908 resultados para Economic inequality- Brazil


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Includes bibliography.

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Includes bibliography.

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This paper shows that the Brazilian economic relations with China are intensifying at an unprecedented pace. This obviously brings about new challenges and opportunities. It is also shown that relations with specific provinces in China vary significantly, as illustrated by the available indicators for Shanghai, in comparison to other provinces. And last but not least, the paper has shown the rich recent experience of one Brazilian company that has benefited from the sharp increase of Chinese demand for raw material. This is a typical case of a new scenario for Brazilian firms, one where the firm has to learn how to flex its muscles as one of the major players in the international market, and in particular to learn in its dealing with its main client. The relationship between one of the major suppliers and the most active demander is of particular interest in itself.

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This article analyses the trend of unfair inequality in Brazil (1995-2009) using a nonparametric approach to estimate the income function. The entropy metrics introduced by Li, Maasoumi and Racine (2009) are used to quantify income differences separately for each effort variable. A Gini coefficient of unfair inequality is calculated, based on the fitted values of the non-parametric estimation; and the robustness of the estimations, including circumstantial variables, is analysed. The trend of the entropies demonstrated a reduction in the income differential caused by education. The variables “hours worked” and “labour-market status” contribute significantly to explaining wage differences imputed to individual effort; but the migratory variable had little explanatory power. Lastly, the robustness analysis demonstrated the plausibility of the results obtained at each stage of the empirical work.

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Studies on efficiency achieved greater relevance in organisations within an open market framework, which in Brazil began around 1990. The objective of this paper, applying the data envelopment analysis methodology, is to analyse the efficiency of banks operating in the country using the database termed 'the biggest banks', periodically divulged by the Central Bank of Brazil in 2010-2012. The methodology was applied to the 26 largest banking organisations via two approaches, one was financial intermediation and the other was results. In the financial intermediation approach, the efficiency increase was the highest among banks specialised in credit from 2010 to 2012. Retail banks, especially the large ones, felt most intensely the reaction of 2011, a year considered as the sector's low performance year. In the results approach, the efficiency increase was higher among retail banks. Factors such as retractions in the SELIC rate and bank spreads impacted all banks, regardless of the segment.

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The tourism spending like other activities has direct and secondary effects on the economy, and presents complex interaction with other activities deserving a special treatment for measuring its contribution to the global result of production and consumption. In this paper, it is used the Money Generation Model to measure the global economic impact of tourism sales in Ouro Preto, this method is not so limited by the data and it is able to produce good approximations to reality. It was not possible to adopt the WTO methodology due to data limitation. The results revealed the real importance of tourism for Ouro Preto, representing up to 10.4% of GDP in 2002, up to 21.8% of tax revenues in 2004, and approximately 11% of the region’s population in 2002 was related to tourism sales. Some actions can be outlined from these results in order to illustrate the current economic reality of the tourism in Ouro Preto. It is also possible to improve the tourist planning accomplished by the local City Hall in a coherent way with the economic results generated by the tourism.

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Background: Infant mortality is an important measure of human development, related to the level of welfare of a society. In order to inform public policy, various studies have tried to identify the factors that influence, at an aggregated level, infant mortality. The objective of this paper is to analyze the regional pattern of infant mortality in Brazil, evaluating the effect of infrastructure, socio-economic, and demographic variables to understand its distribution across the country. Methods: Regressions including socio-economic and living conditions variables are conducted in a structure of panel data. More specifically, a spatial panel data model with fixed effects and a spatial error autocorrelation structure is used to help to solve spatial dependence problems. The use of a spatial modeling approach takes into account the potential presence of spillovers between neighboring spatial units. The spatial units considered are Minimum Comparable Areas, defined to provide a consistent definition across Census years. Data are drawn from the 1980, 1991 and 2000 Census of Brazil, and from data collected by the Ministry of Health (DATASUS). In order to identify the influence of health care infrastructure, variables related to the number of public and private hospitals are included. Results: The results indicate that the panel model with spatial effects provides the best fit to the data. The analysis confirms that the provision of health care infrastructure and social policy measures (e. g. improving education attainment) are linked to reduced rates of infant mortality. An original finding concerns the role of spatial effects in the analysis of IMR. Spillover effects associated with health infrastructure and water and sanitation facilities imply that there are regional benefits beyond the unit of analysis. Conclusions: A spatial modeling approach is important to produce reliable estimates in the analysis of panel IMR data. Substantively, this paper contributes to our understanding of the physical and social factors that influence IMR in the case of a developing country.

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Purpose: To test the association between income inequality and elderly self-rated health and to propose a pathway to explain the relationship. Methods: We analyzed a sample of 2143 older individuals (60 years of age and over) from 49 distritos of the Municipality of Sao Paulo, Brazil. Bayesian multilevel logistic models were performed with poor self-rated health as the outcome variable. Results: Income inequality (measured by the Gini coefficient) was found to be associated with poor self-rated health after controlling for age, sex, income and education (odds ratio, 1.19; 95% credible interval, 1.01-1.38). When the practice of physical exercise and homicide rate were added to the model, the Gini coefficient lost its statistical significance (P>.05). We fitted a structural equation model in which income inequality affects elderly health by a pathway mediated by violence and practice of physical exercise. Conclusions: The health of older individuals may be highly susceptible to the socioeconomic environment of residence, specifically to the local distribution of income. We propose that this association may be mediated by fear of violence and lack of physical activity. (C) 2012 Elsevier Inc. All rights reserved.

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OBJECTIVE: To analyze cause-specifi c mortality rates according to the relative income hypothesis. METHODS: All 96 administrative areas of the city of Sao Paulo, southeastern Brazil, were divided into two groups based on the Gini coefficient of income inequality: high (>= 0.25) and low (<0.25). The propensity score matching method was applied to control for confounders associated with socioeconomic differences among areas. RESULTS: The difference between high and low income inequality areas was statistically significant for homicide (8.57 per 10,000; 95% CI: 2.60; 14.53); ischemic heart disease (5.47 per 10,000 [95% CI 0.76; 10.17]); HIV/AIDS (3.58 per 10,000 [95% CI 0.58; 6.57]); and respiratory diseases (3.56 per 10,000 [95% CI 0.18; 6.94]). The ten most common causes of death accounted for 72.30% of the mortality difference. Infant mortality also had signifi cantly higher age-adjusted rates in high inequality areas (2.80 per 10,000 [95% CI 0.86; 4.74]), as well as among males (27.37 per 10,000 [95% CI 6.19; 48.55]) and females (15.07 per 10,000 [95% CI 3.65; 26.48]). CONCLUSIONS: The study results support the relative income hypothesis. After propensity score matching cause-specifi c mortality rates was higher in more unequal areas. Studies on income inequality in smaller areas should take proper accounting of heterogeneity of social and demographic characteristics.

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SETTING: Respiratory mortality rates are declining in several countries, including Brazil; however, the effect of socio-economic indicators and sex is unclear. OBJECTIVE: To identify differences in mortality trends according to income and sex in the city of Sao Paulo, Brazil. DESIGN: We performed a time-trend analysis of all respiratory diseases, including chronic obstructive pulmonary disease (COPD), lung cancer and tuberculosis, using Joinpoint regression comparing high, middle and low household income levels from 1996 to 2010. RESULTS: The annual per cent change (APC) and 95% confidence intervals (95%CIs) for death rates from all respiratory disease in men in high-income areas was -1.1 (95%CI -2.7 to 0.5) in 1996-2002 and -4.3 (95%CI -5.9 to -2.8) in 2003-2009. In middle- and low-income areas, the decline was respectively -1.5 (95%CI -2.2 to -0.7) and -1.4 (95%CI -1.9 to -0.8). For women, the APC declined in high-income (-1.0, 95%CI -1.9 to -0.2) and low-income areas (0.8, 95%CI -1.3 to -0.2), but not in middle-income areas (-0.5, 95%CI -1.4 to 0.3) from 1996 to 2010. CONCLUSION: Death rates due to COPD and all respiratory disease declined more consistently in men from high-income areas. Mortality due to lung cancer decreased in men, but increased in women in middle- and low-income areas.

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Background Support for the adverse effect of high income inequality on population health has come from studies that focus on larger areas, such as the US states, while studies at smaller geographical areas (eg, neighbourhoods) have found mixed results. Methods We used propensity score matching to examine the relationship between income inequality and mortality rates across 96 neighbourhoods (distritos) of the municipality of Sao Paulo, Brazil. Results Prior to matching, higher income inequality distritos (Gini >= 0.25) had slightly lower overall mortality rates (2.23 per 10 000, 95% CI -23.92 to 19.46) compared to lower income inequality areas (Gini <0.25). After propensity score matching, higher inequality was associated with a statistically significant higher mortality rate (41.58 per 10 000, 95% CI 8.85 to 73.3). Conclusion In Sao Paulo, the more egalitarian communities are among some of the poorest, with the worst health profiles. Propensity score matching was used to avoid inappropriate comparisons between the health status of unequal (but wealthy) neighbourhoods versus equal (but poor) neighbourhoods. Our methods suggest that, with proper accounting of heterogeneity between areas, income inequality is associated with worse population health in Sao Paulo.