CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / The role of Brazilian cities had great changes over the last twenty-six. The process of decentralization allowed with the 1988 Constitution aimed the financial and political strengthening of the states and especially the municipalities in relation to the federal government. Thus, given the cities greater autonomy, as became 'federative'. Areas such as health and education have gained proper attribution of the local governments and increase the administrative burden, thereby increasing the financial and cities now have to raise more to fulfill them. The administration of a municipality is what organizes and prepares it for development. The need for a management organized so that the population is well served in their rights converge for the concept of sustainable development. Whereas a municipality depends on many factors to develop sustainably, that is, given its population and thinking of the future generations, we need studies that seek to analyze the situation of the municipalities in its various aspects in order to find answers or directions to removal or replacement of obstructing the process. As well as for the development to occur in one place, one needs appropriate to their stimulus policies, the government also needs favorable framework conditions for public policies of local development induction be effective. Thus, the aim of this study was to analyze whether the municipal administrations of the state of Cearà contributed, from 2009 to 2012 for the development and sustainability of their municipalities. A Municipal Management index was constructed (IGM) for 2009 and 2012 through structure indicators of the management of municipalities. Through the use of analysis techniques of Principal Components was calculated Municipal Sustainability Index (ISM), and the same variables was made by the group of municipalities in seven clusters. To see the relationship between municipal management and sustainability, we used the cumulative distribution method by quantile regression. Variables such as spending on health, spending on education and the municipal debt proved to be very important for the sustainability of cities. It was concluded that for most municipalities there was no change in sustainability over the three years, though there have been changes of management, however the values decreased, which implies that some of the characteristics of the municipalities at the beginning of his administration in 2009 may have It has been lost, such as stocks and services that are no longer running and available to the population, councils who failed to act, municipal plans that no longer exist, joints that were undone. It was noticed that the management has a direct impact on sustainability, being instrumental in the development of the municipality, in all aspects, but mainly by the variables used here to generate adequate living conditions for its residents. / O papel dos municÃpios brasileiros sofreu grandes mudanÃas nos Ãltimos vinte e seis anos. O processo de descentralizaÃÃo permitido com a ConstituiÃÃo de 1988 teve por objetivo o fortalecimento financeiro e polÃtico dos estados e, principalmente, dos municÃpios em relaÃÃo ao governo federal. Com isso, conferiu aos municÃpios maior autonomia, pois passaram a ser âentes federativosâ. Ãreas como saÃde e educaÃÃo ganharam atribuiÃÃes prÃprias dos municÃpios e se aumentam as obrigaÃÃes administrativas, consequentemente, aumentam as financeiras e os municÃpios passaram a ter que arrecadar mais para cumprÃ-las. A administraÃÃo de um municÃpio à o que o organiza e o prepara para o desenvolvimento. A necessidade de uma gestÃo organizada para que a populaÃÃo seja bem atendida em seus direitos converge, entÃo, para este conceito de desenvolvimento sustentÃvel. Considerando que um municÃpio depende de muitos fatores para se desenvolver com sustentabilidade, ou seja, atendendo sua populaÃÃo e pensando nas geraÃÃes futuras, sÃo necessÃrios estudos que procuram analisar a situaÃÃo dos municÃpios em seus mais variados aspectos para que se encontrem respostas ou direcionamentos para a remoÃÃo ou substituiÃÃo dos entraves ao processo. Assim como, para que ocorra o desenvolvimento em um local, precisa-se de polÃticas adequadas ao seu estÃmulo, o poder pÃblico tambÃm necessita de condiÃÃes estruturais favorÃveis para que as polÃticas pÃblicas sejam efetivas. Dessa forma, o objetivo geral deste estudo foi analisar se as gestÃes municipais do estado do Cearà contribuÃram, no perÃodo de 2009 a 2012, para o desenvolvimento com sustentabilidade dos seus municÃpios. Foi calculado um Ãndice de GestÃo Municipal (IGM) para 2009 e 2012 atravÃs de indicadores de estrutura da gestÃo dos municÃpios. AtravÃs do uso das tÃcnicas de AnÃlise dos Componentes Principais foi calculado o Ãndice de Sustentabilidade Municipal (ISM), e com as mesmas variÃveis fez-se o agrupamento dos municÃpios em sete clusters. Para ver as relaÃÃes entre a gestÃo municipal e a sustentabilidade, utilizou-se o mÃtodo de distribuiÃÃo cumulativa, atravÃs da RegressÃo QuantÃlica. VariÃveis como despesa com saÃde, despesa com educaÃÃo e o endividamento municipal mostraram-se muito importantes para a sustentabilidade dos municÃpios. Concluiu-se que para a maior parte dos municÃpios nÃo houve mudanÃa na sustentabilidade ao longo dos trÃs anos, porÃm houveram mudanÃas de gestÃo, entretanto os valores diminuÃram, o que pressupÃe que algumas das caracterÃsticas dos municÃpios no inÃcio de sua gestÃo em 2009 podem ter sido perdidas, como aÃÃes e serviÃos que deixaram de ser executados e oferecidos à populaÃÃo, conselhos que deixaram de atuar, planos municipais que deixaram de existir, articulaÃÃes que foram desfeitas. Percebeu-se que a gestÃo tem impacto direto sobre a sustentabilidade, sendo peÃa fundamental no desenvolvimento do municÃpio, em todos os aspectos, mas principalmente, pelas variÃveis utilizadas aqui, para gerar condiÃÃes de vida adequadas para seus habitantes.

Submitted by (edna.saturno@ufrpe.br) on 2016-06-06T14:30:31Z No. of bitstreams: 1 Micheline Correia de Souza.pdf: 1073767 bytes, checksum: b3e089ee2ef19f17792bc2ebffaac77a (MD5) / Made available in DSpace on 2016-06-06T14:30:31Z (GMT). No. of bitstreams: 1 Micheline Correia de Souza.pdf: 1073767 bytes, checksum: b3e089ee2ef19f17792bc2ebffaac77a (MD5) Previous issue date: 2013-02-25 / The present work aimed to analyze the evolution of the wage differentials among gender, after the change of the economic scenario with increasing structural investments in Pernambuco. As well as, to estimate the wage differentials by gender for different groups of work by means of a linear regression model and observe the socioeconomic profile of the workforce in Pernambuco, over the years 2000. The data used were those of PNAD, collected by IBGE, in the years 2001 and 2009. The sample matched 24,964 people in the year 2001 and 24,600 in the year 2009. To estimate the wage differentials by gender for different groups of occupation have been used the OLS and quantile regression. In General, there was a decrease in the wage differential between men and women for the estimates through the OLS, as well as for the quantile series. As well as, on an analysis by occupational groups the differential effect also decreases. Note that the categories of workers and entrepreneurs registered presented the biggest differential. It is therefore concluded that the effects of workers ' productive characteristics (education, experience, number of children) have enough correlation in the determination of wages. And to the variable of interest "genre" discrimination for women is still quite visible, but the reasons may be subjective to the local labour market in the face of the advance of structural investments and new requirements arising from the lack of skilled labor in the analysis period. / O presente trabalho objetivou analisar a evolução dos diferenciais de salários, entre gênero, após a mudança do cenário econômico com o aumento dos investimentos estruturais em Pernambuco. Assim como, estimar os diferenciais de salário por gênero para diferentes grupos de ocupação do trabalho, através de um modelo de regressão linear e observar o perfil socioeconômico da mão de obra em Pernambuco, ao longo dos anos 2000. Os dados utilizados foram os da PNAD, coletados pelo IBGE, nos anos de 2001 e 2009. A amostra correspondeu 24.964 pessoas no ano de 2001 e 24.600 no ano de 2009 em Pernambuco. Para estimar os diferenciais de salários por gênero para diferentes grupos de ocupação de trabalho foram utilizados o MQO e de regressão quantílica. De forma geral, houve uma diminuição do diferencial de salário entre o homem e a mulher para as estimações através do MQO, bem como para a série quantílica. Assim como, na análise por grupos ocupacionais o efeito do diferencial também diminui. Ressalte-se que as categorias de empresário e dos trabalhadores com carteira assinada apresentaram o maior diferencial. Conclui-se, portanto, que os efeitos das características produtivas dos trabalhadores (educação, experiência, número de filhos) apresentam bastante correlação na determinação dos salários. E para a variável de interesse “gênero” a discriminação para a mulher ainda é bastante observada, porém os motivos podem ser subjetivos ao mercado de trabalho local diante do avanço dos investimentos estruturais e das novas exigências surgidas pela falta de mão de obra especializada no período analisado.

nÃo hà / This study applies traditional techniques in Finance and Econometrics in order to analyze the impacts of Financial Crisis on some sectors of the Brazilian economy based upon market indicators provided by Getulio Vargas Foundation (FGV). Initially we apply the theory proposed by Markowitz to sectoral indicators for eight economic sectors and estimate efficient portfolios in the pre and post-financial crisis periods and we verify that the weights established in the two cases differ dramatically. After that, we estimate quantile regressions for three sectors: Mining, Metallurgic and Textiles are estimated confronting the its returns against the return of the market portfolio and the implicit volatility measured. First of all, the model captures the increase in the risk premium demanded by investors in times of crisis; in spite of the models allow us to infer that there is a change in consumer behavior in times of economic instability in order to make him more risk-tolerant. / O estudo utiliza tÃcnicas tradicionais de FinanÃas e Econometria para analisar os impactos da crise financeira de 2008 sobre alguns setores da economia brasileira, tomando por base os indicadores setoriais de mercado da FundaÃÃo GetÃlio Vargas (FGV). Inicialmente aplica-se a teoria de Markowitz aos indicadores setoriais de mercado de oito setores e estimam-se portfÃlios eficientes no perÃodo prà e pÃscrise financeira, constatando que os pesos atribuÃdos aos dois perÃodos diferem dramaticamente. Posteriormente, regressÃes quantÃlicas para os setores MineraÃÃo, Metalurgia e TÃxtil sÃo estimadas, confrontando o retorno setorial com o retorno da carteira de mercado e a volatilidade implÃcita. AlÃm de captar a elevaÃÃo do prÃmio de risco exigido pelos investidores em perÃodos de crise, os modelos permitem inferir que hà uma mudanÃa de comportamento do consumidor em perÃodos de instabilidade econÃmica no sentido de tornÃ-lo mais tolerante ao risco.

In the real world, many problems are continuous in nature. In some cases, finding the global solutions for these problems is di±cult. The reason is that the problem's objective function is non convex, nor concave and even not differentiable. Tackling these problems is often computationally too expensive. Although the development in computer technologies are increasing the speed of computations, this often is not adequate, particularly if the size of the problem's instance are large. Applying exact methods on some problems may necessitate their linearisation. Several new ideas using heuristic approaches have been considered particularly since they tackle the problems within reasonable computational time and give an approximate solution. In this thesis, the variable neighbourhood search (VNS) metaheuristic (the framework for building heuristic) has been considered. Two variants of variable neighbourhood search metaheuristic have been developed, continuous variable neighbourhood search and reformulation descent variable neighbourhood search. The GLOB-VNS software (Drazic et al., 2006) hybridises the Microsoft Visual Studio C++ solver with variable neighbourhood search metaheuristics. It has been used as a starting point for this research and then adapted and modified for problems studied in this thesis. In fact, two problems have been considered, censored quantile regression and the circle packing problem. The results of this approach for censored quantile regression outperforms other methods described in the literature, and the near-optimal solutions are obtained in short running computational time. In addition, the reformulation descent variable neighbourhood search variant in solving circle packing problems is developed and the computational results are provided.

L'objectif de cette thèse consiste à étudier les liens entre les mécanismes internes de gouvernance des banques et le comportement de prise de risque. Nous montrons qu’Adam Smith avait déjà mis en évidence la défaillance des mécanismes de gouvernance dans la Banque « Ayr » comme principal facteur induisant la prise de risque excessive et, par conséquent, sa faillite. Nous développons un modèle qui illustre qu’une rémunération indexée sur les actifs risqués n’implique pas une prise de risque plus importante. Nous constatons, aussi, que pour inciter le dirigeant à réaliser la meilleure combinaison d’actifs, le conseil d’administration est tenu de lui payer la rémunération la plus élevée. La thèse porte également sur l’étude des attributs standards du CA et ceux liés à la gouvernance des risques dans les banques de l'UE durant la période 2005-2015. Les résultats de la régression panel à effet fixe indiquent que les caractéristiques du CA affectent le niveau des crédits non performants et l’insolvabilité des banques de l’UE. Les résultats de la régression quantile à effet fixe révèlent une hétérogénéité dans la relation entre le risque bancaire et les attributs étudiés. Plus précisément, nous constatons que l’effet positif de l’indépendance et la fréquence des réunions du CA sur la gestion des risques bancaires est plus important dans les banques les plus risquées. Nos résultats mettent en évidence, également, que la prévention des comportements de prise de risque excessive des banques de l’UE nécessite l’amélioration de l’efficacité des CA à travers l’établissement des comités de risque et d’audit. / The purpose of this thesis is to study the internal mechanisms of banks’ governance and their impact on the risk-taking behavior. We show that Adam Smith had already highlighted the inadequacy of the governance’ mechanisms in “Ayr” Bank as the primary factor leading to an excessive risk-taking and, consequently, to its bankruptcy. We develop a model that aims to evaluate the extent to which governance mechanisms play a moderating role on the compensation policy and the level of risk taken by the CEO. We illustrate that a remuneration indexed on risky assets does not imply a greater risk taking. We also conclude that in order to induce the CEO to achieve the best combination of assets, the board of directors (BD) is required to pay the highest compensation. The thesis also focuses on the study of standard BD attributes as well as those related to risk’ governance in EU banks from 2005 to 2015. The empirical investigation showed that certain BD features affect the level of non-performing loan and the insolvency of EU banks. The results of the fixed-effect quantile regression reveal that the effect of the standard BD and risk’ governance attributes on risk-taking is heterogeneous. More specifically, we can note that the positive effect of the independence and frequency of board meetings on bank’ risk management is more significant in the riskier banks. In addition to this, our empirical results suggests that the prevention of excessive risk taking by EU banks requires the improvement of the effectiveness of BD through the establishment of risk an audit committees.

Les applications les plus courantes des méthodes non paramétriques concernent l’estimation d’une fonction de régression (i.e. de l’espérance conditionnelle). Cependant, il est souvent intéressant de modéliser les quantiles conditionnels, en particulier lorsque la moyenne conditionnelle ne permet pas de représenter convenablement l’impact des covariables sur la variable dépendante. De plus, ils permettent d’obtenir des graphiques plus compréhensibles de la distribution conditionnelle de la variable dépendante que ceux obtenus avec la moyenne conditionnelle. À l’origine, la « quantification » était utilisée en ingénierie du signal et de l’information. Elle permet de discrétiser un signal continu en un nombre fini de quantifieurs. En mathématique, le problème de la quantification optimale consiste à trouver la meilleure approximation d’une distribution continue d’une variable aléatoire par une loi discrète avec un nombre fixé de quantifieurs. Initialement utilisée pour des signaux univariés, la méthode a été étendue au cadre multivarié et est devenue un outil pour résoudre certains problèmes en probabilités numériques. Le but de cette thèse est d’appliquer la quantification optimale en norme Lp à l’estimation des quantiles conditionnels. Différents cas sont abordés : covariable uni- ou multidimensionnelle, variable dépendante uni- ou multivariée. La convergence des estimateurs proposés est étudiée d’un point de vue théorique. Ces estimateurs ont été implémentés et un package R, nommé QuantifQuantile, a été développé. Leur comportement numérique est évalué sur des simulations et des données réelles. / One of the most common applications of nonparametric techniques has been the estimation of a regression function (i.e. a conditional mean). However it is often of interest to model conditional quantiles, particularly when it is felt that the conditional mean is not representative of the impact of the covariates on the dependent variable. Moreover, the quantile regression function provides a much more comprehensive picture of the conditional distribution of a dependent variable than the conditional mean function. Originally, the “quantization” was used in signal and information theories since the fifties. Quantization was devoted to the discretization of a continuous signal by a finite number of “quantizers”. In mathematics, the problem of optimal quantization is to find the best approximation of the continuous distribution of a random variable by a discrete law with a fixed number of charged points. Firstly used for a one-dimensional signal, the method has then been developed in the multi-dimensional case and extensively used as a tool to solve problems arising in numerical probability. The goal of this thesis is to study how to apply optimal quantization in Lp-norm to conditional quantile estimation. Various cases are studied: one-dimensional or multidimensional covariate, univariate or multivariate dependent variable. The convergence of the proposed estimators is studied from a theoretical point of view. The proposed estimators were implemented and a R package, called QuantifQuantile, was developed. Numerical behavior of the estimators is evaluated through simulation studies and real data applications.

The thesis deals with brief introduction of the quantile regression theory. The thesis is divided into three thematic parts. In the first part the thesis deals with general introduction to the quantile regression, with theoretical aspects regarding quantile regression and with basic approaches to estimation of quantile regression parameters. The second part of the thesis focuses on general and asymptotic properties of the quantile regression. Goal of this part is to compare the quantile regression with traditional OLS regression and outline its possible application. In the third part the thesis describes statistical inference, construction of the confidence intervals and testing statistical hypotheses about quantile regression parameters. The goal of this part is to introduce traditional approach and the approach based on resampling procedures and in the end of the day perform mutual comparison of different approaches eventually propose partial modification.

Les applications les plus courantes des méthodes non paramétriques concernent l'estimation d'une fonction de régression (i.e. de l'espérance conditionnelle). Cependant, il est souvent intéressant de modéliser les quantiles conditionnels, en particulier lorsque la moyenne conditionnelle ne permet pas de représenter convenablement l'impact des covariables sur la variable dépendante. De plus, ils permettent d'obtenir des graphiques plus compréhensibles de la distribution conditionnelle de la variable dépendante que ceux obtenus avec la moyenne conditionnelle. A l'origine, la "quantification" était utilisée en ingénierie du signal et de l'information. Elle permet de discrétiser un signal continu en un nombre fini de quantifieurs. En mathématique, le problème de la quantification optimale consiste à trouver la meilleure approximation d'une distribution continue d'une variable aléatoire par une loi discrète avec un nombre fixé de quantifieurs. Initialement utilisée pour des signaux univariés, la méthode a été étendue au cadre multivarié et est devenue un outil pour résoudre certains problèmes en probabilités numériques.Le but de cette thèse est d'appliquer la quantification optimale en norme Lp à l'estimation des quantiles conditionnels. Différents cas sont abordés :covariable uni- ou multidimensionnelle, variable dépendante uni- ou multivariée. La convergence des estimateurs proposés est étudiée d'un point de vue théorique. Ces estimateurs ont été implémentés et un package R, nommé QuantifQuantile, a été développé. Leur comportement numérique est évalué sur des simulations et des données réelles. / One of the most common applications of nonparametric techniques has been the estimation of a regression function (i.e. a conditional mean). However it is often of interest to model conditional quantiles, particularly when it is felt that the conditional mean is not representative of the impact of the covariates on the dependent variable. Moreover, the quantile regression function provides a much more comprehensive picture of the conditional distribution of a dependent variable than the conditional mean function. Originally, the "quantization'" was used in signal and information theories since the fifties. Quantization was devoted to the discretization of a continuous signal by a finite number of "quantizers". In mathematics, the problem of optimal quantization is to find the best approximation of thecontinuous distribution of a random variable by a discrete law with a fixed number of charged points. Firstly used for a one-dimensional signal, themethod has then been developed in the multi-dimensional case and extensively used as a tool to solve problems arising in numerical probability.The goal of this thesis is to study how to apply optimal quantization in Lp-norm to conditional quantile estimation. Various cases are studied: one-dimensional or multidimensional covariate, univariate or multivariate dependent variable. The convergence of the proposed estimators is studied from a theoretical point of view. The proposed estimators were implemented and a R package, called QuantifQuantile, was developed. Numerical behavior of the estimators is evaluated through simulation studies and real data applications. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

With advances in high-throughput techniques, the availability of large-scale omics data has revolutionized the fields of medicine and biology, and has offered a better understanding of the underlying biological mechanisms. However, the high-dimensionality and the unknown association structure between different data types make statistical integration analyses challenging. In this dissertation, we develop three dimensionality reduction methods to detect nonlinear association structure using omics data. First, we propose a method for variable selection in a nonparametric additive quantile regression framework. We enforce a network regularization to incorporate information encoded by known networks. To account for nonlinear associations, we approximate the additive functional effect of each predictor with the expansion of a B-spline basis. We implement the group Lasso penalty to achieve sparsity. We define the network-constrained penalty by regulating the difference between the effect functions of any two linked genes (predictors) in the network. Simulation studies show that our proposed method performs well in identifying truly associated genes with fewer falsely associated genes than alternative approaches. Second, we develop a canonical correlation analysis (CCA)-based method, canonical distance correlation analysis (CDCA), and leverage the distance correlation to capture the overall association between two sets of variables. The CDCA allows untangling linear and nonlinear dependence structures. Third, we develop the sparse CDCA (sCDCA) method to achieve sparsity and improve result interpretability by adding penalties on the loadings from the CDCA. The sCDCA method can be applied to data with large dimensionality and small sample size. We develop iterative majorization-minimization-based coordinate descent algorithms to compute the loadings in the CDCA and sCDCA methods. Simulation studies show that the proposed CDCA and sCDCA approaches have better performance than classical CCA and sparse CCA (sCCA) in nonlinear settings and have similar performance in linear association settings. We apply the proposed methods to the Framingham Heart Study (FHS) to identify body mass index associated genes, the association structure between metabolic disorders and metabolite profiles, and a subset of metabolites and their associated type 2 diabetes (T2D)-related genes. / 2023-11-05T00:00:00Z

The U.S.-American foreclosure crisis and related economic crises have had severe and wide-reaching effects for the global economy, homeowners, and municipalities alike. These negative changes led to federal, state, regional, and local responses intended to prevent and mitigate foreclosures. As of yet, no research has examined the community- and neighborhood-level impacts of local foreclosure responses. This research seeks to determine the economic, physical, social, and political changes that resulted from these responses. A mixed methods case study of Cuyahoga County, Ohio, home to Cleveland, was used to identify local level foreclosure responses—i.e. those carried out at the county level and below—and their effects. The qualitative component was comprised of semi-structured stakeholder interviews, including local governmental representatives, advocacy groups, and neighborhood representatives. Two community subcases were investigated in depth to further examine the mechanisms and effects of foreclosure responses. The quantitative component supplements the qualitative component by means of a quantile regression model that examines relationships between foreclosure responses and changes in property value at the Census tract level, used to approximate communities. The model integrates data for the entire county and estimates coefficients at various quantiles of the dependent variable, which uncovers variations in the associations between the variables along the dependent variable’s distribution. That is, with quantile regression it is possible to determine whether foreclosure responses have different effects depending on community conditions. The results indicate that the national and local context are of particular importance when responding to the foreclosure crisis. Lackluster national level responses necessitated creative and innovative responses at the local level. The Cleveland region is characterized a weak housing market and its concomitant vacancy and abandonment problems. Thus, post-foreclosure responses that deal with blighted property are essential. A wide variety of foreclosure responses took place in Cuyahoga County, in the form of systems reform, foreclosure prevention, targeting, property acquisition and control, legal efforts, and community- and neighborhood-level efforts. Several strategies used in these responses emerged as themes: targeting, addressing blight, strengthening the social fabric, planning for the future, building institutions and organizational capacity, and advocacy. Physical and economic impacts are closely linked and are brought about especially by responses using targeting and blight reduction strategies. Social impacts, such as increased identification with, investment in, and commitment to the community occurred as the result of responses that used the strategies of strengthening the social fabric and planning a shared future for the community. Finally, the strategies of building institutions and organizational capacity and advocacy resulted in increased political power in the form of more local control and additional resources for neighborhoods and communities. These results provide deeper insight into the effects of the foreclosure crisis and local responses to it on neighborhoods and communities. This case study identifies the importance of targeting, blight removal, strengthening social bonds, planning for a shared future, increasing organizational capacity, and advocacy in addressing the foreclosure crisis on the community and neighborhood levels, especially in weak housing market cities where need far outstrips the available resources.