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Against the backdrop of consolidating the achievements of poverty alleviation and promoting rural revitalization, whether digital village construction can alleviate the risk of rural families returning to poverty and then help long-term poverty prevention needs systematic and scientific empirical investigation. Using data from the 2020 China Rural Revitalization Survey (CRRS), this paper analyzes the impact of digital village construction on rural household poverty vulnerability and explores its potential channels. The results show that (1) digital village construction can significantly alleviate the poverty vulnerability of rural households. (2) Improving entrepreneurial activity is an effective way for digital village construction to affect the risk of rural households returning to poverty. (3) Digital village construction has a greater effect on reducing the poverty vulnerability of households in the eastern and the plains regions, and it is necessary to be vigilant against the emergence of the “digital divide”. Based on these findings, this paper proposes policy recommendations to prevent the risk of rural areas returning to poverty through digital village construction, which achieves sustainable poverty reduction and rural revitalization goals.

Enhancing the synergies between agriculture and related sectors in rural areas is considered an important development strategy to eliminate rural poverty. This article provides evidence for this view by analyzing the effect of industry convergence between agriculture and related sectors on rural poverty. Based on China’s provincial panel data, we use two-way fixed effects model, system generalized method of moments and panel-corrected standard error estimator to quantitatively assess this effect. We find that: (1) the convergence of agriculture and tourism (ATOU), the convergence of agriculture and processing industry (APOS), and the convergence of planting and breeding industry (MIXA) have positive and significant effects on poverty reduction. The convergence of agriculture and the internet industry (AINT) has a positive but not significant effect. (2) Rural local employment plays an important role as a bridge in the impact of convergence on poverty reduction. ATOU and MIXA reduce poverty by increasing self-employment opportunities. APOS reduces poverty by providing more jobs. (3) Except for APOS, the effects of other types of convergence tend to stabilize or improve in the later period. (4) Convergence has the most significant impact on poverty reduction in western China. The findings provide inspiration for developing countries with agricultural foundations to choose appropriate rural development paths for reducing rural poverty.

The quest to eradicate poverty, central to the United Nations Sustainable Development Goals (SDGs), poses a significant global challenge. Advancement in sustainable rural development is critical to this effort, requiring the seamless integration of environmental, economic, and governmental elements. Previous research often omits the complex interactions among these factors. Addressing this gap, this study evaluates sustainable rural development in China by examining the interconnection between agricultural production and government-led poverty reduction, with annual rainfall considered an influential factor of climate change impacts on these sectors and overall sustainability. Utilizing a Meta-frontier entropy network dynamic Directional Distance Function (DDF) within an exogenous Data Envelopment Analysis (DEA) model, we categorize China’s 27 provinces into southern and northern regions according to the Qinling-Huaihe line for a comparative study of environmental, economic, and governmental efficiency. This innovative approach overcomes the limitations of previous static analyses. The findings reveal: (1) Rainfall, as an exogenous variable, significantly affects agricultural production efficiency. (2) The overall efficiency in both southern and northern regions increases when accounting for rainfall. (3) Government effectiveness in poverty reduction is comparatively lower in the northern region than in the southern region when rainfall is considered. These insights underscore the importance of including climatic variables in sustainable development policies and emphasize the need for region-specific strategies to bolster resilience against climatic challenges.

This study investigated the energy poverty spatiotemporal interaction characteristics and socioeconomic determinants in rural China from 2000 to 2015 using exploratory time–space data analysis and a geographical detector model. We obtained the following results. (1) The overall trend of energy poverty in China’s rural areas was “rising first and then declining”, and the evolution trend of energy poverty in the three regions formed a “central–west–east” stepwise decreasing pattern. (2) There was a dynamic local spatial dependence and unstable spatial evolution process, and the spatial agglomeration of rural energy poverty in China had a relatively higher path dependence and locked spatial characteristics. (3) The provinces with negative connections were mainly concentrated in the central and western regions. Anhui and Henan, Inner Mongolia and Jilin, Jilin and Heilongjiang, Hebei and Shanxi, and Liaoning and Jilin constituted a strong synergistic growth period. (4) From a long-term perspective, the disposable income of rural residents had the greatest determinant power on rural energy poverty, followed by per capita GDP, rural labor education level, regulatory agencies, and energy investment. In addition, our findings showed that the selected driving factors all had enhanced effects on rural energy poverty in China through interaction effects.

Environment and poverty are the focus of global concern, and green poverty reduction is China’s strategic choice to deal with these two major problems. However, due to the vast territory, there are regional differences in environment and poverty in China. On the basis of this, selecting renewable resource utilization, environmental protection, and incidence of poverty as measurement indicators from two dimensions of green and poverty reduction, this paper employed the analysis of spatial autocorrelation and spatial econometric regression based on dynamic spatial Durbin model to explore the internal mechanism of green and poverty in rural areas of 21 provinces in China. The results show that there was a significant spatial autocorrelation in the poverty in rural areas among provinces, which shows that poverty reduction has significant regional connections within spatial scopes. Meanwhile, it is green that has a spatial spillover effect on poverty reduction. Therefore, on the one hand, intergovernmental governments should establish effective communication and cooperation mechanisms between regions; on the other hand, intergovernmental governments should pay enough attention to the spatial spillover effects of green on poverty reduction in green poverty reduction, so as to promote green poverty reduction to achieve overall and sustainable development.

This article highlights why the Bill & Melinda Gates Foundation has focused on financial inclusion to advance women's economic empowerment and drive progress on gender equality. It highlights key lessons from financial inclusion-related projects the foundation has supported within the \"Putting Women and Girls at the Center of Development (WGCD) Grand Challenge\" in 2015. The article also shares the logic and research informing the foundation's strategy to close the gender gap in financial inclusion - a key pillar of its strategy on women's economic empowerment - and improve the lives and livelihoods of millions of women around the world.

Accurately identifying the degree of poverty and poverty-causing factors of poverty-stricken farmer households is the first key step to alleviating absolute and relative poverty. This paper introduces a multiobjective spatio-temporal evolution analysis method to examine poverty reduction of poverty-stricken farmer households under different development goals. A G-TOPSIS model was constructed to evaluate poverty-stricken households under short-, medium-, and long-term development goals. Then, GIS analysis methods were employed to reveal the spatio-temporal distribution of poverty-stricken households, and poverty causing factors were detected using the obstacle degree model. Taking Fugong County in Yunnan Province, China, as an example, the empirical results show that: (1) Great progress has been made in poverty reduction during the study period; however, some farmer households which have escaped absolute poverty are still in relative poverty and are still highly vulnerable. (2) Farmers with higher achievement rates under three different development goals are mainly distributed in the central and northern regions of study area, with a pattern of high–high agglomeration under the medium and low development goals, while low–low agglomeration mostly appears in central-southern regions. (3) Under the short-term development goals, the main poverty-causing factors are per capita net income, safe housing, sanitary toilets, years of education of labor force and family health. Under the medium- and long-term goals, per capita net income, labor force education and safe housing are the development limitations. (4) Infrastructure and public service are crucial to ending absolute poverty, and the endogenous force of regional development should be applied to alleviate the relative poverty through sustainable development industries and high-quality national education.

Scientific evaluation of the interaction between poverty reduction efficiency (PRE) and ecosystem services (ES) in state poverty counties is essential in promoting the rural revitalization strategy and the construction of an ecological civilization. Using the DEA model, the InVEST model, and fixed-effect panel data, this study was analyzed using the panel data of 832 poverty counties in China for 2010–2019 to evaluate the relationship between poverty reduction efficiency and ecosystem services. The main results are as follows: (1) The overall poverty reduction efficiency showed an upward trend, while ES exhibited a declining trend with spatial heterogeneity. The poverty reduction efficiency of state poverty counties in the western region increased rapidly. (2) The impact of different types of ecosystem services on poverty reduction efficiency varied considerably. Habitat quality was significantly negatively impacted, while food production and carbon storage showed significant positive effects. There was a significant positive relationship between ecosystem services and poverty reduction efficiency in all regions, with the eastern region having the strongest correlation. (3) The panel regression analysis showed a significant positive impact. The environmental parameters were the primary factors affecting poverty reduction efficiency, while economic and social factors were the driving and external factors. The rural revitalization strategy should strive towards the win-win effect of ecological protection and economic development.

The prioritization of innovation can be considered a key driver of economic growth which is a mainstream tool for fostering economic change and sustainable development. Focusing on how innovation is expected to bring about poverty alleviation is crucial given that the academic community has been concerned about which type of innovation will accelerate the achievement of sustainable socio-economic development. The study therefore examines how poverty rate can be impacted by process innovation in Nigeria over the period 2000–2021, using Autoregressive Distributed Lag (ARDL) and Pairwise Granger Causality Test. The findings indicate that reduced poverty rate is linked to process innovation propensity. Results back up the hypothesis that process innovation can significantly influence poverty reduction in the short-term as well as in the long-term. It is also discovered that increased poverty level could engender the drive towards process innovation. This is because poverty rate rise is likely to stimulate the propensity to innovate, thereby enhancing innovation capacities across economic institutions and sectors. The evidence established through the empirical analysis reflects the need to create favorable framework conditions for process innovation to thrive. This rests on the view that innovation-enhancing governance ideology aimed at improving economy performance is central for facilitating the pro-poor agenda.

This study investigates the potential of digital financial inclusion to reduce regional poverty in China, an issue that has received varying opinions from the academic community. Using panel data from 31 provinces, municipalities, and autonomous regions (2011–2020) and employing the system GMM, this paper analyzes the dynamic relationship between regional poverty and the growth of digital financial inclusion, as measured by the ‘Peking University Digital Financial Inclusion Index’. Controlling for factors such as the Gini coefficient, industrial structure, financial support for agriculture and education, and economic openness, this research finds that digital financial inclusion has a marked ability to reduce poverty rates. Moreover, our results indicate an intergenerational transmission characteristic in poverty, where prior levels significantly influence current poverty incidence. The study concludes that the recent acceleration of digital financial inclusion can be harnessed for meaningful poverty reduction. This study’s policy recommendations highlight the need for financial development to foster industrial and social growth and stress the importance of financial education for low-income populations. Additionally, it calls for increased management and oversight of inclusive and agricultural digital financial products and services.