Amplamente relacionado à forma com que os indivíduos valorizam as temáticas humanas, sociais e econômicas, o bem-estar pode ser vislumbrado sob diferentes aspectos, no entanto, todos intimamente atrelados entre si. Uma das formas de se observar o bem-estar é através da dimensão econômica, cujo enfoque é direcionado aos elementos que proporcionam maior nível de comodidade econômica e satisfação individual ou coletiva. Tendo em vista a importância de indicadores para subsidiar a implementação e monitoramento de políticas públicas, assim como disponibilizar informações transparentes à população, a construção de um índice de bem-estar econômico que busque captar a realidade econômica e regional dos estados brasileiros se justifica. Considerando o exposto, o presente estudo teve por objetivo a construção de um Índice de Bem-Estar Econômico (IBEE) para as unidades da federação brasileira, considerando os anos de 2002 e 2008. Especificamente, buscou-se verificar os níveis de bem-estar econômico e de seus sub-componentes nos anos de 2002 e 2008, além de compará-los entre os estados brasileiros. Ademais, fez-se a proposta de analisar comparativamente os resultados do IBEE em relação aos valores apresentados pelo PIB per capita. Por fim, objetivou-se a estimação do Índice de Desenvolvimento Humano (IDH) a partir da substituição da variável renda que o compõe pelos valores obtidos no cômputo do IBEE, de forma a avaliar possíveis diferenças entre o IDH calculado de maneira convencional e o IDH modificado (IDH-M). O índice proposto foi composto por quatro dimensões distintas: Fluxos de Consumo, Riqueza Real Legado Intergeracional, Equidade e Seguridade Econômica. Os principais resultados demonstraram que, independentemente da ponderação utilizada, Santa Catarina foi o estado brasileiro que apresentou o maior bem-estar econômico em relação aos demais. Por outro lado, Alagoas foi o estado com pior desempenho, ocupando a última posição do ranking em todas as análises. A comparação entre o PIB per capita e o IBEE mostrou que, com exceção do Distrito Federal, todos os estados apresentaram o índice de bem-estar superior ao PIB per capita. Além disso, observou-se que o Distrito Federal perde sua vantagem quando considerados outros aspectos relacionados ao bem-estar econômico. Ademais, verificou-se que não há um comportamento regular entre os dois indicadores, ou seja, não é possível afirmar que um estado com elevado PIB por indivíduo necessariamente apresentará altos níveis de bem-estar econômico e vice-versa. A análise do IDH e do IDH-M permitiu observar que todas as unidades da federação apresentaram estimativas do índice modificado inferior ao IDH, sugerindo uma possível superestimação ao ser utilizada a renda per capita para estimação do acesso a recursos econômicos. Desta forma, a partir da necessidade de construção de uma medida sintética de bem-estar econômico, o IBEE apresenta-se como um índice capaz de mensurar de maneira mais adequada os distintos aspectos associados a um padrão de vida decente. / A way to evaluate the well-being of a society is through economic dimensions, which focuses directly on the elements that provide higher level of economic comfort, and individual or collective satisfaction. Given the importance of indicators to support the implementation and monitoring of public policies, as well as to provide clear information to the population, the elaboration of an index of economic well-being that seeks to capture the economic and regional reality of the Brazilian states is justified. The objective of this study is to build an Index of Economic Well-Being (IEWB) for the Brazilian federation units, considering the years 2002 and 2008. Specifically, we determine the levels of economic well-being and their sub-components in the years 2002 and 2008. Furthermore, we analyze comparatively the results of the IEWB in relation to the values presented by Gross Domestic Product (GDP) per capita. Finally, we estimate the Human Development Index (HDI) by substituting its \"income\" variable by the values obtained for the IEWB in order to evaluate possible differences between the standard HDI and the modified HDI (HDI-M). The proposed index was composed of four distinct dimensions: \"Consumption Flows\", \"Real Wealth Intergenerational Legacy\", \"Equity\" and \"Economic Security\". The main results demonstrated that, independently of the weights attributed in the index, Santa Catarina was the Brazilian state that revealed the highest economic well-being in relation to the others. On the other hand, Alagoas was the worst state. The comparison between GDP per capita and IEWB showed that, except for the Federal District, all states presented index of well-being greater than GDP per capita. In addition, it was observed that the Federal District loses its advantages when considering other aspects related to economic well-being. Moreover, it was found that there is not a regular behavior between the two indicators, consequently, it is not possible to assure that a state with a high GDP per capita will necessarily exhibit high levels of economic well-being and vice versa. The analysis of the HDI and the HDI-M allowed to observe that all federation units presented estimates of the modified index lower than the HDI, suggesting a possible overestimation when income per capita is used to evaluate the access to economic resources. Therefore, considering the necessity to construct a synthetic measure to determine the economic well-being, the IEWB demonstrated to be capable to measure more adequately the distinguished aspects associated with a decent standard of living.

Nas últimas décadas, diversos estimadores de estado foram desenvolvidos e aplicados em sistemas elétricos de potência (SEP), dos quais se destaca o baseado no método da mínima mediana. Isso em razão desse, conhecido como estimador por mínima mediana do resíduo ponderado ao quadrado (do inglês, Weighted Least Median of Squares - WLMS), ser capaz de filtrar erros grosseiros (EGs) existentes em medidas redundantes que atraem a convergência do processo de estimação de estado. Essas medidas são chamadas de ponto de alavancamento. Todavia, o estimador WLMS requer um alto custo computacional, tornando-se inviável para aplicação, em tempo real, em SEP de grande porte. De uma forma geral, os motivos desse custo computacional são devido ao estimador WLMS exigir a realização das seguintes tarefas: (i) sorteio, dentre todas as medidas disponíveis, de diversos conjuntos observáveis de medidas com número de medidas igual ao número de variáveis de estado a serem estimadas; (ii) análise da redundância local das medidas disponíveis para cada um dos conjuntos observáveis sorteados; e (iii) execução de vários fluxos de carga. Neste trabalho, propõe-se o desenvolvimento de um estimador de estado estatisticamente robusto, baseado no método da mínima mediana, porém, viável para aplicação em tempo real em SEP de grande porte. Para isso, foram propostas novas metodologias para realização das tarefas supracitadas. A metodologia proposta para realização das tarefas (i) e (ii) faz uso da estrutura da matriz H\'delta\', pois, através dessa matriz, as análises de observabilidade e de redundância de medidas são realizadas de forma simples e direta. Para realizar a tarefa (ii), desenvolveu-se uma metodologia para cálculo de fluxo de carga, tomando por base um método de varredura direta/inversa. Por fim, para aumentar a eficiência computacional em tempo real do estimador proposto, as tarefas a serem executadas pelo mesmo que não dependem de informações, que se tornam disponíveis em tempo real, são realizadas num processo off-line. Como principais resultados deste trabalho, destacam-se: (i) um estimador de estado robusto; e (ii) uma metodologia eficiente para determinação da mínima redundância local de medidas e para sortear os conjuntos observáveis de medidas. / In the last decades several state estimators were developed and applied to power systems. Among these estimators, the one based on the least median method is of interest to us. This because the weighted least median of squares (WLMS) estimator is capable of filtering gross errors corrupting redundant measurements called leverage points. Leverage points are highly influential measurements that attract the state estimations solution towards them. However, some of the WLMS estimator tasks require excessive computing time, making that estimator impracticable to large-scale power systems in real-time environment. The WLMS estimator tasks requiring excessive computing time are: (i) selection, among all available measurements, of several samples with N non-redundant measurements for which the system is observable, where N is the number of system states to be estimated; (ii) determination of the minimum redundancy of the available measurements set; and (iii) the solution of several load flows (one for each selected samples of N measurements). This work proposes a robust state estimator based on the least median method applicable to large-scale power systems in real-time environment. In order to do this, new methodologies were proposed to perform the tasks mentioned above. The proposed methodology to perform tasks (i) and (ii) is based on the analysis of the H\'delta\' matrix structure (this analysis enables both observability and redundancy analysis in a straightforward manner). To perform task (ii), it was developed a load flow methodology based on a forward/backward sweep power flow method. Finally, in order to increase the computational efficiency of the proposed estimator in real-time environment, the tasks that do not depend on real-time information will be conducted by an off-line process. As the main results of this work we could enumerate: (i) a robust state estimator; and (ii) an efficient methodology to determine both the minimum redundancy of the available measurement set and the observable samples with N non-redundant measurements.

Submitted by Sandra Pereira (srpereira@ufrrj.br) on 2016-10-18T10:23:51Z No. of bitstreams: 1 2016 - Catherine Torres de Almeida.pdf: 4011870 bytes, checksum: 95ec0ec572d24a8a7285ec3bb17fac37 (MD5) / Made available in DSpace on 2016-10-18T10:23:51Z (GMT). No. of bitstreams: 1 2016 - Catherine Torres de Almeida.pdf: 4011870 bytes, checksum: 95ec0ec572d24a8a7285ec3bb17fac37 (MD5) Previous issue date: 2016-02-17 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / The Gross Primary Productivity (GPP) is the rate at the atmospheric CO2 is converted by photosynthetic activity in organic substances and is a measure of the total carbon fixed by the ecosystem. In the context of climate change, the focus for the fixation of carbon by forest ecosystems is the basis to mitigate emissions of anthropogenic CO2. There are several methods for the quantification of carbon stored in the vegetation, using data obtained by micrometeorological towers or by remote sensing. Among these methods, stands out the eddy covariance technique, that is much used to quantify the CO2 flux in many forest ecosystems. However, this technique has a high cost, limited operation and covers a small extent. Accordingly, the methods that employ remote sensing have the advantage of providing terrestrial primary productivity estimates for large areas where the methods at the field level are not feasible. This work has as main objective to evaluate the dynamics of the GPP in the Brazilian Legal Amazon over land use and land cover and weather variables. For understanding the relationship of the eddy covariance GPP with meteorological data, rainfall data from TRMM 3B43 product and environmental variables of flux towers were used. Data from TRMM satellite were validated with data from seven conventional weather stations of Amazonas state. The comparison was based on the Average Error (AE), Root Mean Square Error (RMSE), linear correlation coefficient (r) and Wilmott agreement index (d). We also used the Spearman correlation coefficient and a regression tree model to assess the relationship between flux tower GPP and environmental variables. To evaluate GPP estimates from two versions of the MOD17A2 product, derived from MODIS sensor data, these have been validated with surface data from seven LBA flux towers, of which four are in forest cover, one in transition forest and two in disturbed areas. The statistical analyzes were performed with R software, version 3.1.0. The results of the validation of TRMM 3B43 were positive, with high linear correlation (r = 0.83), high level of agreement (d = 0.85) and an adequate RMSE (59.77 mm), showing that this product can be used as an alternative source of quality data. Regarding the influence of the land use and land cover in GPP, it was found that the disturbed areas had lower productivity compared to the conserved areas and had their water balance affected, presenting higher values of the Bowen ratio. The GPP seasonality was predominantly related to radiation at the top of the atmosphere in forest areas of the equatorial Amazon. In areas more distant of the Ecuador, the GPP was influenced by radiation at the top of the atmosphere and also by rainfall and VPD, indicating limitation both by radiation and by water availability. MOD17A2 had no satisfactory agreement between in estimating GPP compared to the method of eddy covariance, underestimating productivity for most locations studied. The seasonality derived from the MODIS algorithm was only similar to the seasonality of GPP by eddy covariance method for non-equatorial locations. The areas in Equatorial Amazon exhibit distinct MOD17A2 GPP seasonal pattern of that verified by data from the micrometeorological towers. Given this, it is necessary to improve the MOD17A2 algorithm to enable it to estimate GPP depending on the different vegetation responses to drought and radiation. This improved understanding may help to produce better estimates of GPP in Amazon and the use of remote sensing in conjunction with the surface data can contribute to generate an overview of GPP in this biome. / A Produtividade Prim?ria Bruta (PPB) ? a taxa na qual o CO2 atmosf?rico ? convertido pela atividade fotossint?tica em subst?ncias org?nicas e ? uma medida do total de carbono fixado pelo ecossistema. No contexto das mudan?as clim?ticas, o enfoque para a fixa??o de carbono pelos ecossistemas florestais ? a base para mitigar as emiss?es de CO2 antropog?nico. Existem diversos m?todos destinados ? quantifica??o do carbono estocado na vegeta??o, que utilizam dados obtidos por meio de torres micrometeorol?gicas de fluxo ou atrav?s de sensoriamento remoto. Dentre esses m?todos, se destaca a t?cnica de covari?ncia de v?rtices turbulentos, por ser muito empregada para quantificar o fluxo de CO2 em diversos ecossistemas florestais. Por?m, esta t?cnica possui um custo alto, operacionalidade restrita e abrange uma pequena extens?o. Nesse sentido, os m?todos que empregam o sensoriamento remoto t?m a vantagem de fornecer estimativas de produtividade prim?ria terrestre para grandes ?reas, onde os m?todos ao n?vel do terreno n?o s?o vi?veis. Este trabalho tem como objetivo geral avaliar a din?mica da PPB na Amaz?nia Legal brasileira em rela??o ao uso e cobertura do solo e ?s vari?veis meteorol?gicas. Para compreender a rela??o da PPB obtida pelo m?todo de covari?ncia de v?rtices turbulentos com dados meteorol?gicos, foram utilizados dados de chuva do produto 3B43 do sat?lite TRMM e vari?veis ambientais das torres de fluxo. Os dados do sat?lite TRMM foram validados com dados de sete esta??es meteorol?gicas convencionais do estado do Amazonas. A compara??o foi baseada no Erro M?dio (EM), Raiz do Erro M?dio Quadr?tico (REMQ), coeficiente de correla??o linear (r) e ?ndice de concord?ncia de Wilmott (d). Tamb?m utilizou-se o coeficiente de correla??o de Spearman e um modelo de ?rvore de regress?o para avaliar a rela??o entre a PPB da torre de fluxo e as vari?veis ambientais. Para avaliar as estimativas de PPB de duas vers?es do produto MOD17A2, derivadas de dados do sensor MODIS, estas foram validadas com dados de superf?cie de sete torres de fluxo do Projeto LBA, das quais quatro se encontram em cobertura florestal, uma em floresta de transi??o e duas em ?reas antropizadas. As an?lises estat?sticas foram realizadas no software R, vers?o 3.1.0. Os resultados da valida??o do produto 3B43 do TRMM foram positivos, com alta correla??o linear (r = 0,83), alto ?ndice de concord?ncia (d = 0,85) e REMQ satisfat?rio (59,77 mm), mostrando que este produto pode ser utilizado como uma fonte alternativa de dados de qualidade. Em rela??o ? influ?ncia do uso e da cobertura do solo na PPB, verificou-se que as ?reas antropizadas apresentaram menor produtividade em rela??o ?s ?reas conservadas e tiveram seu balan?o h?drico afetado, pois apresentaram altos valores da raz?o de Bowen. A sazonalidade da PPB foi predominantemente relacionada ? radia??o no topo da atmosfera nas ?reas de floresta da Amaz?nia equatorial. Nas ?reas mais distantes do Equador, a PPB foi influenciada pela radia??o no topo da atmosfera e tamb?m pela chuva e VPD, indicando limita??o tanto pela radia??o quanto pela disponibilidade de ?gua. O MOD17A2 n?o apresentou boa estimativa de PPB comparado ao m?todo de v?rtices turbulentos, subestimando a produtividade para a maioria das localidades estudadas. A sazonalidade da PPB deste algoritmo somente foi similar ? sazonalidade da PPB pelo m?todo de v?rtices turbulentos para as localidades n?o-equatoriais. As ?reas na Amaz?nia Equatorial apresentaram padr?o sazonal da PPB do MOD17A2 distinto do verificado pelos dados das torres micrometeorol?gicas. Diante disto, ? necess?rio melhorar o algoritmo MOD17A2 para que este possa estimar PPB em fun??o das diferentes respostas da vegeta??o ? seca e ? radia??o. Esse melhor entendimento poder? contribuir para produzir melhores estimativas da PPB para a Amaz?nia e o uso do sensoriamento remoto em conjunto com os dados de superf?cie pode contribuir para gerar uma vis?o geral da PPB nesse bioma.

The dissertation focuses on the incentives and economic effects of gross receipts taxes (GRTs) versus corporate income taxes (CITs). Conventional wisdom holds that GRTs are very poor tax instruments; however, several states have shown renewed interest in GRTs since 2002. An interesting question to ask is why states are reconsidering GRTs in spite of all criticisms. Are GRTs really as bad as what conventional wisdom says? There is little rigorous theoretical or empirical work on GRTs. My dissertation aims to help fill this gap by providing both theoretical and empirical analysis on the comparative advantages and disadvantages of GRTs versus CITs. Essay one provides the first systematic theoretical analysis to compare and contrast the incentives and economic effects of gross receipts taxes versus corporate income taxes. Specifically, it focuses on the incentives for vertical integration in the sense of make-or-buy decisions, the effects on profit shifting between out-of-state and in-state firms, the incentives to change organizational form for tax purposes, and the incentives for cost-saving innovation under each tax system. Several results contradict conventional wisdom and deepen our understanding of GRTs. Based on Essay one, Essay two empirically tests the theoretical prediction that GRTs eliminate the distortion on organizational form choice, increasing the chance for a firm to incorporate. The analysis uses state-industry panel data from Nonemployer Statistics during the period 2002- 2008. The results show that states with a GRT have a higher share of corporate firms. Further, by replacing the CIT with a GRT, states may promote the real activity of C corporations.

The main objective of this research paper is to find the association between unemployment rate and GDP growth which is presented empirically by Arthur Okun’s in early 1960s. For this purpose I have used annual time series data during the period 1981-2005 of Pakistan. I applied difference version of Okun’s law which is more appropriate to access results directly from empirical data. In order to find long run relation between the variables I used Engle-Granger cointegration technique and Error Correction Mechanism (ECM) to find the short term behavior of GDP growth to its long run value. This paper verifies negative relationship between unemployment rate and GDP growth and both variables have long run relation with each other. Moreover GDP growth will adjust more quickly towards equilibrium in the long run.

In this work, a novel method is proposed to optimize the array geometry for DOA estimation. The method is based on minimization of fine error variances with the constraint that the gross error probability is below a certain threshold. For this purpose, a metric function that reflects the gross and fine error characteristics of the array is offered. Theoretical analyses show that the minimization of this metric function leads to small DOA estimation error variance and small gross error probability. Analyses have been carried out under the assumptions of planar array geometry, isotropic array elements and AWGN. Genetic algorithm is used as an optimization tool and performance simulation is performed by comparing the DOA estimation errors of optimized array to a uniform circular array (UCA). Computer simulations support the theoretical analyses and show that the method proposed leads to significant improvement in array geometry in terms of DOA estimation performance.

Thèse : Lettres : Göteborg : 1983. / Texte remanié de : Diss. : Sprachwissenschaft : Göteborg : 1983. - Bibliogr. p. 163. Résumé en anglais. -

Recent studies of the environmental Kuznets curve raise questions regarding the relationship between environmental indicators and GDP and the fundamental reasons that explain this relationship. In response, this thesis presents one-sector and two-sector models to analyze the alternative causal relationships between an environmental indicator and GDP at different stages of economic development. These models analyze how economic scale, technology, preferences, and economic structure influence the causality and shape of the relationship. These theoretical studies are followed by two empirical studies. The first tests the causal relationship between CO2 emissions and GDP in Canadian manufacturing industries. The second explores several factors as the fundamental causes that influence the CO2 emissions in the same industries. Factors, such as economic scale, preferences, technological progress, structural change, and energy input, are found to be crucial in the determination of CO2 emissions. The empirical results are positive, but there are data limitations. The empirical studies can be re-evaluated as more data becomes available.

The economic crisis of 2007 has had debilitating effects on the global economy, affecting GDP growth, unemployment and trade to name a few. In response to these economic effects, numerous policy interventions were implemented. There are various existing time-series methods available to determine better estimates of GDP growth rates, one of which is Stein’s Paradox which uses observed averages to estimate unobservable quantities which are closer to the true unknown GDP growth rates or theta (θ) in order to determine better growth rates post the economic crisis. The resulting James-Stein estimator (z) is said to be better than the arithmetic average, and thus a closer approximation to the true GDP growth rates which are unobservable. This dissertation analyses the effects of the 2008 financial crisis on the global economy, with specific reference to South Africa and America, and their corresponding policy interventions to determine the growth trajectory after the crisis. The main objective is to determine if better estimates of GDP growth can be calculated using Stein’s Paradox, across a sample of 30 countries, using quarterly GDP growth for the period 2005 to 2008. Annual GDP data was also used for the period 2009-2011, and future GDP growth rates were forecasted for the period 2012 to 2016. To reinforce the Stein’s Paradox, the Monte Carlo study is undertaken. It is used to determine how the James-Stein estimates perform under different conditions using a common c or unique c, and to determine which condition will provide more accurate GDP growth rates (Muthen. 2002). Analysis of time series data across a sample of 30 countries using Stein’s Paradox provided better estimates of GDP growth rates than the individual average growth rates for each country based on the lower standard deviation and total squared error of estimation achieved. This shows that the results are closer to theta and have a smaller amount of error, particularly when a common c was used. The Monte Carlo results indicate that better GDP growth rates are achieved when using a common c instead of a unique c given that a smaller standard deviation and variance is derived. Therefore the Monte Carlo study aims to reinforce or verify Stein’s Paradox. The study also indicates that emerging and developing countries seem to be the driving forces of growth in the future, while developed countries seem to be lagging behind. / Thesis (M.Com.)-University of KwaZulu-Natal, Pietermaritzburg, 2013.

Based on an individual longitudinal data on dependent employment we analyse the role of Creative Industries for the employment system of Vienna. We focus on gross job flows and firm dynamics in this priority field of Vienna's urban policy and analyse the characteristics of the different parts of the cluster's production system. We find ample evidence for positive effects of Creative Industries on employment growth and firm birth, but also reveal considerable job turnover and a large heterogeneity of firm growth in the cluster. Especially, we find rather different evolutions along the clusters value chain, which points to weak linkages between upstream and downstream activities in the cluster. (author's abstract) / Series: Creative Industries in Vienna: Development, Dynamics and Potentials