Population and poverty

Comparisons of levels of poverty across contexts and circumstances overlook the composition and characteristics of the domain of non-poor. But implications of poverty in terms of compromised welfare as well as its potential for alleviation do depend on the structure and composition of the non-poor. On this premise, this note empirically illustrates a contrast between the levels and burden of poverty for Indian states. It finds that burden of poverty is not linear with levels of poverty implying that similar levels of poverty have differential potential for its alleviation.

While there is a consistent body of literature on household demography, land use, and migration in agricultural frontiers, especially in the Amazon, few studies address changes in households’ poverty due to change in their portfolio of capitals. This paper provides insights on poverty experience among rural households as frontier evolves from settlement to expansion and market integration. Building on the livelihoods approach, we focus on the estimation of time spent in poverty according to key household capitals, which have been shown to affect household well-being. Empirical evidence on how these capitals affect rural household income and poverty experience are provided by novel longitudinal data for Machadinho d’Oeste, Rondônia, in the Brazilian Amazon. Different from other household level data in the Amazon, ours include interviews applied to settlers at the onset of the settlement project, back to 1985, with follow-ups up to 2010, covering a 25 years period. We concentrate in the panel 1987-1995 to simulate how improvement in key capitals would impact the average time each household spent as poor and non-poor. This evidence will contribute to similar simulations based upon other study areas in the Amazon and in Thailand, providing material for meta-analysis of poverty and capitals in agricultural frontiers worldwide.

The present paper is a trial to assess the magnitude of poverty and its variations among regions and socioeconomic sectors of Egypt. Causes of poverty and characteristics of the poor are discussed aiming to identify empirical policies to reduce poverty. Poverty profile analyzed using data from the Egypt Integrated Household Survey (EIHS). Our results indicate that poverty rate in Egypt increased from 16.7% of the population in 2000 to 25.2% in 2010. High illiteracy rate, high population growth, low employment opportunities, and Ineffective policies are the main causes of poverty in Egypt. Poverty is highly concentrated in Upper Egypt governorates. Poverty is over-represented in agricultural activities. Egyptians spend half of their income on food and drink, followed by housing (18%). Share of health services not exceeds 8% of their income while entertainment and culture takes up to 2.2% of family expenditures. Illiteracy, child labor, large household size, high fertility rate, and families headed by female are the main socioeconomic characteristics associated with poverty in Egypt. Income generating activities and good distribution policies are important policies instruments to reduce poverty and achieving social equality.

This paper aims to present results from the research titled “The Living Place of the Excluded from and by the Metropolis”. The investigation analyses the population dynamics among low-income emigrants departing from Belo Horizonte – MG, Brazil, the metropolitan core, toward its neighboring cities: Ribeirão das Neves, Vespasiano, Santa Luzia, Sabará e Ibirité. Thus, we seek to understand and qualify this population dispersal process within Belo Horizonte’s Metropolitan Region. We deploy a hybrid analysis, based on historical cartography and satellite imagery, to analyze the behavior of the urban sprawl emanating from Belo Horizonte between 1918 to 2010. We conjugate this procedure with the analysis of the 2000 and 2010 Census migration data on the population below the poverty line. Results reveal a consistent out-migration trend among the poor from Belo Horizonte, fomented by their incapacity to afford the costs of living in the main city, especially those related to housing.

It is important to develop a methodology to capture the evolution of the MDGs from the intramunicipal or local to the national levels and in a way that makes possible an international comparison, to support performance analysis and possible adjustments to the targets one wants to achieve.
To accomplish this analysis two administrative units were selected: the municipality of Ilhabela, on the coast of São Paulo, Brazil, and the municipality of Porto Novo, on the island of Santo Antão, Cape Verde.
The selected indicators are: literacy rate for the population aged between 15 and 24 years, ratio of literate women and men and population with access to improved sanitation.

This study investigates how social exclusion impact household poverty among the older persons in Nigeria. This has become essential in order to improve the preparation for old age among Nigerians. Data were gathered using questionnaire and multi-stage sampling technique was used to select 242 respondents. Simple percentages cross tabulations and chi-square statistics were used to analyze the data. The study found that more than half of the respondents admitted to have been discriminated based on their age while about one-third of the respondents said they have not been discriminated based on their age. This indicates that the concept of ageism which is prejudice based on age still persists. The study found out the majority of the respondents agreed that household poverty is an important predictor of whether or not an elderly would be socially excluded. It was also indicated that a slight majority of the elders do not contribute to the decision making process of their household which indicates role loss. In conclusion, the reintegration of the elderly into the value system of the modern society is paramount to enhance higher moral standing, so as not to lose cultural heritage, also the rate of social inequality should be reduced.

This paper compares slums (subnormal clusters) with formal city to identify similarities and differences between these populations. The exercise is done for two Brazilian cities: Rio de Janeiro and Belo Horizonte, both with over 2 million inhabitants. In Rio de Janeiro 22% of population lives in 763 slums while in Belo Horizonte 13% of population lives in 211 slums spread throughout the city territory. The analysis consists of comparing the formal city with slums regarding individual demographic characteristics of the population such as age structure, composition by race / color as well as characteristics of households like access to basic sanitation, including access to potable water and waste disposal. Using data from the 2010 National Demographic Census, the results indicate that, in fact, there is not a great disparity between slums and rest of the city with regard to the differences in attendance to basic services, being this difference was more pronounced with regard to the age structure of the population and social inequalities understood as differences in income and race/color. Finally, some recommendations are made for public policies aimed at the population living in slums.

This paper aims to track the Millennium Development Goals by districts in India using District Level Household and Facility Survey-3 data. The findings reveal that more than half of the districts are still underneath stern poverty; the districts will very soon achieve universal primary education; primary education has overcome gender disparity in all the districts, but gender disparity in secondary education still exists in most of the districts; coverage of measles vaccination in all the districts is improving; in more than half of the districts occurrence of institutional births is very less; knowledge of HIV/AIDS is wide spread among women, on the contrary low condom use among men is a matter of concern to combat HIV/AIDS, ensuring environmental sustainability in all the districts is a challenging task for India. Achieving the MDGs is a critical challenge for India and it has just five years to translate the goals into reality.

Should older persons work for money? This paper aims to provide the first and important step to answer that question, by analysing the employment patters of older persons in Indonesia. It examines what the older persons did in and outside the labour market. It finds that older persons were more likely to work in more flexible working arrangements. Working as self-employed or unpaid workers seemed to be more suitable for the older persons. Older persons were more likely to work as “skilled agricultural and fishery workers”. Also, they tended to work in agricultural or service sectors. This pattern may reflect the current labour market situation and the human capital of the older persons because advances in technology and social innovations, coupled with enhanced human capital of the older persons, will produce completely different employment patterns among older persons, including the older women, in the future.
The published data from 2007 National Labour Force Survey is the main source of the analysis. This paper examines the empirical conditions of older persons’ employment: sex ratio and age structure of the labour force;

Building on the capability approach, this paper discusses the multidimensionality of deprivation in urban Brazil between 2003 and 2008. Based on a temptative four dimensions index (e.g., living conditions, health standards, education levels and labor market participation) relating thirteen indicators, we find that the majority of individuals lived in households with no deprivation or deprived in only one indicator. Then, we explicitly addressed the inter-indicator covariance structure of the thirteen items using factorial analyses. Deprivation tended to come in pairs, as water and sewage, or child labor and school attendance, or in triples, as assets, functional illiterate and non-working adult. After this, we compared this index with poverty measured by income standards for states in Brazil. Evidences confirmed the regional inequality in both types of measurement. However, comparisons showed that correlations between them, although positive and significant, were not strongly. Finally, we discussed the dynamics of deprivation using data for synthetic cohorts and OLS and logistic models. We verified the association between attributes, such as sex, race, cohort and educational level and the propensity of a household to fall and continue in poverty or deprivation.