887 resultados para panel data with spatial effects
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BACKGROUND Respiratory tract infections and subsequent airway inflammation occur early in the life of infants with cystic fibrosis. However, detailed information about the microbial composition of the respiratory tract in infants with this disorder is scarce. We aimed to undertake longitudinal in-depth characterisation of the upper respiratory tract microbiota in infants with cystic fibrosis during the first year of life. METHODS We did this prospective cohort study at seven cystic fibrosis centres in Switzerland. Between Feb 1, 2011, and May 31, 2014, we enrolled 30 infants with a diagnosis of cystic fibrosis. Microbiota characterisation was done with 16S rRNA gene pyrosequencing and oligotyping of nasal swabs collected every 2 weeks from the infants with cystic fibrosis. We compared these data with data for an age-matched cohort of 47 healthy infants. We additionally investigated the effect of antibiotic treatment on the microbiota of infants with cystic fibrosis. Statistical methods included regression analyses with a multivariable multilevel linear model with random effects to correct for clustering on the individual level. FINDINGS We analysed 461 nasal swabs taken from the infants with cystic fibrosis; the cohort of healthy infants comprised 872 samples. The microbiota of infants with cystic fibrosis differed compositionally from that of healthy infants (p=0·001). This difference was also found in exclusively antibiotic-naive samples (p=0·001). The disordering was mainly, but not solely, due to an overall increase in the mean relative abundance of Staphylococcaceae in infants with cystic fibrosis compared with healthy infants (multivariable linear regression model stratified by age and adjusted for season; second month: coefficient 16·2 [95% CI 0·6-31·9]; p=0·04; third month: 17·9 [3·3-32·5]; p=0·02; fourth month: 21·1 [7·8-34·3]; p=0·002). Oligotyping analysis enabled differentiation between Staphylococcus aureus and coagulase-negative Staphylococci. Whereas the analysis showed a decrease in S aureus at and after antibiotic treatment, coagulase-negative Staphylococci increased. INTERPRETATION Our study describes compositional differences in the microbiota of infants with cystic fibrosis compared with healthy controls, and disordering of the microbiota on antibiotic administration. Besides S aureus, coagulase-negative Staphylococci also contributed to the disordering identified in these infants. These findings are clinically important in view of the crucial role that bacterial pathogens have in the disease progression of cystic fibrosis in early life. Our findings could be used to inform future studies of the effect of antibiotic treatment on the microbiota in infants with cystic fibrosis, and could assist in the prevention of early disease progression in infants with this disorder. FUNDING Swiss National Science Foundation, Fondation Botnar, the Swiss Society for Cystic Fibrosis, and the Swiss Lung Association Bern.
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The work of Russell Dalton has undoubtedly played a seminal role in the study of the relation between political sophistication and partisan dealignment. We furthermore acknowledge the presence of a consensus on the occurrence of lower levels of partisanship in Germany. Using panel data as well as pooled cross-sectional observations, however, it is clear that generational replacement is not the sole driving force of partisan dealignment, but that period effects should also be taken into account. While on an aggregate level rising levels of political sophistication have occurred simultaneously with decreasing partisanship, individual level analysis suggests clearly that the least sophisticated are most likely to feel alienated from the party system. We close with some very specific suggestion on how to address the democratic consequences of declining levels of partisanship.
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The Brazilian state of Paraná exhibits a violent geography of inequality and duality, hosting both the most developed city in the country, internationally recognized by its urban and environmental innovations, and southern Brazil’s most concentrated cluster of poverty and underdevelopment. Over the course of the past decades, the state underwent a major economic transformation, modernizing and increasing its industrial structure and shifting to the service sector with a larger participation of the knowledge economy. This study is concerned on the interplay between formal education and socioeconomic development during this process, and above all its spatial character. It attempts make sense of the rich literature on education and growth and/or development, discussing it through the lenses of human geography and planning. In order for the analysis to be possible, this study created a consistent database of municipal scores of education over the course of 40 years, dealing with changing census methodologies and municipal boundaries. Making use of modern exploratory spatial data analysis combined with spatial regressions, the study identifies a clustered, time-persistent interplay between education and development that is stronger for low and basic levels of education. Moreover, it provides evidence that not only education is a predictor of future development, but also that analyses of this kind must take into consideration spatial autocorrelation in order to be accurate.
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Esse trabalho investiga empiricamente a relação entre custo de agência e as medidas de monitoramento interno disponíveis aos investidores brasileiros nas empresas nacionais, utilizando amostras de companhias abertas entre os anos de 2010 e 2014, totalizando 134 empresas analisadas e 536 observações. Para medir tal relação, foram utilizadas, como variáveis de monitoramento interno, informações sobre a remuneração variável dos executivos, entre elas o uso de outorgas de opções de compra de ações, a composição do conselho de administração, dando ênfase à representatividade dos conselheiros independentes e à dualidade entre Chairman e CEO, e o percentual do capital social das companhias que está sob propriedade dos executivos. Como proxy para custo de agência, foram utilizados os indicadores Asset Turnover Ratio e General & Administrative Expenses (G&A) como percentual da Receita Líquida. Neste contexto, foram estabelecidas duas hipóteses de pesquisa e estimados modelos de regressão em painel controlados por efeitos fixos de tempo e empresa, empregando como variável dependente as variáveis proxy do custo de agência e utilizando as variáveis endividamento e tamanho das empresas como variáveis de controle. Os resultados dos modelos demonstram que, na amostra selecionada, há uma relação positiva e significativa entre o percentual da remuneração variável e as proxies de custo de agência, comportamento este contrário ao esperado originalmente. Conclui-se assim que as empresas que apresentam uma maior composição variável no total remunerado ao executivo, incorrem em um maior custo de agência, o que leva à conclusão de que tais ferramentas não são boas estratégias de alinhamento de interesses entre executivos e acionistas. As demais variáveis de monitoramento interno não apresentaram significância.
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Thesis (Ph.D.)--University of Washington, 2016-06
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This paper presents a metafrontier production function model for firms in different groups having different technologies. The metafrontier model enables the calculation of comparable technical efficiencies for firms operating under different technologies. The model also enables the technology gaps to be estimated for firms under different technologies relative to the potential technology available to the industry as a whole. The metafrontier model is applied in the analysis of panel data on garment firms in five different regions of Indonesia, assuming that the regional stochastic frontier production function models have technical inefficiency effects with the time-varying structure proposed by Battese and Coelli ( 1992).
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The estimated parameters of output distance functions frequently violate the monotonicity, quasi-convexity and convexity constraints implied by economic theory, leading to estimated elasticities and shadow prices that are incorrectly signed, and ultimately to perverse conclusions concerning the effects of input and output changes on productivity growth and relative efficiency levels. We show how a Bayesian approach can be used to impose these constraints on the parameters of a translog output distance function. Implementing the approach involves the use of a Gibbs sampler with data augmentation. A Metropolis-Hastings algorithm is also used within the Gibbs to simulate observations from truncated pdfs. Our methods are developed for the case where panel data is available and technical inefficiency effects are assumed to be time-invariant. Two models-a fixed effects model and a random effects model-are developed and applied to panel data on 17 European railways. We observe significant changes in estimated elasticities and shadow price ratios when regularity restrictions are imposed. (c) 2004 Elsevier B.V. All rights reserved.
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Electricity market price forecast is a changeling yet very important task for electricity market managers and participants. Due to the complexity and uncertainties in the power grid, electricity prices are highly volatile and normally carry with spikes. which may be (ens or even hundreds of times higher than the normal price. Such electricity spikes are very difficult to be predicted. So far. most of the research on electricity price forecast is based on the normal range electricity prices. This paper proposes a data mining based electricity price forecast framework, which can predict the normal price as well as the price spikes. The normal price can be, predicted by a previously proposed wavelet and neural network based forecast model, while the spikes are forecasted based on a data mining approach. This paper focuses on the spike prediction and explores the reasons for price spikes based on the measurement of a proposed composite supply-demand balance index (SDI) and relative demand index (RDI). These indices are able to reflect the relationship among electricity demand, electricity supply and electricity reserve capacity. The proposed model is based on a mining database including market clearing price, trading hour. electricity), demand, electricity supply and reserve. Bayesian classification and similarity searching techniques are used to mine the database to find out the internal relationships between electricity price spikes and these proposed. The mining results are used to form the price spike forecast model. This proposed model is able to generate forecasted price spike, level of spike and associated forecast confidence level. The model is tested with the Queensland electricity market data with promising results. Crown Copyright (C) 2004 Published by Elsevier B.V. All rights reserved.
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Current Physiologically based pharmacokinetic (PBPK) models are inductive. We present an additional, different approach that is based on the synthetic rather than the inductive approach to modeling and simulation. It relies on object-oriented programming A model of the referent system in its experimental context is synthesized by assembling objects that represent components such as molecules, cells, aspects of tissue architecture, catheters, etc. The single pass perfused rat liver has been well described in evaluating hepatic drug pharmacokinetics (PK) and is the system on which we focus. In silico experiments begin with administration of objects representing actual compounds. Data are collected in a manner analogous to that in the referent PK experiments. The synthetic modeling method allows for recognition and representation of discrete event and discrete time processes, as well as heterogeneity in organization, function, and spatial effects. An application is developed for sucrose and antipyrine, administered separately and together PBPK modeling has made extensive progress in characterizing abstracted PK properties but this has also been its limitation. Now, other important questions and possible extensions emerge. How are these PK properties and the observed behaviors generated? The inherent heuristic limitations of traditional models have hindered getting meaningful, detailed answers to such questions. Synthetic models of the type described here are specifically intended to help answer such questions. Analogous to wet-lab experimental models, they retain their applicability even when broken apart into sub-components. Having and applying this new class of models along with traditional PK modeling methods is expected to increase the productivity of pharmaceutical research at all levels that make use of modeling and simulation.
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The paper provides evidence that spatial indexing structures offer faster resolution of Formal Concept Analysis queries than B-Tree/Hash methods. We show that many Formal Concept Analysis operations, computing the contingent and extent sizes as well as listing the matching objects, enjoy improved performance with the use of spatial indexing structures such as the RD-Tree. Speed improvements can vary up to eighty times faster depending on the data and query. The motivation for our study is the application of Formal Concept Analysis to Semantic File Systems. In such applications millions of formal objects must be dealt with. It has been found that spatial indexing also provides an effective indexing technique for more general purpose applications requiring scalability in Formal Concept Analysis systems. The coverage and benchmarking are presented with general applications in mind.
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Essa pesquisa investiga empiricamente o desempenho das empresas do Grande ABC, região industrializada e cada vez mais representativa economicamente para o país. As sete cidades que representam a região, Santo André, São Bernardo do Campo, São Caetano do Sul, Diadema, Mauá, Ribeirão Pires e Rio Grande da Serra, tiverem nos últimos anos um crescimento econômico consideravelmente acima do crescimento do país e seu desenvolvimento tem impulsionado o crescimento do país. A análise empírica utiliza dados em painel e investiga o desempenho das firmas das sete cidades que compõe o Grande ABC durante os anos de 2001 a 2008 utilizando a metodologia multinível e três medidas de desempenho: ROA, OROA e ROE. A metodologia multinível possibilitou a identificação dos principais efeitos que estão associados ou não ao desempenho das empresas, entre esses efeitos estão o ano, a própria empresa, o subsetor, o setor e a cidade que a empresa se localiza. Entre as três medidas de desempenho utilizadas houve significativa convergência e, além disso, o estudo identificou que há um significativo efeito no desempenho das empresas associado ao ano e à própria empresa, além de mostrar que os setores, os subsetores e a cidade que a empresa se localiza não apresentam um efeito significativo associado ao desempenho dessas firmas.
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As várias teorias acerca da estrutura de capital despertam interesse motivando diversos estudos sobre o assunto sem, no entanto, ter um consenso. Outro tema aparentemente pouco explorado refere-se ao ciclo de vida das empresas e como ele pode influenciar a estrutura de capital. Este estudo teve como objetivo verificar quais determinantes possuem maior relevância no endividamento das empresas e se estes determinantes alteram-se dependendo do ciclo de vida da empresa apoiada pelas teorias Trade Off, Pecking Order e Teoria da Agência. Para alcançar o objetivo deste trabalho foi utilizado análise em painel de efeito fixo sendo a amostra composta por empresas brasileiras de capital aberto, com dados secundários disponíveis na Economática® no período de 2005 a 2013, utilizando-se os setores da BM&FBOVESPA. Como resultado principal destaca-se o mesmo comportamento entre a amostra geral, alto e baixo crescimento pelo endividamento contábil para o determinante Lucratividade apresentando uma relação negativa, e para os determinantes Oportunidade de Crescimento e Tamanho, estes com uma relação positiva. Para os grupos de alto e baixo crescimento alguns determinantes apresentaram resultados diferentes, como a singularidade que resultou significância nestes dois grupos, sendo positiva no baixo crescimento e negativa no alto crescimento, para o valor colateral dos ativos e benefício fiscal não dívida apresentaram significância apenas no grupo de baixo crescimento. Para o endividamento a valor de mercado foi observado significância para o Benefício fiscal não dívida e Singularidade. Este resultado reforça o argumento de que o ciclo de vida influência a estrutura de capital
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This paper contrasts the effects of trade, inward FDI and technological development upon the demand for skilled and unskilled workers in the UK. By focussing on industry level data panel data on smaller firms, the paper also contrasts these effects with those generated by large scale domestic investment. The analysis is placed within the broader context of shifts in British industrial policy, which has seen significant shifts from sectoral to horizontal measures and towards stressing the importance of SMEs, clusters and new technology, all delivered at the regional scale. This, however, is contrasted with continued elements of British and EU regional policy which have emphasised the attraction of inward investment in order to alleviate regional unemployment. The results suggest that such policies are not naturally compatible; that while both trade and FDI benefit skilled workers, they have adverse effects on the demand for unskilled labour in the UK. At the very least this suggests the need for a range of policies to tackle various targets (including in this case unemployment and social inclusion) and the need to integrate these into a coherent industrial strategy at various levels of governance, whether regional and/or national. This has important implications for the form of any 'new' industrial policy.
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One of the central explanations of the recent Asian Crisis has been the problem of moral hazard as the source of over-investment and excessive external borrowing. There is however rather limited firm-level empirical evidence to characterise inefficient use of internal and external finances. Using a large firm-level panel data-set from four badly affected Asian countries, this paper compares the rates of return to various internal and external funds among firms with low and high debt financing (relative to equity) among financially constrained and other firms. Selectivity-corrected estimates obtained from random effects panel data model do suggest evidence of significantly lower rates of return to long-term debt, even among firms relying more on debt relative to equity in our sample. There is also evidence that average effective interest rates often significantly exceeded the average returns to long-term debt in the sample countries in the pre-crisis period. © 2006 Elsevier Inc. All rights reserved.