Non-poor Households Research Articles

ARE WE COUNTING ALL THE POOR?

AbstractHaving accurate poverty statistics is of primary importance for researchers and policy-makers. Based on original data on Burundi, we investigate the sensitivity of poverty headcount calculations to considering individual- instead of household-level consumption. Relying on a survey module which provides information on the share of expenses allocated to each member of the households, we calculate poverty statutes on an individual basis. Exploiting these direct measures to compute poverty headcounts allows us to put forward the discrepancy between individual- and household-level poverty computations. We identify “hidden poor,”i.e.poor individuals living in non-poor households, and show that they are predominantly children. We finally discuss potential mechanisms that could drive the results, and emphasize the importance of improving data collection devices for poverty-related policy making.

Neighborhood Poverty and Children's Academic Skills and Behavior in Early Elementary School

Neighborhoods provide resources that may affect children's cognitive and behavioral outcomes. However, it is unclear to what degree associations between neighborhood disadvantage and outcomes persist into elementary school and whether neighborhood disadvantage interacts with household disadvantage. Using data from the 2010–2011 Early Childhood Longitudinal Study‐Kindergarten Cohort (N = 15,100 children) merged with census data from the American Community Survey, this study examines associations between neighborhood poverty and children's math, reading, and behavioral outcomes at kindergarten and first and second grades. Findings indicate that as tract‐level poverty increases, children's achievement worsens after controlling for child and family characteristics. These associations persist into second grade and are stronger for children in poor versus nonpoor households. Findings suggest that neighborhood disadvantage may contribute to poorer achievement scores, particularly among children with few household resources, but that household disadvantage and other characteristics largely explain behavioral outcomes. Research and policy implications are discussed.

The long-run performance of increasing-block pricing in Taiwan's residential electricity sector

This article examines the performance regarding efficiency and equity of increasing-block pricing (IBP) in Taiwan's residential electricity sector. By using long-term nationwide household data (1999–2014), actual variations in IBP rate structure are explored. Empirical results show that cross-subsidization under IBP have resulted in inefficient over-consumption by the poor and inefficient under-consumption by the rich. In addition, the financial burden increased with decreases of household's income levels and a relatively high percentage of subsidies mistakenly went to non-poor households. The upward price adjustments and broadened first block in recent years have increased the household's financial burden and the rates of wrongly excluding the poor and wrongly including the rich to enjoy the subsidy. Being unable to take family size into consideration and send correct price signals to all users are two serious problems for IBP, which may hinder the achievement of equity and efficiency in electricity use.

Should I stay or should I go?: consistency and switching of delivery locations among new mothers in 39 Sub-Saharan African and South/Southeast Asian countries.

The objective of this article is to assess the extent and determinants of switching delivery location between women’s first and second deliveries. We used Demographic and Health Survey data from 39 low- and middle-income countries on delivery locations from >30 000 women who had their first two deliveries in the 5-year survey recall period. Each delivery was characterized as occurring at home or in a health facility, facilities were classified as public- or private-sector. The extent of switching was estimated for each country, region and overall. Multivariable logistic regression models assessed determinants of switching (home to facility or facility to home), using four dimensions (perceived/biological need, socioeconomic characteristics, utilization of care and availability of care). Overall, 49.0% of first and 44.5% of second deliveries occurred in health facilities. Among women who had their first delivery at home, 11.8% used a facility for their second (7.0% public-sector and 4.8% private-sector). Among women who had their first delivery in a facility, 21.6% switched to a home location for their second. The extent of switching varied by country; but the overall net effect was either non-existent (n = 20) or away from facilities (n = 17) in all but two countries—Cambodia and Burkina Faso. Four factors were associated with switching to a facility after a home delivery: higher education, urban residence, non-poor household status and multiple gestation. Majority of women consistently used the same delivery location for their first two deliveries. We found some evidence that where switching occurred, women were being lost from facility care during this important transition, and that all four included dimensions were important determinants of women’s pattern of delivery care use. The relative importance of these factors should be understood in each specific context to improve retention in and provision of quality intrapartum care for women and their newborns.

Differential Characteristics of Poor and Non-Poor Communities in Malaybalay City

Poverty is a multi-dimensional phenomenon. In this study, eight dimensions were considered: demography, economic activities, environmental sanitation, literacy and education, social welfare, food shortage and food threshold of 14,528 households of Malaybalay City, Bukidnon. Given these dimensions, discriminant analysis was used to establish the characteristics of poor and non-poor households on the basis of multiple responses on all households. The classification results reveal 87.9% of households were classified correctly into poor and non-poor groups. Initial results further revealed that literacy and education and environmental sanitation were the strongest predictors of the group classification. Furthermore, on the basis of the classification rule developed in the study, of the identified poor households only 32.14% were recipients of the poverty reduction program of the city while 67.86% of the recipients were actually non-poor. The classification rule developed by this study did not match the classification rule of the city. The analysis of this paper is certainly not of sufficient complexity to allow a comprehensive poverty reduction strategy for Malaybalay City to be devised entirely from this result. Nevertheless, it does provide policy planners with objective measures on the distribution of goods and services for poverty alleviation that might be realized from sectoral poverty reduction strategy. Policy planners should view this result as a guide to allocate resources for poverty reduction in a more informed evidence-based manner.Keywords: differential characteristics, poverty, discriminant analysis

De facto Privatization and Inequalities in Educational Opportunity in the Transition to Secondary School in Rural Malawi.

There has been a recent, rapid de facto privatization of education in many African countries, as the number of private secondary schools operating in the region grew. The majority of these schools are "low-cost" private schools where tuition and fees are set as low as possible to cover operating costs and still generate profit. Proponents of low-cost private schools argue that these schools have proliferated in impoverished areas to meet unmet demand for access to education and where private schools may offer better quality than locally available public schools. Theories of inequality of educational opportunity suggest that if private schools offer better quality education, students from more advantaged families will be more likely to enroll at these institutions, potentially exacerbating educational inequality in the region. This analysis uses data from a school-based longitudinal survey, the Malawi Schooling and Adolescent Study, to examine socio-economic inequalities in the transition to secondary school and on-time enrollment in upper secondary. My findings indicate that youth from non-poor households are not only more likely to enroll in secondary school than poor youth, but they are also more likely to substitute enrollment in private schools for enrollment in second-tier government schools. Enrollment at private schools, however, does not yield schooling advantages; relative to both tiers of government secondary schooling, students who initially enrolled at private schools were the least likely to enroll on time in upper secondary school. These patterns suggest that these schooling circumstances may yield less segregation of opportunity than might otherwise be assumed.

Social Network Effects on Mobile Money Adoption in Uganda

This study analyses social network effects on the adoption of mobile money among rural households in Uganda. We estimate conditional logistic regressions controlling for correlated effects and other information sources. Results show that mobile money adoption is positively influenced by the size of the social network with which information is exchanged. We further find that this effect is particularly pronounced for non-poor households. Thus, while social networks represent an important target for policy-makers aiming to promote mobile money technology, the poorest households are likely to be excluded and require more tailored policy programmes and assistance.

Neural network rule extraction for gaining insight into the characteristics of poverty

Nearly one in five families in the country was poor in 2012, according to the Philippine Statistics Authority. While this proportion is lower than the corresponding figures from 2006 and 2009, the absolute number of poor families has actually grown from 3.8 million in 2006 to 4.2 million in 2012 due to the increase in population. Using data samples that have been collected from 69,130 households through a comprehensive community-based monitoring survey conducted in one of the cities that comprise Metro Manila, we attempt to identify the characteristics that differentiate between poor and non-poor households. Using back-propagation neural networks, we are able to correctly predict 73% of the poor households and 60% of the non-poor households. Moreover, the rules extracted from one of these networks provide concise description of how households are classified as poor based on their demographic characteristics and information pertaining to their surrounding living conditions.

Covariate and Idiosyncratic Shocks and Coping Strategies for Poor and Non-poor Rural Households in India

The objective of the paper is to track the association between different type of shocks experienced by rural households and corresponding coping strategies opted by them as they are, not only exposed to household-level and community level shocks, but also, lack effective risk management strategies which make them vulnerable to get into chronic poverty. A probit analysis has been used to articulate the comparative static distinction of risk management strategies between poor and non poor rural households using Additional Rural Incomes Survey/Rural Economic and Demographic Survey (ARIS/REDS) data surveyed by National Council of Applied Economic Research (NCAER) in rural India across 17 states to get a comparative static analysis. Households, generally, withdraw savings, seek remittances from migrant family members, take loan from formal and informal lenders and sell their existing assets and participate in Government sponsored welfare based programs to control after effect of shocks. Comparatively non-poor rural households could build up safety net (precautionary measure) to cope with price rise and other sudden shocks. But, extremely poor, generally, if don’t get help from relatives or can’t borrow from informal sources, ultimately starve at the time of sudden shocks. The welfare based government programs fail to arrest this extreme situation of grief during the idiosyncratic shocks.

Accuracy of Targeting and Rationing Under the Rural Employment Guarantee Programme: A Comparison between West Bengal and Rest of India

One major indicator of success of a social welfare programme is the accuracy of targeting of the benefits to the intended population or groups. Using nationally as well as state representative data for 2009-10 and 2011-12, this paper attempts to assess the Mahatma Gandhi Rural Employment Guarantee Act (MGNREGA) in terms of accuracy of targeting in West Bengal and compares it with rest of India. Using non-parametric and parametric methodologies, it aims to explore if poorer and deprived households are rationed out more than the non-poor households as far as participation in the programme is concerned. Though implementation of MGNREGA in West Bengal has been largely poor, its targeting performance is found to be fair when compared to other parts of the country. The findings should give impetus for the concerned authorities to improve on other dimensions of the programme and effectively implement it to realize the optimal benefits.

Does equity in healthcare spending exist among Indian states? Explaining regional variations from national sample survey data

BackgroundEquity and justice in healthcare payment form an integral part of health policy and planning. In the majority of low and middle-income countries (LMICs), healthcare inequalities are further aggravated by Out of Pocket Expenditure (OOPE). This paper examines the pattern of health equity and regional disparities in healthcare spending among Indian states by applying Andersen’s behavioural model of healthcare utilization.MethodsThe present study uses data from the 66th quinquennial round of Consumer Expenditure Survey, of the National Sample Survey Organization (NSSO), conducted in 2009–10 by Ministry of Statistics and Programme Implementation (MoSPI), Government of India (GoI). To measure equity and regional disparities in healthcare expenditure, states have been categorized under three heads on the basis of monthly OOPE i.e., Category A (OOPE > =INR 100); Category B (OOPE between INR 50 to 99) and Category C (OOPE < INR 50). Multiple Generalised Linear Regression Model (GLRM) has been employed to explore the effect of various socio-economic covariates on the level of OOPE.ResultsThe gap in the ratio of average healthcare spending between the poorest and richest households was maximum in Category A states (richest/poorest = 14.60), followed by Category B (richest/poorest 11.70) and Category C (richest/poorest 11.40). Results also indicate geographical concentration of lower level healthcare spending among Indian states (e.g., Odisha, Chhattisgarh and all the north-eastern states). Results from the multivariate analysis suggest that people residing in urban areas, having higher economic status, belonging to non-Muslim communities, non-Scheduled Tribes (STs), and non-poor households spend more on healthcare than their counterparts.ConclusionsIn spite of various efforts by the government to reduce the burden of healthcare spending, widespread inequalities in healthcare expenditure are prevalent. Households with high healthcare needs (SCs/STs, and the poor) are in a more disadvantaged position in terms of spending on health care. It has also been observed that spending on healthcare was comparatively lower among backward or isolated states. No doubt, the overall social security measures should be enhanced, but at the same time, looking at the regional differences, more priority should be assigned to the disadvantaged states to reduce the burden of OOPE. It is proposed that there is need to increase government spending, especially for the disadvantaged states and population, to minimise the burden of OOPE.

Neighborhood Poverty and Children's Academic Skills and Behavior in Early Elementary School

Neighborhoods provide resources that may affect children’s cognitive and behavioral outcomes. However, it is unclear to what degree associations between neighborhood disadvantage and outcomes persist into elementary school, and whether neighborhood disadvantage interacts with household disadvantage. Using data from the 2010-2011 Early Childhood Longitudinal Study- Kindergarten Cohort (N = 15,100 children), merged with census tract-level poverty data from the American Community Survey, this study examines associations between neighborhood poverty and children’s math, reading, and behavioral outcomes at kindergarten, first, and second grades. Findings indicate that as tract-level poverty increases, children’s achievement worsen, after controlling for child and family characteristics. These associations persist into second grade, and are stronger for children in poor vs. non-poor households. Findings suggest that neighborhood disadvantage may contribute to poorer achievement scores, particularly among children with few household resources, but that household disadvantage and other characteristics largely explain behavioral outcomes. Research and policy implications are discussed.

Efectos del gasto público en riego en los hogares de la sierra del Perú

This study assesses the impact that public spending on irrigation has on households in the Peruvian highlands that hold cultivable land and practice agriculture on an independent basis. To this end, we calculated the budget executed for irrigation by central, regional, and local government between 2008 and 2010, which entailed crosschecking the Integrated Financial Administration (System de Administracion Financiera, SIAF) database and the National Public Investment Project Bank (Banco de Proyectos del Sistema Nacional de Inversion Publica, SNIP) to adequately identify this expenditure. We applied the differences-in-differences method with control covariates, for which we constructed a pool of households taken from the National Household Survey (Encuesta Nacional de Hogares, Enaho) conducted by the National Institute of Statistics (Instituto Nacional de Estadistica, INEI), using the cut-off years of 2007 and 2017 as the baseline and 2012 and 2013 for follow-up. We segmented the sample into two groups based on the incidence of monetary policy by district, per the 2007 Poverty Map: households in poor districts, and households in nonpoor districts. This segmentation allowed us to isolate the endogenous effect of the treatment of using the poverty line calculated for each household in the Enaho. The impacts estimated evince a positive effect on the non-poor households assessed, in the form of an increase in agricultural nonwage income (independent production) and in non-agricultural wage income (non-agricultural dependent activities). In the poor households, the effect on primary and secondary net income and on net agricultural income is statistically equal to zero.

Effect of Public Pension on Depression among Korean Older Adults： The Differences between Poor and Non-poor Households

Effect of Public Pension on Depression among Korean Older Adults： The Differences between Poor and Non-poor Households

High Coverage and Utilization of Fortified Take-Home Rations among Children 6-35 Months of Age Provided through the Integrated Child Development Services Program: Findings from a Cross-Sectional Survey in Telangana, India.

The Integrated Child Development Services (ICDS) in the State of Telangana, India, freely provides a fortified complementary food product, Bal Amrutham, as a take-home ration to children 6–35 months of age. In order to understand the potential for impact of any intervention, it is essential to assess coverage and utilization of the program and to address the barriers to its coverage and utilization. A two-stage, stratified cross-sectional cluster survey was conducted to estimate the coverage and utilization of Bal Amrutham and to identify their barriers and drivers. In randomly selected catchment areas of ICDS centers, children under 36 months of age were randomly selected. A questionnaire, constructed from different validated and standard modules and designed to collect coverage data on nutrition programs, was administered to caregivers. A total of 1,077 children were enrolled in the survey. The coverage of the fortified take-home ration was found to be high among the target population. Nearly all caregivers (93.7%) had heard of Bal Amrutham and 86.8% had already received the product for the target child. Among the children surveyed, 57.2% consumed the product regularly. The ICDS program’s services were not found to be a barrier to product coverage. In fact, the ICDS program was found to be widely available, accessible, accepted, and utilized by the population in both urban and rural catchment areas, as well as among poor and non-poor households. However, two barriers to optimal coverage were found: the irregular supply of the product to the beneficiaries and the intra-household sharing of the product. Although sharing was common, the product was estimated to provide the target children with significant proportions of the daily requirements of macro- and micronutrients. Bal Amrutham is widely available, accepted, and consumed among the target population in the catchment areas of ICDS centers. The coverage of the product could be further increased by improving the supply chain.

To Specialize or Diversify: Agricultural Diversity and Poverty Dynamics in Ethiopia

Recent agricultural development policies have begun to shift focus from the promotion of a few staple crops toward encouraging crop diversity. The belief is that crop diversification is an effective strategy for dealing with a variety of issues, including poverty alleviation. However, there is a lack of empirical evidence to justify these positions. We contribute to filling this research gap by providing quantitative evidence on the impact of diversity in crop cultivation on household poverty. Using household panel data from Ethiopia we develop a diversity index to measure the effect of crop diversity on poverty status. To control for endogeneity and selection bias resulting from unobserved heterogeneity we utilize a recently developed parametric method for estimating dynamic binary response models with endogenous contemporaneous regressors. Our results provide evidence that households which grow a diverse set of crops are less likely to be poor than households that specialize in their crop production. Additionally, crop diversity reduces the probability that a non-poor household will fall into poverty and the probability that a poor household will remain in poverty. We conclude that crop diversification is a viable way to deal with the exigencies of being poor.

Is Poverty Decentralizing? Quantifying Uncertainty in the Decentralization of Urban Poverty

In this article we argue that the recent focus on the suburbanization of poverty is problematic because of the ambiguities and inconsistencies in defining suburbia. To improve transparency, replicability, and comparability, we suggest that research on the geographical changes to the distribution of poverty should focus on three questions: (1) How centralized is urban poverty? (2) To what extent is it decentralizing? (3) Is it becoming spatially dispersed? With respect to all three questions, the issue of quantifying uncertainty has been underresearched. The main contribution of the article is to provide a practical and robust solution to the problem of inference based on a Bayesian multivariate conditional autoregressive (CAR) model, made accessible via the R software package CARBayes. Our approach can be applied to spatiotemporally autocorrelated data and can estimate both levels of and change in global relative centralization index (RCI), local RCIs, and dissimilarity indexes. We illustrate our method with an application to Scotland's four largest cities. Our results show that poverty was centralized in 2011 in Glasgow, Dundee, and Aberdeen. Poverty in Edinburgh, however, was decentralized: Nonpoor households tend to live closer to the center than poor ones and increasingly so. We also find evidence of statistically significant reductions in centralization of poverty in all four cities. To test whether this change is associated with poverty becoming more dispersed, we estimate changes to evenness and local decentralization of poverty, revealing complex patterns of change.

Chain Financing Mode and the Effects of Precision Poverty Alleviation: Empirical Study Based on Quasi Experiment

Based on a quasi experiment of chain financing of farmers in Sichuan,Chongqing and Jiangxi in 2013 and 2015,and two-stage panel data of large sample farmer households,this paper uses difference-in-difference method and double difference matching method based on propensity scores to make a systematically empirical study of the poverty reduction effect between poor and non-poor households under the chain financing mode. It arrives at the results as follows: firstly,the role of industry chain financing in poverty reduction effect is sound overall; the proportion of poor households participating in industrial poverty alleviation is higher than the one of non-poor households,and the poverty reduction effect from chain financing also shows a phenomenon of diminishing marginal returns; secondly,compared to direct financing from financial institutions,the poverty reduction effect of chain financing based on industrial poverty alleviation is better; among them,the mode from credit of financial institutions to leading enterprises (industry support) and then to farmers and the mode from financial institutions to professional cooperatives (service industry) and then to farmers have significant poverty reduction effects on poor and non-poor households; the mode from rural mutual financial cooperative to farmers has a significant poverty reduction effect on non-poor households,while the mode from commercial financial institutions to farmers does not have significant poverty reduction effects on poor and non-poor households.

Income and Asset Poverty among Pastoralists in Northern Kenya

ABSTRACTIn this study we use household panel data collected in Marsabit district of Northern Kenya, to analyse the patterns of livelihood sources and poverty among pastoralists in that area. We estimate income poverty using imputed household income relative to the adjusted poverty line and asset poverty using a regression-based asset index and tropical livestock units (TLU) per capita. Our results indicate that keeping livestock is still the pastoralists’ main source of livelihood, although there is a notable trend of increasing livelihood diversification, especially among livestock-poor households. The majority of households (over 70%) are both income and livestock-poor with few having escaped poverty within the five-year study period. Disaggregating income and asset poverty also reveals an increasing trend of both structurally poor and stochastically nonpoor households. The findings show that the TLU-based asset poverty is a more appropriate measure of asset poverty in a pastoral setting.

Higher education decisions in Peru: on the role of financial constraints, skills, and family background

This paper analyzes the relative importance of short-term financial constraints vis-a-vis skills and other background factors when explaining higher education access in Peru. We focus on the disparities in university enrollment between rich and poor households. We use a novel household survey that includes special tests to measure cognitive and socio-emotional skills of the urban population age 14–50. These are complemented with retrospective data on basic education and family socioeconomic conditions in a multinomial model. We find that the strong correlation between university enrollment and family income in urban Peru is not only explained by short-term credit constraints, but also by poor cognitive skills and by family and educational backgrounds affecting tastes and aptitudes for formal education. Family income explains, at most, half of the university access gap between poor and non-poor households. The other half is related to differences in parental education, educational backgrounds, and cognitive skills. Our results indicate that credit or scholarship schemes alone will not suffice to change the regressive nature of higher education enrollment in Peru, and that such programs will face strong equity–efficiency trade-offs.