Income Poverty Research Articles

Gender Dimensions of Forced Displacement: A Brief Review and Introduction to the Special Issue

Displacement has increased continuously over the last 12 years and the number of forcibly displaced persons has reached an unprecedented level. More than half of all forcibly displaced persons are girls or women; yet very little is known about how gender intersects the behavior and welfare of forced displacement. This special issue focuses specifically on the gender dimensions of forced displacement. We make both topical and methodological contributions to knowledge about gender norms, livelihoods, multi-dimensional and income poverty, and gender-based violence and discuss the implications of our findings for future research, policy and practice.

Spatial suitability of urban land use models for poverty alleviation in the cities of Nigeria

Many models depicting the spatial dimensions of poverty are based on cities in developed countries, raising questions about their appropriateness for urban spaces in developing countries. This study evaluates the spatial suitability of these models in understanding poverty distribution and informing alleviation efforts related to Sustainable Development Goal (SDG). One in cities of developing nations. A grid sampling technique in ArcGIS 10.8 was used to select 1098 households across 56 wards in three mid-sized Nigerian cities. Household data were collected through structured questionnaires using GeoODK, and Maxar high-resolution imagery was used to assess urban building density. The Foster-Greer-Thorbecke (FGT) poverty indices and Pearson correlation were applied for analysis. Results showed that over 29 wards had a poverty incidence and gap index greater than 0.20, while poverty severity remained below 0.20 in most wards. High building density was more prevalent in the city’s interior. Significant correlations were found between the income poverty gap (p = 0.005, r = 0.367), poverty severity (p = 0.009, r = 0.346), and building density. The study concludes that these models are suitable for informing poverty alleviation policies in mid-sized cities of developing countries, especially Nigeria.

Impact of the Agricultural Sector on Unemployment, Inequality and Rural Poverty: A Panel Regression Analysis in Indonesian Provinces

This study examined how the agricultural sector impacted unemployment, income inequality, and rural poverty across Indonesia’s provinces from 2015 to 2021. Using data from the Central Bureau of Statistics (BPS) and a panel regression model, the research analyzed the relationships between these factors. It also explored the structural changes caused by the COVID-19 pandemic in 2020-2021. The findings showed that the agricultural sector’s Gross Regional Domestic Product (GRDP), farmer exchange rates, and informal labor significantly influenced unemployment and income inequality in rural areas. However, the pandemic did not have a major effect on income inequality or poverty levels in these areas. The GRDP and value-added in agriculture played a crucial role in reducing rural poverty. The findings also showed that the COVID-19 pandemic did not directly increase or decrease the number of poor people, but it affected informal agricultural workers due to physical distancing measures. The research highlighted the agricultural sector’s importance in addressing unemployment and inequality during the pandemic in Indonesia.

Impact of compliance with project requirements on projects value outcomes: Evaluation from TASAF-III beneficiaries’ perspectives in Tanzania

The study sought to evaluate the impact of compliance with projects requirements on projects value outcomes from Tanzania Social Action Fund (TASAF)-III beneficiaries’ perspectives in Tanzania. Specifically, the study evaluated the impact of compliance with project requirements on households’ relief from transitional income poverty (as a measure of projects value outcomes) in Tanzania. The study was a cross sectional design with multiple cases approach undertaken in twelve TASAF-III supported community economic development (CED) projects. Under multistage sampling procedure, the said CED projects, their six hosting districts and regions (Kilosa–Morogoro; Handeni–Tanga; Misungwi–Mwanza; Uyui–Tabora; Kibondo–Kigoma; and, Rungwe–Mbeya) were identified using stratified sampling. Simple random sampling enhanced to determine a sample of 480 households. Data were collected using research schedules and were descriptively and inferentially analyzed using STATA software. Propensity score matching (PSM), coupled with logistic model was considered the apt test statistic. The average treatment effect on the treated (ATT) observation results shown that, the mean differences in incomes [TZS. 7 794.30; t=0.61(t<2.00)] and spending [TZS 11 388.50; t=0.96 (t<2.00)] between the treated and control households’ are non-significant at t<2.00. This implied that, compliance with TASAF-III project requirements has no significant impact on households’ income poverty relief in Tanzania. Moreover, compliance with requirements does not necessarily lead to desired projects value outcomes—if requirements are not well defined. The study stresses on the selection of right projects’ requirements with positive outcomes rather than having a set of requirements which are non-predictive to the desired targets’ felt needs—when in compliance with.

The prevalence of overweight among 4-year-olds during and after the COVID-19 pandemic was associated with socioeconomic burden.

To assess the prevalence of overweight among Swedish 4 year olds in 2018, 2020 and 2022, taking socioeconomic variables into account. Aggregated regional data on children's body mass index were collected. The socioeconomic Care Need Index (CNI), foreign background, low education, being a single parent, low income and childhood poverty, were assessed. The differences in overweight, including obesity, were tested for Sweden and for regions. Data were available for 303 843 children, representing 87% of children born in 2014, 2016 and 2018. Overweight or obesity were found in 11 177 (11.4%) of children in 2022, decreasing from 2020 (13.3%, p < 0.001) but at the same level as in 2018. Regional low CNI, low level of foreign background, education and income as well as being a single parent were associated with a higher prevalence of overweight or obesity in all cohorts (p < 0.001). In regions with high levels of childhood poverty, overweight or obesity were more prevalent during (p = 0.009) and after the pandemic (p < 0.001). Three national cohorts demonstrate that the increase in overweight during the COVID-19 pandemic has returned to pre-pandemic levels, but the inequalities in health associated with socioeconomic vulnerability of the regions remained.

Exploring Livestock and Agricultural Income Poverty among Farming Households: Study Based on Mirzapur District of Uttar Pradesh

Exploring Livestock and Agricultural Income Poverty among Farming Households: Study Based on Mirzapur District of Uttar Pradesh

Small cash transfers to older people: do they reduce poverty?

Abstract The literature has shown that, in developing countries, large cash transfers to older people improve the wellbeing of the recipients and their families. While social pensions have recently emerged in East Asia to deliver small cash benefits to older people, there is little consistent evidence of their effects. We examine the effects of the Basic Pension Scheme, a social pension in South Korea, on income and consumption poverty among older adults. We apply a difference-in-differences event study design and other complementary approaches to data covering the full period of program development from 2006 to 2021. The results show that the social pension decreases income poverty but not consumption poverty. While this study analysed the best data currently available, using better-quality data in future research would enable more robust analysis. Further research is also warranted to find how to improve the effectiveness of a non-contributory pension programme as a tool for reducing income and consumption poverty among older adults.

Income Distribution, Inequality and Poverty: Evidence, Explanations and Policies

In recent years, there has been an increasing focus on the complex challenges posed by income inequality and poverty, both in developed and developing nations [...]

Association Between Secondhand Smoking and Cardiovascular Health Among the U.S. Adult Population Who Participated in the 2017-2018 NHANES Survey

The purpose of this study was to expand upon previous research by investigating the relationship between exposure to secondhand smoking and cardiovascular health in the general U.S. population across various demographic variables. Methods: Using a nationally representative sample, from the 2017-2018 NHANES survey, patterns of secondhand smoking and cardiovascular health issues were examined. This relationship was examined individually and in combination with other sociodemographic characteristics such as gender, family income/poverty, race, education level, birth country, U.S. citizenship status, and language of interview using multivariate logistic regression. Results: The data included 3882 subjects including 23.6% of participants who were exposed to secondhand smoking while 76.33% had not been exposed. Individuals who reported that they were not exposed to secondhand smoke had 32.1% lower odds (95% CI: 0.56-0.82) of having cardiovascular health issues compared to individuals who reported being exposed secondhand smoke, (95% CI: 0.56-0.82). Additionally, statistically significant associations between secondhand smoking and cardiovascular health were identified when factoring in various demographic factors such as gender, ratio of family income poverty, birth country, U.S. citizenship status, education level, and cardiovascular health issues. Conclusion: These results indicate that secondhand smoking exposure should be avoided to potentially reduce the risk of cardiovascular health issues

Leveraging Greenspace to Manage Urban Flooding: An Investigation of Nature-Based Solutions Implementation in U.S. Public Parks

Many cities are looking to adopt nature-based solutions (NBS) in greenspace to manage urban flooding and provide diverse co-benefits. Yet little research exists to inform the planning and design of park NBS. This study investigated NBS adoption in 58 public parks across major U.S. cities, using a 2022 survey by the Trust for Public Lands and other secondary datasets. We developed a typology to conceptualize a wide range of park NBS into five high-level categories by size/capacity, location of the gray–green spectrum, and design objectives. We then employed this typology to explore how a park’s adopted NBS types may relate to its landscape and sociodemographic contexts. We found that the most used type of NBS in the studied parks was ECO (a typology we defined as conserving, restoring, or creating ecosystems to mitigate flooding through ecological processes and functions), while the least used NBS type was ENG (a typology we defined as imitating natural infiltration processes but having no living elements). Further, parks that adopted ECO had significantly higher percentages of greenspace in the surrounding, as well as higher flood risks. We also found notable—though not statistically significant—evidence of potential associations between the type of NBS implementation in a park and its nearby neighborhoods’ income level, poverty, and population racial and age compositions. Moreover, our findings indicated that park visitors were more privileged compared to residents living near a park. We concluded that park contextual factors deserve more explicit consideration in the planning and design of NBS and discussed key implications of this study for practice and future research around park NBS for urban flooding.

Age-friendly human resource practices: a comparison of Baltic and Nordic countries

PurposeDue to population ageing, the European Union (EU) has adopted active ageing as a guiding principle in labour and retirement policies. Among the strategies for active ageing, age-friendly workplaces play a crucial role. This study compares age-friendly human resource (HR) practices in the Baltic and Nordic countries. The latter are pioneers in active ageing, and as the employment rate of older employees in the Baltics is like that in the Nordic countries, we may assume equally age-friendly workplaces in both regions.Design/methodology/approachWe used the latest CRANET survey data (2021–2022) from 1,452 large firms in seven countries and constructed the fuzzy logic model on age-friendliness at the workplace.FindingsDespite a high employment rate of older individuals in the Baltics, HR practices in these countries fall short of being age-friendly compared to their Nordic counterparts. Larger firms in the Nordic countries excel in every studied aspect, but deficiencies in the Baltics are primarily attributed to the absence of employer-provided health and pension schemes. The usage of early retirement is more frequent in the Nordic countries; however, its conceptualisation as an age-friendly HR practice deserves closer examination. Our findings suggest that the success of active ageing in employment has translated into age-friendly HR practices in larger organisations in the Nordics, but not in the Baltics. It is likely that high employment of older individuals in Estonia, Latvia and Lithuania is a result of the relative income poverty rate.Originality/valueOur model represents one of the few attempts to utilise fuzzy logic methodology for studying human resource practices and their quantitative evaluation, especially concerning age-friendly workplaces.

Geospatial determinants of urban poverty in Nigeria: an analysis of locally weighted factors

ABSTRACT Determining the factors that influence poverty has been seen as one of the ways of identifying appropriate poverty alleviation strategies in cities. This has been done, in most cases, through the application of ordinary least squares (OLS), which assumes homogeneous influence without considering the spatial heterogeneity that may occur in this influence. This study aims to determine the spatial heterogeneity in the influence of public infrastructure, economic, environmental, and social factors on poverty, by carrying out comparison analysis using OLS and Geographically Weighted Regression (GWR) in ArcGIS Pro 3.0.1, with a view of proffering poverty alleviation strategies for each section of an urban area. A questionnaire in Geographic Open Data Kit (GeoODK) was administered to 366 urban residents across the twenty wards in the selected city in Nigeria. The results reveal that factors that influence income poverty are spatially varying in direction and weight across a city. Spatial heterogeneity of poverty’s determinants should be considered in the formulation and implementation of effective poverty alleviation policies and programs.

Effect of Fintech on Sustainable Development Goals: An Empirical Analysis

Abstract This paper empirically examines the impact of financial technology (FinTech) and financial inclusion on sustainable development goals (SDGs). The adoption of FinTech has a significant positive effect on key SDGs in developing nations. Specifically, FinTech contributes to reducing income inequality and poverty, while promoting gender equality, access to basic sanitation, clean energy, and education. Additionally, the increasing adoption of FinTech is linked to overall economic growth. To address potential biases from heteroscedasticity and endogeneity, we conduct robustness checks using simultaneous equation modeling and Poisson pseudo-maximum likelihood estimations. Our findings confirm that the benchmark results are robust. JEL Codes: O1, O19, O20, Q01. Keywords: Sustainable Development Goals, SDG, Fintech, Financial Inclusion, Pseudo – Poisson Maximum Likelihood (PPML), Simultaneous Equations Model (SEM).

Navigating poverty in developing nations: unraveling the impact of political dynamics on sustainable well-being

Political instability, dismal governance, and corruption are among the factors that currently distress poverty. The primary objective of this research was to determine how political factors distress poverty in developing nations, which has perhaps not been investigated yet. The main objective was also to observe if the effect of political factors on poverty is a dilemma or a reality. Poverty (dependent variable) has been divided into two segments: income poverty index and Human Health Poverty Index; however, political factors (independent variables) studied were corruption, democracy, governance, and political globalization. Twenty-six years of data were taken from 1997 to 2022 of twenty-four developing nations. The poverty and institutional quality indices were constructed through Principal Component Analysis (PCA). The Fixed Effect, System GMM, and 2SLS approaches were used to determine the dynamic impact on poverty. Furthermore, this study incorporated fixed effects with Driscoll-Kraay standard errors to address cross-sectional dependence. The findings indicated that, although there was a significant connection between governance and income and human poverty. Democracy also showed a negative and significant relationship in the income poverty model but insignificant in the human poverty model. Political globalization showed negative and significant associations with poverty models (income and human poverty). Conversely, corruption showed a significant positive relationship in poverty models, i.e., income and human poverty.

Effects Of Rural Agriprenuership Investment On Income Generation And Poverty Reduction In Southeast, Nigeria

The study assessed the effects of rural agriprenuership investment as nexus for poverty reduction and income generation in southeast Nigeria using 200 respondents selected through random sampling technique. Data were collected using questionnaire administered in the form of interview schedule. Data collected were analyse using descriptive statistics such as frequencies percentages, and multiple regression. Results indicated that agriprenuership investors were mainly male (63%) investors with average age of 41years and were married with average household size of 6 persons. Furthermore, the agriprenuers investors’ had 10 years average experience in agriprenuership investment that earned average annual household income of N676,176.00, and were members of co-operative societies. Result also showed that the income distribution of female agriprenuerial households was at high inequality as seen in the convex nature of the Lorenz curve to the line of equality. Results also showed that the income distribution of male agriprenuers where evenly distributed as it was almost parallel to the line of equality. Result further showed agricultural enterprises accounted for 72% changes in income generation of agriprenuers as evident from the R2 of 0.72 that income from livestock production (3.390), crop production (2.710) and processing sector (1.301) were positive and significantly related to the income generation. Similarly, agricultural enterprises accounted for 84% changes in poverty reduction as production (1.674) and processing sector (3.688) were positive and significantly related to poverty reduction. From the finding, it was concluded that rural agripreneurship investment had positively and significantly influenced agriprenuers income generation and poverty reduction in Southeast, Nigeria. The study recommended for the creation of environment that favours investment in the rural areas especially in linking rural areas with microfinance

Understanding and Explaining Recent Changes in Income, Consumption and Poverty Among Agricultural Households Across Major States of India

The study, using unit level data from two nationally representative surveys, examines changes in levels and sources of household income, consumption expenditure, incidence of poverty and determinants of household income and poverty among agricultural households. The study shows that across most of the states, there has been a significant decrease in the per cent share of income from cultivation coupled with an equally significant increase in the share of income from wages and salary; average annual household income of such households is higher than their average annual consumption expenditure and there has been a significant decrease in the incidence of poverty among them. The results of regression analysis show that household size, head of the household being male, literacy, farm size, income from cultivation, awareness of minimum support price (MSP), access to technical training, engagement in non-farm business and engagement in wages and salary have significant positive effect on households income and lower the probability of a household being poor across major states. JEL Codes: Q1, C1, C2, D1, R2

Addressing financial hardship in malignant hematology and hematopoietic cell transplant: a team approach

AbstractFinancial hardship is a common experience for patients and their families after the diagnosis of a hematologic malignancy and is associated with worse outcomes. Health care costs, increased costs of living, income poverty, and inadequate wealth contribute to financial hardship after the diagnosis and treatment of a hematologic malignancy and/or hematopoietic cell transplant. Given the multidimensional nature of financial hardship, a multidisciplinary team-based approach is needed to address this public health hazard. Hematologists and oncologists may mitigate the impact of financial hardship by matching treatment options with patient goals of care and reducing symptom burden disruptive to employment. Social workers and financial navigators can assist with screening and resource deployment. Policymakers and researchers can identify structural and policy changes to prevent financial hardship. By alleviating this major health care burden from patients, care teams may improve survival and quality of life for patients with hematologic malignancies.

Effects of the Minimum Wage (MW) on Income Inequality: Systematic Review and Analysis of the Spanish Case

The minimum wage has become a standard measure in the economic and social policies of countries all over the world. The primary objective of this measure is to guarantee that workers receive a minimum wage that allows them to lead a decent life, thereby reducing inequality and poverty. However, studies on the minimum wage have not focused on assessing the effects on these dimensions but only on employment. The objective of this study is to address this research gap by analysing the effects of minimum wage increases on income inequality and poverty. To this end, firstly, a systematic review of the empirical analyses was conducted using the PRISMA methodology, with a view to ensuring that all empirical evidence was available. Secondly, the Spanish case was examined. The significant increase in minimum wage in Spain in 2019 (21.3% in real terms) presents an invaluable opportunity to utilise this event as a natural experiment to generate new evidence. A difference-in-differences approach was employed to assess the impact of this phenomenon in the period 2018–2019 with microdata from European Statistics on Income and Living Conditions (EU-SILC for Spain). In doing so, two basic scientific contributions were made. The first one, a systematic, exhaustive, and up-to-date literature review (up to June 2024), as there is, to our knowledge, no recent systematic review of this relationship (minimum wage vs. inequality). The available evidence indicates a clear inverse relationship between the minimum wage and inequalities and poverty. The second one, regarding the Spanish case, there has been a dearth of scientific studies on this subject. Thus, this paper provides new scientific evidence demonstrating that a significant increase in the minimum wage can significantly improve the income of low-wage earners, thereby reducing income inequality and in-work poverty. Furthermore, there is evidence of a spillover effect towards income groups closer to the treatment group.

Targeting SDG7: Identifying heterogeneous energy dilemmas for socially disadvantaged groups in India using machine learning

To achieve Sustainable Development Goal (SDG) 7, prioritizing the socially disadvantaged segments of the population is imperative, given their inherent susceptibility to heightened risks of energy exclusion. However, a comprehensive understanding of the diverse energy challenges faced by households with socio-economic disparities remains elusive. This article thus addresses this gap by examining three widely acknowledged categories of marginalized households in India: racial inferiority, income poverty, and gender inequality. It notably pioneers the quantification of an umbrella pattern of energy deprivation within the SDG7 framework, encompassing energy unaffordability, energy unreliability, energy inaccessibility, and energy inequality. To do so, leveraging the latest household survey dataset and employing least squares estimates, we preliminarily capture that these three disadvantaged groups encounter significant energy barriers in the pursuit of SDG7 achievement. Given respectively selected models based on Least Absolute Shrinkage and Selection Operator (LASSO) approach, the gradient boosting model (GBM), another state-of-the-art machine learning technique, is subsequently adopted to verify feature significance and rank its importance in determining diverse energy deprivation faced by each group. The results reveal that the disadvantaged caste groups and those experiencing greater gender inequality encounter the greatest impediments to their right to reliable energy access. In comparison, energy unaffordability poses a paramount challenge for low-income households. These findings enable policymakers to design straightforward interventions that address a spectrum of socio-economic disparities, thereby fostering an just energy transition grounded in data-driven evidence.

Unionization rates, inequality, and poverty in Canadian provinces 2000–2020

Unions can increase the power of workers through both collective bargaining and political avenues, potentially creating less income inequality and poverty. However, this potential may not be realized. Drawing on power resource theory, this study uses panel data to investigate the connection between unionization and two measures of after-tax inequality – the income share of the top 1% and the Gini coefficient – and three measures of poverty – the percentage of the population below the low-income cut-off, the average income of the bottom decile, and the percent of the population below the low-income measure – between Canadian provinces from 2000 to 2020. We find that unionization is negatively associated with income inequality in Canada. This relationship is statistically significant. However, we do not find evidence of any statistical association between unionization and poverty in Canada.