Poor Individuals Research Articles

Who are the convoys of the happiness of Chinese urban residents? Research on social relations and subjective well-being based on the convoy model.

While the rapid advancement of urbanization has driven the improvement of material living standards, it has also brought about rapid social changes and intensified competition. In this "involutive" environment characterized by highly competitive and strong pressure, urban residents tend to fall into a state of "mental exhaustion." Anxiety, depression, sleep disorders, and other mental illnesses have seriously threatened public health in Chinese cities. Support from social relations is crucial for enhancing residents' subjective well-being (SWB) and promoting their mental health, especially in China's highly contextualized collectivist culture. According to the social structure of China's "difference sequence pattern," this paper constructs a theoretical framework of the relationship between social relations and SWB based on the convoy model and uses CGSS2018 data to verify the applicability of the theoretical framework. Kinship and friendship positively relate to SWB, and their interaction effect is significantly negative. There is no necessary correlation between neighborhood and SWB. The relationship between social relations and SWB of different age groups is heterogeneous. In addition, the moderating effects of relative income and social class are significantly negative. Kinship and friendship are Chinese urban residents' SWB convoys, and these two factors have an obvious substitution effect. The neighborhood has withdrawn from the convoy orbit of Chinese urban residents' SWB, which may be related to neighborhood indifference caused by China's housing system reform. From the life course perspective, the SWB convoys of young and middle-aged groups consist of kinship and friendship, while those of elderly people include kinship and neighborhood. In addition, for poor individuals living at the bottom of society, support from kinship is the most important source of social capital. These findings provide new insights into the relationship between social relations and the welfare of Chinese urban residents.

Can social capital facilitate households' donations in rural China?

Charitable donations by individuals are an important component of the third distribution. This paper examines the causal effect of social capital on donations by households in rural China. To do so, we draw on two waves of nationally representative household survey data collected by the authors themselves on 3295 households from eight provinces in China in 2018 and 2022. Our data show that about 24% of sample households ever donated money in 2019–2021, with the primary purpose of helping poor and sick individuals. We further use an instrumental variable approach to address the potential endogeneity of social networks. Results from two-stage least squares suggest that rural households with more social capital (as indicated by stronger social networks and with CPC family members) not only tend to be more likely to donate, but also donate more frequently and more amount during the study period. Results from mechanism analyses suggest that social capital promotes rural households' donations through the information effect, responsibility effect and reputation effect. The above results are robust to different model specifications and weighting schemes. This paper adds empirical evidence to inform policy-making in promoting charitable donations in China's pursuit of common prosperity.

Disparities in Maternal-Infant Drug Testing, Social Work Assessment, and Custody at 5 Hospitals.

To evaluate for disparities in peripartum toxicology testing among maternal-infant dyads across a hospital network and subsequent child protective services (CPS) involvement. Retrospective chart review of 59,425 deliveries at 5 hospitals in Massachusetts between 2016 and 2020. We evaluated associations between maternal characteristics, toxicology testing, and child welfare involvement with disproportionality risk ratios and hierarchical logistical regression. Toxicology testing was performed on 1959 (3.3%) dyads. Younger individuals and individuals of color were more likely to be tested for cannabis use or maternal medical complications compared to white non-Hispanic individuals. Among those without a substance use disorder, age <25 (adjusted odds ratio [aOR] 2.81; 95% confidence interval [CI], 2.43-3.26), race and ethnicity (non-Hispanic Black (aOR 1.80; 95% CI, 1.52-2.13), Hispanic (aOR 1.23; 95% CI, 1.05-1.45), mixed race/other (aOR 1.40; 95% CI, 1.04, 1.87), unavailable race (aOR 1.92; 95% CI, 1.32-2.79), and public insurance (Medicaid [aOR 2.61; 95% CI, 2.27-3.00], Medicare [aOR 13.76; 95% CI, 9.99-18.91]) had increased odds of toxicology testing compared to older, white non-Hispanic, and privately insured individuals. The disproportionality ratios in testing were greater than 1.0 for individuals under 25 years old (3.8), Hispanic individuals (1.6), non-Hispanic Black individuals (1.8), individuals of other race (1.2), unavailable race (1.8), and individuals with public insurance (Medicaid 2.6; Medicare 10.6). Among dyads tested, race and ethnicity was not associated with CPS involvement. Peripartum toxicology testing is disproportionately performed on non-white, younger, and poorer individuals and their infants, with cannabis use and medical complications prompting testing more often for patients of color than for white non-Hispanic individuals.

Feature selection based on a multi-strategy African vulture optimization algorithm and its application in essay scoring

Reducing the dimensions of the original data set while preserving the information as much as possible is conducive to improving the accuracy and efficiency of the model. To achieve this, this paper presents a multi-strategy African vulture optimization algorithm that is the chaotic and elite opposition-based African vulture optimization with the simplex method and differential evolution strategy(CESDAVO). Three main improvements are introduced into African vultures optimization(AVO) to improve its capabilities in this study. Firstly, the chaotic elite opposition-based learning strategy is used to initialize and diversify individual positions of vultures. Secondly, the simplex method is used to optimize those poor individuals so as to further improve the local exploitation ability of the algorithm. Thirdly, the differential evolution strategy is used to make the algorithm escape from the local optimum and improve the global optimization capability of the algorithm. The results of the ablation experiments show that mixing the three strategies greatly improves the optimization performance of the algorithm. In addition, Nine algorithms are compared with CESDAVO on 15 benchmark functions, and this experimental result shows that its optimization capability is superior to the others. Then, the proposed CESDAVO is employed for feature selection, and 12 standard datasets are used for experiments. According to the experimental results, CESDAVO obtained the highest average classification accuracy on 11 datasets and the highest feature selection rate on 8 datasets, which is significantly better than other algorithms. Finally, CESDAVO is also applied to feature reduction for essays, removing 24 features and significantly improving the classification accuracy on multiple classifiers.

Enhanced SparseEA for large-scale multi-objective feature selection problems

Large-scale multi-objective feature selection problems are widely existing in the fields of text classification, image processing, and biological omics. Numerous features usually mean more correlation and redundancy between features, so effective features are usually sparse. SparseEA is an evolutionary algorithm for solving Large-scale Sparse Multi-objective Optimization Problems (i.e., most decision variables of the optimal solutions are zero). It determines feature Scores by calculating the fitness of individual features, which does not reflect the correlation between features well. In this manuscript, ReliefF was used to calculate the weights of features, with unimportant features being removed first. Then combine the weights calculated by ReliefF with Scores of SparseEA to guide the evolution process. Moreover, the Scores of features remain constant throughout all runs in SparseEA. Therefore, the fitness values of excellent and poor individuals in each iteration are used to update the Scores. In addition, difference operators of Differential Evolution are introduced into SparseEA to increase the diversity of solutions and help the algorithm jump out of the local optimal solution. Comparative experiments are performed on large-scale datasets selected from scikit-feature repository. The results show that the proposed algorithm is superior to the original SparseEA and the state-of-the-art algorithms.

An aspirational hope of a Sharīʿah-based microfinance model to alleviate extreme poverty

PurposeThis study aims to propose a Sharīʿah-based and information and communication technology-driven microfinance model (SIMM) to reduce extreme poverty in rural areas. Existing microfinance models run by microfinance institutions exclude severely poor individuals from their activities.Design/methodology/approachThis study uses an exploratory sequential mixed-method design structured as Studies 1 and 2. Study 1 uses the grounded theory methodology to develop the emergent SIMM through interviews and focus group discussions with the participants (12 rich, 6 rural elites and 18 poor) of the target village. Study 2 uses a survey of 421 household members in the target village to evaluate their attitudes (ATT), subjective norms (SN) and perceived behavioural control (PBC) related to SIMM. Partial least squares-based structural equation modelling is used to evaluate relationships between constructs.FindingsStudy 1 identifies seven themes, in which aspirational hope is recognised as a core theme. Study 2 indicates significant relationships between ATT and PBC and between SN and PBC. Thus, the SIMM can alleviate poverty in rural communities.Practical implicationsThe application of the SIMM in the pilot study provides aspirational hope for eradicating extreme poverty.Social implicationsOther rural communities should be encouraged to apply the SIMM to alleviate extreme poverty in their villages.Originality/valueThis study contributes to the development of an innovative microfinance model (SIMM) to eradicate extreme poverty in rural areas.

Including Men in a Female Financial Model: An Analysis of Informal Grassroots Financial Associations

There is an increasing push among development actors to engage men in gender-focused development efforts. This is also observed in initiatives organizing economically poor individuals into groups where members save and borrow among each other. This study investigates the influence of male membership on the savings group’s profit-generating capacity. Further, the study aims to understand if this relationship is moderated by the level of gender equality in the country where the group is located. Drawing on random effects regression analysis on a sample of data on 81,853 savings groups from 30 African countries covering the period 2010 to 2017, the results show that the group’s profit-generating capacity reduces as the percentage of male members increases. Further, gender inequality in the countries where these groups are located worsens the observed negative relation. The findings highlight the need to thoroughly evaluate policy initiatives aimed at such savings groups to avoid harming core group functions.

Analisis Pengaruh Pendidikan dan Gini Rasio terhadap Tingkat Pengangguran di Kalimantan Selatan

Purpose: The unemployment rate as well as the labor force indicate the large number of people who must be included in the development process. This shows that the dynamics of the development process must be able to involve the entire work force, meaning that a large number of work force can become a burden for economic development. Apart from education, another aspect that influences the unemployment rate is the unequal distribution of income (gini ratio). Inequality in income distribution is a problem of differences in income between the richest and the poorest individuals. The greater the income gap, the greater the variation in income distribution. This study aims to obtain quantitative "evidence" regarding the effect of education and the gini ratio on the unemployment rate. Methodology: Based on the research objectives, this research is a quantitative research with the type of explanatory research, which will explain the causal relationship between the independent variables and the dependent variable through hypothesis testing. The type of data used in this study is secondary data. The secondary data used is in the form of a time series from 2013 to 2017. The data analysis used is multiple linear regression analysis. Results: Based on the research results it is known that (1) Education partially has a positive and significant effect on the unemployment rate in South Kalimantan. This means that education can reduce the number of unemployed in accordance with the theory of human capital, therefore education is one of the factors that needs to be improved so that the quality of human resources increases and has competitiveness; (2) The Gini ratio (income inequality) partially has a positive and significant effect on the unemployment rate in South Kalimantan. This means that when income inequality is high, the unemployment rate will also increase.

Labor Market Responses to Unemployment Insurance: The Role of Heterogeneity

We document considerable scope of heterogeneity within the unemployed, especially when they are divided along eligibility for and receipt of unemployment insurance (UI). We study the implications of this heterogeneity on UI’s insurance-incentive trade-off using a heterogeneous-agent job search model capable of matching the wealth and income differences that distinguish UI recipients from nonrecipients. Insurance benefits are larger for UI recipients who are predominantly wealth poor. Meanwhile, incentive costs are nonmonotonic in wealth because the poorest individuals, who value employment, exhibit weak responses. Differential elasticities imply that accounting for the composition of recipients is material to the evaluation of UI’s insurance-incentive trade-off. (JEL D91, E24, E32, J64, J65)

COVID-19 and the Exacerbation of Existing Inequalities: Why the Lower Socioeconomic Stratums Were Influenced the Most

Since the outburst of the COVID-19 virus many changes have taken place that concern most aspects of human life. A group that seemed to be affected most by the pandemic was that of the lower socio-economic stratums. This paper aims to demonstrate how individuals were most influenced. Firstly, their health was severely affected mainly due to the higher prevalence of social determinants that make them more vulnerable to COVID-19 and as they were more likely to delay seeking the necessary care for the virus. They also had to deal with a greater financial burden throughout the pandemic. Individuals of lower socio-economic stratums were much more likely to lose their jobs, to have their earnings reduce and to have to work while sick or in unsafe conditions. The last areas that have been negatively affected by the pandemic is digital, educational and health accessibility, as poorer individuals appear having reduce to technical means.

Short and Long Run Effects of Monetary Policy on Food Inflation: A Study of Pakistan

Food plays a major role in the consumption basket of developing countries such as Pakistan, with a significant portion of the insufficient income of poor individuals spending on food. Therefore, higher food inflation severely affects the purchasing power of poor people. This study is designed to estimate the short and long-run impacts of monetary policy on food inflation in Pakistan. For this purpose, time series data from September 2005 to October 2020 was used through the Autoregressive Distributed Lag (ARDL) model. The findings indicate that food inflation can become stable by restrictive monetary policy in both the short and long run. The results show that the short-run shocks can be adjusted at the speed of 13.9% per month. To tackle food inflation, a balanced monetary policy is suggested. On the other hand, a fiscal policy providing subsidized food items to people can also be implemented to tackle food inflation in Pakistan.

Keuangan digital: suatu studi literatur

The financial industry has experienced a continuous evolution in service delivery due to digitization, where this evolution is characterized by expanded connectivity and improved information processing speed both at the customer interface and in back-office processes. The role of contracts in the economy has recently received great attention, where contracts are an important element of the operation of a market economy. The relevance of digital finance and financial inclusion for poverty alleviation and economic growth is of interest to policymakers and academics alike, particularly because of a number of issues that if addressed can make digital finance work better for individuals, businesses, governments and economies. Digital finance and financial inclusion have several benefits for financial service users, digital financial providers, governments and the economy such as increasing financial access among poor individuals, reducing financial intermediation costs for banks and fintech providers, and increasing aggregate spending for governments. The purpose of this study was to determine the determinants of digital finance. This study used a systematic literature review method and used 18 articles as study material, which were obtained from the scopus.com and sciencedirect.com pages. The results of the study show the determinants of digital finance, both variables that influence, are influenced or mediate. The results of the literature study did not find digital finance as a moderating variable.

Behind the growth of FinTech in South Korea: Digital divide in the use of digital financial services

Advancements in financial technology, known as “FinTech,” will help both businesses and consumers of financial services. South Korea has a well-established FinTech infrastructure and resources, and has already incorporated digital financial services into daily life. However, the benefit of the proliferation of FinTech might be disproportionate in reaching diverse groups. The goal of this study is to examine how digital financial services are used in South Korea with an emphasis on disparities in the use of digital financial services. This study used the 2019 Digital Divide Survey conducted in South Korea to conduct OLS regression analysis, and create the Concentration Index (CI), which estimates the disparities that are systematically related to income level. Next, decomposition analysis on the CI was conducted to determine what factors help explain the disparity in the use of digital financial services. The analysis confirmed that there are considerable differences in the usage by income level. The multivariate results reveal that one’s device proficiency and active involvement in utilizing the internet for basic activities played significant roles in explaining the level of digital financial services usage. Poorer individuals' attitudes toward new technologies, such as a lack of interest in participating in learning and confidence in obtaining new digital skills, may prevent them from using digital financial services. This study is one of few studies to use the CI technique to examine the digital divide in digital financial services, and provide insights for educators, businesses, and policymakers.

A preference-based theory unifying monetary and non-monetary poverty measurement

Multidimensional poverty measures are increasingly used in practice even though they face criticism and generate long-lasting debates. These contentions primarily find their origin in the divergence between standard poverty identification practices and a preference-based definition of the poor. This paper fills this gap by proposing a poverty measurement theory that (i) adopts a preference-based definition of the poor, (ii) acknowledges that the relevant preference is only partially known and (iii) encompasses both market and non-market dimensions of well-being. A preference-based definition satisfying two mild substitutability assumptions implies that two types of individuals are poor: individuals who experience an extremely low outcome in at least one dimension (“extremors”) and individuals who cumulate moderately low outcomes in several dimensions (“cumulators”). The paper shows that standard identification practices are not flexible enough to properly identify both types of poor individuals and proposes a simple refinement that improves on this issue. The theory provides a conceptual foundation from which practitioners may derive guidance for the many choices they face.

Understanding the Determinants of Aspirations in Rural Tanzania: Does Financial Literacy Matter?

Aspirations have recently received increased attention in the analysis of poverty and its dynamics. The argument is that aspirations provide reference points for individuals’ forward-looking decisions and behaviours. Understanding of what determines aspirations is vitally important to design development interventions that can raise aspirations. In this paper, we analyse whether financial literacy is associated with individuals’ aspirations. Using data from more than 2000 Tanzanian households, we find a robust positive correlation between financial literacy and aspirations. Our results are robust to using alternative financial literacy measure, controlling for extensive covariates and non-cognitive traits, and sensitivity analyses to omitted variables. Overall, our findings suggest that aspirations could be influenced to improve poor individuals’ future investments and forward-looking behaviour.

On the effects of income heterogeneity in monopolistically competitive markets

This paper studies the market and welfare effects of income heterogeneity in monopolistically competitive product markets in the context of nonhomothetic preferences. In a closed economy, where richer individuals' expenditures are less sensitive to price change compared to poorer ones', a mean-preserving contraction of income distribution entices firms to charge higher markups, reduce output, and fosters creation of new varieties. General equilibrium effects have a negative impact on poorer individuals and, in specific circumstances, on the whole population. In an open economy with free trade, lower income inequality in one country creates price divergence between trading countries. Lower inequality not only further decreases trade volumes and values but also creates a general equilibrium effect that may negatively affect poor individuals. Finally, general equilibrium effects are shown to be quantitatively nonnegligible.

Risk factor contributions to socioeconomic inequality in cardiovascular risk in the Philippines: a cross-sectional study of nationally representative survey data

BackgroundPrimary prevention of cardiovascular diseases (CVD) increasingly relies on monitoring global CVD risk scores. Lack of evidence on socioeconomic inequality in these scores and the contributions that specific risk factors make to this inequality impedes effective targeting of CVD prevention. We aimed to address this evidence gap by measuring and decomposing socioeconomic inequality in CVD risk in the Philippines.MethodsWe used data on 8462 individuals aged 40–74 years from the Philippines National Nutrition Survey and the laboratory-based Globorisk equation to predict 10-year risk of a CVD event from sex, age, systolic blood pressure, total cholesterol, high blood glucose, and smoking. We used a household wealth index to proxy socioeconomic status and measured socioeconomic inequality with a concentration index that we decomposed into contributions of the risk factors used to predict CVD risk. We measured socioeconomic inequalities in these risk factors and decomposed them into contributions of more distal risk factors: body mass index, fat share of energy intake, low physical activity, and drinking alcohol. We stratified by sex.ResultsWealthier individuals, particularly males, had greater exposure to all risk factors, with the exception of smoking, and had higher CVD risks. Total cholesterol and high blood glucose accounted for 58% and 34%, respectively, of the socioeconomic inequality in CVD risk among males. For females, the respective estimates were 63% and 69%. Systolic blood pressure accounted for 26% of the higher CVD risk of wealthier males but did not contribute to inequality among females. If smoking prevalence had not been higher among poorer individuals, then the inequality in CVD risk would have been 35% higher for males and 75% higher for females. Among distal risk factors, body mass index and fat intake contributed most to inequalities in total cholesterol, high blood sugar, and, for males, systolic blood pressure.ConclusionsWealthier Filipinos have higher predicted CVD risks and greater exposure to all risk factors, except smoking. There is need for a nuanced approach to CVD prevention that targets anti-smoking programmes on the poorer population while targeting diet and exercise interventions on the wealthier.

The impact of incorporating surgical simulation into trichiasis surgery training on operative aspects of initial live-training surgeries.

While surgical simulation is regularly used in surgical training in high-income country settings, it is uncommon in low- and middle-income countries, particularly for surgical training that primarily occurs in rural areas. We designed and evaluated a novel surgical simulator for improving trachomatous trichiasis (TT) surgery training, given that trichiasis is mostly found among the poorest individuals in rural areas. TT surgery programs were invited to incorporate surgical simulation with a new, high fidelity, low-cost simulator into their training. Trainees completed standard TT-surgery training following World Health Organization guidelines. A subset of trainees received three hours of supplemental training with the simulator between classroom and live-surgery training. We recorded the time required to complete each surgery and the number of times the trainer intervened to correct surgical steps. Participants completed questionnaires regarding their perceptions. We also assessed trainer and trainee perceptions of surgical simulation training as part of trichiasis surgery training. 22 surgeons completed standard training and 26 completed standard training plus simulation. We observed 1,394 live-training surgeries. Average time to first live-training surgery completion was nearly 20% shorter the simulation versus the standard group (vs 34.4 minutes; p = 0.02). Trainers intervened significantly fewer times during initial live-training surgeries in the simulation group (2.7 vs. 4.8; p = 0.005). All trainers indicated the simulator significantly improved training by allowing trainees to practice safely and to identify problem areas before performing live-training surgeries. Trainees reported that simulation practice improved their confidence and skills prior to performing live-training surgeries. A single high-fidelity surgical simulation session can significantly improve critical aspects of initial TT surgeries.

Can Blockchain Help Improve Financial Inclusion? A Comparative Study

The financial inclusion of poor populations and/or refugees can be hindered by difficulties in proving or reluctance to disclose their identity. Bank accounts and mobile money services require that identities be provided. Financial digital services based on blockchain technology can provide anonymous authentication to poor/refugee populations and be a first step towards financial inclusion. We scrutinize several examples of such projects by comparing them with blockchain-based digital identity or financial inclusion programs that are not necessarily restricted to poor/migrant populations. We use social network activity as a proxy for the failure or success of such projects. We find that blockchain projects targeted to migrants and poor individuals are more likely to fail than are those targeted to all. We more closely examine one particular case to check the consistency of our proxy. We present plausible explanations for our result: the discrepancy between the needs of populations of low socioeconomic status and the proposed blockchain-backed financial services and the fact that maintaining such services is energy intensive.

G-CSF drives autoinflammation in APLAID

Missense mutations in PLCG2 can cause autoinflammation with phospholipase C gamma 2-associated antibody deficiency and immune dysregulation (APLAID). Here, we generated a mouse model carrying an APLAID mutation (p.Ser707Tyr) and found that inflammatory infiltrates in the skin and lungs were only partially ameliorated by removing inflammasome function via the deletion of caspase-1. Also, deleting interleukin-6 or tumor necrosis factor did not fully prevent APLAID mutant mice from autoinflammation. Overall, these findings are in accordance with the poor response individuals with APLAID have to treatments that block interleukin-1, JAK1/2 or tumor necrosis factor. Cytokine analysis revealed increased granulocyte colony-stimulating factor (G-CSF) levels as the most distinct feature in mice and individuals with APLAID. Remarkably, treatment with a G-CSF antibody completely reversed established disease in APLAID mice. Furthermore, excessive myelopoiesis was normalized and lymphocyte numbers rebounded. APLAID mice were also fully rescued by bone marrow transplantation from healthy donors, associated with reduced G-CSF production, predominantly from non-hematopoietic cells. In summary, we identify APLAID as a G-CSF-driven autoinflammatory disease, for which targeted therapy is feasible.