O MODELO DE KRUGMAN EXPLICA A CRISE CAMBIAL BRASILEIRA EM JANEIRO DE 1999?

Krugman (1979) desenvolveu um modelo canônico de crises cambiais e ataques especulativos que deu origem aos chamados "modelos de 1''' geração". Nesse contexto, esse trabalho tem por objetivo a análise do modelo de Krugman (1979) para o Brasil, no período de janeiro de 1995 a dezembro de 1998. Para isso, utilizamos o teste de causalidade de Granger (1969) que testa a precedência temporal entre reservas internacionais e crédito interno. Os resultados revelam o caso de independência, tendo em vista que não ocorreu causalidade unidirecional, tampouco bidirecional ou simultaneidade. Portanto, concluímos pela insustentabilidade da proposição de Krugman (1979).Krugman (1979) developed a canonical model of currency crises and speculative attack. Later, it was called "models of 1st generation ". In this context, this paper analyzes the model of Krugman (1979) to Brazil, in the period of January of 1995 to December of 1998. We used the test of Granger Causality to test the temporary precedence between international reserves and domestic credit. The results reveal the case of independence causality, since it didn't happen unidirectional causality, bi-directional causality or simultaneity causality. Therefore, the proposition of Kiugman (1979) is untenable

Credibilidade e crises cambiais : uma aplicação do modelo de Velasco

Este artigo analisa as crises cambiais dos principais países da América do Sul, no período de 1992 a 1998, com base no modelo de Velasco (1996). Este é um modelo que sintetiza dois enfoques: ataques especulativos resultantes de desequilíbrios nos fundamentos macroeconômicos e resultantes de profecias auto-realizáveis, mesmo quando as economias apresentam bons fundamentos. Nove países latino-americanos são classificados por meio da construção de um índice derivado de uma função perda. Desse modo é possível agrupar os países pelo grau de vulnerabilidade às crises, estabelecendo-se zonas de credibilidade. Os resultados indicam que a economia brasileira, por apresentar problemas nos fundamentos macroeconômicos, foi classificada em uma zona de credibilidade nula. A Argentina moveu-se de uma zona de alta credibilidade para uma faixa intermediária. Isto indica que a Argentina tornou-se suscetível às crises autorealizáveis. As demais economias situaram-se numa região de alta credibilidade.This paper analyzes the currency crises of the South American countries during the period from 1992 to 1998, based on the Velasco (1996) model. This is a model that synthesizes two approaches: speculative attacks resulting from unbalanced macroeconomics fundamentals and resulting from self-fulfilling prophecies, even when the economies show good fundamentals. Nine Latin American countries are classified by means of a loss function index. Thus, it is possible to classify the countries by the degree of vulnerability to the crises, establishing zones of credibility. The results indicate that the Brazilian economy, since it shows problems in its macroeconomic fundamentals, was classified in the zone of null credibility. Argentina moves from a zone of high credibility to an intermediate or partial zone. This is an indication that Argentina became susceptible to self-fulfilling crises. All other countries were classified in the zone of high credibility

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

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Credibilidade e crises cambiais: uma aplicação do modelo de Velasco

Este artigo analisa as crises cambiais dos principais países da América do Sul, no período de 1992 a 1998, com base no modelo de Velasco (1996). Este é um modelo que sintetiza dois enfoques: ataques especulativos resultantes de desequilíbrios nos fundamentos macroeconômicos e resultantes de profecias auto-realizáveis, mesmo quando as economias apresentam bons fundamentos. Nove países latino-americanos são classificados por meio da construção de um índice derivado de uma função perda. Desse modo é possível agrupar os países pelo grau de vulnerabilidade às crises, estabelecendo-se zonas de credibilidade. Os resultados indicam que a economia brasileira, por apresentar problemas nos fundamentos macroeconômicos, foi classificada em uma zona de credibilidade nula. A Argentina moveu-se de uma zona de alta credibilidade para uma faixa intermediária. Isto indica que a Argentina tornou-se suscetível às crises autorealizáveis. As demais economias situaram-se numa região de alta credibilidade

Distance from the edge of forest fragments influence the abundance of aphidophagous hoverflies (Diptera: Syrphidae) in wheat fields

This study aimed to evaluate the influence of the distance from the edge of native forests on the abundance of aphidophagous hoverflies in wheat fields. The study was conducted in four commercial fields in the North of Paraná State, Brazil, during the wheat crop season of 2009. Two transects were surveyed parallel to the edge of the forest at two distances: 25 (“near”) and 525 meters (“far”) from the edge. The abundance of hoverflies was compared using a χ2 test (p ≤ 0.05). In total, 1,845 hoverflies adults were collected, which represented 15 species and three genera. The most abundant species was Allograpta exotica (60.43%), followed by Toxomerus dispar (17.78%) and Toxomerus watsoni (7.26%) (Diptera: Syrphidae). An important inference was that all fields showed a higher abundance of aphidophagous hoverflies closer to the edge of the forest (25 m) during the wheat tillering stage. The initial abundance of aphidophagous hoverflies in wheat fields is likely greater near the edge because of the availability of resources in the surrounding forest that enhance hoverfly survival during periods of low aphid infestation. 

Effects of climate change on leaf breakdown by microorganisms and the shredder Phylloicus elektoros (Trichoptera: Calamoceratidae)

Climate change may affect species diversity and, consequently, ecological processes such as leaf decomposition. We evaluated the effects of increased temperature and carbon dioxide (CO2) on fungal biomass, leaf breakdown, and on survival and growth of the shredder Phylloicus elektoros. We hypothesized that climatic changes would result in lower survival and growth of shredders and lower leaf consumption by these organisms. On the other hand, we predicted an increase in fungal biomass in response to climatic changes. We conducted an experiment in Manaus, Brazil, using four microcosms that simulate real-time air temperature and CO2 (control chamber), as well as three other chambers subjected to fixed increases in temperature and CO2 as compared to the control chamber. The “extreme” condition represented an increase of ~4.5°C in temperature and ~870 ppm in CO2 in relation to the control chamber. Total and shredder leaf-breakdown rates, fungal biomass, and shredder survival rates were significantly lower in warmer and CO2 concentrated atmospheres. Shredder growth rate and leaf breakdown by microorganisms were similar among all climatic conditions. With climatic changes, we found an increase in the relative importance of microorganisms on leaf-breakdown rates as compared to shredders. Thus, lower leaf breakdown and a change in the main decomposer due to future climatic conditions may result in major changes in the pathways of organic matter processing and, consequently, in aquatic food webs. © 2016, Springer International Publishing Switzerland