Multidimensional Poverty Reduction Research Articles

Agricultural Productivity and Multidimensional Poverty Reduction in Colombia: An Analysis of Coffee, Plantain, and Corn Crops

This article presents the correlation between the Multidimensional Poverty Index (MPI) and the area planted, production in tons, and productive yield for various crops in Colombia from 2018 to 2021. The aim of this study is to determine the relationship between agricultural productivity and multidimensional poverty in Colombia, focusing on the cultivation of coffee, plantain, and corn. The methodology employed included a literature review through a bibliometric analysis to understand the relationships between the MPI and agricultural production. In the second stage, the agricultural sector statistics for the years 2018 to 2021 and the MPI by regions and departments of Colombia during the same period was systematized. Finally, a quantitative statistical analysis was conducted to establish the correlation of the MPI with the area planted, production in tons, and productive yield for coffee, plantain, and corn crops in Colombia. The MPI identifies those who are deprived in 50% or more of the index’s dimensions as living in extreme poverty. The results show that higher productive yields in the crops analyzed correspond to a lower MPI. Coffee crops have an MPI below 50%; plantain crops have an MPI between 20% and 50%, and for mechanized corn crops, the data show an MPI between 20% and 30%. This demonstrates that coffee, plantain, and corn crops represent an alternative for reducing the MPI in Colombia.

Association of crop commercialization and rural households' multidimensional poverty using targeted maximum likelihood estimation

Recent evidence shows the highest prevalence of multidimensional poverty in the world. To alleviate poverty, Ethiopia is investing in stimulating agricultural commercialization for poverty reduction, driving sustainable economic growth, and creating jobs. Therefore, this study investigated the causal relationship between crop commercialization and multidimensional poverty across Ethiopian rural households using the Ethiopia Socioeconomic Survey 2018/19 data, which included 1129 crop commercialized and 1585 completely subsistence rural households. Moreover, this study also examined the causal effect of crop commercialization on the multidimensional poverty mediated by mobile phone ownership status. The study used the double robust method of the augmented inverse probability of treatment weighted (AIPTW) and targeted maximum likelihood estimation (TMLE) methods. The result showed that crop commercialization has an association with multidimensional poverty. Specifically, the TMLE with a default super learner model estimates were the most precise and suggest that the prevalence of risk of being multidimensionally poor among rural households who were crop commercialized is 12.2 % lower than for those who were completely subsistence households. Thus, it is important to have more robust policies like crop commercialization to target rural multidimensional poverty reduction. Moreover, the controlled direct effect estimation analyses showed that crop-commercialized rural households reduced the adjusted risk of multidimensional poverty by; 12 % for those who owned mobile phones and 7.8 % for those who did not. To ensure sustainable livelihoods for rural multidimensional poor households, it is necessary to have a multidisciplinary policy intervention to promote crop commercialization through the spread of mobile phones in rural areas.

Achieving sustainable development in ECOWAS countries: the impact of trade openness, poverty and human capital

This study investigates the relationship among trade openness, poverty, and human capital development in the pursuit of sustainable development across a panel of ten ECOWAS economies over a 34-year period (1987–2020). Specifically, it examines the roles of trade openness, poverty, and human capital development in sustainable development, while also exploring the moderating role of trade openness on the poverty-sustainable development relationship within the ECOWAS region. To conduct this analysis, the study employs panel autoregressive distributed lag (ARDL) using both the Pool Mean Group (PMG) estimator and Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) techniques, taking into account cross-sectional dependence, cointegration, and other relevant diagnostic tests. The findings indicate that poverty has a consistent negative long-run impact on sustainable development, while human capital is positively associated with sustainability over the long term. Trade openness lacks a significant relationship with sustainability in both the short and long run. Inflation is insignificantly related to sustainability. Exchange rates demonstrate mixed effects. In terms of moderation, trade openness positively and significantly moderates the poverty-sustainability relationship in the long run but not the short run. Robustness testing using the AMG and P-OLS models further validates the significant positive impact of human capital and the insignificant effect of trade openness on sustainable development. Given poverty’s significant negative association and human capital’s positive link with sustainable development, the findings suggest the need for integrated policy mixes prioritizing multidimensional poverty reduction and human capability enhancement to promote sustainability objectives across both short- and long-term horizons in ECOWAS countries. Furthermore, prudent management of exchange rates and well-designed trade policies should complement these efforts to mitigate potential risks and harness any benefits for sustainability.

Does e-agriculture practice matter for poverty reduction among coastal farm households?

The study hypothesizes that e-agriculture practice may contribute to multidimensional poverty reduction in the coastal areas of Bangladesh. Two-stage instrumental variable (IV) Tobit and seemingly unrelated regression (SUR) analyses are used to identify the relationship. We collected data from 351 rice producing households applying a multi-stage sampling technique. Results reveal that e-agriculture adoption significantly reduces multidimensional poverty by 32 percentage points compared to non-adoption. Besides, education, farming experience, residence in the peri-urban area, and access to agricultural extension services are identified as positive predictors of e-agriculture adoption. The SUR regressions show that e-agriculture practice can help improve the standard of living of coastal farm households. In addition, multiple cropping patterns significantly contribute to the reduction of all the deprivations of multidimensional poverty. Based on the research outcomes, the study advocates broadening access to extension services to seamlessly incorporate small and marginalized farm households in remote coastal areas. Such integration may equip coastal communities with comprehensive insights into e-agriculture, thereby empowering them to fully leverage the advantages inherent in this farming technique.

Tác động của tài chính toàn diện đến nghèo đa chiều ở cấp độ hộ gia đình tại Việt Nam năm 2020

The relationship between financial inclusion and poverty is of interest to governments and researchers worldwide, including Vietnam. The research focuses on assessing the current status of financial inclusion at the household level in Vietnam in 2020 and its impact on multidimensional poverty. The study employs principal component analysis and a logistic regression model. Based on data from the Household Living Standards Survey, the study shows that the assessment of the financial inclusion differs between ecological regions, with households living in the Red River Delta and Southeast regions having the highest level of financial inclusion. An increase in financial inclusion at the household level has a statistically significant impact on reducing multidimensional poverty (relative risk reduces by 0.5 times). Based on research results, sustainable multidimensional poverty reduction policies can be implemented in combination with comprehensive financial inclusion development strategies. Furthermore, factors such as region, education, and occupation of the household head need to be considered when addressing poverty reduction and promoting financial inclusion.

Impact of income diversification on multidimensional poverty: Household level evidence from tea estates in Bangladesh

Policy advocates commonly use income diversification strategies worldwide to address economic disturbances such as poverty. Realizing the importance of poverty reduction and the raging debate on whether the household should specialize or diversify their income, this study attempts to investigate the poverty and income diversification nexus in a tea estate of Bangladesh. A multistage sampling procedure was applied to select 1 tea estate and 382 households. Primary data was collected through interview schedule. The Simpson diversification index and Alkire-Foster multidimensional poverty index were used to measure income diversification and multidimensional poverty respectively. Additionally, this paper used the propensity score matching method to assess the causal impact of income diversification on multidimensional poverty. The findings revealed that the research area has a 35% household level income diversity, a 43% household level multidimensional poverty rate, and income diversification has a positive impact on multidimensional poverty reduction. The multidimensional poverty was reduced by 0.095% on average for income diversified households. Therefore, from a policy perspective, income diversification can be a good solution for reducing household-level multidimensional poverty. Government and other stakeholders should redesign working guidelines for tea workers regarding working hour, days and wage in such a way that they can engage in several income-generating activities apart from tea production-related activities in the tea estates.

The Household Multidimensional Poverty Reduction Effects of Digital Financial Inclusion: A Financial Environment Perspective

The Household Multidimensional Poverty Reduction Effects of Digital Financial Inclusion: A Financial Environment Perspective

Breaking the chains of poverty: examining the influence of smartphone usage on multidimensional poverty in rural settings

We analyze the impact of smartphone usage on multidimensional poverty reduction. Utilizing the A-F approach, we compute a multidimensional poverty index based on five dimensions: education, health, income, living standard, and labor force. This index categorizes multidimensional poverty into three levels: Vulnerable Multidimensional Poverty Index (VMPI), General Multidimensional Poverty Index (GMPI), and Extreme Multidimensional Poverty Index (EMPI), following MPI criteria. Furthermore, we investigate the mediating role of social capital in the smartphone-multidimensional poverty relationship through a mediating effects analysis. We used the survey data of 382 sample out-of-poverty rural households in Jiangxi, China, in 2020. Our results indicated that: (1) Education (37.80%), labor force (29.7%), and health (20.40%) were identified as the primary contributors to multidimensional poverty. (2) Increasing deprivation categories correlated with declining multidimensional poverty index, following an inverted U-shaped pattern. (3) Smartphone usage significantly reduced VMPI (57.6%), GMPI (52.6%), and EMPI (5%). (4) Social capital fully mediated EMPI reduction through smartphones (91.67%), and partially mediated VMPI (14.09%) and GMPI (20.84%) reduction. These insights inform targeted policy formulation for rural multidimensional poverty reduction.

Can technological innovations contribute to more overcome the issue of poverty reduction in africa?

Although recent years have shown that innovation can also thrive in economies where the challenges of absolute poverty and inequality remain long-standing problems, the effects of innovation on poverty reduction has remained a largely unexplored field of investigation. . So this study assesses the effect of technological innovations on poverty reduction using a panel of 36 sub-Saharan African countries over the period 2008 to 2019. More specifically, the study examines the influence of technological innovation on poverty reduction. Using the principal component analysis (PCA) we constructed an indicator of the use, adoption and adaptation of technological innovations and that of multidimensional poverty. After applying several estimation techniques for panel data such as fixed effects, Driscoll and Kraay, kiviet (2020), Lewbel two stage least square (Lewbel 2SLS), mediating effects, the results shows that technological innovations significantly reduce poverty in sub-Saharan Africa. Our results survive several robustness checks. Taking into account the level of urbanization, it appears that technological innovations reduce poverty in countries with low urbanisation rates and increase it in countries with high urbanization rates. Finally, the analysis of mediation effects suggests that almost 30 % of the total effect of the use, adoption and adaptation of technological innovations on multidimensional poverty reduction is through the improvement of productivity in the industrial sector while 62.5 % is through the productivity of the agricultural sector. These results imply that poverty reduction policies in sub-Saharan Africa need to refocus on capacity building in the use, adoption and adaptation of technological innovations, particularly in the agricultural and industrial sectors.

Emprego fora da fazenda e pobreza multidimensional: evidências empíricas da bacia do rio Amarelo na China

ABSTRACT: As an essential way to enhance farmers’ self-development ability, off-farm employment plays an indispensable role in farmers’ multidimensional poverty reduction in many countries. Employing a survey of 1926 farmers in five provinces of the Yellow River Basin in China, this paper examined the multi-dimensional poverty reduction effect of off-farm employment and the heterogeneous influence of different dimensions of off-farm employment (modes, levels, distances and frequency). The results showed that (1) although absolute poverty in the income dimension was largely eliminated in the Yellow River Basin, the poverty in social resources, transportation facilities, employment security were the key bottlenecks restricting farmers’ self-development. (2) The province with the best multidimensional poverty reduction effect for non-farm employment was Shaanxi, with the largest contribution to employment security. (3) Improving off-farm employment level, distance and time can significantly alleviate the multi-dimensional poverty of farmers. Therefore, to lessen the multi-dimensional poverty of farmers in the Yellow River Basin, it is necessary to focus on the governance of multi-dimensional key poverty-stricken areas, such as the middle and upper courses of the Yellow River, adopting multidimensional poverty alleviation strategy of off-farm employment according to local conditions, working on the farmers’ deficiencies in social resources, mobility, employment security, and deepening the effect of off-farm employment on benefiting farmers and helping the poor.

Economic growth and quality of education: Evidence from the national high school exam in Vietnam

This study considers the impact of economic growth on the quality of K-12 education in a transitional country over the 2016–2019 period, utilizing sub-national-level data. The study employs two-stage least squares for the panel-data model, confirming that (i) a one percentage point rise in per capita income increases national test scores in Vietnam by around 0.4–1.83%, and (ii) this nexus is influenced by the quality of institutions and by poverty levels. Notably, we find a non-linear relationship between economic growth and education: economic growth exhibits a U-shaped relationship with English scores, while its association with mathematics scores follows an inverse U-shaped pattern. The current study thus adds to the body of evidence supporting the link between educational quality and economic growth. As a result, policymakers in transitional nations can use the forces of economic growth to advance social objectives, rather than concentrating primarily on changing the educational system through increased government spending. In order to maximize the benefits of economic growth for the education system, the government policies should focus on assuring institutional quality improvement and multidimensional poverty reduction.

Unveiling groundwater potential zones as catalyst for multidimensional poverty reduction using analytical hierarchical process and geospatial decision support systems (S-DSS) approach in the semiarid region, Jigawa, Nigeria

Integrating agricultural production with the identification and use of groundwater resources has been shown to reduce multidimensional poverty in semi-arid regions. Poverty reduction and socioeconomic growth depend on sustainable water supply, especially in developing countries with limited rainy seasons. Poverty eradication is a top priority among the 17 Sustainable Development Goals (SDGs), and its reduction in the 21st century has led to significant advances in research. This study used remote sensing, geographic information system (GIS), and geospatial decision support system (S-DSS) approaches to uncover potential groundwater zones. The Analytic Hierarchy Process (AHP) integrates geospatial data to create a groundwater potential zone map and suggests the best land requirements for groundwater abstraction for poverty alleviation programs. The groundwater potential zone maps indicate that the majority of the region was in the high-potential zone, covering 59.75% of the total area, followed by a moderate-potential zone at 23.21%, an extremely high-potential zone at 14.6%, a low-potential zone at 2.44%, and an extremely low-potential zone at 0%. In addition, the study emphasizes the need for alternative water sources and infrastructure development in dry seasons in areas with fewer drainage systems and proposes measures such as rainwater harvesting structures and small reservoirs. Diversifying income sources by promoting alternative livelihoods can help reduce poverty and vulnerability to fluctuations in agricultural productivity. The integration of socioeconomic data into the S-DSS framework will provide a comprehensive understanding of the complex relationship between groundwater resources, poverty, and socioeconomic development, enabling informed decision-making in water resource management for poverty reduction initiatives and the achievement of the 2030 Agenda for Sustainable Development Goals.

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

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.

Multidimensional poverty and the variables that contribute to it in the Gurage Zone of Ethiopia: Using rural-urban migration as a decomposition parameter

BACKGROUND: Poverty alleviation is a critical issue for national and international development goals. Data on different poverty-reduction measures are eagerly sought by policymakers. Analytical data on the role of migration in poverty alleviation is one of them. OBJECTIVES: This study is designed to investigate the prevalence of multidimensional poverty and its determinants in connection to rural-urban migration. METHODS: Primary data was collected from 384 randomly selected rural households and analyzed using econometric models. RESULTS: Non-migrant and migrant-sending households had adjusted headcount ratios of 19.8% and 10.5%, respectively. Poor living conditions were identified in 43.5% of non-migrant households and 25.6% of migrant-sending households, respectively. Non-migrant households and migrant-sending households contributed 70.5% and 29.5%, respectively, to the entire sample’s adjusted headcount ratio. According to the findings, household size, the number of migrants per household, the education level of the household head and livestock ownership all has a significant effect on households’ multidimensional poverty. CONCLUSIONS: The results demonstrate that rural-urban migration helps poverty reduction in the region. Therefore, proper consideration should be given to maximizing the benefit of migration on the long-term reduction of multidimensional poverty through productive remittance investment and assisting households to improve their productive capacity.

MANAGING AND DEVELOPING SUSTAINABLE MULTI-DIMENSIONAL POVERTY REDUCTION AND VOCATIONAL TRAINING MODELS FOR LOCAL ETHNIC MINORITY WOMEN IN THE CENTRAL HIGHLANDS IN THE CURRENT PERIOD: SITUATION AND PROBLEMS

The research and development of effective vocational training models, associated with livelihood development and sustainable multi-dimensional poverty alleviation for local ethnic minority women in accordance with socio-cultural characteristics. The socio-culturalization of each particularly difficult commune in the Central Highlands is an important and urgent issue in the current period with profound social and humanistic meanings. This article has conducted an overview of the issue of vocational training, vocational training model and sustainable multi-dimensional poverty reduction for local ethnic minority women, thereby deeply analyzing the current situation and problems posed for the vocation training models of local ethnic minority women, continue to research and effectively implement vocational training models for rural workers in general and for ethnic minority women, especially local ethnic minority women in particular in the Central Highlands during the current period.

Does Women’s Empowerment Influence Multidimensional Poverty? Empirical Insight from Rural Odisha of India

The prominent role played by women’s empowerment and multidimensional poverty reduction in the development process is justified by including Goal-1 and Goal-5 under the 2030 agenda of UNDP’s Sustainable Development Goals. This study examines the nexus between women’s empowerment and multidimensional poverty in rural areas of the Jagatsinghpur district of Odisha. The Alkire-Foster method is used to construct Women Empowerment Index and Multidimensional Poverty Index. Education, health, economic, and standard of living dimensions construct MPI and economic, social, political, and domestic empowerment dimensions for WEI. This study observed that more than two-thirds of women are deprived of asset ownership and employment, and more than half of nutrition, access to improved sanitation, and clean energy for cooking. The results of the OLS model revealed the positive impact of women’s empowerment with occupation, age, and education in reducing multidimensional poverty. Based on the findings, the study envisages appropriate policy intervention in enhancing the educational level and generation of self-employment opportunities in empowering women and reducing multidimensional poverty.

Inclusive Poverty Reduction for Sustainable Development in Nigeria

This study is premised upon the fact that any poverty reduction programme that is not inclusive can not fully deliver on sustainable development. Hence, the study focus is on how poverty alleviation policies can be inclusive so as to guarantee susatainable development in Nigeria. The study appraised some of the poverty reduction programmes in Nigeria so as to assess the extent to which they are inclusive when compared with global best practice using the Chinese multi-dimensional poverty reduction model. The study revealed that the Chinese model was designed to capture various dimensions of poverty with the intention of solving them based on their uniqueness and that some poverty levels are environmentally determined. The study further revealed that the poverty reduction approaches in Nigeria cannot be said to be inclusive and sustainable. level and to suggest possible solutions in order for poverty reduction policies to bring about desired inclusivity and sustainable development in Nigeria. The study recommended that Government policy on poverty alleviation should follow a multisectoral approach where all the stakeholders are given specific roles to play and that the Government should determine how the intended beneficiaries are to be identified to ensure that the benefits reach them directly.

Does Land Lease Affect the Multidimensional Poverty Alleviation? The Evidence from Jiangxi, China

This study uses field survey data from 382 families in the year 2020 in Jiangxi province, China, to explore the effects of land lease and labor migration, a well-known occurrence in China, on rural households’ multidimensional poverty status. We used the A-F method to measure the household’s multidimensional poverty in terms of health, education, income, living standard, and social relations. The Bootstrap Test approach, which worked well with our data, was used to build our mediating effect models while taking into account the influence mechanisms of land leasing and multidimensional poverty. According to our findings, 76.70% of sample homes experience multidimensional poverty at the threshold of 0.33. The reduction of multidimensional poverty is significantly aided by both leasing in and leasing out land. Land lease out and land lease in, however, have asymmetrical effects on multidimensional poverty alleviation, with the proportion of land lease out being 1.147 without control variables and the proportion of land lease in being 0.969 without control variables. Land lease in and lease out have positive effects on the multifaceted alleviation of poverty due to the mediating effect of labor migration. For policymakers to develop and put into action more relevant policies to help multidimensional poverty alleviation, our analysis offers critical insights.

Evolution of Multidimensional Poverty in Crisis-Ridden Mozambique

Mozambique experienced important reductions in the poverty rate until recently, before two major natural disasters hit, an armed insurgency stroke in the northern province of Cabo Delgado, and the country started suffering from a hidden debt crisis with associated economic slowdown. As the last available national household expenditure survey is from 2014/15, just before these crises started unfolding, there is need for a poverty assessment based on alternative data sources. We study the evolution of multidimensional poverty in Mozambique using survey data from the Demographic and Health Surveys (DHS). Using both the standard Alkire–Foster multidimensional poverty index and the first-order dominance (FOD) method, we find that the multidimensional poverty reduction trend observed between 2009–11 and 2015 halted between 2015 and 2018. Meanwhile, the number of poor people increased, mainly in rural areas and in the central provinces. Importantly, the poorest provinces did not improve their rankings over time, and between 2015 and 2018, no progress took place for most areas and provinces, as measured by the FOD approach.