Multidimensional Poverty Research Articles

Impact of climate-smart agriculture practices on multidimensional poverty among coastal farmers in Bangladesh

Climate-smart agriculture technology helps safeguard crop income from climate change-induced crop loss. Here we identify the factors determining the adoption of climate-smart agriculture and the impact of its adoption on multidimensional poverty among coastal climate-vulnerable farm households. We employ full information maximum likelihood estimation under the endogenous switching regression approach to account for counterfactual scenarios. Results indicate that the decision to adopt climate-smart agriculture is influenced by crop vulnerability, crop income, access to extension service, and training on input management. The current adopters of climate-smart agriculture experience a 41-percentage point reduction in multidimensional poverty compared to if they had not adopted this technique. Likewise, if the current non-adopters adopted climate-smart technology they could reduce poverty by 15 percentage points. Findings also claim that some specific climate-smart technologies are particularly effective in reducing poverty, providing valuable information to coastal farmers in making informed decisions about which technologies may be effective.

Analyzing the Influence of International Remittances on Multidimensional Poverty: Insights from BRI Countries

ABSTRACT Efforts to facilitate international remittances hold substantial potential to impact various dimensions of poverty, underscoring the importance of comprehending this relationship in developing economies. International remittances between Belt and Road Initiative (BRI) countries have shown a marked growth trajectory. Unlike other studies that focus on the impact of remittances on income-based poverty in developing countries, this research delves into a more comprehensive analysis of how remittances affect various facets of poverty. Therefore, this paper aims to estimate the broader global implications of international remittances on multidimensional poverty in selected BRI countries. This study applied Driscoll-Kraay and Fully Modified Ordinary Least Square estimators to evaluate international remittances’ impact on MPI in BRI countries between 2010 and 2022. The results reflected a significant effect on countries that have contributed to the Belt and Road Initiative, with its impact on MPI courtesy of political stability, international remittances, agricultural growth, and forest plantation. Besides, the results of the Granger causality indicated a bi-directional causal link between forest plantation and MPI and a uni-directional causal link between MPI and international remittance. Countries along the BRI should enact policies to attract more remittances and design strategies to reduce unemployment and poverty.

Evaluating the level of access and equity of the bus rapid transit (BRT) system: The case of Dar-Es-Salaam, Tanzania

Bus Rapid Transit (BRT) systems have witnessed significant growth worldwide, particularly in rapidly urbanizing cities in the developing world, often implemented through public-private partnerships to foster economic growth. However, the success of such ambitions relies on ensuring equitable transit access for all residents, including those living with poverty or other social disadvantages. The purpose of this study is to explore transit access, coverage, and equity of the BRT system in Dar-es-Salaam, Tanzania using infrastructure-based measures of proximity to transit stations and stops. In particular, the equitable distribution of transit access patterns is explored in relation to neighborhood socio-economic strata in the catchment areas within a 30-min walking distance. The study's findings reveal notable disparities in the level of access among various socio-economic strata, with the least deprived population benefiting the most from the Dar-es-Salaam BRT system. As more BRT phases are implemented, there is a continuous increase in the Multidimensional Poverty Index (MPI) within the areas not covered by the BRT system. This suggests that access improvements predominantly favor the wealthier population rather than effectively addressing the needs of the impoverished population. To enhance access and achieve more equitable outcomes, it is crucial to implement targeted strategies and measures. These may include improved integration of the BRT with a feeder system, continuous improvement of Non-Motorized Transport (NMT) facilities, and the promotion of equitable transit-oriented development along the BRT corridor. These initiatives play a vital role in ensuring that vulnerable populations, especially the poor, have access to and can benefit from the BRT services.

Research on the Current State of Global Poverty and Directions for Improvement

In today's increasingly complex global poverty landscape, effectively reducing poverty remains one of the core issues for global sustainable development. The current state of poverty has transitioned from relatively simple single factors such as natural disasters, extreme weather, and conflicts to multidimensional poverty caused by the interaction of multiple factors. Due to the complexity and diversity of contributing factors, multidimensional poverty varies in severity, making it challenging to reduce effectively and resulting in a prolonged global poverty problem. Compounded by limited global resources and funds, as well as slowing economic growth, addressing multidimensional poverty requires sustained long-term efforts, posing challenges in resource allocation. This leads to a cyclical pattern of multidimensional poverty, wasting resources and affecting people's confidence and attention to poverty reduction efforts, thus hindering progress. This paper analyzes the current state, challenge and existing problems of global poverty, and explores effective and sustainable approaches for poverty reduction considering the methods currently employed and their shortcomings. Through analysis, it is found that effective poverty reduction could focus on coordinating resources, adopting a combination of natural and artificial approaches, updating technologies, strengthening local improvements, and analyzing cross-regional impacts to prevent factors leading to poverty and mitigate present and future poverty issues.

MULTIDIMENSIONAL POVERTY MODELING IN CENTRAL JAVA, DI YOGYAKARTA, AND EAST JAVA PROVINCES

Indonesia has a National Medium-Term Development Plan (RPJMN) for 2020-2024 to reduce the poverty rate to 6 to 7 percent. However, the poverty rate has only declined by less than one percent in the past year, indicating the need for optimization to achieve the goal. Despite being located in Java, the center of development and economy in Indonesia, the poverty rate in Central Java, DI Yogyakarta, and East Java still exceeds the national average. This study used SUSENAS 2023 March KOR data to address this challenge and examine the multidimensional indicators affecting poverty. The Alkire-Foster method was used to obtain the Multidimensional Poverty Index (MPI) number, which was then analyzed using the Structural Equation Model (SEM) with the Asymptotically Distribution-free (AD-f) method approach. SEM is used to observe latent variables that cannot be measured and the relationship between variables that form a multidimensional poverty index. AD-f method approach is used to overcome data non-normality in SEM processing. The study revealed that the percentage of multidimensional poverty in the three provinces is higher than monetary poverty due to the household unit of analysis used. The standard of living dimension was the most deprived in most households, followed by the health dimension. To tackle this issue, the study recommends optimizing access to the Internet, assets, preschool participation, and nutrition.

Socioeconomic Factors Determining Multidimensional Child Poverty Groups in Central America: A Measurement Proposal from the Wellbeing Approach Using a Comprehensive Set of Children’s Rights

This article aims to show that multidimensional child poverty (MCP) is determined by several socioeconomic factors that influence the formation of stratified groups of poor children under five years of age living in Central America. This study advocates for a comprehensive set of children's rights with the purpose of addressing the different facets of child poverty from the perspective of child well-being, in order to estimate the incidence of MCP, by including multiple childhood deprivations and socioeconomic determinants. Child-specific indicators and household deprivation indicators are considered in the estimation of MCP. The study also states that child poverty is a complex concept, which includes the various types of deprivations experienced by children in the Central American societies and their deprivations are considered as the denial of children’s rights. Therefore, the MCP is estimated based on a conditional latent class analysis that includes not only manifest deprivation variables, but also socioeconomic determinants that help to better predict the incidence and probabilities of children being multidimensionally poor according to different poverty strata. The socioeconomic factors that show high risks of MCP are rural areas, indigenous children, young mothers and low levels of education attained by the head of the household, among others. One of the reasons to investigate the MCP for Belize and El Salvador is because there are few studies that address this problem for these countries and this research sheds light on the characteristics of early childhood poverty. The results indicate that the incidence of MCP is 49% in Belize and 76% in El Salvador. The research work concludes that the International Rights of the Child provide the opportunity to implement comprehensive social policies in Central America to eradicate child poverty.

Microfinance institutions and entrepreneurial activities in Awka south local government area: Evidence from physically challenged persons

Given the need for inclusivity in a bid to curtail multidimensional poverty, hunger, and inequality (as reflected in the Sustainable Development Goals (SDG) 1, 2, and 10 respectively) and in the face of struggles to achieve decent work and economic growth (SDG 8) as well as responsible consumption and production (SDG 12), the main objective of our paper was to determine how microfinance institutions (MFIs) contributed to entrepreneurial successes of physically-challenged persons residing in Awka South Local Government Area (LGA), Anambra, Nigeria. A sample was drawn from the physically challenged community operating business shops and enterprises in Awka South LGA, and descriptive survey research was employed. Copies of a structured questionnaire were distributed and collected on the spot based on the exponential discriminative snowball sampling. Responses were analyzed using pie charts, frequency distributions, and percentages, while the chi-square distribution test was used to test the hypotheses. Our major findings are that, apart from access to loans, the respondents were not aware of other services rendered by microfinance institutions and that they encountered difficulties in accessing credit facilities from MFIs sequel to protocols enshrined in their banking operations. This led to the conclusion that the contributions of microfinance institutions towards the growth of enterprises owned by physically-challenged entrepreneurs in Awka South LGA was suboptimal, although some respondents had successful business startups and scale ups as a result of interventions from MFIs. Our paper, therefore recommends that, in order to build a resilient society, MFIs operating in Awka South LGA should intensify and sustain media awareness on entrepreneurship programmes they offer to physically-challenged persons as well make their services more accessible. Again, the government of Anambra State should adequately sustain entrepreneurial programmes mapped out for physically-challenged persons so that they can become entrepreneurs rather than depend on others for their survival. Keywords: Entrepreneurship, Microfinancing, Physically-challenged, Self-employment JEL Codes: M13, G21, J71, J23, D63

Decomposition of intra-household disparity sensitive fuzzy multi-dimensional poverty index: A study of vulnerability through Shapley machine learning

The well accepted multi-dimensional measures have failed to properly project the vulnerability of human-beings towards poverty. Some of the reasons behind this inability may be the failure of the existing measures to consider the graduality within the concept of poverty and the disparities within the household in wealth distribution. So, this work wants to develop a measure to estimate the vulnerability of households in becoming poor through incorporating the intra-household disparities through the factors which suffer from graduality. The decomposition of the grade of vulnerability on the causal factors is also under the purview of this work. To that respect the idea of fuzzy logic and decomposition through artificial intelligence has been used to develop a mathematical framework. So, the idea of Shapley Value Decomposition method has been used extensively. This decomposition is implemented here with the help of Shapley Machine Learning. This decomposition will help the planners to locate the role of different dimensions behind the vulnerability of human beings to become poor more efficiently.

Estimating vulnerability to income and multidimensional poverty: a new methodological approach

Purpose The purpose of this paper is to propose a new vulnerability to income and multidimensional poverty estimation index (VIMPI). This index is designed to measure the likelihood of individuals falling into and remaining in poverty. Design/methodology/approach The paper introduces a new methodology that integrates the concepts of the well-being gap, individual and indicator-specific weighting, and vulnerability. This approach is simple to apply and accurately measures vulnerability with less susceptibility to measurement error and outliers. The index satisfies all poverty and vulnerability axioms, including transferability and monotonicity. The newly proposed method has been applied to Namibian and Ghanaian data and compared with similar techniques. Findings The results showed that Ghana's vulnerability to income and multidimensional poverty was 37.9% and 56%, respectively. Of the 37.9% of vulnerable individuals, 23.4% were at risk of falling into poverty, while 14.57% were at risk of remaining in poverty. These findings demonstrate the effectiveness of VIMPI in accurately estimating vulnerability to poverty and its potential to inform targeted policies to alleviate poverty. Originality/value This paper proposes a new methodology to estimate vulnerability to income and multidimensional poverty.

Measurement and Comparison of Poverty in Abhujmadiya Tribe: Income-based and Deprivation-based Poverty Approach

The present paper is attempted to measure and compare the difference and discrepancy between the income-based and deprivation-based poverty measurement in poverty of Abhujmadiya tribes of Chhattisgarh. Two international poverty measurement approach is considered for poverty measurement of Abhujmadiya tribes, first income-based measurement developed by World Bank and second, Multidimensional Poverty Index developed by United Nation Development Program (UNDP). Research study is based on primary data of 80 household collected from 8 village of 2 block of Narayanpur district of Chhattisgarh State. Results shows that 90% Abhujmadiya peoples are poor in income-based poverty whereas, 48.43% Abhujmadiya peoples are poor in deprivation-based poverty measurement. A difference of 41.57% is found in the measurement of poverty by both the poverty measurement approach and this discrepancy is more in income-based poverty as compare to multidimensional poverty measurement. The study also reveals that health facilities, year of schooling, cooking fuel, sanitation and housing conditions are the major contributor in the poverty of Abhujmadiya Tribes.

Energy poverty and health in Turkey: Evidence from Longitudinal data

This study critically examines the effect of energy poverty on health in Turkey between 2018 and 2021 using the Income and Living Conditions Survey Longitudinal Micro Data Set. It considers the multidimensional structure of household energy poverty and its individual effects on health, resulting in several significant findings. Firstly, the multidimensional energy poverty index at the household level is obtained as a continuous variable using principal component analysis, considering subjective and objective indicators of energy poverty. Secondly, the impact of energy poverty on health at the individual level and the effect of several socioeconomic variables, including unobserved heterogeneity, are estimated with the random effects ordered logit model. Finally, commonly used measures of energy poverty in the literature and their health impacts are compared. The robustness analysis results show that the model's goodness of fit is highest when the multidimensional energy poverty index is constructed using principal component analysis. In addition, the analysis results show that unobserved heterogeneity across individuals significantly impacts health. These results indicate that decentralized policies should be implemented to increase policy effectiveness in combating energy poverty.

Spatial prediction of poverty in Gauteng province (South Africa) in‐between Censuses using land use datasets

AbstractTo realize the first sustainable development goal of ending “poverty in all its forms everywhere,” local governments in South Africa need to implement informed targeted policy interventions based on up‐to‐date data and sound analytics. Statistics South Africa (Stats SA) Censuses reveal the socioeconomic circumstances of people living in South Africa but are only conducted every 10 years. As a result, most analytical studies done in‐between Censuses rely on outdated socioeconomic data. This study demonstrates how poverty levels in one of the provinces of South Africa, Gauteng, can be predicted when up‐to‐date Census datasets are not available. The spatial lag model is used to explain the relationship between the South African Multidimensional Poverty Index (SAMPI) and statistically significant variables extracted from land use datasets (i.e., land areas classified as built‐up, informal, residential, township, and non‐urban), and to ultimately predict the levels of poverty. Out‐of‐sample predicted poverty levels obtained based on the spatial lag model correlate with the actual levels of poverty thereby reflecting known spatial patterns of the levels of poverty in Gauteng province.

A data-driven approach to mapping multidimensional poverty at residential block level in Mexico

A data-driven approach to mapping multidimensional poverty at residential block level in Mexico

Energy Poverty and Women’s Economic Well-Being in Global South: Evidence from Burkina Faso

Although the relationship between household access to energy and economic well-being has received increasing attention in recent years, studies of this link have generally focused on unidimensional measures of fuel poverty. What is the link between multidimensional energy poverty and women’s economic well-being? Using data from the Continuous Multisectoral Survey on Household Living Conditions, this paper focuses on quantifying energy poverty and its effect on the economic well-being of households, particularly women, in Burkina Faso within a multidimensional framework. The results indicate that 84% of households are in a situation of multidimensional energy poverty. These energy-poor households are deprived, on average in 67.01% of the indicators. The results of the econometric estimations show that an increase in multidimensional energy deprivation is associated with a decrease in women’s economic well-being. Given that energy poverty reduces women’s economic well-being, they should be given priority in the implementation of energy policies.

Multidimensional Poverty and its Determinants in Somalia: A Household Level Analysis

Purpose: Poverty is widespread and problematic in least developed countries such as Somalia. The main objective of this study is to analyze the extent and determinants of multidimensional poverty in Somalia. Methodology: To achieve this objective, this study used the Somali Health and Demographic Survey carried out by the Somali National Statistics Bureau in 2020. Alkire and Foster’s methodology was used to measure the extent of multidimensional poverty, and an ordered logistic regression model was employed to identify its determinants at the household level. Findings: The results of the descriptive analysis show that 84.2 percent of the sampled households are multidimensionally poor, while the intensity of poverty and adjusted headcount ratio were 56.8 percent, and 0.479 respectively. Meanwhile, the study found that the living standard dimension was the major contributor (45 percent) to the overall multidimensional poverty index, followed by education and health dimensions, contributing 28.2 percent, and 26.8 percent, respectively. The ordered logit results indicate that household size significantly increases the likelihood of a household’s status being multidimensionally poor. In contrast, household education, employment of at least one household member, livestock ownership, ownership of agricultural land, and having a bank account significantly reduce the probability of being multidimensionally poor. Unique Contribution to Theory, Practice and Policy: Based on these findings, the study recommends that the government and international partners target the living standards dimension to reduce multidimensional poverty, improve quality and quantity of education, expand employment opportunities, promote financial inclusion, and foster the livelihoods of households involved in agriculture and livestock.

Improving compliance around protected areas through fair administration of rules.

Protected area management often depends heavily on law enforcement to secure compliance with rules. However, this can contribute to conflict between protected area authorities and local people, negatively affecting both human well-being and conservation outcomes. Compliance is affected by many factors, including whether those who enforce rules are perceived to do so fairly, as well as the perceived rule-related behavior of others. We used factorial survey experiments to explore how fair respondents living around protected areas in Indonesia and Tanzania perceive sanctions distributed by law enforcers to be. We presented scenarios to respondents to assess how crime type, offender characteristics, and corruption influenced their judgments regarding the fairness of administered sanctions. We also assessed how descriptive norms and corruption influenced individuals' willingness to obey protected area rules. Data were collected from 229 people in Indonesia and 217 in Tanzania. Results showed that in both locations, lawful sanctions, such as arrests or warnings, were perceived as fairer, and sanctions that involved corruption were perceived as least fair. Attitudes toward protected area rules, corruption, and descriptive norms all influenced people's willingness to comply, whereas multidimensional poverty did not. Our results highlight the need for conservation policy and practice to move beyond narratives that focus on the need for more law enforcement. To improve protected area compliance and secure better outcomes for people and nature, conservation must focus on ensuring the fair administration of rules and enhancing the legitimacy of rules themselves.

Stochastic dominance testing of poverty in Mozambique

AbstractNational assessments produced regularly from 1996/97 to 2019/20 provide standard estimates of the evolution of poverty in Mozambique. Stylised facts point to significant reduction in monetary and multidimensional poverty until 2014/15, even though characterised by persistent urban–rural and regional inequalities in several dimensions, followed by worsening deprivation during 2014/15–2019/20. In this paper, we rely on first-order dominance (FOD) methodology to check the robustness of standard poverty estimates while providing deeper insights into what happened in this poverty-stricken country. Our main findings include that the capital city, Maputo, and surrounding areas progressively came to dominate all other provinces in terms of well-being, and the provincial rankings from spatial FOD analysis are very stable over time. Rural areas, mainly those in the northern and central regions, are, with a few exceptions, always at the bottom of the ranking. Moreover, our FOD temporal analysis reveals that 2019/20 dominates, with a high degree of confidence, the results from earlier years, pointing to positive development over time, but with one important exception. The comparison between 2019/20 and 2014/15 is indeterminate, indicating that no significant advancement took place during this period. What stands out is the compelling need for concerted policy action to address the strong and persistent spatial gaps in welfare and poverty, including the capacity to respond effectively to external and internal shocks.

The impact of national savings on economic development: a focused study on the ten poorest countries in Sub-Saharan Africa

The purpose of this study is to examine the impact of national savings on economic development, as measured by the Human Development Index (HDI), Inequality-adjusted HDI (iHDI), and Multidimensional Poverty Index (MPI), in ten of the poorest countries in Sub-Saharan Africa. The study employs a sequential Generalized Method of Moments (GMM) analysis to address potential endogeneity issues and account for the dynamic nature of the relationships, covering the period from 2009 to 2019. The findings reveal a complex relationship between national savings and the selected development indicators. While national savings exhibit positive impacts on HDI and iHDI, the results are not consistently statistically significant across all the sequential models. However, the analysis suggests that national savings have a positive influence on reducing multidimensional poverty, as measured by MPI, particularly when effectively channeled into productive investments. The study also highlights the significant positive impact of government expenditure and foreign direct investment (FDI) on human development, underscoring the importance of strategic public investments and foreign capital. The results suggest that while national savings are crucial, their effective utilization is essential for enhancing human development indices. Strategic investments in public goods and foreign capital are also important. The mixed effects of inflation and official development assistance (ODA) emphasize the need for stable economic policies and effective utilization of foreign aid. The modest positive impact of institutional quality suggests that improvements in governance and institutional frameworks can contribute to human development. The findings underscore the need for policies promoting financial inclusion, efficient public expenditure, foreign direct investment, and stable macroeconomic conditions to leverage national savings for economic development. The study’s findings provide valuable insights for policymakers in Sub-Saharan Africa, highlighting the need for comprehensive strategies that leverage national savings, public expenditure, and foreign investment to drive sustainable economic development and poverty reduction.

Does use of formal and informal credit reduce poverty in rural Mexico?

AbstractMotivationDespite efforts to reduce poverty, both income and multidimensional poverty continue to be high in Mexico, especially in rural areas. Most studies concerned with the effect of credit use on poverty analyse formal credit, but little is known about the impacts of different types of credit on poverty.PurposeWe investigate the impacts of the use of formal credit and informal loans obtained (primarily) for productive and investment purposes on multidimensional and income poverty of rural households in Mexico.Approach and methodsWe use data from the 2013 and 2015 CONEVAL Surveys of Rural Households in Mexico, representative of rural communities with fewer than 2,500 inhabitants, to investigate the impact of credit on poverty. We apply inverse probability of treatment weighting (IPTW) to account for differences between users of formal credit, users of informal loans, and non‐users of credit.FindingsBoth formal and informal credit usage reduce poverty in rural Mexico, generally with clearer impacts on moderate rather than extreme poverty. Informal credit appears to have largely reached households that could most benefit from it. Broader access to formal credit would potentially further reduce poverty.Policy implicationsPublic policies to reduce rural poverty should promote a greater access to the formal financial sector. Including vulnerable low‐income rural households in formal finance should be accompanied by financial education.

Can carbon tax revenue recycling coordinate climate mitigation and energy poverty alleviation?

Energy poverty is a key dimension of multidimensional poverty and a major challenge for climate action. This study examines how climate policies affect energy poverty, especially the role of carbon tax revenue recycling in coordinating climate mitigation and energy poverty alleviation. Using an integrated Climate-Economy-Energy Poverty (RICE-EP) model that incorporates inequality aspects of energy poverty, the study analyzes the effects of climate policies on household energy consumption. The study simulates various scenarios of climate actions and carbon tax revenue recycling and finds that: i) Carbon tax revenue recycling can simultaneously advance climate change mitigation and energy poverty reduction goals, it can promote climate mitigation and enhance equity by lowering the abatement costs borne by low-income populations; ii) However, the interactions between stringent climate targets and energy affordability are complex. Modeling suggests that even optimal revenue recycling fails to prevent exacerbated energy poverty among disadvantaged groups under ambitious 2 °C climate targets; iii) Analysis indicates that an emissions reduction rate approaching 43 %, enabled by a carbon tax calibrated to incentivize an equitable transition, could maximize alleviation of energy poverty by directing subsidy support to low-income groups. The study methodology and findings offer valuable, actionable insights into coordinating equitable climate and economic policies.