Search Results (214)

Vietnam’s sustained poverty reduction has coincided with rising foreign direct investment (FDI) and a major shift from income-based to multidimensional poverty measurement, raising challenges for interpreting poverty dynamics and the role of FDI across regimes. This study examines the relationship between FDI and poverty reduction in Vietnam by accounting for poverty persistence, regional heterogeneity, and changes in poverty measurement. Using provincial panel data for 2002–2022 and a System GMM framework, three main findings emerge. First, poverty dynamics differ across measurement regimes: during the income-poverty period (2002–2016), poverty dynamics exhibited lower persistence and faster convergence, whereas under the multidimensional framework (2016–2022), poverty became more persistent and convergence slowed, reflecting the increasingly structural nature of remaining deprivation. Second, FDI is negatively associated with poverty under both measures, but its effects are conditional and uneven. Interaction effects indicate that the poverty-reducing impact of FDI depends on provincial income levels and initial deprivation, with weaker effects in provinces facing deeper multidimensional poverty. Third, higher FDI exposure is associated with greater poverty persistence, reflecting the spatial concentration of FDI in better-off regions rather than a poverty-increasing effect. The analysis is subject to limitations related to measurement regimes, and results are interpreted as conditional associations. Policy implications highlight that the poverty-reducing effects of FDI depend critically on investment quality, the strength of local production linkages, and complementary public spending, particularly in provinces facing persistent deprivation. Full article

Objective: The aim of this study was to investigate the association between dental caries and multidimensional poverty in Colombia using data from the National Oral Health Survey (ENSAB IV, Spanish acronym). Methods: A cross-sectional analytical study was conducted using data from 20,534 individuals in six regions of the country. Dental caries was assessed using the ICDAS system, and multidimensional poverty was measured using a proxy Multidimensional Poverty Index (MPI) adapted from the method adjusted for Colombia. Descriptive analyses and bivariate comparisons were carried out, and Poisson regression models adjusted for sociodemographic variables were applied. Results: Households containing at least one member with caries had a higher incidence (59.9%) and intensity (46.7%) of multidimensional poverty compared to those without caries (52.6% and 45.6%, respectively). Significant associations were identified between caries and deprivation in education (low educational attainment: RR = 1.27), child labor (RR = 1.16), unemployment (RR = 1.04), lack of health insurance (RR = 1.09), and inadequate housing conditions (RR = 1.19). The model that analyzed the presence of caries in a household and multidimensional poverty, when controlled for housing conditions, confirmed a positive association between the MPI and the presence of caries (IRR = 1.08; 95% CI: 1.050–1.107; p-value < 0.001). A female head of household and rural residence were also identified as variables associated with the presence of caries in a household. Conclusions: The presence of a household member with dental caries is significantly associated with multidimensional poverty in Colombia. This study highlights the need to consider oral health as a sensitive indicator of structural inequality and proposes its inclusion in social progress metrics. The findings support the design of comprehensive public health strategies that address the social determinants of oral health, especially in vulnerable populations. Full article

Climate-smart agricultural practices (CSAPs) are promoted as pathways for improving productivity and resilience among smallholder farmers; however, empirical evidence on their welfare effects remains limited in South Africa. This study examines the impact of CSAP adoption on household welfare among smallholder maize farmers in KwaZulu-Natal Province. A cross-sectional survey of 300 households was conducted using a multistage sampling approach. Welfare outcomes was measured using multidimensional indicators including the Household Dietary Diversity Score (HDDS), the Household Food Insecurity Access Scale (HFIAS), the Coping Strategy Index (CSI), and the Foster–Greer–Thorbecke (FGT) poverty index. An Endogenous Switching Regression (ESR) model was employed to correct for selection bias and to generate counterfactuals that estimate what adopters’ welfare would have been in the absence of CSAP uptake. Results show that access to extension, group membership, and training significantly increased the likelihood of CSAP adoption. ESR outcomes indicate that adopters had higher dietary diversity, lower food insecurity, and reduced reliance on severe coping strategies. Counterfactual analysis reveals that adopters would have experienced significantly poorer welfare outcomes had they not adopted CSAPs. The findings demonstrate that CSAP adoption yields measurable welfare benefits and improves household resilience. The study recommends targeted investments in extension support, farmer organizations, and institutional arrangements to accelerate the adoption of CSAP and enhance household welfare. Full article

Based on the 2021 Jiangxi rural survey data, this paper employs the Alkire–Foster (A-F) method to measure the multidimensional relative poverty index of farmers. Using linear regression and mediation effect models, we empirically analyze the impact and mechanism of land certification on farmers’ multidimensional relative poverty. The results indicate that land certification significantly reduces the overall level of multidimensional relative poverty among farmers. It has a notable positive effect on the allocation of credit, land, labor, and capital factors, effectively encouraging farmers to increase their agricultural investments, expand farmland transfers, and enhance agricultural labor input. Furthermore, farmland certification exerts an indirect effect on multidimensional relative poverty by inhibiting poverty through the allocation of these production factors. Specifically, credit, labor, and capital allocation play partial mediating roles, while land allocation serves as a complete mediator. Based on these findings, recommendations are put forward to further implement the “separation of three land rights” policy, adopt targeted measures for different types of poverty among farmers, and improve factor markets at the county level as soon as possible. Full article

Climate change is a pressing issue that has far-reaching effects on the global ecosystem, societies, and economies. Climate-induced disasters exacerbate multidimensional poverty through economic, social, and environmental pathways. This study examines the relationship between climate-induced disasters and multidimensional poverty, applying a mixed-method design comprising a PRISMA-guided systematic review and thematic analysis. Articles published between 1999 and 2025 were retrieved from Scopus and Web of Science, yielding 3587 articles. After reference checking and screening for relevance and availability, we finally reviewed 17 articles. The results highlight that climate-induced disasters disrupt economic and livelihood activities, negatively impact GDP, slow financial development, reduce per capita expenditure ability, and harm agricultural production. Disasters also have negative impacts on health and well-being, education, gender, the natural environment, and culture; these disasters promote intergenerational poverty. Among all stressors, floods and droughts are the most pervasive, and they have different magnitudes and durations of impacts. The assessment identifies governance quality, gender inequality, education, social positions, and environmental degradation as the significant mediating systems influencing vulnerability and recovery. To cope with vulnerabilities, individuals employ a variety of strategies based on their socioeconomic status. Building on these insights, the study develops the Multidimensional Climate–Poverty Dynamics (MCPD) Framework to conceptually capture climate–poverty as a socially constructed and institutionally mediated process. The study contributes theoretically to environmental sociology and empirically to climate policy by framing adaptation as a social process of transformation rather than as solely a survival mechanism. Full article

Water vulnerability in Piura, northern Peru, is shaped by structural, climatic and governance factors. Surface water from the Chira, Huancabamba and Piura basins is stored and conveyed through major reservoirs (Poechos and San Lorenzo) and canals (Daniel Escobar, Miguel Checa), while service and storage infrastructure is denser on the coast than in the highlands. This study adapts and operationalizes Escribano’s multidimensional scarcity framework—originally developed for the Gulf of Guinea—into a provincial-scale water-vulnerability index for Piura. Structural, climatic-exposure and institutional-capacity indicators from official statistics are min–max normalized to 0–1, aggregated into dimension indices as arithmetic means, and combined with equal weights. All indicators, normalization procedures and aggregation rules are documented, and the resulting indices are mapped with GIS to reveal intra-regional disparities. Findings show that highland provinces such as Ayabaca and Morropón exhibit higher composite vulnerability than coastal provinces, due to persistent poverty, predominantly rural settlement patterns and weaker governance capacity. Some coastal provinces, notably Paita and Sechura, also display elevated vulnerability, whereas Piura and Sullana score lower despite higher demand. Overall, vulnerability appears to be driven more by socio-institutional asymmetries than by physical availability, providing a transparent screening tool for adaptive, territorial water governance. Full article

Global extreme poverty has fallen dramatically over the past two centuries, yet hundreds of millions remain impoverished, underscoring the need for scalable monitoring tools. In Mexico, poverty metrics are available only sporadically in terms of time and space (e.g., every 5 years at the municipal level), making it difficult for decision-makers to access reliable, up-to-date, and sufficiently detailed information, highlighting the need for higher-resolution, timely methods. To address this problem, we propose a two-stage approach that combines socioeconomic and Earth Observations-based data. Initially, a machine learning model maps census variables to official poverty indicators belonging to a multidimensional model, yielding fine-scale poverty estimates. A census-based model trained with eXtreme Gradient Boosting (XGBoost) achieved a determination coefficient ($R^2$) of approximately $0.842$, indicating strong agreement with official poverty figures and providing high-resolution proxies. Afterward, we use features based on remote observations to predict these poverty estimates at a 469 m grid scale. In this case, advanced foundation models outperformed other machine learning (ML) approaches, achieving an $R^2$ of $0.683$. While foundation models enable more accurate, fine-scale poverty mapping and could accelerate poverty assessments, their use comes at a heavy price in terms of carbon emissions. Full article

Multi-dimensional inequality among rural residents has become a major obstacle hindering the achievement of global poverty alleviation goals. This study utilized household sample data from the China Family Panel Studies (CFPS) over four periods from 2014 to 2020 and applied them to a high-dimensional fixed effects model to estimate the impact of digital literacy on multi-dimensional inequality among rural residents. The results show that digital literacy can effectively alleviate the multi-dimensional inequality of rural residents. From the perspective of a mediating effect, digital literacy alleviates the multi-dimensional inequality of rural residents by improving the level of social capital and promoting social harmony. Moreover, the alleviation of multi-dimensional inequality among rural residents by digital literacy varies among different groups. The impact of digital literacy on the multi-dimensional inequality of agricultural workers and rural residents in western regions is relatively greater than that of non-agricultural workers and rural residents in other regions. Information processing literacy in digital literacy has the most significant impact on the multi-dimensional inequality of rural residents. This paper enriches the mechanism paths of digital literacy in alleviating the multi-dimensional inequality among rural residents in terms of both material and spiritual aspects, and provides a certain reference value for achieving the all-round development of rural residents and contributing to rural production practices. Full article

This study investigates thermal stress and energy-related anxiety as lived, multidimensional manifestations of energy poverty in Western Macedonia, Greece, a coal phase-out region undergoing just transition. Using a 261-household survey, we construct a thermal stress index from four Likert-type items capturing seasonal thermal adequacy, energy anxiety, and restricted use of rooms. High thermal stress is defined as the upper quartile of the index. Descriptive results indicate that high thermal stress affects 27.2% of households, exceeding a 20% threshold, while energy-related anxiety and restricted room use are widespread. We then estimate logistic regression models to examine whether vulnerability characteristics (disability-related thermal/electric needs, single parenthood, dependent children, benefit receipt, elderly presence), financial stress indicators (arrears, energy debt, frequent forced reductions in consumption), and socio-economic controls (income, employment, tenure, age, gender) predict high thermal stress. Adjusted models show that vulnerability markers do not retain statistically independent associations once controls are included. In contrast, tenure and energy-related financial stress are significantly associated with the probability of high thermal stress. The findings highlight the importance of measurement choices and suggest that experiential indicators capture energy-poverty dynamics that are not reducible to income-based targeting, with implications for just-transition policy design and energy justice. Full article

The significance of access to energy sources for fostering innovation is increasing. Regions should, however, base their competitiveness not merely on innovation, but also on social cohesion and ecological ambitions. In this context, the objective of this article is to evaluate the sustainable competitiveness potential of Polish regions from the perspective of energy-related factors, as well as to identify the trends and the disparities observed over the past decade. The study employs a multidimensional comparative analysis (MCA), operationalized through the development of a Synthetic Measure of Potential (SMP) constructed from ten disaggregated indicators encompassing resource-related, economic, environmental, and social dimensions of energy. This approach is complemented by a cluster analysis using Ward’s method to identify patterns and groupings within the data. The empirical results demonstrate that sustainable competitiveness potential with regard to energy factors has generally increased, although it was not a linear process. The most favorable trend was observed for the generation of energy from renewable sources. An interesting side effect of transformation was observed in the energy balance. Further, despite the significant decrease in industrial electricity consumption per unit of gross value added, the energy poverty level increased. The study offers several practical implications for advancing the green transformation, emphasizing the uneven regional impacts of this process and underscoring the necessity of a coordinated policy framework to support the energy transition. Full article

Anti-Poverty Programmes (APPs) are closely linked to rural livelihoods, yet comparative evidence on how participants and non-participants differ in livelihood-capital composition and income-generation patterns remains limited in ecologically fragile pastoral regions. This study draws on a cross-sectional household survey conducted in Northern Tibet in July 2020, covering 696 households—including 225 APP participants and 471 non-participants. Using the Sustainable Livelihoods Framework and the entropy weight method, we construct multidimensional livelihood-capital indices (human, social, natural, physical, and financial capital) and compare the two groups. We further apply Ordinary Least Squares (OLS) regressions to examine factors associated with per capita net income. The results reveal substantial heterogeneity in livelihood capital and income across both groups. APP participants exhibit higher human-capital scores, largely driven by a higher share of skills training, whereas they show disadvantages in physical and financial capital relative to non-participants. Natural capital shows no statistically significant difference between the two groups under the local grassland contracting regime. Significant differences are observed and identified in certain dimensions of social capital. Regression results suggest that income is positively associated with skills training, contracted grassland endowment, and fixed assets, with skills training showing the strongest association. For participants, herd size and labour capacity are not statistically significant correlates of income; for non-participants, larger herds and greater labour capacity are associated with lower income. Taken together, the findings indicate that APP participation is associated with stronger capability-related capital (notably training) alongside persistent constraints in productive assets and financial capacity. Policy implications include improving the relevance and quality of training, strengthening cooperative governance and market linkages, and designing complementary packages that connect skills, inclusive finance, and productive asset accumulation. Given the cross-sectional design and administratively targeted certification of programme participation, the results should be interpreted as context-specific associations rather than strict causal effects. Full article

Assessments of poverty among agricultural households in Sub-Saharan Africa often rely on either monetary or multidimensional indicators considered separately, overlooking key structural constraints. This study investigates the determinants of both monetary and multidimensional poverty among agricultural households in Togo. Using nationally representative EHCVM 2021/22 data from 2893 households, monetary poverty is measured using the Foster–Greer–Thorbecke Index, while multidimensional poverty is assessed with the Alkire–Foster method. A survey-weighted logit model is employed to identify the drivers associated with each poverty dimension. Results show that multidimensional poverty (59.40%) is more widespread than monetary poverty (51.50%). Education substantially reduces poverty risk, whereas larger household size, limited market access, and residence in the Savannah region increase it. Economic and natural shocks are negatively associated with monetary and absolute poverty, while cooperative membership raises the likelihood of being poor. Investment in livestock (TLU) reduces monetary poverty but increases multidimensional deprivation. These findings highlight that poverty among agricultural households in Togo is shaped by interconnected socioeconomic and institutional constraints rather than income deprivation alone. Therefore, integrated strategies aligned with the Sustainable Development Goals, particularly those promoting education, rural credit access, market integration, and resilience-building, are essential for achieving effective and context-specific poverty reduction. Full article

Against the backdrop of China’s transition from the eradication of absolute poverty toward the pursuit of common prosperity, equitable access to energy has become an increasingly important policy concern. This study develops a multidimensional framework to assess energy poverty from three interrelated dimensions: energy use level, energy structure, and energy capability. Using panel data for 30 provincial-level regions from 2005 to 2020, a provincial energy poverty index (EPI) is constructed based on the entropy-weighting approach. The spatial and temporal dynamics of energy poverty are examined using Moran’s I, the Dagum Gini decomposition, kernel density estimation, and spatial Markov chain analysis. The results reveal several key patterns. (1) Although energy poverty has declined nationwide, it remains pronounced in parts of western, central, and northeastern China. (2) Energy poverty exhibits significant spatial clustering, with high-poverty clusters concentrated in resource-dependent regions such as Shanxi and Inner Mongolia, while low-poverty clusters are mainly located along the eastern coast. (3) Regional disparities follow an inverted U-shaped trajectory over time, with east–west differences constituting the primary source of overall inequality. (4) Moreover, the evolution of energy poverty displays strong path dependence and club convergence. These findings highlight the need to strengthen dynamic monitoring and governance mechanisms, promote region-specific clean energy development, and enhance cross-regional coordination to support energy security and green transformation under China’s “dual-carbon” objectives. Full article

This study aims to analyze the effect of remittances on multidimensional poverty in Mexico by comparing them with other sources of household income, such as labor income and social spending from transfers, subsidies, and allocations. Furthermore, economic growth dynamism is incorporated as a control variable. A micro-panel with cross-sectional and temporal fixed effects covering the 32 federative entities from 2010 to 2024 is used for this purpose. The results reveal that, although remittances have a moderate alleviating effect on poverty, it is greater than the impact of social spending by state governments. In contrast, labor income is identified as the main factor in reducing multidimensional poverty. These findings underscore the importance of promoting the utilization of remittance flows through financial inclusion strategies to strengthen their contribution to sustained household well-being and consolidate them as a structural instrument against the persistent challenges of multidimensional poverty in Mexico. Full article

The conceptual foundation of this study is that a country’s exposure to risk when using green bonds as a mechanism for financing sustainable development is shaped by a combination of macroeconomic, market, and social factors. This paper develops and empirically validates a fuzzy-set model to assess national-level risks associated with green financing projects within the Water–Energy–Food (WEF) Nexus in BRICS countries. Building on established theoretical frameworks and empirical evidence, the study conceptualises risk as a function of economic development, the scale of the domestic green bond market, institutional trust, and performance on the Multidimensional Poverty Index (MPI). The study employs fuzzy-set modelling to integrate these heterogeneous indicators into a unified quantitative risk score. This approach enables cross-country comparison and captures the non-linear nature of relationships between socio-economic and institutional factors. The country sample includes Brazil, Russia, India, and China, which have successively chaired the BRICS association between 2021 and 2025, thereby ensuring methodological consistency and representativeness. The empirical results reveal a clear stratification of green-finance risk levels across the four economies: China demonstrates the lowest risk (Y = 0.243), followed by Russia with a below-average risk (Y ≈ 0.41), while India (Y = 0.53) and Brazil (Y = 0.51) exhibit the highest relative risks. These outcomes highlight the critical role of institutional trust and market maturity in reducing financing uncertainty within the WEF nexus. The study contributes to the literature by integrating macroeconomic, social, and institutional indicators into a unified fuzzy-logic model of green-finance risk; offering a transparent methodology for country-level comparison; and providing policy insights for improving the enabling environment for green bond markets in emerging economies. Full article