On December 26th, 2004, 280,000 people lost their lives. A massive earthquake struck Indonesia, triggering a tsunami that affected several countries, including Thailand. The disaster had important implications for health status of Thai citizens, as well as health system planning, and thus underscores the need to study its long-term effect. This dissertation examined the patterns, determinants, and spatial analysis of health service utilization following the tsunami in Thailand. The primary aim was to determine whether tsunami-affected status (personal injury or property loss) and distance to a health facility (public health center or hospital) influenced health service utilization. The study population included Thai citizens (aged 14+), living in the tsunami-affected Thai provinces: Phuket, Phang Nga, Krabi, and Ranong. Study participants were randomly selected from the ‘affected’ and ‘unaffected’ populations. One and two years after the tsunami, participants were interviewed in-person on demographic and socio-economic factors, disaster impact, health status, and health service utilization. Five types of health services were examined: outpatient services, inpatient services, home visits, medications, and informal (unpaid) care. Distance to a health facility was calculated using Geographic Information System’s Network Analyst. The Grossman model of the demand for health care and a distance decay concept provided the foundation for this study. A propensity score method and a two-part model were used to examine the study objectives. There were 1,889 participants. One year after the tsunami, individuals affected by property loss were more likely to use medications than unaffected participants. Two years after the tsunami, individuals with personal injury were more likely to use outpatient services, medications, and informal care than unaffected participants. Distance to a health facility was associated with the use of medications and informal care. The results confirmed the long-term effect of a tsunami. This dissertation may assist the decision- and policy-makers in the identification of those most likely to use health services and in the request of health resources to the affected areas. The patterns, determinants, and spatial analysis of health service utilization found in this study may not be specific to a tsunami and may provide insights on post-disaster contexts of other natural disasters.

On December 26th, 2004, 280,000 people lost their lives. A massive earthquake struck Indonesia, triggering a tsunami that affected several countries, including Thailand. The disaster had important implications for health status of Thai citizens, as well as health system planning, and thus underscores the need to study its long-term effect. This dissertation examined the patterns, determinants, and spatial analysis of health service utilization following the tsunami in Thailand. The primary aim was to determine whether tsunami-affected status (personal injury or property loss) and distance to a health facility (public health center or hospital) influenced health service utilization. The study population included Thai citizens (aged 14+), living in the tsunami-affected Thai provinces: Phuket, Phang Nga, Krabi, and Ranong. Study participants were randomly selected from the ‘affected’ and ‘unaffected’ populations. One and two years after the tsunami, participants were interviewed in-person on demographic and socio-economic factors, disaster impact, health status, and health service utilization. Five types of health services were examined: outpatient services, inpatient services, home visits, medications, and informal (unpaid) care. Distance to a health facility was calculated using Geographic Information System’s Network Analyst. The Grossman model of the demand for health care and a distance decay concept provided the foundation for this study. A propensity score method and a two-part model were used to examine the study objectives. There were 1,889 participants. One year after the tsunami, individuals affected by property loss were more likely to use medications than unaffected participants. Two years after the tsunami, individuals with personal injury were more likely to use outpatient services, medications, and informal care than unaffected participants. Distance to a health facility was associated with the use of medications and informal care. The results confirmed the long-term effect of a tsunami. This dissertation may assist the decision- and policy-makers in the identification of those most likely to use health services and in the request of health resources to the affected areas. The patterns, determinants, and spatial analysis of health service utilization found in this study may not be specific to a tsunami and may provide insights on post-disaster contexts of other natural disasters.

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Esta tese visa propor extensões dos modelos de regressão quantílica bayesianos, considerando dados de proporção com inflação de zeros, e também dados censurados no zero. Inicialmente, é sugerida uma análise de observações influentes, a partir da representação por mistura localização-escala da distribuição Laplace assimétrica, em que as distribuições a posteriori das variáveis latentes são comparadas com o intuito de identificar possíveis observações aberrantes. Em seguida, é proposto um modelo de duas partes para analisar dados de proporção com inflação de zeros ou uns, estudando os quantis condicionais e a probabilidade da variável resposta ser igual a zero. Além disso, são propostos modelos de regressão quantílica bayesiana para dados contínuos com um componente discreto no zero, em que parte dessas observações é suposta censurada. Esses modelos podem ser considerados mais completos na análise desse tipo de dados, uma vez que a probabilidade de censura é verificada para cada quantil de interesse. E por último, é considerada uma aplicação desses modelos com correlação espacial, para estudar os dados da eleição presidencial no Brasil em 2014. Nesse caso, os modelos de regressão quantílica são capazes de incorporar essa informação espacial a partir do processo Laplace assimétrico. Para todos os modelos propostos foi desenvolvido um pacote do software R, que está exemplificado no apêndice. / This thesis aims to propose extensions of Bayesian quantile regression models, considering proportion data with zero inflation, and also censored data at zero. Initially, it is suggested an analysis of influential observations, based on the location-scale mixture representation of the asymmetric Laplace distribution, where the posterior distribution of the latent variables are compared with the goal of identifying possible outlying observations. Next, a two-part model is proposed to analyze proportion data with zero or one inflation, studying the conditional quantile and the probability of the response variable being equal to zero. Following, Bayesian quantile regression models are proposed for continuous data with a discrete component at zero, where part of these observations are assumed censored. These models may be considered more complete in the analysis of this type of data, as the censoring probability varies with the quantiles of interest. For last, it is considered an application of these models with spacial correlation, in order to study the data about the last presidential election in Brazil in 2014. In this example, the quantile regression models are able to incorporate spatial dependence with the asymmetric Laplace process. For all the proposed models it was developed a R package, which is exemplified in the appendix.

DYNAMIC MODELING, GUIDANCE, AND CONTROL OF HOMING MISSILES &Ouml / ZKAN, B&uuml / lent Ph. D., Department of Mechanical Engineering Supervisor: Prof. Dr. M. Kemal &Ouml / ZG&Ouml / REN Co-Supervisor: Dr. G&ouml / kmen MAHMUTYAZICIOgLU September 2005, 236 pages In this study, the dynamic modeling, guidance, and control of a missile with two relatively rotating parts are dealt with. The two parts of the missile are connected to each other by means of a roller bearing. In the first part of the study, the governing differential equations of motion of the mentioned missile are derived. Then, regarding the relative rotation between the bodies, the aerodynamic model of the missile is constructed by means of the Missile Datcom software available in T&Uuml / BiTAK-SAGE. After obtaining the required aerodynamic stability derivatives using the generated aerodynamic data, the necessary transfer functions are determined based on the equations of motion of the missile. Next, the guidance laws that are considered in this study are formulated. Here, the Linear Homing Guidance and the Parabolic Homing Guidance laws are introduced as alternatives to the Proportional Navigation Guidance law. On this occasion, the spatial derivation of the Proportional Navigation Guidance law is also done. Afterwards, the roll, pitch and yaw autopilots are designed using the determined transfer functions. As the roll autopilot is constructed to regulate the roll angle of the front body of the missile which is the controlled part, the pitch and yaw autopilots are designed to realize the command signals generated by the guidance laws. The guidance commands are in the form of either the lateral acceleration components or the flight path angles of the missile. Then, the target kinematics is modeled for a typical surface target. As a complementary part of the work, the design of a target state estimator is made as a first order fading memory filter. Finally, the entire guidance and control system is built by integrating all the models mentioned above. Using the entire system model, the computer simulations are carried out using the Matlab-Simulink software and the proposed guidance laws are compared with the Proportional Navigation Guidance law. The comparison is repeated for a selected single-body missile as well. Consequently, the simulation results are discussed and the study is evaluated.

Esta tese visa propor extensões dos modelos de regressão quantílica bayesianos, considerando dados de proporção com inflação de zeros, e também dados censurados no zero. Inicialmente, é sugerida uma análise de observações influentes, a partir da representação por mistura localização-escala da distribuição Laplace assimétrica, em que as distribuições a posteriori das variáveis latentes são comparadas com o intuito de identificar possíveis observações aberrantes. Em seguida, é proposto um modelo de duas partes para analisar dados de proporção com inflação de zeros ou uns, estudando os quantis condicionais e a probabilidade da variável resposta ser igual a zero. Além disso, são propostos modelos de regressão quantílica bayesiana para dados contínuos com um componente discreto no zero, em que parte dessas observações é suposta censurada. Esses modelos podem ser considerados mais completos na análise desse tipo de dados, uma vez que a probabilidade de censura é verificada para cada quantil de interesse. E por último, é considerada uma aplicação desses modelos com correlação espacial, para estudar os dados da eleição presidencial no Brasil em 2014. Nesse caso, os modelos de regressão quantílica são capazes de incorporar essa informação espacial a partir do processo Laplace assimétrico. Para todos os modelos propostos foi desenvolvido um pacote do software R, que está exemplificado no apêndice. / This thesis aims to propose extensions of Bayesian quantile regression models, considering proportion data with zero inflation, and also censored data at zero. Initially, it is suggested an analysis of influential observations, based on the location-scale mixture representation of the asymmetric Laplace distribution, where the posterior distribution of the latent variables are compared with the goal of identifying possible outlying observations. Next, a two-part model is proposed to analyze proportion data with zero or one inflation, studying the conditional quantile and the probability of the response variable being equal to zero. Following, Bayesian quantile regression models are proposed for continuous data with a discrete component at zero, where part of these observations are assumed censored. These models may be considered more complete in the analysis of this type of data, as the censoring probability varies with the quantiles of interest. For last, it is considered an application of these models with spacial correlation, in order to study the data about the last presidential election in Brazil in 2014. In this example, the quantile regression models are able to incorporate spatial dependence with the asymmetric Laplace process. For all the proposed models it was developed a R package, which is exemplified in the appendix.

Indiana University-Purdue University Indianapolis (IUPUI) / Accurate estimation of alcohol price elasticity is important for policy analysis – e.g.., determining optimal taxes and projecting revenues generated from proposed tax changes. Several approaches to specifying and estimating the price elasticity of demand for alcohol can be found in the literature. There are two keys to policy-relevant specification and estimation of alcohol price elasticity. First, the underlying demand model should take account of alcohol consumption decisions at the extensive margin – i.e., individuals' decisions to drink or not – because the price of alcohol may impact the drinking initiation decision and one's decision to drink is likely to be structurally different from how much they drink if they decide to do so (the intensive margin). Secondly, the modeling of alcohol demand elasticity should yield both theoretical and empirical results that are causally interpretable. The elasticity estimates obtained from the existing two-part model takes into account the extensive margin, but are not causally interpretable. The elasticity estimates obtained using aggregate-level models, however, are causally interpretable, but do not explicitly take into account the extensive margin. There currently exists no specification and estimation method for alcohol price elasticity that both accommodates the extensive margin and is causally interpretable. I explore additional sources of bias in the extant approaches to elasticity specification and estimation: 1) the use of logged (vs. nominal) alcohol prices; and 2) implementation of unnecessarily restrictive assumptions underlying the conventional two-part model. I propose a new approach to elasticity specification and estimation that covers the two key requirements for policy relevance and remedies all such biases. I find evidence of substantial divergence between the new and extant methods using both simulated and the real data. Such differences are profound when placed in the context of alcohol tax revenue generation.

This research highlights the importance of considering the degree students’ integration into school classes when estimating school effects. Combining and using two different datasets collected before and after education reform in Taiwan, the study compares school effects under two different education systems in order to answer the question about the efficiency of education reform. I estimate multilevel growth models to assess how school environments affect changes in students’ initial and change rate of their academic performance across junior high school years. Besides, two-part random-effects models are also introduced into the analyses to testify how school environment influence adolescent performance in their high school enrollments. My results support and extend Blau’s structural theory, revealed that school contexts and school networks directly and indirectly influences students’ performance in their school classes and in their high school enrollments, suggesting students’ outcome are conditioning by the local structure, the school environments. However, through making more friends inside and outside school classes, students still have their own power to modify the environmental impacts on themselves. With respect to the comparisons of school effects on individuals’ performance under two different education systems in Taiwan, the decreasing peer influences and the decreasing significance of school networks indicate that the school effects gradually decline after the administration of education reform. One should note that simply a little change on education system might alter students, parents, and teachers’ behaviors. The decreasing peer effects and the decreasing school effects on students’ academic performance suggesting that students might change their behaviors on interacting with their friends and change their behaviors at schools in order to jostle higher education after education reform. The increasing cram schooling and the increasing significance of family SES support the inference that students modify their behaviors to come up against the education reform in Taiwan. These findings suggest the need for more panel datasets collected from the newly cohorts after education reform was administrated for a period and the need for more studies of education reform and school effects, to have more understanding about the mechanisms of school efficiency.

Submitted by Hugo de Andrade Lucatelli (h.lucatelli@hotmail.com) on 2017-06-10T00:54:14Z No. of bitstreams: 1 Tese_Hugo Lucatelli.pdf: 1969280 bytes, checksum: 7eca95ab0a82921b3b59ee3d58c073e0 (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2017-06-12T12:08:05Z (GMT) No. of bitstreams: 1 Tese_Hugo Lucatelli.pdf: 1969280 bytes, checksum: 7eca95ab0a82921b3b59ee3d58c073e0 (MD5) / Made available in DSpace on 2017-06-12T13:04:48Z (GMT). No. of bitstreams: 1 Tese_Hugo Lucatelli.pdf: 1969280 bytes, checksum: 7eca95ab0a82921b3b59ee3d58c073e0 (MD5) Previous issue date: 2017-05-23 / Paper I – The paper shows that in bundle markets, when a monopolist faces sizeable constraints on supply capacity, implementing a two-part tariff is the optimal strategy for the firm. This contractual design allows the firm setting the consumers’ consumption level at the firm’s desired point. In this scenario, it is expected the final tariff of the contract to be smaller than it would be in a fixed tariff contract, what lead to the entrance of more consumers in the market. This equilibrium improves the welfare of producers and consumers. Paper II – The aim of this work is to study the optimal pricing strategy of a firm that introduces a new product and competes by quality and price in a market. In this environment, prices are not only able to signal quality, but can also change the quality perceived by the consumers. This work analyzes the problem in a theoretical dimension in an environment where firms are aware of their ability to change the consumers experience with its pricing policy. The paper analyzes the model fit to the empirical literature. Paper III – The third essay of this thesis empirically analyzes the relationship between perceived quality and the elements which form the consumers’ satisfaction: prices, market competition and product/service intrinsic quality. Using Brazilian data on mobile telecommunications, this study estimated these relationships. We found a robust connection between prices and satisfaction, endorsing the results found to others markets by the literature. As was expected, competition also seems to promote better services supply, what translates into better consumers’ evaluations. Finally, services with better operational quality appear to have substantial better consumers' rating. These results are especially important for markets where consumers evaluate the whole experience of consuming the service, as we verified in the robustness test. The analysis also found some evidence of the existence of important infrastructure bottlenecks in the sector. In an environment where the telecommunication services tend to converge, with high probability of demand growth, network sizing problems could become relevant. / Ensaio I – O ensaio mostra que em mercados de pacotes, quando um monopolista enfrenta significativas restrições de capacidade de oferta, implementar contratos compostos por tarifas de duas partes é a estratégia ótima para a firma. Este desenho contratual permite a firma posicionar o nível de consumo dos consumidores no nível ótimo desejado. Neste cenário, espera-se que a tarifa final do contrato seja inferior à tarifa exercida em um contrato composto por uma tarifa fixa, o que implica na entrada de mais consumidores no mercado. Este equilíbrio melhora o bem-estar da firma e dos consumidores, de forma agregada. À luz do modelo apresentado, o trabalho discute o uso de franquias de consumo em contratos de provisão de internet fixa no Brasil. Ensaio II – O ensaio tem como objetivo estudar a estratégia ótima de preços de uma firma que introduz um produto novo em determinado mercado consumidor e compete em preços e qualidade em um ambiente onde os preços, não apenas sinalizam a qualidade do bem, mas também têm a possibilidade de alterar a percepção sensorial e a classificação de qualidade dos consumidores. Busca-se avaliar o problema em sua dimensão teórica, ao estudar o comportamento das firmas em um ambiente em que são conscientes quanto a sua capacidade de alterar a experiência dos consumidores e a sua reputação de mercado com a sua política de preços. O artigo avalia o ajuste do modelo a literatura empírica. Ensaio III – O terceiro ensaio da tese estuda, empiricamente, a relação entre qualidade percebida e os elementos formadores da satisfação do consumidor: preços, competição de mercado e qualidade intrínseca do produto ou serviço. Utilizando dados do mercado de telefonia móvel do Brasil, o trabalho estimou estas relações. Encontramos uma robusta associação entre preços e satisfação, em linha com os resultados estabelecidos pela literatura para outros mercados. Competição, como esperado, também parece promover a oferta de melhores serviços, o que se traduz em melhores avaliações dos consumidores. Por fim, serviços ofertados com melhor qualidade operacional apresentam sensíveis melhores notas dos usuários. Estes resultados são especialmente importantes em um mercado onde os consumidores avaliam toda a experiência de consumo com o serviço, conforme foi verificado no exercício de robustez deste artigo. O trabalho também encontrou evidências de que existem gargalos de infraestrutura importantes no setor. Em um ambiente onde há tendência de convergência de serviços de telecomunicações, com indicativo de crescente demanda, problemas de dimensionamento de rede podem se tornar relevantes.

<p>The internal and external challenges construction companies face such as variability, low productivity, inefficient processes, waste, uncertainties, risks, fragmentation, adversarial contractual relationships, competition, and those resulting from internal and external challenges such as cost overruns and delays negatively affect company performance and profitability. Though research publications abound, these challenges persist, which indicates that the following gaps exist. Lean construction, process improvement, and performance improvement research have been conducted wherein improvement principles, and best practices are used to ameliorate performance issues, but several knowledge gaps exist. Few companies use these improvement principles and best practices. For those companies applying improvements, there is no established link between these improvements and performance/profitability to guide companies. Further, even when companies use improvement principles and best practices, they apply only one or two, whereas an integrated application of these improvement principles and best practices would be more effective. The other gap the author identified is the lack of strategic tools that construction companies can use to improve and manage their profitability. This thesis tried to fill the knowledge gap, at least partially, by developing a two-part excellence model for profitability improvement of construction companies. The excellence model lays out strategies that would enable companies to overcome the challenges and improve their profitability. The excellence model also gives an iterative and recursive continuous improvement model and flowchart to improve the profitability of construction companies. The researcher used high impact principles, guidelines, and concepts from the literature on organizational effectiveness, critical success factors, strategic company profitability growth enablers, process improvement, and process maturity models, performance improvement, and organizational excellence guidelines to develop the two-part excellence model.</p> <p>The author also translated the two-part excellence model into the diagnostic tool and Decision Support System (DSS) by use of process diagrams, fishbone diagrams, root cause analysis, and use of improvement principles, countermeasures and best practices at the most granular (lowest intervention) levels to do away with root causes of poor performance. The author developed the diagnostic tool and Decision Support System (DSS) in Access 2016 to serve as a strategic tool to improve and manage the profitability of construction companies. The researcher used improvement principles, and best practices from scientific and practitioner literature to develop company and project process flow diagrams, and fishbone (cause and effect) diagrams for company, department, employee, interactions and project performance for the profitability improvement, which are the engines of the diagnostic tool and DSS. The diagnostic tool and DSS use continuous improvement cycles iteratively and recursively to improve the profitability of construction companies from the current net profit of 2-3 percent to a higher value.</p>