Incidence Of Multidimensional Poverty Research Articles

What are the factors associated with catastrophic health expenditure in Colombia? A multi-level analysis.

Target 3.8 of the Sustainable Development Goals calls for the guaranteeing of universal health service coverage without generating financial risks for households and individuals. In Colombia, there is no up-to-date information on the proportion of households that suffer catastrophic health expenditure (CHE), nor about how these expenses are associated with the place of residence. To contribute to an understanding of these issues, this study analyses the differences in the levels of CHE among Colombian households, and their association with the province and area (urban or rural) of residence. This is a descriptive and analytical cross-sectional study using the 2016-2017 National Household Budget Survey, the household and population Census 2018, and the Register of Health Providers 2017. We used the definition of CHE proposed by the World Health Organization, with a threshold of 20%. We estimated the percentage of households facing CHE, and its intensity, and estimated a multi-level logistic regression model, using as the dependent variable the question of whether a household experienced CHE, and the province as a second level, where explanatory variables related to the province were included. We found differences in CHE levels according to the province of residence. At the national level, 1.77% of households experienced CHE, and households in the provinces of Boyacá (5.04%), Nariño (4.04%), Cauca (3.82%), and Chocó (3.78%) faced the highest CHE. For most households with CHE in these provinces, spending on medicines and medical consultations represented close to 50% of their out-of-pocket spending. The multi-level logistic regression model indicated that there are significant variations in CHE attributed to the provinces under study, where the contextual variables of hospital-bed density (AOR = 0.91; 95% CI 0.86-0.96) and incidence of multi-dimensional poverty (AOR = 1.13; 95% CI 1.01-1.30) were factors associated with CHE. For an urban household, 6.58% of the CHE variation is attributed to the province in question, while for a rural household the corresponding variation is 1.56%. The geographical location of the household is a key factor when studying CHE in Colombia, where rural households present higher levels of CHE, mainly in the delivery of medicines and medical consultations. The findings reveal the need to analyse financial protection at the local level and establish policies to protect households, especially poor households, from CHE.

Dynamics of multidimensional poverty and its determinants among the middle-aged and older adults in China

The aim of this study was to understand the dynamics of multidimensional poverty and its determinants among mid-aged and older adults. We used 2011, 2013, 2015, and 2018 data from the China Health and Retirement Longitudinal Study. We utilised basic descriptive statistics, the poverty transition matrix, Kaplan–Meier estimates, and the discrete-time proportional hazards model for data analysis. From 2011 to 2018, the incidence of multidimensional poverty among mid-aged and older people basically decreased, but the average poverty intensity remained stable. Most mid-aged and older adults had transient multidimensional poverty. The longer an individual remained multidimensionally poor, the smaller the probability of exit from poverty; The longer an individual remained nonpoor after escaping from poverty, the smaller the probability of returning to poverty. As to other factors, individual characteristics, family structure, living arrangements, social capital, and living areas significantly affected the risks of multidimensional poverty exit and reentry. Based on these results, the government should implement targeted interventions for frail older adults with the identified characteristics to prevent them from persistent multidimensional poverty or return to poverty.

Impact of poverty alleviation through relocation: From the perspectives of income and multidimensional poverty

Poverty alleviation through relocation (PAR) is a milestone project in winning the battle against extreme poverty and aims to relocate poor people from inhospitable areas and lift them out of poverty. The effect of PAR on poor households merits evaluation as it is also the basis for understanding the achievements of targeted poverty alleviation and preventing a large-scale return to poverty. This study analyzed the effect of PAR on poor households from the perspectives of income and multidimensional poverty, based on panel data of 1009 poor households from eight provinces in China. The results showed that the incidence of multidimensional poverty in poor households exceeded that of income poverty, and its decline was faster than that of income poverty. However, the overlap between multidimensional poverty and income poverty was low, at 26.3%, 4.9%, and 0% in 2016, 2018, and 2020, respectively. PAR showed a significantly negative effect on poor households’ income and multidimensional poverty, and the longer the relocation time, the more significant the effect. PAR reduced the income poverty of poor households mainly by increasing their wage income and property income, and multidimensional poverty mainly by improving their living standards. The impact of PAR on income and multidimensional poverty is regional heterogeneous. Post-relocation measures should improve the income and capability of poor households through industrial development, employment assistance, infrastructure upgrades, and public service improvements. In addition, the income and multidimensional poverty standards should be jointly adopted in the governance of relative poverty.

Nexus of multidimensional poverty and educational deprivation among the social groups: Evidence from a developing country

The interface between the incidence of multidimensional poverty and its fallout on educational deprivation is often debated in the realm of human development perspective. The paper aims to explore the nexus of multidimensional poverty and educational deprivation among the households belonging to different social groups, namely Scheduled Castes (SC), Scheduled Tribes (ST), Other Backward Castes (OBC), and Forward Castes (FC) in rural areas of a developing country, India (Gaur & Rao, 2020). A decomposition analysis within the human development framework using primary data from selected regions of India, namely Kerala, West Bengal, and Bihar, is attempted to explore whether there is any deprivation gap in education in the selected regions. The multidimensional poverty and educa-tional deprivation of select states are analysed using the Multidimensional Poverty Index (MPI) developed by Oxford Poverty and Human Development Initiatives (OPHI) (Alkire & Foster, 2011; Organisation for Economic Co-operation and Development [OECD], 2022; PIB Delhi, 2020; Ballon & Krishnakumar, 2010). The study identified the determinants of educational deprivation and its nexus with the multidimensional poverty of the households belonging to the social groups of rural India. The paper highlights the influence of disproportional attainment of education, which worsens deprivation leading to unequal outcomes of human development among the different social groups of rural India. The discussion further unfolds the incidence of disproportional multidimensional poverty among social groups in rural India that enables the explanation of the policy implications and interventions in educational entitlements.

The Impact of Social Capital on Multidimensional Poverty of Rural Households in China.

Getting rid of multidimensional poverty is both the people's wish and the direction of governance. Based on 2018 China Household Tracking Survey (CFPS) data, this paper identifies household multidimensional poverty in rural areas using a combination of the MPI index and the A-F method. The relationship between social capital and multidimensional poverty was also empirically analyzed using a Logit model. The results showed that: (1) 1599 multidimensional poverty households were identified, the incidence of multidimensional poverty was 24.94%, and the multidimensional poverty index was 0.103. In terms of poverty incidence, the three highest indicators of poverty incidence are adult education, health, and chronic diseases, reaching 42.06%, 37.65%, and 29.90%, respectively, and mainly concentrated in the education and health care systems. (2) Social capital can significantly reduce the probability of multidimensional poverty in rural households. Among them, social network significantly and negatively affects the occurrence of multidimensional poverty in rural households, social trust in neighbors has a significant negative effect on multidimensional poverty in rural households at the 1% level, and social prestige is positively related to multidimensional poverty in rural households. (3) Age of household head, household size, and income from working outside the home are significantly associated with multidimensional poverty in rural households. This paper expands the scope of social capital theory research and provides new perspectives and empirical evidence for alleviating multidimensional poverty.

An innovative approach to measure multidimensional poverty: A synthesis method

This paper presents a new approach to measure multidimensional poverty, combining the strengths of the Fuzzy Set method and the Alkire and Foster method, and addresses some of their limitations. The approach applies the Fuzzy Set method to resolve the discontinuity problem that arises when the latter is used in the Alkire and Foster method to identify the multidimensionally poor people. The resultant process satisfies poverty axioms of a good poverty measure. It also incorporates some s statistical techniques in selecting indicators and computing weights for the membership function. The empirical assessment is done to primary data, collected from the Uva province of Sri Lanka, an economically, neglected comprising of people representing various socio-economic backgrounds. This study examines poverty under three main dimensions; material, social dimensions and human capital. The results reveal that, 42.3 percent of people in the Uva province have a propensity to poverty. The incidence of multidimensional poverty is 56 percent and the intensity is 48.6 percent. The adjusted fuzzy headcount index is 27.2 percent. Interestingly, the highest contribution to overall poverty comes from deprivation by social dimensions. The application of the this method undoubtedly would encourage the analysis of further research on multidimensional poverty.

Mapping Multi-Dimensional Poverty Learning Among Fisherfolk in Thiruvananthapurum District in Kerala, India

Kerala has received worldwide attention for its remarkable achievements in social sector. However, marine fisherfolk is an ‘outlier' community in the state. Many studies identified fisherfolk in Thiruvananthapuram district as the most vulnerable among them. As poverty is a cause and consequence of vulnerability, this paper analyses the incidence and intensity of multidimensional poverty among fisherfolk in Thiruvananthapuram. The study employs cross-sectional research design and primary data was collected from 600 fisher households in three coastal villages. Multidimensional poverty index (MPI) was constructed by using Alkire-Foster methodology. Results indicate that MPI of marine fisher-folk households is 0.1 and 26 percent of these households are MPI poor. As per estimates of OPHI,MPIof Kerala is 0.004 and only one percent of people in Kerala are MPI poor. This reveals that incidence of multidimensional poverty is higher among fisherfolk as compared to general population in Kerala. Average intensity of deprivation among the poor is almost 40 percent.

Social protection and multidimensional poverty: Lessons from Ethiopia, India and Peru

• We investigate the impact of three large-scale social-protection schemes in Ethiopia, India, and Peru on multidimensional poverty. • We employ a difference-in-differences strategy to produce estimates that deal with non-random program assignment. • We find a significant decline in multidimensional poverty incidence and intensity, particularly for the severely poor. • We also find a positive sustained impact on asset formation, livestock holding, and some living standard indicators. • The effects of the social programs mainly emanate from the direct income effect of benefits irrespective of their design. We investigate the impact of three large-scale social-protection schemes in Ethiopia, India, and Peru on multidimensional poverty. Using data from the Young Lives cohort study, we show the trend, changes and evolution of multidimensional poverty for individuals in program participant households. We follow a number of strategies to produce estimates that deal with non-random program placement. Our findings show that both the incidence and intensity of multidimensional poverty declined in all three countries over the period 2006–2016, more so for program participants than non-participants. We find positive short-term impact on asset formation, livestock holding, and some living standard indicators. In all three countries these positive impacts are sustained even in the medium and longer-term.

Emergency surgery workforce and its inverse relationship with multidimensional poverty in Colombia

General surgeons, anesthesiologists, obstetricians and gynecologists (ob-gyns), and orthopedic surgeons are the vital disciplines to provide emergency surgery within a healthcare system. This paper aims to examine the relationship (if any) between multidimensional poverty (MDP) and GDP per-capita with the emergency surgery workforce density in Colombia. We performed an ecological study, where the observation units were the 32 Colombian departments. The total numbers of general surgeons, anesthesiologists, ob-gyns, and orthopedic surgeons were obtained from the "Registro Unico Nacional de Talento Humano en Salud" (ReTHUS) registry. The 2020 population projections, the incidence of MDP and the GDP per capita were obtained from the Colombian National Administrative Department of Statistics. A spearman's correlation coefficient was calculated to measure the strength of the correlations between the surgical workforce density with MDP and GDP per-capita. There were significant moderate inverse linear correlations between the incidence of multidimensional poverty and workforce density. The correlation coefficients for the incidence of multidimensional poverty and the workforce density were - 0.5273, - 0.5620, - 0.4704, and - 0.4612 for surgeons, anesthesiologists, ob-gyns, and orthopedic surgeons, respectively. Conversely, the correlation coefficients for the GDP per-capita and the workforce density were 0.4045, 0.3822, 0.4404, and 0.3742 for surgeons, anesthesiologists, ob-gyns, and orthopedic surgeons, respectively. This study found that Colombian trauma and emergency surgery workforce density was inversely and directly correlated with multidimensional poverty and GDP per-capita levels, respectively. The relationship of these economic indicators with the surgical capacity deserves further investigation.

Multidimensional Poverty in Brazil in the Early 21st Century: Evidence from the Demographic Census

This paper examines multidimensional poverty in Brazil in 2000 and 2010, based on the microdata of the Demographic Censuses. Our analysis is disaggregated into five classes of municipalities according to their degree of urbanisation and remoteness, highlighting wide rural–urban inequalities in the levels and dynamics of poverty. We compare estimates of traditional monetary poverty with multidimensional poverty measures based on two methods: (i) the Alkire-Foster counting identification approach; and (ii) the Permanyer two-stage poverty identification approach. The two-stage approach introduces the concepts of complementarity/substitutability within and across poverty dimensions, which enables a more precise identification of the population targeted by anti-poverty policies. All methods highlight substantial progress in poverty alleviation. In absolute terms, the reduction in the incidence of multidimensional poverty was significantly larger in the initially poorest areas—rural and intermediate municipalities, as well as those in the North and North–East regions. Important advances were made in standard of living, especially in the access to electricity, durable consumer goods and private bathroom in the households in rural and intermediate municipalities. However, remote municipalities remain relatively poorer from any perspective, facing more difficulties in reducing monetary poverty.

Pobreza multidimensional no Brasil: uma análise do período 2004-2015

RESUMO Este artigo constrói um Índice de Pobreza Multidimensional (IPM) para o Brasil, utilizando informações da PNAD/IBGE e faz a análise de sua evolução no período 2004-2015. O IPM proposto foi adaptado daquele desenvolvido por Alkire e Santos (2013). Os resultados obtidos corroboram a redução da incidência da pobreza multidimensional no Brasil. Contudo, as pessoas saem da pobreza para a condição de vulnerabilidade, mostrando uma melhoria gradual das condições de vida da população. Regionalmente, houve redução da incidência da pobreza em todas as regiões, principalmente nas regiões Norte e Nordeste.

Multidimensional Poverty and Inequality: Insights from the Upper Blue Nile Basin, Ethiopia

As stated in the 2018 global Multidimensional Poverty Index (MPI) report, Ethiopia has the second largest multidimensionally poor population in Africa (after Nigeria). The global MPI was created to measure household’s multiple deprivations, but little systematic study has been carried out on the application of MPI measures on a smaller scale and vis-a-vis other measures of poverty. In addition, most of the few existing studies ignore any measure of inequality amongst the multidimensionally poor. This study explored multidimensional poverty in three different drought-prone agro-ecological settings of the Upper Blue Nile basin, Ethiopia. A preliminary participatory exercise was carried out at the study sites to select important indicators and then a structured survey was administered to 390 systematically and randomly selected households. The Alkire–Foster method was used to analyse multidimensional poverty and verified it with Correlation Sensitive Poverty Index (CSPI). Multidimensional poverty incidence, adjusted head count ratio and inequality were significantly different between study sites (p < 0.001). Results indicated a high incidence (88%, 82% and 80%), intensity (52%, 55% and 56%), MPI (46%, 45% and 45%) and inequality (53%, 60% and 63%) of poverty in Aba Gerima, Guder and Dibatie study sites, respectively. A high level of divergence was revealed between the MPI and CSPI in terms of identifying the poor. The living standard and land and livestock ownership dimensions contributed the most to MPI. The case study signifies the importance of inclusion of land and livestock indicators for the national MPI. Besides, it implies that researchers and policymakers need to account for smaller scale contextualised indicators and location differences when studying and designing anti-poverty interventions.

Pobreza multidimensional no Brasil: uma análise do período 2004-2015

The main goals of this paper were to construct a Multidimensional Poverty Index (MPI) for Brazil using data from PNAD and also provides an analysis of its evolution for the period 2004-2015. The proposed IPM follows the method developed by Alkire and Santos (2013). The results confirm the reduction on the incidence of multidimensional poverty in Brazil. However, people move out of poverty into the stage of vulnerability, showing a gradual improvement on living conditions. Regionally,there was a reduction in the incidence of poverty in the whole country, and notably in the North and Northeast regions. JEL Classification: I32; I31; D31.

Multidimensional Poverty: An Exploratory Study in Purulia District, West Bengal

This paper explores the incidence and extent of multidimensional poverty for the households in Purulia district, the western most backward district of West Bengal in India. In context of Purulia district the decompositions of multidimensional poverty index (MPI) across the social castes and across the indicators have also been explained. MPI and its decomposition across the sub-groups have been computed using the methodology developed by Alkire and Foster (2007) and Alkire et al. (2011). This study covers twelve non income indicators under three dimensions education, health and living conditions. Collecting a set of primary data from 698 households in Purulia district during 2018, this study reveals that the incidence of multidimensional poverty in the district of Purulia is higher than that in national level. But the breadth of poverty is almost equal to that in India as a whole. In respect of poverty there is wide variation across the social castes. Among the indicators, use of dirty cooking fuel, not having improved sanitation have highest contribution to the district MPI.

Multidimensional Poverty in Paraguay: Trends from 2000 to 2015

To meet Paraguay’s national development goals and the Sustainable Development Goals, policy makers require more information about poverty in the country. We propose a multidimensional poverty index (MPI) for Paraguay constructed using the Alkire–Foster dual-cutoff method for multidimensional poverty identification to complement existing national poverty measures based on income. Indicators, dimensions, weighting schemes, and cutoffs used in the Paraguayan MPI were determined based on national definitions of poverty and national and international development priorities. The MPI is estimated for the years 2000–2015 using national household surveys. From 2000 to 2015, the multidimensional poverty incidence in Paraguay declined by an average annualized rate of 9.2%, from 58% of the population in 2000 to 17% of the population in 2015. In 2015, 7% of the population is estimated to be living in multidimensional poverty, but not income poverty. This population would have remained invisible based on income poverty measures alone. This is the first MPI proposed for Paraguay that reflects the country’s national development priorities. The adoption of the MPI may assist policy makers in targeting previously invisible, vulnerable populations and assessing the impact of public policies on reaching the country’s development goals.

Urban Poverty and Inequality in Kenya

This paper explores urban poverty and inequality in Kenya. We use the 2009 Kenyan population census data and estimate multidimensional poverty and inequality measures in the capital city and other secondary cities and towns. The results of our analysis show that poverty levels vary considerably across the different hierarchies of cities and towns in the country. The incidence of multidimensional poverty is relatively lower in the capital city, Nairobi (27%), and its satellite towns such as Ruiru (22%) and Thika (27%), while the figure is relatively higher in other large secondary cities such as Mombasa (44%) and Kisumu (46%). However, we also find large disparities in poverty levels within these cities/towns. For instance, location level poverty estimates in Nairobi range from more than 60% in Korogocho and Laini saba locations to less than 5% in Kileleshwa and Kilimani. Consistent with this, location-based horizontal inequality estimates are the highest in Nairobi, followed by Thika town. We also find gender gaps in poverty levels in all urban centers. In particular, individuals living in female-headed households are on average poorer than those who live in male-headed households. Our results suggest that comparing living standards across different urban centers based on average poverty estimates masks significant within-urban-center inequalities. Understanding these spatial inequalities in multidimensional poverty is crucial to honing the targeting of anti-poverty policy.

Urbanization of multidimensional poverty: empirical evidences from Pakistan

Urban poverty has become an emerging dilemma in the developing countries, which is distinct from rural poverty due to several socio-economic attributes and remained unexplored at the national level. The methodological structure, encircles the absence of multiple domains i.e. health, education and housing services, to offer a deeper and wider understanding of wellbeing. The study estimates the magnitude of multidimensional poverty at regional level in urban Pakistan along with percentage contribution of each sub-group in overall poverty index through adjusted FGT measures on the basis of household integrated economic survey (HIES/PSLM) five data sets (1998–1999, 2001–2002, 2004–2005, 2005–2006 and 2007–2008). The overall incidence of urban poverty at the national level in Pakistan was estimated around 29, 32, 25, 29 and 28 % respectively during the study period. The incidence of multidimensional poverty on average slightly decreased across the regions (administrative divisions) over the span of 10 years, while urbanizing the multidimensional poverty dilemma through increasing the regional proportionate contribution. Meeting the core ideology of millennium development goals, present study emphasis the urbanization of poverty in the multidimensional spectrum at regional level in Pakistan and propose policy inputs to construct poverty reduction strategy papers (PRSPs) and curbing out urbanization of poverty.

Poverty assessment as a multidimensional socio-economic concept: the case of the Rawalpindi region in Pakistan

The definition on poverty has progressed into a multidimensional concept focusing more on socio-economic dimensions than being a mere measure of financial deprivation. Corresponding to this advancement, this study investigated the incidence of multidimensional poverty (MDP) in the Rawalpindi region of Pakistan, taking into account three dimensions, i.e. education, health and housing. Findings revealed an inconsistent declining trend of MDP over time. This inconsistency was mainly attributed to observed fluctuations in deprivation levels of education, health and housing in the region. Over time, education deprivation showed a significant net increase. Notably, the magnitude of MDP in rural areas was higher than in urban areas.

A Robust Multi-dimensional Poverty Profile for Uganda

We compute a Multi-dimensional Poverty Index (MPI) for Uganda following the specification by Alkire and Santos and the general approach of Alkire and Forster. Using household survey data we show how the incidence of multi-dimensional poverty has fallen in recent years and we use the decomposability features of the index to explain the reduction in multi-dimensional poverty. The robustness of our results is tested in a stochastic dominance framework and using statistical inference. Notably, we extend the one-dimensional analysis of stochastic dominance to include household size as a second dimension, thus taking into account that MPI indicators are collected at both household and individual levels. Moreover, we extend the standard two-stage application of the MPI to include a third stage, which is important given the high degree of multiple deprivations within the standard of living dimension.

Incidence of Multidimensional Poverty Among Riverine Households in Southwestern Nigeria

What constitutes poverty transcends the lack of income but generally captures such other subjective and supplementary aspects that represent human functioning and capability. This view enables the design and implementation of policies to alleviate poverty among the poor, especially the riverine households with their attendant risks. Data were obtained from 448 riverine households in South-western Nigeria to examine the level of multidimensional deprivation and poverty among them. The mean household size was 5; fifty-six (56%) having less than minimum 9 year compulsory and basic education; only about 16% of them having members gainfully engaged and about 68% of the household heads engaging in Onshore livelihood activities. Majority (60.3%) of the households suffered deprivation in eight indicators (61.54% of the total possible number of deprivation) and above, all (100%) of the riverine households being adjudged poor in about 6%, 12% and 19% respectively’ of the thirteen dimensions of deprivation. At dual cutoff value (k = 8), the adjusted multidimensional poverty rate of the households (M0 = 0.3422); adjusted poverty gap (M1 = 0.1608), and poverty severity (M2 = 0.0761) showed high level of inequality among the deprived households. Conclusively, poverty was manifested in basic standard of living commodities and services among the riverine households as indicated by their low level of education, limited access to hygienic source of drinking water, food, energy, health care, toilet facilities as well as improved means of livelihood.