The dissertation identifies and responds to two gaps in the current literature on the elasticity of taxable income (ETI). Firstly, there is a lack of a deep understanding of the process underlying behavioral responses of taxable income to taxation. Secondly, there is a lack of inquiry into the functional form of the ETI. This dissertation seeks to fill these gaps in the ETI literature. It constructs a theoretical framework for behavioral responses of taxable income to taxation, based on a review of the literature on taxpayer compliance behavior. The dissertation also introduces a new approach to estimating the ETI. This study is the first attempt to fill in the gap of the ETI for a lack of studying the functional form of the ETI and factors determining the ETI function. Using the functional form derived from the Allingham-Sandmo model and empirical data on the function's arguments in the years 1979, 1982, 1985, and 1988, the dissertation studies behavior of the declared income elasticity function. / Ph. D.

In this thesis, two methods for assessing the functional form of covariates in the Cox proportional hazards model are evaluated. The methods include one graphical check based on martingale residuals and one graphical check, together with a Kolmogorov-type supremum test, based on cumulative sums of martingale residuals. The methods are evaluated in a simulation study under five different covariate misspecifications with varying sample sizes and censoring degrees. The results from both methods indicate that the type of covariate misspecification, sample size and censoring degree affect the ability to detect and identify the misspecification. The procedure based on smoothed scatterplots of martingale residuals reveals difficulties with assessing whether the behaviour of the smoothed curve in the plot is an indication of a misspecification or a phenomenon that can occur in a correctly specified model. The graphical check together with the test procedure based on cumulative sums of martingale residuals is shown to successfully detect and identify three out of five covariate misspecifications for large sample sizes. For small sample sizes, especially combined with a high censoring degree, the power of the supremum test is low for all covariate misspecifications.

Today a standard procedure to analyze the impact of environmental factors on productive efficiency of a decision making unit is to use a two stage approach, where first one estimates the efficiency and then uses regression techniques to explain the variation of efficiency between different units. It is argued that the abovementioned method may produce doubtful results which may distort the truth data represents. In order to introduce economic intuition and to mitigate the problem of omitted variables we introduce the matching procedure which is to be used before the efficiency analysis. We believe that by having comparable decision making units we implicitly control for the environmental factors at the same time cleaning the sample of outliers. The main goal of the first part of the thesis is to compare a procedure including matching prior to efficiency analysis with straightforward two stage procedure without matching as well as an alternative of conditional efficiency frontier. We conduct our study using a Monte Carlo study with different model specifications and despite the reduced sample which may create some complications in the computational stage we strongly agree with a notion of economic meaningfulness of the newly obtained results. We also compare the results obtained by the new method with ones previously produced by Demchuk and Zelenyuk (2009) who compare efficiencies of Ukrainian regions and find some differences between the two approaches. Second part deals with an empirical study of electricity generating power plants before and after market reform in Texas. We compare private, public and municipal power generators using the method introduced in part one. We find that municipal power plants operate mostly inefficiently, while private and public are very close in their production patterns. The new method allows us to compare decision making units from different groups, which may have different objective schemes and productive incentives. Despite the fact that at a certain point after the reform private generators opted not to provide their data to the regulator we were able to construct tree different data samples comprising two and three groups of generators and analyze their production/efficiency patterns. In the third chapter we propose a semiparametric approach with shape constrains which is consistent with monotonicity and concavity constraints. Penalized splines are used to maintain the shape constrained via nonlinear transformations of spline basis expansions. The large sample properties, an effective algorithm and method of smoothing parameter selection are presented in the paper. Monte Carlo simulations and empirical examples demonstrate the finite sample performance and the usefulness of the proposed method.

Orientador: Luzia Aparecida Trinca / Resumo: A classe dos modelos de regressão incorporando polinômios fracionários - FPs (Fractional Polynomials), proposta por Royston & Altman (1994), tem sido amplamente estudada. O uso de FPs em modelos mistos constitui uma alternativa muito atrativa para explicar a dependência das medidas intra-unidades amostrais em modelos em que há não linearidade na relação entre a variável resposta e variáveis regressoras contínua. Tal característica ocorre devido aos FPs oferecerem, para a resposta média, uma variedade de formas funcionais não lineares para as variáveis regressoras contínuas, em que se destacam a família dos polinômios convencionais e algumas curvas assimétricas e com assíntotas. A incorporação dos FPs na estrutura dos modelos mistos tem sido investigada por diversos autores. Porém, não existem publicações sobre: a exploração da problemática da modelagem na parte fixa e na parte aleatória (principalmente na presença de várias variáveis regressoras contínuas e categóricas); o estudo da influência dos FPs na estrutura dos efeitos aleatórios; a investigação de uma adequada estrutura para a matriz de covariâncias do erro; ou, um ponto de fundamental importância para colaborar com a seleção do modelo, a realização da análise de diagnóstico dos modelos ajustados. Uma contribuição, do nosso ponto de vista, de grande relevância é a investigação e oferecimento de estratégias de ajuste dos modelos polinômios fracionários com efeitos mistos englobando os pontos citados acima com o objetiv... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The class of regression models incorporating Fractional Polynomials (FPs), proposed by Royston & Altman (1994), has been extensively studied. The use of FPs in mixed models is a very attractive alternative to explain the within-subjects’ measurements dependence in models where there is non-linearity in the relationship between the response variable and continuous covariates. This characteristic occurs because the FPs offers a variety of non-linear functional forms for the continuous covariates in the average response, in which the family of the conventional polynomials and some asymmetric curves with asymptotes stand out. The incorporation of FPs into the structure of the mixed models has been investigated by several authors. However, there are no works about the following issues: the modeling of the fixed and random effects (mainly in the presence of several continuous and categorical covariates), the study of the influence of the FPs on the structure of the random effects, the investigation of an adequate structure for the covariance of the random errors, or, a point that has central importance to the selection of the model, to perform a diagnostic analysis of the fitted models. In our point of view, a contribution of great relevance is the investigation and the proposition of strategies for fitting FPs with mixed effects encompassing the points mentioned above, with the goals of filling these gaps and to awaken the users to the great potential of mixed models, now even mor... (Complete abstract click electronic access below) / Doutor

This dissertation consists of three projects in matched case-control studies. In the first project, we employ a general bias preventive approach developed by Firth (1993) to handle the bias of an estimator of the log-odds ratio parameter in conditional logistic regression by solving a modified score equation. The resultant estimator not only reduces bias but also can prevent producing infinite value. Furthermore, we propose a method to calculate the standard error of the resultant estimator. A closed form expression for the estimator of the log-odds ratio parameter is derived in the case of a dichotomous exposure variable. Finite sample properties of the estimator are investigated via a simulation study. Finally, we apply the method to analyze a matched case-control data from a low-birth-weight study. In the second project of this dissertation, we propose a score typed test for checking adequacy of a functional form of a covariate of interest in matched case-control studies by using penalized regression splines to approximate an unknown function. The asymptotic distribution of the test statistics under the null model is a linear combination of several chi-square random variables. We also derive the asymptotic distribution of the test statistic when the alternative model holds. Through a simulation study we assess and compare the finite sample properties of the proposed test with that of Arbogast and Lin (2004). To illustrate the usefulness of the method, we apply the proposed test to a matched case-control data constructed from the breast cancer data of the SEER study. Usually a logistic model is needed to associate the risk of the disease with the covariates of interests. However, this logistic model may not be appropriate in some instances. In the last project , we adopt idea to matched case-control studies and derive an information matrix based test for testing overall model adequacy and investigate the properties against the cumulative residual based test in Arbogast and Lin (2004) via a simulation study. The proposed method is less time consuming and has comparative power for small parameters. It is suitable to explore the overall model fitting.

Submitted by Rafael Santana (rafael.silvasantana@ufpe.br) on 2017-07-14T18:46:22Z No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Dissertação_Walter DM Oliveira_ Oceanografia_UFPE.pdf: 1745886 bytes, checksum: 62870c6bfbb9848afc84e4fb94eff45e (MD5) / Made available in DSpace on 2017-07-14T18:46:22Z (GMT). No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Dissertação_Walter DM Oliveira_ Oceanografia_UFPE.pdf: 1745886 bytes, checksum: 62870c6bfbb9848afc84e4fb94eff45e (MD5) Previous issue date: 2016-05-31 / Os recifes costeiros são comumente afetados por ações antrópicas que vão desde o turismo contemplativo a poluição por efluentes domésticos. Essas formações recifais abrigam muitas espécies de peixe que em busca de abrigo para diferentes fazes do ciclo de vida e alimento. Nesses sentido as cristas recifais formam um importante papel para o desenvolvimento desses organismos, sem comumente um local de berçário natural. A cobertura de substrato é um outro fator importante para essas espécies pois pode gerar proteção, alimentação direta a indireta com invertebrados epifíticos. As cristas recifais do litoral sul de Pernambuco são dominadas por cobertura algal. Os recifes locais são importantes como fonte de renda para as comunidades locais e para conservação dos ambientes marinhos costeiros. Foram analisadas as relações entre a ictiofauna e a categorias de algas nas cristas recifais de Porto de Galinhas, Serrambi e São José da Coroa Grande, tendo sido amostrados três piscinas em cada praia. Para isso foram feitas amostragens com transecto de faixa de 20x2 m² em cada piscina, com registros fotográficos da cobertura de substrato, essas fotos foram posteriormente analisadas para estimar o percentual de cada categoria representada na cobertura do substrato da crista recifal. Os dados mostraram que Stegastes fuscus, Abudefduf saxatilis, Sparisoma axillare, Halichoeres poeyi e Ophioblennius trinitatis foram as espécies mais representativas nas cristas recifais analisadas. As algas calcárias articuladas e turf foram as algas mais abundantes nessas formações. As algas folhosas foram pouco abundantes, sendo mais representadas em São José da Coroa Grande. A maioria da abundância de peixes representou a categoria trófica de herbívoros errante e a mais rica foi comedores de invertebrados móveis. St. fuscus e O. trinitatis foram registrados em todas as classes de tamanho, enquanto A. saxatilis, Sp. axillare,e H. poeyi foram observados em fases juvenis. A relação verificada entre a comunidade de peixes, a cobertura de substrato e as características estruturais foi baixa visto que a distribuição de peixes foi homogênea e houve pouca variação nas categorias de algas. / The reef crests form an important habitat for fish of different habits and life stages. Coastal reefs are commonly affected by human activities ranging from the contemplative tourism to the pollution from domestic sewage. The substrate coverage can indicate the distribution of fish species that use this place to establish throughout the life cycle or in transitional phases. The reef crests of the southern coast of Pernambuco are dominated by algal cover. Local reefs are important as source of income for local communities and for conservation of coastal marine environments. The relationship between fish community and categories of algae on the reef crests of Porto de Galinhas, Serrambi and São José da Coroa Grande were analyzed. Three points were sampled at each beach. For the sampling of fish were made four transects of 20x2 m in each pool. At the same time were made photos of substrate coverage, these photos were then analyzed to estimate the percentage of each category. The data showed that Stegastes fuscus, Abudefduf saxatilis, Sparisoma axillare, Halichoeres poeyi and Ophioblennius trinitatis were the most significant species in the reef crests analyzed. The jointed calcareous macroalgae and turf were the most abundant in these formations. The sheet-like algaes were less abundant and more represented in São José da Coroa Grande. Most of the abundance of fish represented the trophic category herbivores and the richest was eaters of mobile invertebrates. St. fuscus and O. trinitatis were recorded in all size classes, while A. saxatilis, Sp. Axillare, and H. poeyi were observed in juvenile stages. The relationship between the fish community and substrate coverage and structural characteristics was low as the fish distribution is homogeneous and there was little variation in types of substrate coverage.

Computational tools such as finite element analysis and simulation are commonly used for system performance analysis and validation. It is often impractical to rely exclusively on the high-fidelity simulation model for design activities because of high computational costs. Mathematical models are typically constructed to approximate the simulation model to help with the design activities. Such models are referred to as “metamodel.” The process of constructing a metamodel is called “metamodeling.” Metamodeling, however, faces eminent challenges that arise from high-dimensionality of underlying problems, in addition to the high computational costs and unknown function properties (that is black-box functions) of analysis/simulation. The combination of these three challenges defines the so-called high-dimensional, computationally-expensive, and black-box (HEB) problems. Currently there is a lack of practical methods to deal with HEB problems. This dissertation, by means of surveying existing techniques, has found that the major deficiency of the current metamodeling approaches lies in the separation of the metamodeling from the properties of underlying functions. The survey has also identified two promising approaches - mapping and decomposition - for solving HEB problems. A new analytic methodology, radial basis function–high-dimensional model representation (RBF-HDMR), has been proposed to model the HEB problems. The RBF-HDMR decomposes the effects of variables or variable sets on system outputs. The RBF-HDMR, as compared with other metamodels, has three distinct advantages: 1) fundamentally reduces the number of calls to the expensive simulation in order to build a metamodel, thus breaks/alleviates exponentially-increasing computational difficulty; 2) reveals the functional form of the black-box function; and 3) discloses the intrinsic characteristics (for instance, linearity/nonlinearity) of the black-box function. The RBF-HDMR has been intensively tested with mathematical and practical problems chosen from the literature. This methodology has also successfully applied to the power transfer capability analysis of Manitoba-Ontario Electrical Interconnections with 50 variables. The test results demonstrate that the RBF-HDMR is a powerful tool to model large-scale simulation-based engineering problems. The RBF-HDMR model and its constructing approach, therefore, represent a breakthrough in modeling HEB problems and make it possible to optimize high-dimensional simulation-based design problems.

Computational tools such as finite element analysis and simulation are commonly used for system performance analysis and validation. It is often impractical to rely exclusively on the high-fidelity simulation model for design activities because of high computational costs. Mathematical models are typically constructed to approximate the simulation model to help with the design activities. Such models are referred to as “metamodel.” The process of constructing a metamodel is called “metamodeling.” Metamodeling, however, faces eminent challenges that arise from high-dimensionality of underlying problems, in addition to the high computational costs and unknown function properties (that is black-box functions) of analysis/simulation. The combination of these three challenges defines the so-called high-dimensional, computationally-expensive, and black-box (HEB) problems. Currently there is a lack of practical methods to deal with HEB problems. This dissertation, by means of surveying existing techniques, has found that the major deficiency of the current metamodeling approaches lies in the separation of the metamodeling from the properties of underlying functions. The survey has also identified two promising approaches - mapping and decomposition - for solving HEB problems. A new analytic methodology, radial basis function–high-dimensional model representation (RBF-HDMR), has been proposed to model the HEB problems. The RBF-HDMR decomposes the effects of variables or variable sets on system outputs. The RBF-HDMR, as compared with other metamodels, has three distinct advantages: 1) fundamentally reduces the number of calls to the expensive simulation in order to build a metamodel, thus breaks/alleviates exponentially-increasing computational difficulty; 2) reveals the functional form of the black-box function; and 3) discloses the intrinsic characteristics (for instance, linearity/nonlinearity) of the black-box function. The RBF-HDMR has been intensively tested with mathematical and practical problems chosen from the literature. This methodology has also successfully applied to the power transfer capability analysis of Manitoba-Ontario Electrical Interconnections with 50 variables. The test results demonstrate that the RBF-HDMR is a powerful tool to model large-scale simulation-based engineering problems. The RBF-HDMR model and its constructing approach, therefore, represent a breakthrough in modeling HEB problems and make it possible to optimize high-dimensional simulation-based design problems.

La survie nette est un indicateur très utilisé en épidémiologie des cancers. Il s'agit de la survie que l'on observerait si la seule cause de mortalité était le cancer ; il est le seul indicateur épidémiologique utilisable à des fins de comparaisons de survie (entre périodes/pays) car il s'affranchit des éventuelles différences de mortalité dues aux autres causes que le cancer. Le premier objectif de notre travail était d'analyser les performances des différentes méthodes d'estimation de la survie nette sur données simulées ainsi que sur données réelles afin que les méthodes non biaisées soient reconnues scientifiquement et soient les seules à être utilisées par la suite. Nous avons ainsi démontré que deux approches étaient capables d'estimer sans biais la survie nette : l'approche non paramétrique de Pohar-Perme et l'approche reposant sur une modélisation multivariée du taux de mortalité en excès dû au cancer. Cette dernière approche impose une stratégie de construction difficile à mettre en place. Le deuxième objectif était de développer une boîte à outils composée de différents tests permettant de vérifier les différentes hypothèses faites lors de la construction d'un modèle de régression du taux de mortalité en excès. Ces hypothèses concernent habituellement la proportionnalité ou non de l'effet des covariables, leur forme fonctionnelle, ainsi que la fonction de lien utilisée. Le troisième objectif était une application épidémiologique qui visait à étudier l'impact des facteurs pronostiques, tel que le stade au diagnostic, sur la survie nette conditionnelle, en d'autres termes sur la dynamique du taux de mortalité en excès, après la survenue d'un cancer du côlon / Net survival is one of the most important indicators in cancer epidemiology. It is defined as the survival that would be observed if cancer were the only cause of death. This is the only one indicator allowing comparisons of cancer impact between countries or time periods because it is not influenced by death because of other causes. The first objective of this work was to compare the performance of several estimators of the net survival in a simulation study and then on real data in order to promote unbiased methods. Those methods are the non-parametric Pohar-Perme method and the parametric multivariable excess rate model. The latest one needs a model building strategy. The use of diagnostic procedures for model checking is an essential part of the modeling process. The second objective was to develop a tool box composed of diagnostic tools allowing to check hypothesis usually considered when constructing an excess mortality rate model, that is, the proportionality or not of the effect of covariates, their functional form and the link function. The third objective deals with the study of the impact of prognostic variables, such as stage at diagnosis, on conditional net survival, that is, on the dynamic of the excess hazard mortality after the diagnosis of colon cancer

This doctoral thesis consists of three essays. In the first essay I investigate the presence of productivity convergence in eight regional pulp and paper industries of U.S. and Canada over the period of 1971-2005. Expectation of productivity convergence in the pulp and paper industries of Canadian provinces and of the states of its southern neighbour is high since they are trading partners with fairly high level of exchanges in both pulp and paper products. Moreover, they share a common production technology that changed very little over the last century. I supplement the North-American regional data with national data for two Nordic countries, Finland and Sweden, which provides a scope to compare the productivity performances of four leading players in global pulp and paper industry. I find evidence in favour of the catch-up hypothesis among the regional pulp and paper industries of U.S. and Canada in my sample. The growth performance is at the advantage of Canadian provinces relative to their U.S. counterparts. However, it is not good enough to surpass the growth rates of this industry in the two Nordic countries. It is well-known that econometric productivity estimation using flexible functional forms often encounter violations of curvature conditions. However, the productivity literature does not provide any guidance on the selection of appropriate functional forms once they satisfy the theoretical regularity conditions. The second chapter of my thesis provides an empirical evidence that imposing local curvature conditions on the flexible functional forms affect total factor productivity (TFP) estimates in addition to the elasticity estimates. Moreover, I use this as a criterion for evaluating the performances of three widely used locally flexible cost functional forms - the translog (TL), the Generalized Leontief (GL), and the Normalized Quadratic (NQ) - in providing TFP estimates. Results suggest that the NQ model performs better than the other two functional forms in providing TFP estimates. The third essay capitalizes on newly available high frequency energy consumption data from commercial buildings in the District of Columbia (DC) to provide novel insights on the realized energy use impacts of energy efficiency standards in commercial buildings. Combining these data with hourly weather data and information on tenancy contract structure I evaluate the impacts of energy standards, contractual structure of utility bill payments, and energy star labeling on account level electricity consumption. Using this unique panel dataset, the analysis takes advantage of detailed building-level characteristics and the heterogeneity in the building age distribution, resulting in buildings constructed before and after mandatory energy standards came into effect. Estimation results suggest that in commercial buildings constructed under a code, electricity consumption is lower by about 0.48 kWh per cooling degree hour. When tenants pay for their own utilities, consumption is lower by 0.82 kWh per cooling degree hour. The Energy Star effect is a 0.31 kWh reduction per cooling degree hour. Finally, peak savings for all three variables of interest occur at 2pm in the summer months, whereas peak summer marginal prices at DC's local electric utility occur at 5pm.