The causal effect of family size on child labor and education

This paper investigates the causal relationship between family size and child labor and educationamong brazilian children. More especifically, it analyzes the impact of family size on child labor,school attendance, literacy and school progression. It explores the exogenous variation in familysize driven by the presence of twins in the family. The results are consistent under the reasonableassumption that the instrument is a random event. Using the nationally representative brazilianhousehold survey (Pnad), detrimental effects are found on child labor for boys. Moreover,significant effects are obtained for school progression for girls caused by the exogenous presenceof the young siblings in the household.

MEDIDAS E DETERMINANTES DA MOBILIDADE DOS RENDIMENTOS DO TRABALHO NO BRASIL

This paper makes an analysis of the evolution of real earnings mobility for Brazilian workers from 1984 to 2001. The evolution of five real earnings mobility indicators is calculated using the Pesquisa Mensal de Emprego data set. The economic and demographic determinants of real earnings mobility in Brazil are estimated using the Fixed Effect Method to the mobility indicators calculated for sample cells. Among the economic variables, the real average earning, the real interest rate and the real minimum wage have a positive effect in earnings mobility; the inflation rate, when controlled by the other variables, has only distributive effects on earnings; the impact of the unemployment rate depends on the concept of mobility adopted. The importance of demographic variables becomes clear when we look at the econometric results. Men, usually, have more mobility than women, except for per capita directional changes in real earnings. Younger groups also have more directional mobility compared to older individuals, but have lower mobility caused by relative trades among them. Education level seems to contribute to diminish the earnings mobility for those that have more than fourteen years of education.

Decentralization And Education Performance: A First View To The Brazilian Process

This paper analyses the impact of the decentralization in educational system that is taking place in Brazil inthe last decade, as a result of several laws that encourage municipalities to invest in fundamental education.The proficiency tests undertaken by the government allows to follow some public schools in two points intime. Therefore we were able to create an experimental group with the schools that were under state system inthe SAEB exam and have migrated to the municipality system by the time of Prova Brasil and a control groupwith the schools that were under the state system between the two exams and compare the difference in theirresults using a fixed effect panel data analysis. The difference in difference estimator indicates that there is nosignificant change in the performance of the students.

Socioeconomic risk markers of congenital Zika syndrome: a nationwide, registry-based study in Brazil

While it is well known that socioeconomic markers are associated with a higher risk of arbovirus infections, research on the relationship between socioeconomic factors and congenital Zika syndrome (CZS) remains limited. This study investigates the relationship between socioeconomic risk markers and live births with CZS in Brazil. We conducted a population-based study using data from all registered live births in Brazil (Live Births Information System) linked with the Public Health Event Record from 1 January 2015 to 31 December 2018. We used logistic regression models to estimate the OR and 95% CIs of CZS based on a three-level framework. In an analysis of 11 366 686 live births, of which 3353 had CZS, we observed that live births of self-identified black or mixed race/brown mothers (1.72 (95% CI 1.47 to 2.01) and 1.37 (95% CI 1.24 to 1.51)) were associated with a higher odds of CZS. Live births from single women compared with married women and those from women with less than 12 years of education compared with those with more than 12 years of education also had higher odds of CZS. In addition, live births following fewer prenatal care appointments had increased odds of CZS in the nationwide data. However, in the analyses conducted in the Northeast region (where the microcephaly epidemic started before the link with Zika virus was established and before preventive measures were known or disseminated), no statistical association was found between the number of prenatal care appointments and the odds of CZS. This study shows that live births of the most socially vulnerable women in Brazil had the greatest odds of CZS. This disproportionate distribution of risk places an even greater burden on already socioeconomically disadvantaged groups, and the lifelong disabilities caused by this syndrome may reinforce existing social and health inequalities

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost