Multidimensional poverty analysis and its determinants in Rwanda

Multidimensional deprivations in Pakistan: Regional variations and temporal shifts

According to official statistics, the incidence of absolute poverty in Italy has sharply risen from 3.6 in 2005 to 7.7 percent in 2020, and this number is likely to rise in the post-pandemic period. However, standard poverty measures only consider the monetary aspect of poverty, neglecting the multidimensional nature of the phenomenon. The last decades have offered solid empirical evidence to guide political efforts to tackle both multidimensional wellbeing and poverty. In these times of rising inequalities, these efforts seem particularly valuable for identifying the most vulnerable groups. While Italy has made significant progress in defining multidimensional wellbeing, less attention has been given to multidimensional poverty. Hence, the goal of this paper is to offer a means for measuring multidimensional poverty (MPI) in Italy based on the Alkire-Foster method by using a widely recognized national framework for wellbeing (BES equitable and sustainable wellbeing) as the normative basis for the construction of the index. The contribution of the paper is twofold: (1) on the theoretical side, it seeks to increase the usability of national and international frameworks for wellbeing by proposing a national assessment scheme as a normative base for defining the dimensions of poverty; (2) on the empirical side, it provides evidence on the frequency and composition of multidimensional poverty in Italian regions. The results show that multidimensional poverty in Italy has increased over time, with the percentage of individuals considered as multidimensionally poor rising from 9.5 percent in 2005 to 17.5 percent in 2015. Moreover, a dimensional breakdown across regions and logistic regression shows that being older, female, from the South and married or widowed increases the probability of facing multidimensional poverty.

Paper 2: Individual Specific Weighting Scheme to a Multidimensional Poverty Measure Abstract Weights in the estimation of multidimensional poverty have a central role by showing the relative importance of dimensions. This paper proposed two differentweighting schemes: endowment and distributional based weighting schemes.The later weighting scheme gives more weight to the dimension with small number of deprived individuals. On the other hand, the endowment based weighting scheme gives more weight to the dimension with large number of deprived individuals. The proposed weighting schemes considerboth distributional equity and simultaneous deprivations of indicators. Using the Ethiopian rural household survey (ERHS) data for the year 2004, the paper compared the proposed weighting schemes with the equal weighting scheme approach. The empirical result showed that, the multidimensional poverty index (MPI) estimation using endowment based equity weight has a lower estimate than the equal weighting approach. This happened because the indicators that have a small number of deprived individuals have got a higher weight under the equal weighting approach.

The present study uses secondary data collected from National Family Health Survey (NFHS) rounds 4 and 5 to track the progress in the multidimensional poverty status of the Indian population. We use differential methodology to identify poor individuals in both rural and urban areas. Further, the multidimensional poverty index (MPI) and agriculture are closely associated, and this is also reflected in the study. Among the agro-climatic regions, it was found that MPI is relatively higher in the Middle Gangetic Plains Region, while MPI in the West Coast Plains and Hills Region is relatively lower compared with other agro-climatic regions. As we develop a new MPI for different agro-climatic zones (ACZ), it has significant policy relevance. We believe that this new index provides a substantial contribution to the literature on poverty measurement and could be an important tool to track progress towards the achievement of SDG 1.

BackgroundThe global poverty profile shows that Africa and Asia bear the highest burden of multidimensional child poverty. Child survival and development therefore depend on socioeconomic and environmental factors that surround a child.The aim of this paper is to measure multidimensional child poverty and underpin what drives it among children aged 5 to 18 years in a resource poor region of Burkina Faso.MethodsUsing primary data collected from a cross sectional study of 722 households in the Mouhoun region of Burkina Faso, the Alkire–Foster methodology was applied to estimate and decompose child poverty among children aged 5–18 years. Seven broad dimensions guided by the child poverty literature, data availability and the country’s SDGs were used. A binary logistic regression model was applied to identify drivers of multidimensional child poverty in the region.ResultsThe highest prevalence of deprivations were recorded in water and sanitation (91%), information and leisure (89%) followed by education (83%). Interestingly, at k = 3 (the sum of weighted indicators that a child must be deprived to be considered multidimensionally poor), about 97% of children are deprived in at least three of the seven dimensions. At k = 4 to k = 6, between 88.7 and 30.9% of children were equally classified as suffering from multidimensional poverty. The odds of multidimensional poverty were reduced in children who belonged to households with a formally educated mother (OR = 0.49) or stable sources of income (OR = 0.31, OR = 0.33). The results equally revealed that being an adolescent (OR = 0.67), residing in the urban area of Boromo (OR = 0.13) and rural area of Safané (OR = 0.61) reduced the odds of child poverty. On the other hand, child poverty was highest among children from the rural area of Yé (OR = 2.74), polygamous households (OR = 1.47, OR = 5.57 and OR = 1.96), households with an adult head suffering from a longstanding illness (OR = 1.61), households with debts (OR = 1.01) and households with above five number of children/woman (OR = 1.49).ConclusionChild poverty is best determined by using a multidimensional approach that involves an interplay of indicators and dimensions, bearing in mind its causation.

Using unit data from 42,762 elderly from 75th round of National Sample Survey, this paper estimates the extent of multidimensional poverty among elderly in India. Multidimensional poverty is measured in the social, economic, health and energy, water, and sanitation dimensions using a set of nine indicators. The incidence of multidimensional poor was estimated at 46% among elderly with an intensity of poverty of 42%. The multidimensional poverty among the elderly was highest in Jharkhand followed by Odisha and lowest in Goa and Delhi. The estimate of multidimensional poverty is higher in rural areas, among the oldest old and female. The highest contribution of multidimensional poverty among elderly is due to deprivation in insurance coverage and economic dependency. Findings of this study underscore the need for strengthening social security and insurance measures to protect the elderly from multiple deprivations.

It is argued that poverty is more than lack of income and consumption. In other words, unidimensional approach is not able to present true picture of deprivation. As the poor person can be deprived from education, good health, nutritious food and clean drinking water. Therefore, this study aimed to determine multidimensional poverty in Pakistan at provincial, regional level for all available surveys of Pakistan Social and living standard (PSLM). This study covered three dimensions’ education, health and living standard along with nine sub-dimensions. The present study used Alkire foster methodology with different cutoff for rural and urban regions. The result revealed that Pakistan multidimensional poverty index (MPI) in 2004-05 is 0.16 which is slightly decreased to 0.12 in 2019-20. In the same way, head count index showed a little decline of 1 percent i.e. 49% in 2004-05 to 48% in 2019-20. Similarly, intensity of poverty declined from 33% in 2004-05 to 31% in 2019-20. The empirical analysis showed little improvement in health, education and living condition over the past sixteen years. Further, multidimensional poverty remains higher in rural areas than urban areas. This study identified that the most deprived province is Balochistan among all provinces. From policy perspective government officials can alleviate poverty by providing education and employment opportunities. As it is the basic condition of millennium and sustainable development goals (MDG’s) to give basic needs of life such as food, shelter and education. Keywords: Multidimensional Poverty, Health, Education, Living Standard. JEL classification: I1, I2, I3

As one of the most severe pandemics in decades, COVID-19 has left lasting impacts on health systems, economies, and social structures across the world. Existing research has documented varied socio-economic effects of the pandemic globally, yet there remains a significant gap in understanding how COVID-19 has affected multidimensional poverty in Bangladesh. This research examines the impact of COVID-19 on the MPI (multidimensional poverty index) in both urban and rural households considering six dimensions: income, health, education, living standards, family and social relationships, and information accessibility taking a total of 29 indicators, each equally weighted. Household surveys using a pre-tested structured questionnaire were conducted in two Upazilas of the Jashore district: Chaugachha (150) and Bagharpara (150) in two strata: urban and rural in two unions per Upazila. The result indicates that MPI has increased drastically by around 172.7% within 2019–2021. The analysis reveals that urban areas showed greater multidimensional poverty index (MPI) growth (40%) than rural areas (28.9%), driven by both rising poverty incidence (+ 8 pp) and intensifying deprivation (+ 8 pp), despite rural areas maintaining higher absolute poverty levels. Health is the most influential factor, followed by education and social capital. The urban faced more difficulties in accessing health facilities due to stricter hospital regulations, and nutrition deficiencies occurred for price hike conditions. Students had limited access to uninterrupted internet facilities which declined the attendance of online classes during the lockdown period and caused poor results and dropouts. Simultaneously, social capital was eroded as lockdowns disrupted community support networks and limited the informal assistance that many vulnerable families rely on during crises. These differential impacts highlight the need for spatially targeted policy responses, with particular emphasis on urban social protection systems and multidimensional poverty alleviation in both domains. This study advances pandemic preparedness by revealing how deprivation dynamics can strengthen sustainable development goals (SDG) synergies (1: poverty, 2: hunger, 3: health, 4: education, 6: water), enabling social protection systems to serve as multi-sectoral shields against multidimensional poverty during health crises.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12889-025-25837-9.

The recognition of poverty as a multidimensional concept has led to the development of more adequate tools for its identification. By allowing for subgroup and regional decompositions, those instruments are useful to allocate public action where most needed. This paper applies the Alkire and Foster (2011a) Multidimensional Poverty Index (MPI) to study single-mother and biparental families in Nicaragua, modifying its original structure to match more closely with the country’s current structural problems. Using Nicaragua’s last Demographic and Health Survey (DHS 2011/2012), our multidimensional poverty figures contrast with the government’s national poverty line estimates, suggesting that income poverty overestimates the number of poor people. Thus, our MPI can help as a complement for traditional consumption poverty and Basic Needs analysis; even extending the exploration by using other official household surveys. On the other hand, multidimensional poverty analysis found poverty dominance of male-headed families over single-mother and female-headed biparental families, which serves to contradict the notion of women being more vulnerable than men. Within the MPI, the most important contributor was the Living Standards dimension, composed by indicators directly related to housing conditions, and the second most deprived dimension was Education. A strong policy implication that arises from our findings is the reduction of the urban–rural poverty gap. Specifically, our findings exalt the need for governmental policies directed to reduce Nicaragua’s housing and educational deficits as a priority, particularly in rural areas.

Inclusive finance is often considered to be a critical element that makes growth inclusive, as access to finance can enable the poor to lift themselves from income poverty. However, can it play such a role when the poor are in multidimensional poverty? Why does financial exclusion and poverty still exist in countries with vigorous development of inclusive finance? We build an evolutionary game model to analyze the equilibrium strategies of inclusive financial institutions and the poor in poverty reduction activities to find the answers. As there is a high incidence of poverty and serious financial exclusion in rural areas of China, we test the poverty reduction effectiveness of inclusive financial development on the poor with different labor capacity in rural China from 2010 to 2016 based on survey data of China Family Panel Studies and relevant statistics collected from 21 provinces. Our study finds there are differences in poverty alleviation effects of inclusive financial development among the poor with different labor capacities; if financial institutions target the service precisely to the working-age population in rural areas, they will achieve the dual goals of maintaining institutional sustainable development and alleviating poverty; And the development of inclusive finance in aspects of permeability, usability, and utility can significantly reduce multidimensional poverty. Therefore, to further improve the multidimensional poverty reduction performance and stimulate the endogenous motivation of the poor, it is necessary to strengthen the support for financial resources served to the working-age population, and to improve the development of rural inclusive finance in aspects of quality and affordability.

Child stunting (chronic undernutrition) is a major public health concern in low- and middle-income countries. In Rwanda, an estimated 33% of children are affected. This study investigated the household living conditions and the impact of gender-related decision-making on child stunting. The findings contribute to ongoing discussion on this critical public health issue. In December 2021, a population-based cross-sectional study was conducted in Rwanda’s Northern Province; 601 women with children aged 1–36 months were included. Stunting was assessed using low height-for-age criteria. The Multidimensional Poverty Index (MPI) was used to determine household socioeconomic status. Researcher-designed questionnaires evaluated gender-related factors such as social support and household decision-making. Multivariable logistic regression analysis identified risk factor patterns. Six hundred and one children were included in the study; 27.1% (n = 163) were diagnosed as stunted; there was a higher prevalence of stunting in boys (60.1%) than girls (39.9%; p<0.001). The MPI was 0.265 with no significant difference between households with stunted children (MPI, 0.263; 95% confidence interval [CI], 0.216–0.310) and non-stunted children (MPI, 0.265; 95% CI, 0.237–0.293). Most households reported a lack of adequate housing (78.9%), electricity (63.0%), good water sources (58.7%), and proper toilets (57.1%). Male-headed households dominated (92% vs. 8.0%; p = 0.018), and women often shared decision-making with their partners. However, 26.4% of women reported forced sexual intercourse within marriage (Odds Ratio [OR] 1.81; 95% CI, 1.15–2.85). Lack of support during illness ([OR], 1.93; 95% CI, 1.13–3.28) and absence of personal guidance (OR, 2.44; 95% CI, 1.41–4.26) were significantly associated with child stunting. Poverty contributes to child stunting in the Northern Province of Rwanda. Limited social support and women’s lack of decision-making power in the household increase stunting rates. Interventions should empower women and address the broader social and economic context to promote both women’s and children’s health.

What can we learn about the natural disasters and multidimensional poverty link for artisanal fishery in Chile?

This study aims to measure and analyze multidimensional poverty in Iran using the Alkire-Foster (AF) index across five dimensions: education, employment, living standards, health, and housing. The study period covers the years 2017 to 2019. The results indicate that approximately 28% of individuals in rural areas and 25% in urban areas are poor. Additionally, about 51% of the poor live in rural areas, while 49% reside in urban areas. The highest deprivation in both regions pertains to employment, accounting for around 40%. In other dimensions, deprivation rates are 16% in education, 4% in living standards, 24.5% in health, and 15.5% in housing. The multidimensional poverty index (MPI) is calculated to be 10% for urban areas and 11.5% for rural areas. The findings show that women, particularly in the education dimension, experience higher levels of deprivation in both urban and rural areas. This study demonstrates that poverty is a multidimensional phenomenon, and effective policies for poverty reduction must address all its dimensions. Based on the results, improving employment conditions and enhancing living standards are primary priorities for reducing poverty. Additionally, special attention to improving health and education services, especially for women, is essential. The research indicates that targeted and precise policies can significantly reduce poverty and social inequalities.

In order to realize the poverty alleviation of China's current standards to achieve total poverty alleviation by 2020, the state has proposed a strategic plan for precision poverty alleviation. Based on the multidimensional poverty analysis methods and latest research results proposed by Alklre and Foster [1]. Taking the existing poverty data sources in Fengqing County of Yunnan Province as the research object, the selection of poverty dimension indicators is carried out. The multi-dimensional poverty threshold deprivation index system of five dimensions and seven indicators is designed, the multidimensional poverty measurement model is designed, and the RBF (radial basis function) neural network technology is used to measure the poverty depth of poor households. Using Python programming to achieve model programming, embedding the platform to achieve poverty measurement function, and constructing a scientific and accurate data analysis model for poverty alleviation, providing decision support for the government to carry out accurate poverty alleviation.

Analysis of incidence, intensity, and gender perspective of multidimensional urban poverty in Kenya