundation, structural condition, illegal demolition and alteration, and illegal use), and the methods of obtaining such data rely mainly on the basic checking of the safety grids under the responsibility of grassroots safety officers. However, the current organizational system of safety officers is not perfect, and the relevant evaluation training also has limitations. On the other hand, due to the city’s finances, development stage, and other reasons, the agricultural-to-residential areas in the cities of poverty-stricken counties are not likely to be renewed as rapidly as the cities of developed regions but instead may face long-term renewal timelines. Therefore, for the agricultural resettlement areas in the cities of poverty-stricken counties, it is necessary to screen the current problems, systematically study the mechanism and strategy of their renewal based on the management framework of the whole process, and carry out the organic renewal of self-built houses, so as to gradually realize a safe and resilient development mode. This paper establishes a framework for the renewal of self-built houses oriented to security resilience based on the theory of fortress land under the urban form theory of Conzen. Taking Lianhua County as a case study, we analyze the problems and issues related to self-built housing areas through an investigation of the current situation. Then, in response to the existing problems, based on the comprehensive investigation of the safety of self-built houses, we clarify the planning objectives and value orientation and suggest (i) the adoption of hierarchical and classified planning and construction control for the self-built housing areas of villages converted to residences in accordance with the local conditions; (ii) the enhancement of government supervision in the use of self-built houses and the establishment of laws and regulations; and (iii) renewal planning in an orderly manner to enhance the safety resilience of the self-built housing areas. Based on the renewal study of self-built houses in Lianhua County, a systematic exploration of the planning, construction, and governance strategies of self-built houses in China is carried out, which can provide a reference for the decision making of relevant departments. Full article

Rural China has undergone a rapid transformation in the past few decades, especially the poverty-stricken areas, making a historic leap from inadequate subsistence to full well-off status. Based on rural regional system theory, this study analyzes the connotation of rural transformation development (RTD), explores the spatio-temporal patterns of RTD in the Yanshan-Taihang Mountainous, and diagnoses its influencing factors using a geographically and temporally weighted regression model. The results show that RTD is a dynamic process of qualitative changes in rural regional systems based on the accumulation of quantitative changes of elements, and the key to its measurement lies in analyzing the coupling coordination degree between quantitative changes of elements. From 2000 to 2020, the rapid development of urban population share, non-agricultural industry share, construction land share and NDVI in the Yanshan-Taihang Mountains contributed to a leap in RTD status, and the proportion of counties in a coupling coordination state increased from 24.24% to 96.97%. Spatially, the RTD level in the Taihang Mountains was significantly superior to that in the Yanshan Mountains. Average years of schooling, road density, per capita GDP and urban–rural dual structure were the main influencing factors of RTD, of which the first three were positive factors and the last one presented a negative correlation. To promote RTD to a higher level, it is an urgent matter to boost the high-quality development of county economy and rural education, improve public transportation infrastructure and innovate the policy system. Full article

Micro-credit for poverty alleviation is an important financial measure of targeted poverty reduction and rural revitalization in China. This paper employs the OLS model and Logit model to empirically test the effect of micro-credit for poverty alleviation on the income level and stability of income growth of farmers based on the field survey data of 458 registered poverty-stricken farmer households in Fuping County and Quyang County of Hebei Province. The results suggest that micro-credit for poverty alleviation can increase farmers’ income, stabilize the growth of their income, and exert significant short-term and long-term effects on income growth and poverty alleviation. The specialized farmer cooperatives, the scale of production and operation, the proportion of family labor force, and the education level of the head of the farmer’s household exert a significantly positive effect on the farmers’ income and the stable growth of their income. There is a significant interaction between micro-credit for poverty alleviation and specialized farmer cooperatives. The physical conditions of family members exert a negative effect on the stable growth of their income, and other financing channels have no significant effect. Full article

In addition to being necessary for the stability, coordination, and sustainable growth of the national economy, narrowing the urban–rural income gap is also an “Important national matter” for the long-term security of the nation. “Big mountain areas, big cities, big reservoir areas, big rural areas, and ethnic areas” are all present in the municipality of Chongqing. All of the poverty-stricken counties have been lifted out of poverty, despite the promotion of targeted poverty alleviation and other policies, significant urban–rural income gaps remain. In view of the current research, there has been no in-depth discussion on the correlation between urban and rural income gap and poverty levels in various regions, and there has been no in-depth discussion on the spatial correlation and spillover effects of various influencing factors. This paper employs panel data from 2010 to 2021 for 37 counties in Chongqing; based on an analysis of the characteristics of the urban–rural income gap’s spatial pattern and spatio-temporal evolution, it classifies each county (city and district) as either a non-poverty or poverty-stricken county and uses spatial econometric models to conduct an in-depth study of the influencing factors and spillover effects of the urban–rural income gap in Chongqing. The outcomes of our analysis of the influencing factors reveal that the level of fixed assets investment, the per capita spending of public funds, the proportion of rural employees, the proportion of grain sowing, the amount of agricultural fertilizer applied per unit area, the proportion of real estate development investment, and population density variables are important causes of the URIG in Chongqing. The spillover effects of these factors vary between poverty-stricken and non-poverty-stricken counties. This paper aims to provide reference to policymakers to design measures to narrow the urban–rural income gap and advance the urban–rural coordinated development strategy on the basis of a thorough examination of the spatial and temporal evolution, influencing variables, and spillover effects of the urban–rural income gap in Chongqing. Full article

Based on the quasi-natural experiment established in China’s national key ecological function areas, this paper takes 102 counties in Hebei Province, China, from 2014 to 2018 as the research object. It uses propensity score matching and difference-in-difference methods to investigate the impact of policy implementation on farmers’ income levels and constructs a mechanism using the air quality index to examine the environmental effect. The results show that when the time and regional fixed effects are not considered, the income level of farmers in the county increased by 3.11% due to the influence of the transfer payment policy, and the policy treatment effect grew over time. Among the control variables, the degree of industrialization and agriculturalization, urbanization rate and government financial scale were all positively related to farmers’ income. Controlling the fixed effects of region and year, the impact of policy on the improvement of farmers’ income was weakened, and the regression coefficient changed from 0.2211 to 0.0366, a drop of 83.45%. This suggests that the policy is greatly affected by the city where farmers live. The “environmental effect” test results showed that transfer payments could increase the income level of farmers in counties affected by the policy. The mechanism is that the priority measure of the ecological compensation policy is to improve the ecological environment, which is conducive to improving local environmental governance and environmental productivity and increasing crop yields, and thus increasing farmers’ incomes. Because the regions where the policy is implemented overlap with highly poverty-stricken areas, it is necessary for the central government to improve transfer payment standards and enrich their content to protect people’s livelihood while promoting ecological protection. As a result, local governments will be encouraged to act ecologically, vigorously develop local ecological industries, and promote the internalization of positive externalities in ecological environmental services, further improving the level of agricultural modernization and ecological sustainability and improving the income levels of farmers and their quality of life. Full article

Under the background of rural revitalization and domestic and international double circulation, vigorously developing the rural distribution industry is an important measure needed to accelerate the process of urban–rural integration, and to enhance the effect of poverty alleviation. In this study, 36 poverty-stricken counties in the southeast of Henan Province, China were selected as research objects; the evolution characteristics and factors influencing the counties’ distribution industries and their development were studied, using the modified gravity model, exploratory spatial data analysis, and a spatial econometric model. The overall scale of the county-level distribution industry in the poverty-stricken areas of southeast Henan expanded, but regional development was uneven, and a spatial pattern of “high in the northeast–low in the southwest” was demonstrated. Meanwhile, the development of the distribution industry in the counties of the district had a circular spatial trend of “agglomeration–diffusion–agglomeration”, with a significant local spatial polarization effect. In addition, the technology level, market demand, population size, and industrial structure adjustment had positive spatial spillover effects on the development of counties’ distribution industries, while labor and capital exerted negative spatial spillover effects. On this basis, to promote the interactive development of the distribution industry and rural economic growth and further accelerate the process of urban–rural integration, we should continually optimize the spatial layout of the distribution industry, improve the construction of county-level circulation infrastructure, and boost new circulation formats and models. Full article

The relationship between government intervention and cooperative development has always been a source of controversy in the developing world. This paper aims to examine the rationale and successful conditions of government intervention to promote cooperative development in poor areas of rural China. In the context of the “targeted poverty alleviation” program (2015–2020), a government-led campaign covering all poverty-stricken villages in west China, cooperative development was listed by the central government as a criterion for evaluating successful intervention at the county government level. Accordingly, the central questions of this paper are: why is government intervention necessary to initiate a process of cooperative development in poor areas of China; and under what conditions can government intervention be successful, leading to sustainable cooperative development? Bearing in mind the complexity of government intervention with mixed results, both successful and failed, the above questions are addressed through a case study of XM Beekeeping Cooperative, representing one type of successful government intervention in poverty-stricken and ethnic-minority-dominated regions of China. Overall, government intervention is crucial in building cooperative ecosystems in poor regions of China. However, government intervention is not invariable because the approaches can be modified to accommodate the effect of the intervention. Full article

The paired assistance approach is an important measure for achieving poverty alleviation in China. The sustainable development of poverty-stricken areas after poverty alleviation has become an important task in preventing a return to poverty and promoting rural revitalization. Paired assistance is a dynamic process of balanced economic, social, and population development. This study establishes a system dynamics (SD) model for developing poverty-stricken regions under paired assistance. This study takes Lvchun County in Yunnan Province as the research object, designates six scenarios, and simulates the development of Lvchun County from 2019 to 2035 to evaluate its sustainable development after poverty alleviation. The results show that the cessation of poverty alleviation funding will not increase the incidence of poverty under paired assistance but will lead to an unbalanced scenario of “poor people and a rich government”. In the multi-scenario simulation, only by continuing the cooperation foundation formed by paired assistance and paying attention to the resource endowment of poverty-stricken areas can collaborative development be adopted to achieve sustainable development by 2030. This result may be a valuable resource for the world’s underdeveloped regions to reference as they seek to eliminate poverty, reduce the risk of returning to poverty, and promote sustainable development. Full article

Both transport development and poverty alleviation are vital for sustainable development. However, due to the lack of long-term, comparable, county-level transport accessibility and poverty incidence data, the spatiotemporal patterns of these factors have rarely been accurately revealed in the poverty-stricken regions of China, causing the impacts of transport accessibility on poverty alleviation to be difficult to quantify. Taking Guizhou Province in China as the study area, this study revealed the spatiotemporal patterns of transport accessibility and poverty alleviation in 88 counties from 2000 to 2018 based on multisource data, including nighttime light data, LandScan population data, and transport network data. It was found that the transport accessibility decreased from 4.9 h to 3.3 h, and the poverty index decreased from 0.75 to 0.29 on average. All these factors exhibited a “core–periphery” spatial pattern. Furthermore, the panel data regression analysis suggested that transport accessibility has played a dominant role in poverty alleviation, with an elasticity coefficient of 0.839. In the future, policies concerned to integrate transport development with rural industries such as agriculture, e-commence, and tourism are recommended for poverty alleviation and rural revitalization, which are especially significant for promoting sustainable development, securing a win–win of economic growth and social equity. Full article