5 resultados para Credit institutions

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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There is now an extensive literature on extinction debt following deforestation. However, the potential for species credit in landscapes that have experienced a change from decreasing to expanding forest cover has received little attention. Both delayed responses should depend on current landscape forest cover and on species life-history traits, such as longevity, as short-lived species are likely to respond faster than long-lived species. We evaluated the effects of historical and present-day local forest cover on two vertebrate groups with different longevities understorey birds and non-flying small mammals - in forest patches at three Atlantic Forest landscapes. Our work investigated how the probability of extinction debt and species credit varies (i) amongst landscapes with different proportions of forest cover and distinct trajectories of forest cover change, and (ii) between taxa with different life spans. Our results suggest that the existence of extinction debt and species credit, as well as the potential for their future payment and/or receipt, is not only related to forest cover trajectory but also to the amount of remaining forest cover at the landscape scale. Moreover, differences in bird and small mammal life spans seem to be insufficient to affect differently their probability of showing time-delayed responses to landscape change. Synthesis and applications. Our work highlights the need for considering not only the trajectory of deforestation/regeneration but also the amount of forest cover at landscape scale when investigating time-delayed responses to landscape change. As many landscapes are experiencing a change from decreasing to expanding forest cover, understanding the association of extinction and immigration processes, as well as their interactions with the landscape dynamic, is a key factor to plan conservation and restoration actions in human-altered landscapes.

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A large historiographic tradition has studied the Brazilian state, yet we know relatively little about its internal dynamics and particularities. The role of informal, personal, and unintentional ties has remained underexplored in most policy network studies, mainly because of the pluralist origin of that tradition. It is possible to use network analysis to expand this knowledge by developing mesolevel analysis of those processes. This article proposes an analytical framework for studying networks inside policy communities. This framework considers the stable and resilient patterns that characterize state institutions, especially in contexts of low institutionalization, particularly those found in Latin America and Brazil. The article builds on research on urban policies in Brazil to suggest that networks made of institutional and personal ties structure state organizations internally and insert them,into broader political scenarios. These networks, which I call state fabric, frame politics, influence public policies, and introduce more stability and predictability than the majority of the literature usually considers. They also form a specific power resource-positional power, associated with the positions that political actors occupy-that influences politics inside and around the state.

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Seeking alternatives for the economic system to face the several crises it has gone through lately (electrical power, cultural, financing and technological) brought about a new market involving the Kyoto Protocol signatory countries: the carbon market. The present article aims at assessing the carbon market institutional issue in Brazil by identifying the risks and opportunities inherent to the institutional agent characteristics and to that market rules. The research methodology was bibliographic and based on the analysis of the Securities and Exchange Commission of Brazil (Comissao de Valores Mobiliarios and Bolsa Mercantil de Valores) contents. Its theoretical basis rests on concepts of the institution and the new institutional economy. The results show that in spite of the risks and institutional problems it involves, the carbon market is promising due to the opportunities create by new technologies and energies developed to achieve and sustain the capitalist system new cycle, addressed to produce a clean development.

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Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.

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Background: Angola is one of the African countries with the highest morbidity and mortality rates and a devastating lack of human resources for health, including nursing. The World Health Organization stimulates and takes technical cooperation initiatives for human resource education and training in health and education, with a view to the development of countries in the region. The aim in this study was to identify how nurses affiliated with nursing education institutions perceive the challenges nursing education is facing in Angola. Methods: After consulting the National Directory of Human Resources in Angola, the nurse leaders affiliated with professional nursing education institutions in Angola were invited to participate in the study by email. Data were collected in February 2009 through the focus group technique. The group of participants was focused on the central question: what are the challenges faced for nursing education in your country? To register and understand the information, besides the use of a recorder, the reporters elaborated an interpretative report. Data were coded using content analysis. Results: Fourteen nurses participated in the meeting, most of whom were affiliated with technical nursing education institutions. It was verified that the nurse leaders at technical and higher nursing education institutions in Angola face many challenges, mainly related to the lack of infrastructure, absence of trained human resources, bureaucratic problems to regularize the schools and lack of material resources. On the opposite, the solutions they present are predominantly centered on the valuation of nursing professionals, which implies cultural and attitude changes. Conclusions: Public health education policies need to be established in Angola, including action guidelines that permit effective nursing activities. Professional education institutions need further regularizations and nurses need to be acknowledged as key elements for the qualitative enhancement of health services in the country.