Multidimensional Poverty Research Articles

Developing Micro-Insurance to Expand the Scope of Social Security for the Informal Economy in Vietnam

Social security is considered a fundamental means to reduce poverty, eliminate social exclusion and promote social cohesion, but the majority of workers in the informal economy are still deprived of the right to social security. Many studies show that microinsurance programs have a strong potential to reach actors in the informal economy and mobilize additional resources for social protection; microinsurance is effective in reducing vulnerability to risks, enhancing the ability to protect participants, and contributing to reducing income poverty as well as reducing multidimensional poverty. Developing micro-insurance contributes to social security, hunger eradication, poverty reduction, and promoting financial inclusion. The article used data collection methods, methods of analysis, synthesis, comparison, and contrast from secondary data sources, clarifying the theoretical basis for micro-insurance development to expand the scope of social security for the informal economy, international experience and the current status of micro-insurance implementation in Vietnam. The article also offers some recommendations/policy suggestions to develop microinsurance in Vietnam shortly.

Optimizing development aid allocation: A data-driven approach using unsupervised machine learning and multidimensional indices

Development aid, often termed foreign assistance, involves the voluntary transfer of resources like goods, services, or capital from governments and international aid agencies to support the development of recipient countries or their people. This practice holds significant importance in international relations and the national economy of many nations. It is also a heavily researched area in economics due to its potential to create a safer, more equitable, environmentally sustainable, and prosperous world. However, it's observed that donor interests often take precedence over recipient needs in aid allocation decisions. Since these allocations are determined by national policies, there is limited room for external input. Consequently, the success of Sustainable Development Goals (SDGs) relies heavily on donor interests. To address this challenge, we propose data-driven approaches to ensure recipient needs are considered and aligned with SDGs. This involves balancing the legitimate interests of donors, recipients, and disadvantaged individuals. In our study, we utilize multidimensional poverty measures to better understand the hardships people face. This approach offers a more accurate representation than traditional monetary indicators, which can miss important dimensions of deprivation. We employ unsupervised machine learning to analyze this data objectively and recommend countries most in need of aid. Such systems can assist donor countries and agencies in efficiently allocating aid, ensuring that the needs of beneficiaries and targeted development goals remain well-aligned.

Design of the Measurement Tools for the SDGs in the Technology-Based Biotechnology Spin-Off Biohogar R&D

Abstract: This article addresses the problem of the economic use of co-products or residues generated in coffee and cannabis crops in Cauca, Colombia. The impact on the social, productive, and economic contexts of the two productive chains is analyzed, highlighting the conditions of multidimensional poverty among coffee-growing families and the impact on the environment due to the generation of crop residues. A sustainable solution is presented through a technology-based Spin-Off company, Biohogar R&D, which transforms waste into bioconstruction materials, promoting sustainable development and compliance with the Sustainable Development Goals (SDG) and identifying their associated KPIs.

Impact of Education on Multidimensional Poverty Reduction at the Post-Poverty Alleviation Era in Xinjiang

Impact of Education on Multidimensional Poverty Reduction at the Post-Poverty Alleviation Era in Xinjiang

Data for decision-making for sustainable food systems transformation in the Eastern Cape of South Africa: what is needed?

Transforming global food systems to promote food and nutritional security can help alleviate both poverty and ill-health, and support sustainable development. Such transformations need to be tailored and sensitive to the vulnerabilities and needs of marginalized communities yet are hindered by knowledge gaps. In particular, the food and nutrition security needs of the most vulnerable are often poorly understood, as are the policy frameworks and resource requirements associated with meeting their needs. To aid the development of frameworks to address these gaps, we review the current state of indicators relating to food systems for the improvement of food and nutrition security at the national and sub-national levels in South Africa. We identify gaps in the decision-making data in South Africa, including absence of food and nutrition security indicators. Integration of the South African Multidimensional Poverty Index and Food System Dashboard indicators could help address this, especially if applied at a sub-national level. Participatory food system mapping could also link data collection with system-level interactions and feedback loops to inform sub-national stakeholders in achieving food and nutritional security.

Broadening the water affordability approach to monitor the human right to water

Multidimensional poverty measurements at the international level include the indicator of having access to safe drinking water within the optimal living standards. At the European level, though, the reference is to the overall affordability of the urban services provided to a household. As a multidimensional concept, though, water poverty must include lack of access (or even poor access) to water services. This paper assumes that the lack of access to certain levels of water services should be considered poverty in access to water, and proposes a multidimensional characterization of levels of service that takes as a reference the specific normative component of the human right to water. In other words, poverty in access to water is matched with deprivation in the realization of a human right. To exemplify the approach, the paper presents a proposal for an evaluative framework for the case of a household in a dense urban area in southern Europe.

Assessing climate change-induced poverty of mixed crop-livestock smallholders in Wolaita zone

Climate changes manifest itself through increased temperature, a more variable rainfall and more extreme events. As a matter of fact, smallholder farmers who produce climate-sensitive crop-livestock species are among the most affected to it due to reliance on rainfall, inadequate use of irrigation, and weak adaptive capacity. Accordingly, there are little evidences that reveals climate change is causing multi-dimensional poverty among mixed crop-livestock smallholders. Thus, this study was aimed at analyzing climate change-induced multidimensional poverty and its factors which contribute to it. Thus, data from households on socio-economic and environmental issues and thirty years rainfall and temperature data were collected. At the meantime, multi-dimensional poverty index, probit model, parametric test were applied to analyze data along with descriptive statistics. Accordingly, eleven variables showed statistically significant differences between poor and non-poor. Furthermore, the temperature in the study area was increased but rainfall trend decreased overtime. Since the livelihood of smallholder farmers is extremely dependent on rain-fed agriculture, the change in these climatic parameters negatively affected their livelihood. On the other hand, using a multidimensional-based measure of poverty; the estimates show that 82% of the sample households were multi-dimensionally poor. The incidence of poverty was highest in Abala Gefeta village (89%) followed by Bossa Wanche (80%) and Abala Shoya (84%). The result of probit regression estimation procedure revealed that variables such as access to climate information, productive safety net program and off/non-farm income at (1%), credit amount gained at (5%), sex, utilizing improved agricultural technologies and livestock holding at (10%) affects climate change-induced poverty negatively and significantly. Therefore, it is concluded that climate change-induced poverty of crop-livestock smallholders would be reduced through improving agricultural technology utilization by the farmers and providing timely climatic information and putting early warning system in place.

Multidimensional poverty and conflict events in Nigeria over time

We analyse the relationship between multidimensional poverty trends and changing dynamics of conflict in Nigeria in 2008–2018. We take a wide notion of poverty going beyond purely monetary hardships and considering simultaneously experienced non-monetary deprivations. Focusing on poverty experienced by people living in conflict affected areas, post conflict-areas and peaceful areas helps us understand how well-being changes with conflict, and how conflict may alter previous trends of poverty reduction. We pay particular attention to address the changing nature of conflict within zones and across neighbouring states. For this, we compare the poverty–conflict nexus across bordering regions in a spatial regression framework. We find that conflict arises not necessarily in the poorest Nigerian states, but in some of the relatively better-off states. Furthermore, we find that although levels of the Multidimensional Poverty Index decreased between 2008 and 2013, conflict may have played a major role in halting these trends, if not reverting them.

The role of fiscal policy on poverty reduction in South Africa

This paper presents the results of ridge regression analysis of the relationship between government spending in emancipation programmes and multidimensional poverty, focusing on South Africa. Through the Principal Component analysis, we retained three variables of this relationship, affected by a range of factors, to determine the size and direction of the relationship. Besides health, we find no clear evidence that government spending on housing and social security significantly reduces multidimensional poverty. Co-production in housing, healthcare delivery, and social security should be encouraged.

Multidimensional poverty: an analysis based on the functionings, dimensions and weights attributed by the families of the Ilha das Onças - Pará, Brazil

Aiming to assess the multidimensional poverty of Ilha das Onças - Metropolitan Region of Belem, Pará, Brazil, we use Sen’s Capabilities Approach, with the objective of defining the dimensions and functionings indicated as priorities by the studied population itself. We build a multidimensional poverty indexes (MPIs) adjusted according to the needs of the local population, using Alkire and Santos (2010) methodology. Field research was carried out during November and December 2018 interviewing 80 families. Four versions of the MPI were calculated. From the original version from Alkire and Santos (2010) to a version adjusted by the proposed dimensions and their respective weights attributed by the interviewees consulted in the field work, which we refer to as the MPIisle. The results show that the inclusion of what people consider important, to be or to do, reveals deprivations not generally considered by indexes constructed from exogenously determined weights, as in synthetic indexes.

Impact of social expenditures on multidimensional poverty in Turkey

Reducing poverty is a critical priority for developing countries. Despite the government allocating approximately 13% of the GDP to social support expenditures, poverty affects around 15% of the population in Turkey. However, there is a need for more research that measures the effects of social expenditures, which is a fundamental tool in the fight against poverty, while also considering the current developments in poverty measurement methods. This study aims to measure the impact of social support expenditures on poverty in Turkey. The study compares a multidimensional poverty approach to a one-dimensional approach. The effects of social support expenditures on households in Turkey were analyzed using econometric methods. The study finds that multidimensional poverty values are approximately 2.5 times higher than one-dimensional values. Government spending was found to have no impact on multidimensional poverty, while private expenditure had a relatively minor impact. The paper concludes by discussing the inefficiency and ineffectiveness of government social expenditures in Turkey.

Evaluating rural poverty and livelihood diversification in the context of climate-induced extreme events in coastal area: Insights from Indian Sundarban

Agriculture has traditionally been the backbone of the Indian economy, accounting for a large portion of our country’s gross domestic product. Climate change scenarios, rising sea surface temperatures, and other environmental concerns have had a significant impact on agricultural production, making this situation more vulnerable and forcing rural communities to seek alternative forms of income. To better grasp the genuine status of livelihood diversification, researchers looked at some of the most vulnerable cyclone-affected villages in the Indian Sundarban’s southwest coastal districts. For this exploratory work based on geomorphological units, 850 households from fifteen different places were surveyed. However, 15 FGDs were performed to get specific information from the community. Using Alkire and Foster technique with Simpson Index, this study seeks to estimate multidimensional poverty index for village households in coastal blocks of West Bengal. The multiple linear regression model (MLRM) subtraction of predictor variables using the T-test uses stepwise regression. Results reveal livelihood diversification as way-out to poverty due to climatic extreme events. Coastal and riverine villages decomposed of roughly 80% of deprivation with 48% intense poverty. Livelihoods in island, coastal and riverine locations heavily transformed during last 10-12 years. In MLRM model food security alone explains (81.7%) the regional livelihood diversification. The majority of rural communities primarily from island, coastal, and riverine areas, have diversified their livelihoods from agriculture and fishing. Multiple factors, both positive and negative, lead to the reduction of livelihood diversification. Extreme occurrences have a substantial impact on livelihood diversification, as do the number of migrants, household assets, education of the head of family, dependence ratio, and amount of savings. In order to address such problems, households in most villages aim to diversify their income opportunities from nature-based (farm-related) to non-formal (non-farm) activities, as shown by the findings of this assessment.

Can monetary poverty measurement detect multidimensionally deprived? Evidence from Egypt

PurposeThis paper aims to examine the mismatch between multidimensional deprivation and monetary poverty in identifying the poor in Egypt and investigates their determinants empirically.Design/methodology/approachThe paper uses the Alkire-Foster multidimensional poverty measurement method using data from Egypt’s 2017/2018 Household Income, Expenditure and Consumption Survey (HIECS 2017/2018). Using a logistic regression model, the paper assesses the empirical relationship between multidimensional and monetary poverty and their determinants at the aggregate level and by dimension.FindingsThe paper demonstrates a significant mismatch between multidimensional and monetary poverty measures, underscoring their complementary nature. Statistics indicate that both measures overlap in classifying 35.81% of Egyptians, whereas monetary poverty ignores 63.12% of multidimensionally poor in at least one dimension. Regression estimates show a significant moderate negative association between expenditure per capita and multidimensional poverty and its dimensions. Moreover, they show that household head’s gender, age, education attainment, marital status, job proficiency, household size and location affect poverty mismatch and match in Egypt.Practical implicationsThis paper offers Egyptian policymakers the multidimensional poverty index that enables more efficient designing and targeting of poverty alleviation programs and assessing current poverty alleviation programs to modify them if needed.Originality/valueTo the best of the authors’ knowledge, this study is the first to examine the mismatch between both poverty measures in Egypt, using the recent full data set of HIECS 2017/2018. This paper confirms that depending only on monetary measures can send inaccurate insights for crafting effective social policies. Also, it offers policymakers a comprehensive insight into the country’s poverty landscape, which enable more efficient design, targeting of poverty alleviation programs and monitoring their effectiveness.

A LOGISTIC REGRESSION ANALYSIS OF MULTIDIMENSIONAL POVERTY: A CASE STUDY OF AIZAWL DISTRICT OF MIZORAM, INDIA

In this paper, we examine poverty in the state of Mizoram, India by taking the case of Aizawl district based on the method of Alkire-Foster counting approach. We also assess the determinants of such poverty using binary logistic regression model by considering household characteristics such as dependency ratio, age, education of the household head, household size and size of agricultural landholdings as explanatory variables. We found that 28.4 percent of the population is MPI poor (i.e. headcount ratio) with a 38.2 percent intensity of poverty (A). The overall MPI in the study area is 0.10. The findings of the study are very close to the findings of Alkire et.al (2015), who estimated the headcount ratio, intensity of poverty, and MPI to be 30.8 percent, 45.1 percent, and 0.139 respectively based on the National Family Health Survey-3 (NFHS-3). The estimated logistic regression also showed that the household size, dependency ratio, age of the household head, and education level of the household head were significant determinants of poverty in the study area. The findings of this study agree with those of previous studies such as Datt (1998) Al-Saleh (2000), Ajakaiye and Adeyeye, (2002), Osowole, Asif (2007), Babu, & Sanyal (2009), etc. However, the size of agricultural landholdings is not a significant determinant of multidimensional poverty in the study area, which is contrary to the findings of Hashmi, et.al. (2008) and Babu, et.al. (2019). KEYWORDS: Multidimensional Poverty, Alkire-Foster Method, Determinants of Poverty, Binary Logistic Regression.

Grid-Scale Poverty Assessment by Integrating High-Resolution Nighttime Light and Spatial Big Data—A Case Study in the Pearl River Delta

Poverty is a social issue of global concern. Although socioeconomic indicators can easily reflect poverty status, the coarse statistical scales and poor timeliness have limited their applications. While spatial big data with reasonable timeliness, easy access, and wide coverage can overcome such limitations, the integration of high-resolution nighttime light and spatial big data for assessing relative poverty is still limited. More importantly, few studies have provided poverty assessment results at a grid scale. Therefore, this study takes the Pearl River Delta, where there is a large disparity between the rich and the poor, as an example. We integrated Luojia 1-01, points of interest, and housing prices to construct a big data poverty index (BDPI). To evaluate the performance of the BDPI, we compared this new index with the traditional multidimensional poverty index (MPI), which builds upon socioeconomic indicators. The results show that the impoverished counties identified by the BDPI are highly similar to those identified by the MPI. In addition, both the BDPI and MPI gradually decrease from the center to the fringe of the study area. These two methods indicate that impoverished counties were mainly distributed in ZhaoQing, JiangMen and HuiZhou Cities, while there were also several impoverished parts in rapidly developing cities, such as CongHua and HuaDu Counties in GuangZhou City. The difference between the two poverty assessment results suggests that the MPI can effectively reveal the poverty status in old urban areas with convenient but obsolete infrastructures, whereas the BDPI is suitable for emerging-development areas that are rapidly developing but still lagging behind. Although BDPI and MPI share similar calculation procedures, there are substantial differences in the meaning and suitability of the methodology. Therefore, in areas lacking accurate socioeconomic statistics, the BDPI can effectively replace the MPI to achieve timely and fine-scale poverty assessment. Our proposed method could provide a reliable reference for formulating targeted poverty-alleviation policies.

The effects of agricultural commercialization on the multidimensional poverty of rural households: Evidence from China

AbstractBased on data from the China Family Panel Survey, this paper explores the impact of agricultural commercialization on household multidimensional poverty and its mechanism. The results show that agricultural commercialization has significantly reduced household multidimensional poverty, especially poverty in health and living standard. However, it may be that the income from commercialization has not all been converted into household multidimensional welfare, making the multidimensional poverty reduction effect of commercialization smaller than the income poverty reduction effect. Further research shows that a possible channel for agricultural commercialization to reduce multidimensional poverty is to improve farmers' ability to convert their endowments into earnings and consumption.

DECOMPOSING MULTIDIMENSIONAL POVERTY: A CASE STUDY OF MAMIT DISTRICT, MIZORAM

Purpose: The study intends to examine the incidence and intensity of multidimensional poverty in Mamit District of Mizoram. Methodology: This study was based on primary data which was collected through a multi-stage stratified random sampling technique. At the first stage, Mamit District was selected solely based on socio-economic indicators for conducting the survey. The second stage involved random selection of 15 villages, five villages from each block. Requisite data were then collected randomly through structured questionnaires which was designed based on the requirement for computation of Multidimensional Poverty Index. From the collected data, the incidence of poverty (headcount ratio), the intensity of poverty and MPI were computed using Alkire-Foster Methodology. The study follows the Global MPI Brief Methodological Note, 2017 in the choice of dimensions, indicators, thresholds and weights assigned to each indicator. Results: From the result of the analysis, the multidimensional poverty in the study area is moderate. The incidence of poverty across the study area is ranging between 0.32 - 0.38 while the intensity of poverty shows slight differences with negligible margin ranging between 0.39-0.411. Decompositions by indicators show that the nutrition has surpassed all other indicators with 22 percent contribution to overall MPI of Mamit district followed by year of schooling with 15 percent. Applications of this study: The findings of the study can be based for formulation of government poverty reduction policies and can be used effectively in improving the existing poverty reduction strategies in the state. KEY WORDS: Multidimensional Poverty, Decomposition, Mamit District, Mizoram.

Wading out the storm: Exploring the effect of flooding on energy poverty amidst disaster management strategies in Dar es Salaam

Although flooding is well-thought-out as one of the deadliest natural disasters, there is scarce evidence on how such an environmental shock affect energy poverty prevelence in a developing country context amidst the implementation of disaster risk management strategies. Using the Disaster Poverty Household Survey in Tanzania’s capital Dar es Salaam, we examine the effect of flooding on multidimensional energy poverty while estimating the moderation effects of non-structural ex-ante risk management strategies. After employing a myriad of robust methods, we observe that flooding increases energy poverty prevalence by about 32 %. The mediation analysis shows that income reduction serves as a pathway through which flooding affects energy poverty. Furthermore, estimates from the interaction analysis reveal how effective fiscal non-structural ex-ante risk management methods are in reducing the incidence of energy poverty among flood victims. However, the defense strategies were noted to be inefficient. These results provide policymakers with the necessary tools to create policies that address energy-related needs in areas affected by natural disasters, especially in developing countries.

Dietary Patterns of Children from the Amazon Region of Ecuador: A Descriptive, Qualitative Investigation.

Many young children in Ecuador suffer from high rates of malnutrition and stunting that affect their long-term growth and development. Little is known about the dietary patterns of children from the Amazon region who experience some of the highest rates of stunting (height-for-age) within Ecuador. Semi-structured interviews were conducted with 50 mothers of young children living in the Ecuadorian Amazon. In addition to descriptions of overall dietary patterns, three themes emerged from the interviews relating to strengths mothers have in feeding their children healthy diets: knowledge, autonomous and independent children, and supportive and responsive parenting. Five themes were found relating to barriers mothers have in feeding their children healthy diets. The first four themes concerned barriers (lack of knowledge of healthy foods, lack of access to healthy foods, not enough money, and child's health) related to multidimensional poverty. All these influenced the last theme found, namely, how difficult of an eater the child was. The implications of intervention efforts to reduce undernutrition and promote children's development by building on specific family and community strengths and identified barriers are also discussed in this paper.

Thinking of the children: Energy poverty and acute respiratory infections among young children in South Asia

Energy poverty has been extensively studied in the literature regarding its impact on physical, mental, and maternity health as well as the social well-being of adults. However, there is still a research gap in understanding how energy poverty specifically affects the health of young children under the age of five, particularly toward the occurrence of acute respiratory infections (ARIs). To address this gap, this paper aims to clarify the link between energy poverty and acute respiratory illness among young children in South Asia. We utilized data from five demographic and health surveys conducted between 2015 and 2018, encompassing 292,196 young children. Employing the multidimensional energy poverty index and principal component analysis, we assessed energy poverty at the household level, considering indicators such as lack of electricity, clean cooking fuels, indoor smoke, and lifestyle-sustaining devices. Applying multilevel logistic and probit instrumental variable regression models, this study revealed that multidimensional energy poverty significantly triggers the risk of ARI among young children. Specifically, a 1 % increase in energy poverty leads to a 48 % increase in the odds of developing ARI among young children in South Asian households. Furthermore, regional disparities in the impact of energy poverty on respiratory infections were identified. Our findings remain robust across different methods and measures of energy poverty. The findings of this research work have a significant policy implication for ensuring sustainable energy services to improve children's health, contributing to sustainable development goals 3 (good health and well-being) and 7 (affordable and clean energy).