Search Results (198)

This study examines the role of private investment in promoting multidimensional poverty reduction in a sustainable manner in Vietnam by analyzing both spatial and temporal spillover effects. Provincial panel data for 2010–2024 are employed. To assess the spatial spillover effects, three econometric models are applied: SAR, SEM, and SDM. Diagnostic tests suggest that the SDM model is the most appropriate for the research data. Results based on the contiguity and inverse distance weight matrices show that private investment not only reduces poverty in recipient provinces but also generates benefits for neighboring areas, highlighting the need for coordinated planning of industrial zones and regional economic hubs. To analyze this relationship over both the short-term and long-term horizons, the study employs PMG and CCEP estimators, while the DCCEP model verifies robustness in a dynamic framework. The findings consistently confirm that private investment contributes to multidimensional poverty reduction. An additional result from the DCCEP model indicates that literacy and urbanization rate have significant positive effects on poverty reduction, while these relationships are not detected in other models. This finding carries important implications for building an enabling investment environment to attract and effectively utilize private capital to implement multidimensional poverty reduction strategies towards sustainability and aligned with sustainable development objectives. Full article

Rural poverty in Indonesia remains a complex issue involving various aspects. West Manggarai, East Nusa Tenggara, is a national tourist destination and a significant focus of national development, yet poverty rates remain very high. Therefore, this study developed a Composite Poverty Index (CPI) using the Sustainable Rural Livelihoods Approach (SRLA) to illustrate the complexity of rural deprivation in West Manggarai Regency. The CPI was developed by normalizing eighteen validated indicators across five livelihood capitals—human, social, natural, physical, and financial. These indicators were then classified using a Likert-type scale, and their weights were determined through the Analytic Hierarchy Process (AHP) to produce village-level CIP scores. The results show that most villages fall into the “Moderate” category (CIP: 0.40–0.60), reflecting chronic but not extreme deprivation. Spatial inequalities are evident, particularly in access to education, infrastructure, clean water, financial services, and ecological resources. Remote villages recorded higher CIP scores. Natural and economic capital were weakest, while human and social capital performed relatively well. Therefore, poverty alleviation in West Manggarai requires an integrated strategy tailored to local spatial conditions and livelihood capital. Full article

The swift advancement of the digital economy presents new pathways toward achieving common prosperity in China. Based on microdata derived from the China Family Panel Studies (2010–2022), this study employs the “Broadband China” pilot policy as a quasi-natural experiment to explore how digital economy development influences multidimensional relative poverty. We develop a multidimensional relative poverty index encompassing economic, health, education, and living condition aspects utilizing the Alkire–Foster dual cutoff method and employ a staggered Difference-in-Differences design for empirical analysis. Results show that the policy leads to an average decrease of 1.8 percentage points in the probability of multidimensional relative poverty across households. The effect is more pronounced in central and western regions, rural households, and those with a high proportion of non-labor force, particularly in the dimensions of economic, health, and living conditions dimensions. Mechanism analysis via interaction term regression indicates that increased population mobility and improved informal employment are key channels. These findings suggest that enhancing digital infrastructure and tailoring mobility and employment policies to fit regional and urban–rural contexts can effectively alleviate multidimensional relative poverty. This study contributes empirical evidence connecting the advancement of the digital economy to poverty alleviation and aligns with the United Nations Sustainable Development Goal 1 (No Poverty). Full article

This article aims to critically engage with the capability approach by exploring its potential contributions to social work practice, specifically social work focusing on reducing child poverty. In high-income countries, an estimated 69 million children are either living in poverty or at risk of poverty. Despite its comprehensive social welfare system, Switzerland is no exception. This contribution is based on empirical research conducted between 2021 and 2025 in Switzerland with children and young people (CYP). The results of this participatory and artistic research not only demonstrate the value of considering the experiential knowledge of CYP affected by poverty in the context of social intervention, but also the importance of the participation of this social work audience in fostering professional and institutional practices along with promoting fairer, more inclusive and transformative public policies. This research precisely identifies how social work practice could support CYP’s evolving capabilities by applying the capability approach within social services. Specifically, it focuses on capabilities for voice and to aspire, as well as their progression vis-à-vis the transformation of social practice, which could be observed through the participation implemented as a foundational principle of action in social work practice. Full article

This study investigates the multidimensional nature of household deprivation in Kazakhstan within the broader context of poverty reduction and sustainable development. Based on a nationally representative household survey (sample size 2005), the data were analyzed using factor analysis in SPSS 25 to uncover latent dimensions of deprivation. The analysis identified six components: socio-cultural, educational, medical, children’s basic needs, food, and infrastructure, which were synthesized into three integrated indices: basic, institutional, and socio-cultural. The results reveal pronounced regional disparities, with the southern and western regions showing higher levels of deprivation, whereas major cities perform significantly better. Income level is a key determinant: households below the subsistence minimum face the highest deprivation risk, particularly in the basic and institutional dimensions of deprivation. Sociocultural deprivation was weakly associated with income. These findings underscore the urgent need for regionally differentiated, income-sensitive policies to mitigate poverty and promote equity. This study offers empirical insights into an underexplored area, contributing to the understanding of household vulnerability in Kazakhstan. Full article

Market gardening plays a crucial role in ensuring food security and reducing poverty in Africa’s rapidly urbanizing regions. However, urban agricultural systems are increasingly threatened by climatic shocks such as floods, droughts, and heat waves. This study uses an integrated approach to analyze the multidimensional factors of climatic vulnerability among urban market gardeners in the Grand Nokoué region of Benin. Based on socio–economic, technico–agronomic, and perceptual data collected from 369 growers, multiple correspondence analysis (MCA) coupled with ascending hierarchical analysis (AHA) was performed to identify vulnerability profiles. K–means partitioning was used to confirm the optimal number of groups, thereby guaranteeing the robustness and internal consistency of the typology. Three distinct vulnerability groups were identified, each characterized by specific socioeconomic, technical, and territorial characteristics, as well as varying exposure to the risks of flooding, drought, and dry spells. The results show that the most vulnerable farmers tend to be young women with low incomes, limited access to land, and a reliance on manual irrigation in flood–prone areas. These findings emphasize the uneven distribution of adaptive capacities and the pressing requirement for tailored public policies to enhance resilience, especially among small–scale, low–income, and land–insecure urban farmers, who are vulnerable to various climate–related risks. Full article

Increasing debt, natural disasters, and extreme weather events claim an ever-larger part of national budgets across the globe, undermining global stability and the capacity of our societies to transition to sustainability. The dominant crisis response policy paradigm treats the economy and the environment as separate domains and is based on a ‘fix-the-economy-first’ principle, i.e., fiscal consolidation and debt sustainability need to be achieved first before addressing other socio-environmental policy goals. This paper demonstrates that this approach entraps countries and the global economy in a vicious cycle. In the absence of an integrated policy framework for addressing these intersecting challenges, our responses to financial stress often exacerbate the environmental crisis and its consequences, adding further financial strain on an already fragile socio-environmental system. Breaking out from this conundrum requires a new crisis response policy paradigm. To this end, this study develops the Unsustainable Growth Vicious Cycle (UGVC) as an analytical framework that exemplifies the incentive structure that governs the dominant crisis response model, and the negative feedback loops that sustain it. Our analysis unfolds in four stages. We analyse how financial stress triggers multidimensional poverty traps and how these impact on the environment. We use the concept of poverty-environment trap 2.0 to capture the emergence of the environmental crisis as a global poverty and inequality trap in its own right. We explicate the limits of the dominant economic policy paradigm through the lens of unsustainable economic growth. We finally discuss the need of transforming ‘economic adjustment programmes’ into ‘sustainability adjustment programmes’, as part of a new global settlement for sustainability transition. Full article

This study examines the feminization of poverty in Indonesia, focusing on the distinct vulnerabilities faced by female-headed households. Utilizing data from the 2023 National Socio-Economic Survey (SUSENAS) involving 291,231 households, this study applies a logistic regression model to investigate gender-specific determinants of household poverty. This research finds that education, digital literacy, financial inclusion, and the employment sector are significant factors influencing poverty status, with female-headed households facing disproportionately higher risks. These gaps are mainly attributed to systemic barriers in financial access, digital literacy gaps, and limited labor market opportunities for women. This study emphasizes the importance of implementing gender-responsive policy measures, including targeted education, enhanced digital literacy training, and inclusive financial programs. By presenting empirical evidence from Indonesia, this study contributes to the discourse on gender and poverty, offering actionable insights for the development of inclusive poverty alleviation strategies. Full article

Energy poverty is a multidimensional phenomenon that impairs access to basic energy services and threatens social well-being, particularly in disadvantaged rural communities. This study investigates the extent and drivers of household energy poverty in a Hungarian village through a survey-based analysis (N = 257) conducted in early 2025. The sample is not nationally representative, however, it reflects approximately 20% of the total village population (1331 inhabitants). This study aims to identify vulnerable household profiles, explore correlations between socio-economic and housing factors and perceived thermal comfort, and compare the effectiveness of multiple measurement indicators the 10% rule, low income high cost, 2M, and M/2. We employ descriptive statistics, Pearson correlation, Fuzzy C-Means clustering, and linear regression, revealing that over half of the sample is energy poor according to the 10% rule, while the LIHC method identifies 29%. Our regression results confirm that cluster membership significantly influences perceived comfort levels (R² = 0.063, p = 0.002). We conclude that single-indicator approaches are insufficient to capture the nuanced realities of rural energy poverty, therefore, we recommend the development of a rural energy poverty index. Such a tool could help identify affected households and support the formulation of context-sensitive, evidence-based energy and social policy interventions. Full article

In order to fulfil SDG 13—taking urgent action to combat climate change and its impact—SDG 2—ending hunger and poverty—and the African Union CAADP Strategy and Action Plan: 2026–2035, which’s goal is ending hunger and intensifying sustainable food production, agro-industrialisation, and trade, the resilience of commercial livestock farmers to agricultural droughts needs to be enhanced. Agricultural drought has affected the economies of many sub-Saharan African countries, including South Africa, and still poses a challenge to commercial livestock farming. This study identifies and determines the factors affecting commercial livestock farmers’ level of resilience to agricultural drought. Primary data from 123 commercial livestock farmers was used in a principal component analysis to estimate the agricultural drought resilience index as an outcome variable, and the probit model was used to determine the factors influencing the resilience of commercial livestock farmers in the Northern Cape Province of South Africa. This study provides a valuable contribution towards resilience-building strategies that are critical for sustaining commercial livestock farming in arid regions by developing a formula for calculating the Agricultural Drought Resilience Index for commercial livestock farmers, significantly contributing to the pool of knowledge. The results showed that 67% of commercial livestock farming households were not resilient to agricultural drought, while 33% were resilient. Reliance on sustainable natural water resources, participation in social networks, education, relative support, increasing livestock numbers, and income stability influence the resilience of commercial livestock farmers. It underscores the importance of multidimensional policy interventions to enhance farmer drought resilience through education and livelihood diversification. Full article

A partially ordered set (or a poset, for short) is a set endowed with a partial order relation, i.e., with a reflexive, anti-symmetric, and transitive binary relation. As mathematical objects, posets have been intensively studied in the last century, coming to play essential roles in pure mathematics, logic, and theoretical computer science. More recently, they have been increasingly employed in data analysis, multi-criteria decision-making, and social sciences, particularly for building synthetic indicators and extracting rankings from multidimensional systems of ordinal data. Posets naturally represent systems and phenomena where some elements can be compared and ordered, while others cannot be and are then incomparable. This makes them a powerful data structure to describe collections of units assessed against multidimensional variable systems, preserving the nuanced and multi-faceted nature of the underlying domains. Moreover, poset theory collects the proper mathematical tools to treat ordinal data, fully respecting their non-numerical nature, and to extract information out of order relations, providing the proper setting for the statistical analysis of multidimensional ordinal data. Currently, their use is expanding both to solve open methodological issues in ordinal data analysis and to address evaluation problems in socio-economic sciences, from multidimensional poverty, well-being, or quality-of-life assessment to the measurement of financial literacy, from the construction of knowledge spaces in mathematical psychology and education theory to the measurement of multidimensional ordinal inequality/polarization. Full article

Energy poverty, resulting from poor energy efficiency and economic and social barriers to accessing appropriate, modern, and sustainable energy services, remains a critical issue in Jordan, a country facing growing climate pressures, particularly given its history of rapid urbanization. This study examines energy poverty through a multidimensional lens, considering its spatial and socio-demographic variations across Jordan. Drawing on data from 19,475 households, we apply a novel energy poverty index and binary logistic regression to analyze key determinants of energy poverty and discuss their intersection with climate vulnerability. The energy poverty index (EPI) is structured around four pillars: housing, fuel, cooling, and wealth. The results show that 51% of households in Jordan are affected by energy poverty. Contributing factors include geographic location, gender, age, education level, dwelling type, ownership of cooling appliances, and financial stability. The results indicate that energy poverty is both a socio-economic and infrastructural issue, with the highest concentrations in the northern and southern regions of the country, areas also vulnerable to climate risks such as drought and extreme heat. Our findings emphasize the need for integrated policy approaches that simultaneously address income inequality, infrastructure deficits, and environmental stressors. Targeted strategies are needed to align social and climate policies for effective energy poverty mitigation and climate resilience planning in Jordan. Full article

In response to the escalating challenges of climate change and the urgent need to reduce greenhouse gas emissions, the energy transition has become a central priority of environmental policy worldwide. The European Union (EU), a global leader in implementing sustainable energy solutions, has pursued numerous initiatives aimed at advancing energy transformation. This paper presents the results of an empirical study assessing the efficiency of the energy transition process in the EU-27 countries over the 2013–2023 period. The assessment is based on the dynamic changes in selected indicators relevant to the energy transition, including decarbonization of the energy sector, improvements in energy efficiency, the share of renewable energy sources, energy import dependency, greenhouse gas emissions, and the extent of energy poverty. A multidimensional analysis was conducted using a specially developed energy transition efficiency index, where indicator weights were determined through the Analytic Hierarchy Process. The study also examined two distinct sub-periods (2013–2018 and 2018–2023), as well as a series of shorter, two-year intervals (2013–2015, 2015–2017, 2017–2019, 2019–2021, and 2021–2023), enabling a more nuanced analysis of the temporal evolution of transition efforts. Additionally, principal component analysis was employed to classify the EU-27 countries based on the similarity of their energy transition profiles. The findings reveal significant disparities in the pace and scope of energy transition across member states. Luxembourg, Malta, and the Netherlands demonstrated the most dynamic progress during the study period, followed by Sweden, Denmark, Germany, and Estonia. In contrast, Bulgaria, Hungary, Poland, Latvia, Croatia, and Romania recorded the lowest performance. These differences underscore the varying starting points, policy approaches, and implementation speeds among EU countries in achieving energy transition objectives. Full article

Understanding the complex and multidimensional nature of poverty is essential for designing effective and targeted policy interventions in rural Ethiopia. This study examined the determinants of multidimensional poverty in Bilate River Basin in South Ethiopia, employing cross-sectional household survey data collected in 2024. A total of 359 households were selected using a multistage sampling technique, ensuring representation across agro-ecological and socio-economic zones. The analysis applied the Generalized Ordered Logit (GOLOGIT) model to categorize households into four mutually exclusive poverty statuses: non-poor, vulnerable, poor, and extremely poor. The results reveal that age, dependency ratio, education level, livestock and ox ownership, access to information and credit, health status, and grazing land access significantly influence poverty status. Higher dependency ratios and poor health substantially increase the likelihood of extreme poverty, while livestock ownership and access to grazing land reduce it. Notably, credit use and access to information typically considered poverty reducing were associated with increased extreme poverty risks, likely due to poor financial literacy and exposure to misinformation. These findings underscored the multidimensional and dynamic nature of poverty, driven by both structural and behavioral factors. Policy implications point to the importance of integrated interventions that promote education, health, financial literacy, and access to productive assets to ensure sustainable poverty reduction and improved rural livelihoods in Ethiopia. Full article

The rapid shift to online education during the COVID-19 pandemic exacerbated mental health risks for students, particularly those experiencing multidimensional poverty—a potential contributor to psychological distress in digital learning environments. This study examines how poverty-driven techno-distress (technology-related stress) impacts university students’ mental health, focusing on 202 Chilean learners engaged in remote classes. Using partial least squares structural equation modeling (PLS-SEM), we analyzed multidimensional poverty and its association with techno-distress, measured through validated scales. The results suggest that poverty conditions are associated with 32.5% of technostress variance (R² = 0.325), while techno-distress may indirectly relate to 18.7% of students’ dissatisfaction with academic life—a proxy for emerging mental health risks. Importance–performance map analysis (IPMA) identified housing habitability (e.g., overcrowding, inadequate study spaces) and healthcare access as priority intervention targets, surpassing purely digital factors. These findings indicate that techno-distress in online education may function as a systemic stressor, potentially amplifying pre-existing inequities linked to poverty. For educators and policymakers, this highlights the urgency of early interventions addressing students’ physical environments alongside pedagogical strategies. By framing techno-distress as a public health challenge rooted in socioeconomic disparities, this work advances preventive approaches to safeguard student well-being in increasingly hybrid educational landscapes. Full article