Income Poverty Research Articles

Rural household income mobility in Ethiopia: Dimensions, drivers and policy.

Welfare dynamics studies are useful in understanding how individuals, families, society, and a country are organised. For the last two decades, Ethiopia's economic reports on income disparity, poverty, and other welfare metrics have been hopeful and controversial. It is crucial to understand how rural households of various income levels perform over time and income mobility. Income mobility can be observed as a change in position over time between two income vectors, with some climbing and others sliding down and changing places at various rates. This study, therefore, explored the rural households' income mobility in Ethiopia using three waves of the Living Standards Measurement Study-Integrated Survey on Agriculture (LSMS-ISA) collected from 2011 to 2016. The Shorrocks rigidity index, transition probability matrix, Fields, and Ok methods were employed to analyse the relative and absolute income mobility. The logit model with conditional fixed effect was used to assess the drivers of individual households' income mobility and the multinomial logit model with conditional fixed effect as an alternative model. Based on the finding of this study, it is suggested to implement different policies targeting income growth to shorten mobility gaps and address factors contributing to downward income mobility in rural households in Ethiopia are necessary.

Identifying groups of children's social mobility opportunity for public health applications using k-means clustering

BackgroundThe Opportunity Atlas project is a pioneering effort to trace social mobility and adulthood socioeconomic outcomes back to childhood residence. Half of the variation in adulthood socioeconomic outcomes was explainable by neighborhood-level socioeconomic characteristics during childhood. Clustering census tracts by Opportunity Atlas characteristics would allow for further exploration of variance in social mobility. Our objectives here are to identify and describe spatial clustering trends within Opportunity Atlas outcomes. MethodsWe utilized a k-means clustering machine learning approach with four outcome variables (individual income, incarceration rate, employment, and percent of residents living in a neighborhood with low levels of poverty) each given at five parental income levels (1st, 25th, 50th, 75th, and 100th percentiles of the national distribution) to create clusters of census tracts across the contiguous United States (US) and within each Environmental Protection Agency region. ResultsAt the national level, the algorithm identified seven distinct clusters; the highest opportunity clusters occurred in the Northern Midwest and Northeast, and the lowest opportunity clusters occurred in rural areas of the Southwest and Southeast. For regional analyses, we identified between five to nine clusters within each region. PCA loadings fluctuate across parental income levels; income and low poverty neighborhood residence explain a substantial amount of variance across all variables, but there are differences in contributions across parental income levels for many components. ConclusionsUsing data from the Opportunity Atlas, we have taken four social mobility opportunity outcome variables each stratified at five parental income levels and created nationwide and EPA region-specific clusters that group together census tracts with similar opportunity profiles. The development of clusters that can serve as a combined index of social mobility opportunity is an important contribution of this work, and this in turn can be employed in future investigations of factors associated with children's social mobility.

Families of children with disabilities: income poverty, material deprivation, and unpaid care in the UK

Child disability and provision of unpaid care by parents may contribute to a family’s poverty status. In this paper, using data from the Family Resources Survey-2018/19, a sample of 5451 families with dependent children was analysed. Sub-samples were created based on the groups of interest: child disability vs no child disability within the family and unpaid care vs no unpaid care for children with disabilities. Logistic regression models show sociodemographic factors have similar effects on children’s material deprivation and after housing costs poverty across all groups. In contrast, having children with no disability has higher odds of after housing costs poverty.

Socio-Economic and Property Crime Rate in Indonesia

This study aims to analyze the effects of socio-economic factors (inequality in income distribution, poverty, unemployment, and population) on crime rates in 31 provinces in Indonesia. The article utilizes yearly data published by the Central Bureau of Statistics (BPS-Indonesia) from 2013 to 2022. This study examines the socio-economic effects on crime rates using the two-step System Generalized Method of Moments (SYS GMM). The estimation shows that the lag in the number of property crimes positively and significantly affects property crime in Indonesia. This result indicates a dynamic relationship with the property crime rate. Moreover, poverty, unemployment, and total population positively and significantly affect short- and long-run property crime rates. However, the Gini index shows a positive correlation but lacks significance in both short- and long-term effects. These estimation results recommend that efforts be made to alleviate poverty and ensure equitable income distribution. Poverty and inequality reduction need to be pursued by all parties, especially the government, through initiatives aimed at expanding employment opportunities and sustainably empowering the community's economy.

Fair and inclusive markets: Why dynamism matters

AbstractWe argue that the economies that achieved inclusive growth, or high sustained and broad‐based growth while keeping a lid on the increase in market income inequality, are characterised by dynamism—a drive towards the acquisition of new capabilities in sophisticated products and processes. What a country produces and how much it competes domestically and internationally are important for achieving fair and inclusive markets. We show empirical evidence that dynamism, as measured by export sophistication, reduces market income inequality and poverty while increasing a broad concept of welfare. We explore policy options to steer industrial and market structures towards raising dynamism, thus providing growth opportunities for both workers and firms.

Impact of Equity in Social Protection Spending on Income Poverty and Inequality

This study aims to investigate whether higher equity in government social protection spending strongly predicts positive changes in income poverty and inequality. Our approach was to regress the measures of absolute poverty and inequality on the indicators of equity in social protection spending at the country level, controlling for the level of spending and the country wealth measured by per capita GDP. For that purpose, we have compiled a dataset of 535 observations from 101 countries over years 1998–2017, including 199 observations for 70 low- and middle-income countries from Europe, Asia, North and South America, and Africa. Our findings support the proposition that equity in social spending (measured by the share of social protection spending going to the bottom quintile) is a significant and strong predictor of improved distributional outcomes (poverty measured at Int$1.90 a day and inequality measured by the Gini index). Moreover, in low- and middle-income countries in our sample the poverty and inequality reducing impact of this equity measure is stronger than in the sample including all countries. The presence of a significant gap in equity of social protection spending between the high-income countries and the rest of countries included in the study signifies that there is a large potential in improving equity in social protection spending in low- and middle-income countries. Social protection reforms in these countries should be focused on extending the coverage of social protection programs and improving access to social protection for the poorest segments of the population.

Geographic Variation in the Quality of Heart Failure Care Among U.S. Veterans

BackgroundThe burden of heart failure is growing. Guideline-directed medical therapies (GDMT) reduce adverse outcomes in heart failure with reduced ejection fraction (HFrEF). Whether there is geographic variation in HFrEF quality of care is not well described. ObjectivesThis study evaluated variation nationally for prescription of GDMT within the Veterans Health Administration. MethodsA cohort of Veterans with HFrEF had their address linked to hospital referral regions (HRRs). GDMT prescription was defined using pharmacy data between July 1, 2020, and July 1, 2021. Within HRRs, we calculated the percentage of Veterans prescribed GDMT and a composite GDMT z-score. National choropleth maps were created to evaluate prescription variation. Associations between GDMT performance and demographic characteristics were evaluated using linear regression. ResultsMaps demonstrated significant variation in the HRR composite score and GDMT prescriptions. Within HRRs, the prescription of beta-blockers to Veterans was highest with a median of 80% (IQR: 77.3%-82.2%) followed by angiotensin-converting enzyme inhibitor/angiotensin receptor blocker/angiotensin receptor-neprilysin inhibitors (69.3%; IQR: 66.4%-72.1%), sodium-glucose cotransporter-2 inhibitors (10.3%; IQR: 7.7%-12.8%), mineralocorticoid receptor antagonists (29.2%; IQR: 25.8%-33.9%), and angiotensin receptor-neprilysin inhibitors (12.2%; IQR: 8.6%-15.3%). HRR composite GDMT z-scores were inversely associated with the HRR median Gini coefficient (R = −0.13; P = 0.0218) and the percentage of low-income residents (R = −0.117; P = 0.0413). ConclusionsWide geographic differences exist for HFrEF care. Targeted strategies may be required to increase GDMT prescription for Veterans in lower-performing regions, including those affected by income inequality and poverty.

Multidimensional Poverty and per Capita Income in Uttar Pradesh: A District-Level Analysis

This article makes an attempt to find the extent of linkage between monetary and non-monetary aspects of poverty based on secondary data. The analysis reveals that the Multidimensional Poverty Index (MPI) of Eastern region is the highest among all regions in Uttar Pradesh. The article finds disparity in terms of MPI and per capita income among districts of Uttar Pradesh. This study also identifies that there is negative relationship between per capita income and multidimensional poverty. Therefore, the article suggests that the government should provide employment oriented education and technical training for skill development especially in backward districts to enhance the ability of their citizens to fetch gainful employment and improve their living standard.

Crecimiento económico inclusivo y comercio internacional en el Perú 2000-2021

Introduction/Purpose: Inclusive economic growth is a concept that has taken on importance in recent years globally; however, it has scarcely been studied in Peru. This research aims to know if there exists a positive relationship between inclusive economic growth and international trade in Peru in the period 2000-2021. Methodology: Inclusive economic growth was measured using the pillars of growth and development (per capita GDP, labour productivity, employment, and life expectancy) and inclusion (income concentration and poverty) of the Inclusive Development Index (IDI) proposed by the World Economic Forum. The Ordinary Least Squares (OLS) method was used to perform the regressions. Findings: The results show that the growth of International Trade in Peru has a positive relationship with two of the indicators of inclusive economic growth analysed: real GDP per capita and Vulnerable Employment. In contrast, it has a negative relationship with Labour Productivity. There is no statistical significance for the Poverty variable. Furthermore, there is no cointegration between Peruvian International Trade and Life Expectancy at Birth or Income Distribution. Conclusions: Therefore, it is concluded that inclusive economic growth has a positive relationship with Peruvian International Trade. The study focuses on four development pillars and two inclusion pillars, so the analysis will serve to propose policies that promote inclusive economic growth in Peru.

Development of work-life/family policy and gendered division of childcare responsibility: the case of South Korea

PurposeThis paper aims to overcome the limitations of studies on work-life balance, which have focused on Western countries without considering “mental” dimensions of gendered childcare. By concentrating on South Korea as a case study, this paper also aims to examine how the gendered division of childcare changed when Korea's work-life/family policy followed European work-family conciliation policy.Design/methodology/approachThe Korean Time Use Survey (KTUS) in 2009 and 2019 are used for multiple regression analyses. Based on discussions about theories on unpaid work distribution within households and its stratification effects, this study examines the relationship between wife's and husband's behaviors and the stratification effects in the gendered division of childcare alongside the work-life/family policy change.FindingsSubstantial findings indicate the necessity of strengthening various legal and institutional structures that might increase husbands' characteristics of caring masculinities. Additionally, while policies developed to support flexible working arrangements, low-income women at risk of being trapped in dual poverty of time and income should be carefully considered.Originality/valueThis study focuses especially on South Korea, thereby contributing to understanding how national policy and gendered distribution of childcare are related. Notably, this link has not been widely discussed in the literature on work-life balance. It also suggests viable directions for future policies depending on gender and socioeconomic status.

Pengaruh Ketimpangan Pendapatan Dan Produktivitas Pertanian Terhadap Kemiskinan Di Provinsi Maluku

The issues of poverty, income inequality, and agricultural productivity are global problems that are still the main focus in many countries around the world. These three factors are interrelated and present complex and multidimensional challenges in sustainable economic development. This study aimed to examine the relationship between income inequality, agricultural productivity, and poverty in Maluku Province from 2018 to 2021. This study used a quantitative approach, and secondary data was taken from the Central Bureau of Statistics (BPS) using time series data. To test the hypothesis, the Ordinary Least Square (OLS) method was used in multiple regression analysis with SPSS 25.0 software. Before carrying out the regression analysis, the data is tested first with classical assumptions. The results showed no insignificant relationship between the poverty variable (Km) and income inequality variable (KP). There is a positive relationship between KP and changes in poverty, where the increase in KP is directly proportional to the increase in poverty and vice versa. However, there is no significant relationship between the variables Km and Agricultural Productivity (PP), so the effect of PP on Km is very small. The KP and PP variables have a relationship of 73.1% and an influence of 57.1% on the KM variable in Maluku Province in 2018-2021

Entrepreneurial Risk and Digital Financial Inclusion: A Cross‐Country Analysis

The inception of financial technologies (Fintech) has enabled expanded use of financial services. Fintech contributes to financial inclusion and by doing so provides impacts on income inequality, poverty and economic growth. A prospective route of influence exerted by Fintech is to assist economic agents in taking entrepreneurial risks. The purpose of this study was to investigate the impact of digital financial inclusion, as enhanced by FinTech, on entrepreneurial risk. An index for measuring levels of digital financial inclusion was constructed based on variation patterns in several indicators of digital activities. A cross‐country model was proposed that relates entrepreneurial risk to digital financial inclusion as well as to a variety of other economic and social factors. Estimation results based on a panel of countries show that digital financial inclusion (0.265), institutional quality (0.169), per capita GDP (0.0456) and education (0.0475) have positive and significant effects on entrepreneurial risk. In contrast, time required to start a business (−0.136) and effective tax rates on capital (−0.494) provide negative and significant effects. In addition, a significant quadratic relationship between entrepreneurial risk and remittances (employee compensation and personal transfers) was found.

KRIMINALITAS DAN MAKROEKONOMI DI ASEAN : APAKAH MEMILIKI HUBUNGAN KAUSALITAS?

This study aims to determine and analyze the causal relationship between crime rates and macroconomic indicators in 5 ASEAN countries. The type of research used is quantitative and descriptive research where the data used are secondary data in the form of panel data from 2012 to 2018. The data analysis used is descriptive and inductive analysis. in the inductive analysis there are several, namely: (1) Unit Root Test (2) Cointegration Test. (3) Granger Causality Test The results of this study indicate that (1). there is no causal relationship between crime and income disparity, (2) Crime does not have a significant short-term causality relationship with poverty. Meanwhile, poverty has a significant long-term causality relationship with crime. (3) There is no causal relationship between crime and unemployment. Based on the results of this study, the authors suggest that the government combines policies of income distribution, poverty, and unemployment, such as implementing progressive taxes and expanding employment, as well as tightening state security.

Urbanization and food security: evidence from Mali

Income poverty remains the main root of urban food insecurity as purchased food represents a major component of the spending of urban residents. The rapid and increasing urbanization and urban sprawl are major concerns for food security in Mali. In Mali, 3.6% of households, are severely food insecure and the food insecurity prevalence rate for urban households is 7.5%. The effect of urbanization on households’ food security was assessed in the literature using only a single measure of food security. In this regard, this study analyzed the effect of urbanization on both objective and subjective measures of food security in Mali, using data from the national survey on food security and nutrition (ENSAN). The data collection was conducted by the Early Warning System against Famine (SAP) on 9,782 households in February 2018. For the objective measure of food security, the study used an OLS model to estimate the effect of urbanization on household food expenditure per capita. Using the household hunger scale (HHS) score, the study estimated two models (logit and ordered probit) to capture the effect of urbanization on subjective measures of food security. The results of the OLS and logit models showed that households living in urban areas are less food secure compared to their counterparts living in rural areas. The results from the ordered probit also confirmed that urban households are more food insecure (mildly and moderately) compared to their counterparts living in rural areas. Based on these results, the study recommends to decision-makers to take into account urban poor households when setting up food safety net programmes.

Time and Income Poverty Measurement. An Ongoing Debate on the Inclusion of Time in Poverty Assessment

Time and Income Poverty Measurement. An Ongoing Debate on the Inclusion of Time in Poverty Assessment

Education Of Children with Special Needs- A Systematic Review of Literature

The education of the Special need children has always been a significant area of study. Children with special abilities are often seen out of school which in turn lowers their chances of progressing in the employment area which further in turn constitutes long term income poverty. For a developing nation like India, it is needed that such marginalization is catered in the right way to progress holistically. Inclusive education has been in talks for long but its implementation at a wider & more comprehensive level is under process. Objectives- Based on this, the present study aims to review secondary sources of data to (a) find concerns of teachers regarding inclusion of the Special need children into mainstream education, (b) understand awareness of Special need regarding their education and its legal provisions, and, ( c) explore the gaps in legislation in awareness and implementation of equitable services for the Special need. Method- Data was collected from secondary sources such as review papers and analysis through systematic review of literature was done and conclusion was derived from it. Conclusion- Regular monitoring of implementation of inclusive education should be adhered to along with both in-service and pre-service teacher and professional personnel training. Further research is required to understand and uplift community awareness and knowledge, attitude and beliefs of the Special need regarding their education and upliftment.

Tackling Crippling Poverty, Panacea to The Nigerian Economic Decay

The issue of poverty is a multidimensional conception and often defined by zeroing mainly on income poverty or broadly by including lack of access to opportunities for raising standards of living. However, tackling crippling poverty in a Nation at crossroads like Nigeria requires the need to identify factors that are strongly associated with poverty and agreeable to modification by policy formulation and implementation. The focus of the research work was basically to examine the poverty level and its determinants in Ado-Ekiti. Primary data were collected from the random sample of 101 salary earners using self-structured questionnaire. Descriptive statistics were used to analyze the socioeconomic characteristics of the respondents. The poverty level was measured using Foster, Greer and Thorbecke (FGT) poverty indices, while probit regression model was employed to examine factors that influence poverty among the salary earners. The result from the descriptive statistics showed that the female salary earners within the age bracket of 34-41 years with polygamous marital status were pro poor. The incidence of poverty show that 46.5% of the sampled salary earners were actually poor based on the poverty line. The poverty depth indicated that an average poor salary earner would require 13.9% of the poverty line to get out of poverty, while the poverty severity was 6.23%. Estimation by gender group revealed that poverty was most pervasive among female salary earners with a value of 3.7% compared to other category. The probit regression further indicated that the likelihood of being poor were more with household size, level of education, place of occupation and income level. The study, therefore, recommended amongst other things that government should embark on a poverty alleviation program, especially for women so that the unemployed among women folk can be financially empowered Keywords: Poverty, Foster, Greer and Thorbecke (FGT) indices, Salary Earners, Probit Journal Reference Format: Oyewole, K.S. & Awoyemi, O.B. (2023): Tackling Crippling Poverty, Panacea to The Nigerian Economic Decay. Humanities, Management, Arts, Education & the Social Sciences Journal. Vol. 11. No. 2, Pp 67-84 www.isteams.net/humanitiesjournal. dx.doi.org/10.22624/AIMS/HUMANITIES/V11N2P7

Modeling the impact of energy poverty on income poverty, health poverty, educational poverty, and environmental poverty: a roadmap towards environmental sustainability.

Energy poverty has gained considerable attention worldwide, adversely affecting income, education, health, and the environment. However, no study has examined the linkages among these dimensions and especially during COVID-19 in the Pakistani perspective. To bridge this research gap, we scrutinized the relationship among these variables to measure the hypotheses. The study analyzed the survey data collected from university students to meet the research objectives. We employed SPSS 26 for statistical description and correlation analysis and AMOS 26 to construct structural equation modeling to test the proposed hypotheses. The findings disclose that COVID-19 pandemic boosts energy poverty in Pakistan. Moreover, energy poverty positively and significantly influences income poverty, health poverty, educational poverty, and environmental poverty. Finally, relevant practical suggestions are provided based on the study findings.

Feeding the future in Ghana: Gender inequality, poverty, and food insecurity

AbstractAs women's empowerment is critical for the adoption of agricultural technologies by farmers, some governments have over the last three decades adopted a gender equality approach to food security. In Ghana, women play a vital role as farmers and food processors, which means they impact household nutrition in important ways. In this article, we explore women's empowerment in maize‐producing sites in Ghana by drawing on original data collected from over 400 farmers and service providers as part of a United States Agency for International Development‐funded Feed the Future project. We employ a quasi‐“women's empowerment in agriculture index” to measure the extent to which men and women maize producers are either empowered or disempowered in the domains of production, access to resources, control over income, leadership, and time allocation. Our study reveals that cost and time poverty are the main factors that influence the adoption of technologies to reduce postharvest losses. We also find that women are disproportionately disempowered in the areas of control over the use of income and time poverty. Importantly, we further find that researchers need to account for perceived versus actual empowerment when examining gender inequality in agriculture. Our study findings and policy recommendations will be of interest to policymakers, scholars, and development practitioners.

Poverty in Ukraine: evolution of interpreting and analysis of impact factors

Purpose. The purpose of the article is to analyze the evolution of interpretation of the poverty as a category. In addition, among the aims of the article is analysis of the dynamics of the poverty level in Ukraine and Lviv region as well as determination of the most effective economic factors affecting the poverty level.
 Methodology / approach. An analysis of the importance of the impact of annual growth of Ukraine’s GDP, GDP per capita, unemployment rate, and other possible factors on poverty level was carried out using statistical tools, namely the Pearson’s, Kendall’s, Spearman’s and Fechner’s correlation coefficients. Research methodology is a systematic approach to the study of the phenomenon of poverty using general scientific methods, as well as statistical methods. The questionnaire method was used to interview residents of cities and villages of Lviv region; methods of correlative-regression analysis were used to assess the importance of individual factors on the poverty level in Ukraine. Authors built VAR-model for the optimal analysis of the poverty level in Ukraine and factors of its influence.
 Results. After analyzing the value of the coefficient of determination, the authors concluded that the most significant factors of poverty in Ukraine are GDP per capita, PPP (R2 = 0.50), unemployment rate (R2 = 0.42), interest rates on loans (R2 = 0.21), inequality of income distribution (Gini index) (R2 = 0.20), taxes on income and profits (R2 = 0.15). GDP annual growth rate accounts for more than 64% of changes in poverty level in the second period. The value of the inequality of income distribution measured by the Gini index in the dynamics of the poverty level increases from 3.9% in the second period to 5.2% in the 10th period. In addition, value of the interest rate on loans and NBU’s account rate increase over time, accounting for approximately 10.0% and 2.4% of the variation in the level of poverty, respectively. Thus, level of interest rates is an important factor influencing the dynamics of poverty level in Ukraine.
 Originality / scientific novelty. An analysis of the dynamics of the poverty level in Ukraine was conducted, including a survey of residents of towns and villages in the Lviv region. A direct relationship between the interest rate on loans and the level of poverty has been established. In addition, the direct relationship between the inequality of income distribution and poverty level was confirmed. 
 Practical value / implications. It is proposed to use the correlation coefficients of Pearson, Kendall, Spearman and Fechner to calculate the strength of connection between the poverty level and its economic factors. Authors suggest applying VAR-model for optimal analysis of the poverty level in Ukraine.