Average Poverty Gap Research Articles

Exploring the association between multidimensional poverty and antenatal care utilization in two provinces of Papua New Guinea: a cross-sectional study

BackgroundAlthough global poverty rates have declined in the last decade, the fall in the Asia-Pacific region has been slow relative to the rest of the world. Poverty continues to be a major cause of poor maternal and newborn health, and a barrier to accessing timely antenatal care. Papua New Guinea has one of the highest poverty rates and some of the worst maternal and neonatal outcomes in the Asia-Pacific region. Few studies have investigated equity in antenatal care utilization in this setting. We explored equity in antenatal care utilization and the determinants of service utilization, which include a measure of multidimensional poverty in Papua New Guinea.MethodsTo explore the association between poverty and antenatal care utilization this study uses data from a ten-cluster randomized controlled trial. The poverty headcount, average poverty gap, adjusted poverty headcount, and multidimensional poverty index of antenatal clinic attendees are derived using the Alkire-Foster method. The distribution of service utilization is explored using the multidimensional poverty index, followed by multivariate regression analyses to evaluate the determinants of service utilization.ResultsThe poverty headcount was 61.06%, the average poverty gap 47.71%, the adjusted poverty headcount 29.13% and the average multidimensional poverty index was 0.363. Further, antenatal care utilization was regressive with respect to poverty. The regression analyses indicated that older women; being a widow (small number of widows (n = 3) asserts interpreting result with caution); or formally employed increase the likelihood of accessing antenatal care more often in pregnancy. Travelling for over an hour to receive care was negatively associated with utilization.ConclusionThis study indicated high levels of multidimensional poverty in PNG and that ANC utilization was regressive; highlighting the need to encourage pregnant women, especially those who are economically more vulnerable to visit clinics regularly throughout pregnancy.

Analysis of medical impoverishment and its influencing factors among China's rural near-poor, 2016-2020.

This study investigates the determinants of medical impoverishment among China's rural near-poor, aiming to enhance public health services and establish preventative and monitoring systems. Using China Family Panel Studies and World Bank methods, we categorized rural populations and calculated their 2020 Poverty Incidence (PI) and Poverty Gap (PG), with impoverishing health expenditures (IHE) as the primary indicator. We analyzed the data from 2016 to 2020 using a conditional fixed-effects multinomial logit model and 2020 logistic regression to identify factors influencing medical impoverishment risk. (1) In 2020, the near-poor in China faced a PI of 16.65% post-health expenditures, 8.63 times greater than the non-poor's PI of 1.93%. The near-poor's Average Poverty Gap (APG) was CNY 1,920.67, notably surpassing the non-poor's figure of CNY 485.58. Health expenses disproportionately affected low-income groups, with the near-poor more prone to medical impoverishment. (2) Disparities in medical impoverishment between different economic household statuses were significant (P < 0.001), with the near-poor being particularly vulnerable. (3) For rural near-poor households in China, those with over six members faced a lower risk of medical impoverishment compared to those with three or fewer. Unmarried individuals had a 7.1% reduced risk of medical impoverishment relative to married/cohabiting counterparts. Unemployment was associated with a 9% increased risk. A better self-rated health status was linked to a lower probability of IHE, with the "very healthy" reporting a 25.8% lower risk than those "unhealthy." Chronic disease sufferers in the near-poor and non-poor categories were at an increased risk of 12 and 1.4%, respectively. Other surveyed factors, including migrant status, age, insurance type, gender, educational level, and recent smoking or drinking, were not statistically significant (P > 0.05). Rural near-poor in China are much more susceptible to medical impoverishment, influenced by specific socio-economic factors. The findings advocate for policy enhancements and health system reforms to mitigate health poverty. Further research should extend to urban areas for comprehensive health poverty strategy development.

Are Budget Neutral Income Floors Fiscally Viable in Sub-Saharan Africa?

AbstractWe use microsimulations to assess whether budget-neutral universal income floors are fiscally viable in twelve Sub-Saharan African countries. We consider three universal basic income scenarios of decreasing levels of generosity: poverty line, average poverty gap and current spending on transfers and subsidies per person. The first two may not be viable because the required increase in taxes to fulfil budget neutrality is significant.

The determinants of household poverty: the case of berehet woreda, amhara regional state, Ethiopia

Nowadays, poverty is one of the most important issues that needs due attention in many developing countries like Ethiopia. Nonetheless, poverty in Ethiopia remains widespread in both rural and urban areas. Therefore, this study aimed to examine the determinants and status of poverty in Berehet Woreda. The study was conducted using a cross-sectional survey. To conduct the study, a sample of 384 households was selected using a stratified simple random sampling technique. Foster Greer Thorbecke’s Poverty Index was used to examine the extent and severity of poverty in the Woreda. Accordingly, about 36% of households in Woreda live below the poverty line, with an average poverty gap of 12% and poverty severity of about 7%. The binary logit model showed that household education status, dependency ratio, residential area, and access to credit were statistically significant in determining household poverty status. Since the poverty situation in Woreda was worse than the national average, the regional government should prioritize this Woreda and develop a special type of projects especially in rural areas that can lift the majority of the poor out of poverty.

Impoverishment impact of out-of-pocket payments for healthcare in rural Bangladesh: Do the regions facing different climate change risks matter?

IntroductionOut-of-pocket (OOP) payments for healthcare severely affect the current consumption, future health and earnings capacity of poor/underprivileged households and hence it is crucial for priority setting. This study assesses the variation in overall as well as disease-specific impoverishment impact of OOP payments between the regions experiencing different climate change risks, defined as high disaster-prone (HDP) areas and low-disaster-prone (LDP) areas, in Bangladesh.Materials and methodsThis paper estimated three poverty measures, such as poverty headcount, poverty intensity and normalized poverty gap for all ailments, catastrophic events, diseases types (communicable, non-communicable (NCDs), and accident and injury), illness conditions (acute and chronic) and hospitalization using 3,791 randomly selected rural households (1,203 from HDP and 2,588 from LDP areas) across the regions. Cost of basic need approach was used for estimating poverty line expenditure.ResultsAbout 13 percent households annually fall into poverty due to OOP outlays for healthcare. Despite having significantly (p-value≤0.01) less OOP payments (HDP areas: BDT 5,117; LDP areas: BDT5,811) the impoverishment impact of OOP payments for healthcare in HDP areas (16.5%) has substantially higher than LDP areas (11.3%).Population in HDP areas, especially char (river island; 19.55 percent) and haor (water submerged; 16.80 percent) are more susceptible to any level of OOP payments due to low level of earnings. Catastrophic healthcare expenditure (61.79%) and NCDs (14.29 percent) are exacerbating the poverty level in Bangladesh. Both absolute and relative average poverty gap are more widen in HDP than LDP areas due to catastrophic OOP outlays for healthcare.ConclusionThe impoverishment effect due to OOP payments for healthcare in both HDP and LDP areas are high, especially for NCDs and catastrophic healthcare expenditure. However, the situation is bit worse in HDP areas. Preventing the escalation of NCDs as well as catastrophic expenditure and hence reducing the level of impoverishment thereof call for restricting tobacco use, increasing physical activity, encouraging to intake healthy diets, ensuring food safety, controlling air pollution, and improving mental health. Moreover, government should give more emphasis, especially in the HDP areas, on making community clinics more functional through providing screening equipment and training to the Community Health Care Providers for early detection of NCDs, and ensuring availability of medicine all the time. Note that other than community clinics, there is little option for providing healthcare in HDP areas due to poor functionality of public facilities as well as lack of private facilities in HDP areas.

Determinants of rural poverty in Ethiopia A Household level analysis in the case of Dejen district

This study examines the main determinants of rural household poverty in the district of Dejen Amhara regional state using primary data collected through questionnaire. Through multi-stage sampling technique the data was collected from a total of 204 sample households from rural area of Dejen district in the year 2016. The FGT poverty index (Foster, Greer and Thorbecke) was employed to examine the extent and severity of rural poverty in Dejen. Accordingly, nearly 49% of the sampled rural households’ lives below poverty line with an average poverty gap of 0.083 and poverty severity gap of 0.065. The probit model used to analyze the main determinants of rural poverty. Based on the probit model analysis output, household size, sex of households, dependency ratio and livestock ownership are found to be the key determinants of rural poverty. Poverty status is negatively correlated with total number of livestock a household owned and sex of household heads (male dummy). On one hand, family size and dependency ratio are positively related to poverty status of households. So, as parts of policy implication this study suggests that promoting and giving awareness about family planning and putting the existing policy in effect and integrated health service with appropriate access would result in curbing the degree of poverty among rural households. Technical advice and training, how to use their cattle’s, should offer from the concerned body in order to strengthen their benefits for the rural poor and help them to exit from poverty. There should also be a need to encourage and give awareness to the population that females are productive and means of development and a way to combat poverty and gender basis development policy measures targeting anti-poverty involvements are useful to curb poverty in rural areas of Dejen.

Analysis of Poverty Profile by Type of House of Households in Nepal

This study focuses on the Poverty Profile by type of house of Households in Nepal among 5,988 households of Nepal. It is based on the Nepal Living Standards Survey-III 2010/11 cross-sectional data. The data were used to analyze descriptive statistics including poverty profiles. The FGT poverty index (index proposed by Foster, Greer and Thorbecke) is employed to examine the head count rate or poverty incidence, poverty gap and severity poverty of Nepal. It reveals that 25.2% of the sample households live below the poverty line (Rs.19261 per individual per year) with an average poverty gap and squared poverty gap of 5.43% and 1.81 % respectively. Households living in Pakki and Non-Pakki houses are 0.8 and 52.4 percent average poor and 0.2 and 1.7 percent core poor respectively.

Analysis of Poverty Profile by Type of House of Households in Nepal

This study focuses on the Poverty Profile by type of house of Households in Nepal among 5,988 households of Nepal. It is based on the Nepal Living Standards Survey-III 2010/11 cross-sectional data. The data were used to analyze descriptive statistics including poverty profiles. The FGT poverty index (index proposed by Foster, Greer and Thorbecke) is employed to examine the head count rate or poverty incidence, poverty gap and severity poverty of Nepal. It reveals that 25.2% of the sample households live below the poverty line (Rs.19261 per individual per year) with an average poverty gap and squared poverty gap of 5.43% and 1.81 % respectively. Households living in Pakki and Non-Pakki houses are 0.8 and 52.4 percent average poor and 0.2 and 1.7 percent core poor respectively.

Analysis of Poverty Profile by Type of House of Households in Nepal

This study focuses on the Poverty Profile by type of house of Households in Nepal among 5,988 households of Nepal. It is based on the Nepal Living Standards Survey-III 2010/11 cross-sectional data. The data were used to analyze descriptive statistics including poverty profiles. The FGT poverty index (index proposed by Foster, Greer and Thorbecke) is employed to examine the head count rate or poverty incidence, poverty gap and severity poverty of Nepal. It reveals that 25.2% of the sample households live below the poverty line (Rs.19261 per individual per year) with an average poverty gap and squared poverty gap of 5.43% and 1.81 % respectively. Households living in Pakki and Non-Pakki houses are 0.8 and 52.4 percent average poor and 0.2 and 1.7 percent core poor respectively.

English

The paper examines the status and determinants of poverty and inequality among rural households in Girar Jarso district of Central Ethiopia. To measure the status of poverty and inequality, the study made use of cost of basic need approach, Foster-Greer-Thorbecke indices and Gini coefficient. Based on the survey of 120 households, the logistic model was estimated. A three-stage sampling procedure was applied for selection of respondents. The poverty line is found to be 4315.7 Ethiopian Birr. The incidence of poverty was computed to be 45% with an average poverty gap and squared poverty gap of 18.6 and 9.99%, respectively. The Gini coefficient was calculated to be 0.33. The logit model shed light on the demographic and socioeconomic characteristics of households behind the persistence of poverty. The result revealed that poverty is strongly linked to family size, remittance, farm and non-farm income and receiving food aid. The findings suggest also that livelihood diversification, encouraging flow of remittances, promotion of non-farm activities, besides agricultural intensification, and appropriate target to avoid distortionary effects of food aid will constitute an important strategy to accelerate poverty reduction. Key words: Poverty, income inequality, determinants, household, Ethiopia.

Effects of China's New Rural Cooperative Medical Scheme on reducing medical impoverishment in rural Yanbian: An alternative approach.

BackgroudThis study aimed to measure the poverty head count ratio and poverty gap of rural Yanbian in order to examine whether China’s New Rural Cooperative Medical Scheme has alleviated its medical impoverishment and to compare the results of this alternative approach with those of a World Bank approach.MethodsThis cross-sectional study was based on a stratified random sample survey of 1,987 households and 6,135 individuals conducted in 2008 across eight counties in Yanbian Korean Autonomous Prefecture, Jilin province, China. A new approach was developed to define and identify medical impoverishment. The poverty head count ratio, relative poverty gap, and average poverty gap were used to measure medical impoverishment. Changes in medical impoverishment after the reimbursement under the New Rural Cooperative Medical Scheme were also examined.ResultsThe government-run New Rural Cooperative Medical Scheme reduced the number of medically impoverished households by 24.6 %, as well as the relative and average gaps by 37.3 % and 38.9 %, respectively.ConclusionsChina’s New Rural Cooperative Medical Scheme has certain positive but limited effects on alleviating medical impoverishment in rural Yanbian regardless of how medical impoverishment is defined and measured. More governmental and private-sector efforts should therefore be encouraged to further improve the system in terms of financing, operation, and reimbursement policy.

The Effectiveness of Zakat in Reducing Poverty Incident: An Analysis in Kelantan, Malaysia

This study attempts to examine the effectiveness of monthly zakat distribution as a mechanism to poverty reduction in the state of Kelantan. The target population of this study is the masakin (poor) and fuqara (hardcore poor) (Note 1) categories of the Kelantan Islamic Religious Department (MAIK) (Note 2) zakat recipients. Simple Random sampling procedure is applied to collect primary data related to zakat recipients from the poor and hardcore poor category of ten districts of Kelantan. The effects of zakat distribution on poverty are analyzed within the context of burden of poverty; specifically in terms of incidence, intensity and severity of poverty. These are examined using four major indices of poverty, which include the Headcount Index, Average Poverty Gap, Income Gap and Sen Index. Results revealed that zakat distribution reduces poverty incidence, reduces the extent of poverty and lessens the severity of poverty. Further, the current zakat distribution in Kelantan only gives a small effect on increasing the income of the poor. Hence, by locating the perfect amount of zakat distribution to eliminate poverty and to offer alternative zakat distribution model is the best way in reducing the income inequality and maximization of social welfare.

Sequential procedures for poverty gap dominance

Poverty evaluations differ from welfare evaluations in one significant aspect, the existence of a threshold or reference point, the poverty line. We build up normative evaluation models in which comparisons are made taking distances from this reference point rather than from the origin to be ethically relevant, by focussing upon poverty gaps and not incomes. When poverty lines differ for different groups in a socially heterogeneous population, choosing poverty gaps instead of incomes as the relevant indicator brings in normatively appealing classes of poverty indices not previously accommodated, for which poverty comparisons are implemented through sequential poverty gap curves (or poverty gap distributions) dominance. These conditions are logically related to those suggested by Atkinson and Bourguignon (Arrow and the foundations of the theory of economic policy, Macmillan, London, 1987) and Bourguignon (J Econom 42:67–80, 1989) for welfare comparisons. However, the proportion of poor individuals in the society and their average poverty gap play a role in our comparisons, though they do not in the existing poverty dominance criteria for heterogeneous populations.

Determinants Of Poverty And Household Livelihood Diversification Strategies In Crude-Oil Producing Areas Of Ondo State Nigeria

This paper seeks to address the question: why does poverty persist in crude-oil producing areas of Nigeria where the bulk of her revenue is being derived? We argue that it is due to lack of right to control fundamental livelihood assets of land and water resources. In addition, the interference of oil exploration and consequent of oil-spills on agricultural land and incursion into freshwater have led to reduction in crop and fish outputs. This study therefore, assesses this impact of this intervention on the profitability of crop-farming and fishing enterprises, poverty levels, and estimates the effect of diversifications on income. This study bases its findings on empirical work, which was build on information gathered from atwo-round survey of 590 farming households in the crude-oil producing communities of Ondo State, Nigeria. The result of the analysis indicated that intervention of oil exploitation has reduced profitability of farm enterprises. Poverty analysis shows that 40% of the sample household heads live below poverty line with an average poverty gap of 0.047. The study further shows that poor household heads attempt to augment their consumption and income through livelihood diversification, among which are; petty trading, mat weaving, palm wine tapping and fuel wood gathering for sale, local gin brewing and craftsmanship. Income earned from diversifications to non-farm activities has helped majority of the households to meet basic needs.Key words: Poverty, livelihood diversifications, oil-spillage, assets depletion

Non-evidence-based policy: How effective is China's new cooperative medical scheme in reducing medical impoverishment?

In recent years, many lower to middle income countries have looked to insurance as a means to protect their populations from medical impoverishment. In 2003, the Chinese government initiated the New Cooperative Medical System (NCMS), a government-run voluntary insurance program for its rural population. The prevailing model of NCMS combines medical savings accounts with high-deductible catastrophic hospital insurance (MSA/Catastrophic). To assess the effectiveness of this approach in reducing medical impoverishment, we used household survey data from 2006 linked to claims records of health expenditures to simulate the effect of MSA/Catastrophic on reducing the share of individuals falling below the poverty line (headcount), and the amount by which household resources fall short of the poverty line (poverty gap) due to medical expenses. We compared the effects of MSA/Catastrophic to Rural Mutual Health Care (RMHC), an experimental model that provides first dollar coverage for primary care, hospital services and drugs with a similar premium but a lower ceiling. Our results show that RMHC is more effective at reducing medical impoverishment than NCMS. Under the internationally accepted poverty line of US$1.08 per person per day, the MSA/Catastrophic models would reduce the poverty headcount by 3.5–3.9% and the average poverty gap by 11.8–16.4%, compared with reductions of 6.1–6.8% and 15–18.5% under the RMHC model. The primary reason for this is that NCMS does not address a major cause of medical impoverishment: expensive outpatient services for chronic conditions. As such, health policymakers need first to examine the disease profile and health expenditure pattern of a population before they can direct resources to where they will be most effective. As chronic diseases impose a growing share of the burden on the population in developing countries, it is not necessarily true that insurance coverage focusing on expensive hospital care alone is the most effective at providing financial risk protection.

Introduction to the Special Section: Poverty and Inequality in China

Introduction to the Special Section: Poverty and Inequality in China

Micro‐level determinants of poverty reduction in Sri Lanka: a multivariate approach

PurposeThe main purpose of this paper is to construct a poverty profile for Sri Lanka, and examine the micro‐level determinants and correlates of poverty.Design/methodology/approachThe study is based on the latest Sri Lanka Integrated Survey commissioned by the World Bank. The unconditional poverty profile was constructed using three different poverty measures (poverty headcount, average poverty gap and squared poverty gap), nested in the Foster‐Greer‐Thorbecke index. The conditional poverty profile was constructed on the basis of a multivariate analysis of poverty correlates. Partial correlates of poverty are computed using two comparable methodologies. First, a logistic regression was estimated, with the probability of a household being in poverty as the dependent variable and a set of economic and demographic variables as correlates. Second, the quantile regression approach was utilized to examine the correlates of per capita consumption at different points on the distribution.FindingsThe empirical findings are broadly encouraging. The estimation results show that the education of the household head, being salary employed and being engaged in business have a significant positive effect on the standard of living. The probability of being poor increases with the household size, household head being female, living in a rural area, and being a casual wage earner. These findings indicate the importance of a set of policies which are super pro‐poor, namely increasing school enrolment and achievement, effective family planning programs to reduce the birth rate and dependency load within households, and granting priorities for specific cohorts (children‐, elderly‐, rural‐ and female‐headed households) in targeted interventions.Originality/valueThis is the first study that examines the probable determinants and correlates of Sri Lankan poverty in a multivariate framework employing both logit and quantile regressions.

Impact of food and nutrition interventions on poverty in an informal settlement in the Vaal Region of South Africa

UNICEF has stated that urban poverty is primarily found in squatter settlements. At present 13.5% of all South African households live in informal settlements. The major research question is to what extent does poverty influence the food, nutrition and health of informal-settlement dwellers. The purpose of the present study was to determine the depth of poverty in this community and to measure the possible effect that planned food and nutrition interventions may have on eliminating poverty in this area. Pre-tested questionnaires were administered to 340 randomly-selected caregivers. A validated quantified FFQ was administered by trained enumerators as the test measurement for dietary intake and food consumption patterns and 24 h recall was used as the reference measurement, and the data were analysed. A poverty model was used to measure the impact of extra income on the poverty levels of 190 households. Of the respondents 89% lived in Zn shacks and the average household size was 4.9 individuals. The unemployment rate was 94.2% for respondents and 64.9% for their partners. The majority of households (68.8%) had an income of <R 500 ( pound35) per month and 58.3% spent <R 100 ( pound6.90) per week on food. The average poverty gap was R 1342.21 ( pound93) and the poverty gap ratio was 56%. The poverty model showed that an increase of R 500 ( pound35) in monthly household income results in a poverty gap ratio of 35%. The poverty model confirmed that the impact of food and nutrition interventions on poverty can be measured and that when planning these interventions the model could be used to measure their feasibility. The results indicate that this community is poverty-stricken and has chronic food insecurity, and they will be used to facilitate planning and implementation of sustainable income-generating community-based interventions to promote urban food security and alleviate poverty in this community.

U-Statistics and Their Asymptotic Results for Some Inequality and Poverty Measures

U-statistics form a general class of statistics that have certain important features in common. This class arises as a generalization of the sample mean and the sample variance, and typically members of the class are asymptotically normal with good consistency properties. The class encompasses some widely used income inequality and poverty measures, in particular the variance, the Gini index, the poverty rate, the average poverty gap ratios, the Foster-Greer-Thorbecke index, and the Sen index and its modified form. This paper illustrates how these measures come together within the class of U-statistics, and thereby why U-statistics are useful in econometrics.

Textiles Protection and Poverty in South Africa

There is an important debate going on in South Africa on whether to apply safeguard trade barriers to protect textiles. This presents an interesting case of how a country might use safeguard trade barriers in order to better achieve a domestic policy objective. Much of the current discourse on textiles protection focuses on static effects of protection. The aim of this paper is to take this discussion a step further by introducing the effect of textiles protection on poverty and its dynamics. To assess these effects of protection, a sequential dynamic computable general equilibrium model linked to a nationally representative household survey of 2000 is used. The simulation involves a doubling of the import tariffs on textiles. The textile sector is, obviously, the biggest winner, followed by the service sector, which sells more than half of its production as inputs for the textile sector. All other sectors experience falling output with the worst affected being the export-oriented sectors. Because the protected sectors are relatively more labour intensive, wages increase in both the short and long terms. Capital returns are sector specific in the short run and go up markedly for textiles and services but decline for all the other sectors. Overall, welfare falls both in the short and long term as the rise in factor prices is completely offset by the increase in consumer prices. The proportion of people living below US$2 per day increases marginally in the short run following increased textiles protection because of the observed increase in consumer price index that is higher than the increase in consumption for most households. Unskilled Indians are the only group to experience a reduction in poverty and welfare increases in the short run. The average poverty gap and the squared poverty gap also follow the same pattern as poverty headcount because most households are being pushed into poverty.