This thesis deals with the development, implementation and application of statistical modeling techniques which can be employed in the analysis of credit ratings. Credit ratings are one of the most widely used measures of credit risk and are relevant for a wide array of financial market participants, from investors, as part of their investment decision process, to regulators and legislators as a means of measuring and limiting risk. The majority of credit ratings is produced by the "Big Three" credit rating agencies Standard & Poors', Moody's and Fitch. Especially in the light of the 2007-2009 financial crisis, these rating agencies have been strongly criticized for failing to assess risk accurately and for the lack of transparency in their rating methodology. However, they continue to maintain a powerful role as financial market participants and have a huge impact on the cost of funding. These points of criticism call for the development of modeling techniques that can 1) facilitate an understanding of the factors that drive the rating agencies' evaluations, 2) generate insights into the rating patterns that these agencies exhibit. This dissertation consists of three research articles. The first one focuses on variable selection and assessment of variable importance in accounting-based models of credit risk. The credit risk measure employed in the study is derived from credit ratings assigned by ratings agencies Standard & Poors' and Moody's. To deal with the lack of theoretical foundation specific to this type of models, state-of-the-art statistical methods are employed. Different models are compared based on a predictive criterion and model uncertainty is accounted for in a Bayesian setting. Parsimonious models are identified after applying the proposed techniques. The second paper proposes the class of multivariate ordinal regression models for the modeling of credit ratings. The model class is motivated by the fact that correlated ordinal data arises naturally in the context of credit ratings. From a methodological point of view, we extend existing model specifications in several directions by allowing, among others, for a flexible covariate dependent correlation structure between the continuous variables underlying the ordinal credit ratings. The estimation of the proposed models is performed using composite likelihood methods. Insights into the heterogeneity among the "Big Three" are gained when applying this model class to the multiple credit ratings dataset. A comprehensive simulation study on the performance of the estimators is provided. The third research paper deals with the implementation and application of the model class introduced in the second article. In order to make the class of multivariate ordinal regression models more accessible, the R package mvord and the complementary paper included in this dissertation have been developed. The mvord package is available on the "Comprehensive R Archive Network" (CRAN) for free download and enhances the available ready-to-use statistical software for the analysis of correlated ordinal data. In the creation of the package a strong emphasis has been put on developing a user-friendly and flexible design. The user-friendly design allows end users to estimate in an easy way sophisticated models from the implemented model class. The end users the package appeals to are practitioners and researchers who deal with correlated ordinal data in various areas of application, ranging from credit risk to medicine or psychology.

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No. of bitstreams: 1 TESE_FERNANDO_CARVALHAES_BARBI_204089_CDEE.pdf: 963906 bytes, checksum: 467d3c75aa7e81be984b8b5f22430c0b (MD5) Previous issue date: 2014-04-08 / In the first essay, 'Determinants of Credit Expansion in Brazil', analyzes the determinants of credit using an extensive bank level panel dataset. Brazilian economy has experienced a major boost in leverage in the first decade of 2000 as a result of a set factors ranging from macroeconomic stability to the abundant liquidity in international financial markets before 2008 and a set of deliberate decisions taken by President Lula's to expand credit, boost consumption and gain political support from the lower social strata. As relevant conclusions to our investigation we verify that: credit expansion relied on the reduction of the monetary policy rate, international financial markets are an important source of funds, payroll-guaranteed credit and investment grade status affected positively credit supply. We were not able to confirm the importance of financial inclusion efforts. The importance of financial sector sanity indicators of credit conditions cannot be underestimated. These results raise questions over the sustainability of this expansion process and financial stability in the future. The second essay, 'Public Credit, Monetary Policy and Financial Stability', discusses the role of public credit. The supply of public credit in Brazil has successfully served to relaunch the economy after the Lehman-Brothers demise. It was later transformed into a driver for economic growth as well as a regulation device to force private banks to reduce interest rates. We argue that the use of public funds to finance economic growth has three important drawbacks: it generates inflation, induces higher loan rates and may induce financial instability. An additional effect is the prevention of market credit solutions. This study contributes to the understanding of the costs and benefits of credit as a fiscal policy tool. The third essay, 'Bayesian Forecasting of Interest Rates: Do Priors Matter?', discusses the choice of priors when forecasting short-term interest rates. Central Banks that commit to an Inflation Target monetary regime are bound to respond to inflation expectation spikes and product hiatus widening in a clear and transparent way by abiding to a Taylor rule. There are various reports of central banks being more responsive to inflationary than to deflationary shocks rendering the monetary policy response to be indeed non-linear. Besides that there is no guarantee that coefficients remain stable during time. Central Banks may switch to a dual target regime to consider deviations from inflation and the output gap. The estimation of a Taylor rule may therefore have to consider a non-linear model with time varying parameters. This paper uses Bayesian forecasting methods to predict short-term interest rates. We take two different approaches: from a theoretic perspective we focus on an augmented version of the Taylor rule and include the Real Exchange Rate, the Credit-to-GDP and the Net Public Debt-to-GDP ratios. We also take an 'atheoretic' approach based on the Expectations Theory of the Term Structure to model short-term interest. The selection of priors is particularly relevant for predictive accuracy yet, ideally, forecasting models should require as little a priori expert insight as possible. We present recent developments in prior selection, in particular we propose the use of hierarchical hyper-g priors for better forecasting in a framework that can be easily extended to other key macroeconomic indicators. / O primeiro ensaio, "Determinantes da expansão do crédito no Brasil", analisa os determinantes do crédito usando um extenso conjunto de dados em painel sobre o sistema bancário. A economia brasileira teve um grande impulso na alavancagem na primeira década de 2000 como resultado de um conjunto de fatores que vão desde a estabilidade macroeconômica passando pela liquidez abundante nos mercados financeiros internacionais antes de 2008 até um conjunto de decisões deliberadas tomadas pelo presidente Lula para expandir o crédito, impulsionar o consumo e obter apoio político das camadas sociais mais baixas. Como conclusões verificamos que a expansão do crédito beneficiou-se da redução da taxa de juros, os mercados financeiros internacionais são uma fonte importante de recursos, o crédito garantido em folha de pagamento e o grau de investimento afetaram positivamente a oferta de crédito. Nós não fomos capazes de confirmar a importância dos esforços de inclusão financeira. A importância dos indicadores de sanidade do setor financeiro de condições de crédito não pode ser subestimada. Estes resultados levantam questões quanto à sustentabilidade desse processo de expansão e estabilidade financeira no futuro. O segundo ensaio, "Crédito Público, Política Monetária e Estabilidade Financeira", discute o papel do crédito público. A oferta de crédito público no Brasil serviu para relançar a economia após a crise desencadeada pela quebra do banco Lehman-Brothers. Mais tarde, ele foi transformado em um motor de crescimento econômico bem como num dispositivo de regulação para forçar os bancos privados a reduzir as taxas de juros. Argumenta-se que a utilização de fundos públicos para financiar o crescimento econômico tem três desvantagens importantes: ele gera inflação, induz taxas de financiamento mais elevadas e pode induzir à instabilidade financeira. Um efeito adicional é impedir o desenvolvimento de soluções de crédito de mercado. O terceiro ensaio, "Previsão Bayesiana de Taxas de Juros: as priors importam?", discute a escolha de priors para previsão das taxas de juros de curto prazo. Bancos Centrais que se comprometem com regimes de metas de inflação devem responder a variações nas expectativa de inflação e no hiato do produto de uma forma clara e transparente, respeitando a regra de Taylor. A estimativa de uma regra de Taylor pode ter que considerar um modelo não-linear com parâmetros variáveis no tempo. Este trabalho usa métodos de previsão bayesiana para as taxas de juro de curto prazo por duas abordagens diferentes. Por uma perspectiva teórica nos concentramos em uma versão aumentada da regra de Taylor. Também testamos uma abordagem baseada na teoria das expectativas da estrutura a termo cauva de juros para modelar os juros de curto prazo. A seleção dos priores é particularmente relevante para a precisão da previsão, no entanto deseja-se usar prior robustas a falta de conhecimento prévio. Apresentamos os recentes desenvolvimentos na seleção de priors, em especial, propomos o uso de priors hierárquicas da família de distribuição hiper-geométrica.

Cette thèse étudie le traitement statistique des images TEP. Plus particulièrement, la distribution binomiale négative est proposée pour modéliser l’activité d’une région mono-tissulaire. Cette représentation a l’avantage de pouvoir prendre en compte les variations d’activité biologique (ou hétérogénéité) d’un même tissu. A partir de ces résultats, il est proposé de modéliser la distribution de l’image TEP entière comme un mélange spatialement cohérent de lois binomiales négatives. Des méthodes Bayésiennes sont considérées pour la segmentation d’images TEP et l’estimation conjointe des paramètres du modèle. La cohérence spatiale inhérente aux tissus biologiques est modélisée par un champ aléatoire de Potts-Markov pour représenter la dépendance locale entre les composantes du mélange. Un algorithme original de Monte Carlo par Chaîne de Markov (MCMC) est utilisé, faisant appel aux notions d’échantillonnage dans un espace Riemannien et d’opérateurs proximaux. L’approche proposée est appliquée avec succès à la segmentation de tumeurs en imagerie TEP. Cette méthode est ensuite étendue d’une part en intégrant au processus de segmentation des informations anatomiques acquises par tomodensitométrie (TDM), et d’autre part en traitant une série temporelle d’images correspondant aux différentes phases de respiration. Un modèle de mélange de distributions bivariées binomiale négative - normale est proposé pour représenter les images dynamiques TEP et TDM fusionnées. Un modèle Bayésien hiérarchique a été élaboré comprenant un champ de Potts-Markov à quatre dimensions pour respecter la cohérence spatiale et temporelle des images PET-TDM dynamiques. Le modèle proposé montre une bonne qualité d’ajustement aux données et les résultats de segmentation obtenus sont visuellement en concordance avec les structures anatomiques et permettent la délimitation et le suivi de la tumeur. / This thesis studies statistical image processing of PET images. More specifically, the negative binomial distribution is proposed to model the activity of a single tissue. This representation has the advantage to take into account the variations of biological activity (or heterogeneity) within a single tissue. Based on this, it is proposed to model the data of the entire PET image as a spatially coherent finite mixture of negative binomial distributions. Bayesian methods are considered to jointly perform the segmentation and estimate the model parameters. The inherent spatial coherence of the biological tissue is modeled by a Potts-Markov random field to represent the local dependence between the components of the mixture. An original Markov Chain Monte Carlo (MCMC) algorithm is proposed, based on sampling in a Riemannian space and proximal operators. The proposed approach is successfully applied to the segmentation of tumors in PET imaging. This method is further extended by incorporating anatomical information acquired by computed tomography (CT) and processing a time series of images corresponding to the phases of respiration. A mixture model of bivariate negative binomial - normal distributions is proposed to represent the dynamic PET and CT fused images. A hierarchical Bayesian model was developed including a four dimensional Potts-Markov field to enforce the spatiotemporal coherence of dynamic PET-CT images. The proposed model shows a good fit to the data and the segmentation results obtained are visually consistent with the anatomical structures and allow accurate tumor delineation and tracking.

Um dos estudos observacionais mais difundidos e usados em epidemiologia veterinária é o estudo do tipo transversal. Sua popularidade ocorre por fatores como baixo custo e rapidez comparados com outros tipos de estudos, além de ajudar a estimar a prevalência de uma doença (desfecho) e postular fatores associados com o desfecho, que poderão ser confirmados como fatores causais em outros tipos de estudos epidemiológicos. Porém, este tipo de estudo apresenta dois importantes desafios: a dependência dos dados, muito frequente dada a típica estrutura populacional de animais dentro do mesmo rebanho ou fazenda e a escolha da medida de associação para desfechos binários, tão frequentes neste modelo de estudo. Com o objetivo de contribuir com a compreensão global da epidemiologia do aborto bovino associado à Neospora caninum tendo em conta a estrutura populacional, construiu-se um modelo misto com os dados de um estudo transversal realizado em duas regiões do Rio Grande do Sul. Usaram-se dados de 60 propriedades amostradas em duas regiões (noroeste e sudeste) e 1256 bovinos. A percentagem de aborto dentro de cada rebanho variou entre 1% e 30%. Vacas soropositivas tiveram 6,63 vezes mais chances de ter histórico de aborto (IC 95%: 4,41-13,20). As chances de uma vaca ter histórico de aborto foram 5,18 vezes maiores na região noroeste em relação à região sudeste (IC 95%: 1,83-20,80). Um coeficiente de correlação intraclasse de 16% foi estimado, indicando que 16% da variação da ocorrência de abortamentos não explicados pelos efeitos fixos foram devido as fazendas. Já na segunda parte deste trabalho, uma revisão sistemática foi realizada considerando um conjunto diverso de revistas e jornais com o objetivo de verificar os métodos estatísticos usados e a adequação das interpretações das medidas de associação estimadas em estudos transversais na área de medicina veterinária. Um total de 62 artigos foi avaliado. A revisão mostrou que, independentemente do nível de prevalência relatado no artigo, 96% deles empregou regressão logística e, portanto, estimaram razão de chances (RC). Nos artigos com prevalência superior a 10%, 23 deles fizeram uma interpretação adequada da RC como uma “razão de chances” ou simplesmente não fizeram uma interpretação direta da RC, enquanto 23 artigos interpretaram de forma inadequada a RC, considerando-a como risco ou probabilidade. Entre os artigos com prevalência inferior a 10%, apenas três interpretaram a RC como uma “razão de chances”, cinco interpretaram como risco ou probabilidade e em um, apesar de ter estimado a razão de prevalências (RP), foi interpretado de forma inadequada. Paralelamente, com o objetivo de exemplificar o uso de métodos estatísticos que estimam diretamente a razão de prevalências (RP), medida mais adequada para os estudos transversais, um conjunto de dados obtidos a partir de um estudo transversal sobre a ocorrência de anticorpos (AC) contra o vírus da diarreia viral bovina (BVDV) foi usado. Os AC foram medidos em amostras de tanque de leite de rebanhos leiteiros localizados no estado do Rio Grande do Sul, em que os possíveis fatores associados puderam ser avaliados. Entre os métodos utilizados, as maiores discrepâncias nas medidas de associação estimadas foram observadas com a regressão logística tomando-se como referência a regressão log-binomial. Finalmente, é importante que este tipo de desafio seja atendido pelos pesquisadores que realizam estudos transversais, ou seja, considerar a estrutura das populações nas análises, cuidado ao escolher o tipo de modelo estatístico empregado para desfecho binário e interpretação dos estimadores. / The commonest study design used in veterinary epidemiology is the cross-sectional study. Its popularity lies on the fact of the short time needed and low costs compared with other types of studies; moreover, this type of study estimates prevalence and associated factors, which may be elucidated as causal in another type of epidemiological studies. However, this type of study presents two major challenges: a very common dependence between data given the typical structure of the animal population, i.e., animals within herds or farms and the choice of measure of association for binary outcomes, frequently used in this type of study. In order to contribute to the understanding of the epidemiology of bovine abortion associated with Neospora caninum, a mixed model accounting for the hierarchical structure of cattle population using data from a cross-sectional study conducted in two regions (northwest and southeast) of Rio Grande do Sul was made. Data from 60 dairy herds and 1256 sampled cattle were used. The percentage of abortions in each herd ranged between 1% and 30%. Seropositive cows were 6.63 times more likely to have a history of abortion (95% CI: 4.41 to 13.20). The chances of a cow have a history of abortion were 5.18 times higher in the northwest comparing with the southeast region (95% CI: 1.83 to 20.80). An intraclass correlation coefficient (ICC) of 16% was estimated which means that 16% of the variation in abortion occurrence not explained by the fixed effects is due to farms. In the second part of this work, a systematic review was conducted considering a range of journals and newspapers in order to verify the statistical methods used and the adequacy of the interpretations of the measures of association estimated in cross-sectional studies from the veterinary medicine field. A total of 62 articles were revised. The review showed that, regardless of the reported prevalence, 96% of them employed logistic regression, therefore estimating odds ratio (OR). From the articles that reported prevalence rates above 10%, 23 of them did a proper interpretation of OR as an odds ratio, or simply did not make a direct interpretation of the OR, while 23 articles interpreted improperly the OR as a risk or probability. Among the articles that reported prevalence rates lower than 10%, only three interpreted the OR as an odds ratio, five interpreted as a risk or probability and only one, despite the estimated prevalence ratio (PR), it was improperly interpreted. Meanwhile, in order to exemplify the use of statistical methods to estimate directly the PR, the more appropriate measure of association in cross-sectional studies, a data set obtained from a cross-sectional study to estimate the occurrence of antibodies (AB) against bovine viral diarrhea virus (BVDV) in milk was used; AB were measured in bulk tank samples from dairy herds located in the state of Rio Grande do Sul, Brazil, and also possible associated factors were estimated. Among the methods used, major discrepancies in the measures of association estimated were observed with the logistic regression, comparing with the log-binomial regression. Finally, it is important that such challenges are met by the researchers that undertake cross-sectional studies.

Um dos estudos observacionais mais difundidos e usados em epidemiologia veterinária é o estudo do tipo transversal. Sua popularidade ocorre por fatores como baixo custo e rapidez comparados com outros tipos de estudos, além de ajudar a estimar a prevalência de uma doença (desfecho) e postular fatores associados com o desfecho, que poderão ser confirmados como fatores causais em outros tipos de estudos epidemiológicos. Porém, este tipo de estudo apresenta dois importantes desafios: a dependência dos dados, muito frequente dada a típica estrutura populacional de animais dentro do mesmo rebanho ou fazenda e a escolha da medida de associação para desfechos binários, tão frequentes neste modelo de estudo. Com o objetivo de contribuir com a compreensão global da epidemiologia do aborto bovino associado à Neospora caninum tendo em conta a estrutura populacional, construiu-se um modelo misto com os dados de um estudo transversal realizado em duas regiões do Rio Grande do Sul. Usaram-se dados de 60 propriedades amostradas em duas regiões (noroeste e sudeste) e 1256 bovinos. A percentagem de aborto dentro de cada rebanho variou entre 1% e 30%. Vacas soropositivas tiveram 6,63 vezes mais chances de ter histórico de aborto (IC 95%: 4,41-13,20). As chances de uma vaca ter histórico de aborto foram 5,18 vezes maiores na região noroeste em relação à região sudeste (IC 95%: 1,83-20,80). Um coeficiente de correlação intraclasse de 16% foi estimado, indicando que 16% da variação da ocorrência de abortamentos não explicados pelos efeitos fixos foram devido as fazendas. Já na segunda parte deste trabalho, uma revisão sistemática foi realizada considerando um conjunto diverso de revistas e jornais com o objetivo de verificar os métodos estatísticos usados e a adequação das interpretações das medidas de associação estimadas em estudos transversais na área de medicina veterinária. Um total de 62 artigos foi avaliado. A revisão mostrou que, independentemente do nível de prevalência relatado no artigo, 96% deles empregou regressão logística e, portanto, estimaram razão de chances (RC). Nos artigos com prevalência superior a 10%, 23 deles fizeram uma interpretação adequada da RC como uma “razão de chances” ou simplesmente não fizeram uma interpretação direta da RC, enquanto 23 artigos interpretaram de forma inadequada a RC, considerando-a como risco ou probabilidade. Entre os artigos com prevalência inferior a 10%, apenas três interpretaram a RC como uma “razão de chances”, cinco interpretaram como risco ou probabilidade e em um, apesar de ter estimado a razão de prevalências (RP), foi interpretado de forma inadequada. Paralelamente, com o objetivo de exemplificar o uso de métodos estatísticos que estimam diretamente a razão de prevalências (RP), medida mais adequada para os estudos transversais, um conjunto de dados obtidos a partir de um estudo transversal sobre a ocorrência de anticorpos (AC) contra o vírus da diarreia viral bovina (BVDV) foi usado. Os AC foram medidos em amostras de tanque de leite de rebanhos leiteiros localizados no estado do Rio Grande do Sul, em que os possíveis fatores associados puderam ser avaliados. Entre os métodos utilizados, as maiores discrepâncias nas medidas de associação estimadas foram observadas com a regressão logística tomando-se como referência a regressão log-binomial. Finalmente, é importante que este tipo de desafio seja atendido pelos pesquisadores que realizam estudos transversais, ou seja, considerar a estrutura das populações nas análises, cuidado ao escolher o tipo de modelo estatístico empregado para desfecho binário e interpretação dos estimadores. / The commonest study design used in veterinary epidemiology is the cross-sectional study. Its popularity lies on the fact of the short time needed and low costs compared with other types of studies; moreover, this type of study estimates prevalence and associated factors, which may be elucidated as causal in another type of epidemiological studies. However, this type of study presents two major challenges: a very common dependence between data given the typical structure of the animal population, i.e., animals within herds or farms and the choice of measure of association for binary outcomes, frequently used in this type of study. In order to contribute to the understanding of the epidemiology of bovine abortion associated with Neospora caninum, a mixed model accounting for the hierarchical structure of cattle population using data from a cross-sectional study conducted in two regions (northwest and southeast) of Rio Grande do Sul was made. Data from 60 dairy herds and 1256 sampled cattle were used. The percentage of abortions in each herd ranged between 1% and 30%. Seropositive cows were 6.63 times more likely to have a history of abortion (95% CI: 4.41 to 13.20). The chances of a cow have a history of abortion were 5.18 times higher in the northwest comparing with the southeast region (95% CI: 1.83 to 20.80). An intraclass correlation coefficient (ICC) of 16% was estimated which means that 16% of the variation in abortion occurrence not explained by the fixed effects is due to farms. In the second part of this work, a systematic review was conducted considering a range of journals and newspapers in order to verify the statistical methods used and the adequacy of the interpretations of the measures of association estimated in cross-sectional studies from the veterinary medicine field. A total of 62 articles were revised. The review showed that, regardless of the reported prevalence, 96% of them employed logistic regression, therefore estimating odds ratio (OR). From the articles that reported prevalence rates above 10%, 23 of them did a proper interpretation of OR as an odds ratio, or simply did not make a direct interpretation of the OR, while 23 articles interpreted improperly the OR as a risk or probability. Among the articles that reported prevalence rates lower than 10%, only three interpreted the OR as an odds ratio, five interpreted as a risk or probability and only one, despite the estimated prevalence ratio (PR), it was improperly interpreted. Meanwhile, in order to exemplify the use of statistical methods to estimate directly the PR, the more appropriate measure of association in cross-sectional studies, a data set obtained from a cross-sectional study to estimate the occurrence of antibodies (AB) against bovine viral diarrhea virus (BVDV) in milk was used; AB were measured in bulk tank samples from dairy herds located in the state of Rio Grande do Sul, Brazil, and also possible associated factors were estimated. Among the methods used, major discrepancies in the measures of association estimated were observed with the logistic regression, comparing with the log-binomial regression. Finally, it is important that such challenges are met by the researchers that undertake cross-sectional studies.

Cette thèse est une contribution à l’analyse économique des institutions politiques et économiques dans les pays en développement. Elle s’inscrit dans la lignée des travaux de la Nouvelle Economie Institutionnelle et de la Nouvelle Economie Politique. Précisément, nous nous intéressons aux institutions telles que la constitution, la corruption et la démocratie. Cette thèse est structurée en cinq chapitres. Le chapitre 1 aborde la problématique des institutions dans sa globalité. Dans ce chapitre, nous définissons le terme institutions comme : « règle et contrainte », « instrument de gouvernance » et « équilibre de jeux ». Nous discutons ensuite des théories du changement institutionnel. Enfin, nous identifions les facteurs influençant la qualité des institutions. Dans le chapitre 2, nous revisitons la théorie de la modernisation. Nos différentes analyses empiriques nous conduisent à conclure que la théorie de la modernisation, telle que définie actuellement et selon laquelle l’éducation, le revenu, l’urbanisation et l’industrialisation influencent la démocratie, n’explique pas la dynamique négative de démocratie en Afrique. Dans le chapitre 3, nous démontrons que le manque d’expérience parlementaire à l’indépendance exerce un effet négatif sur la qualité de la démocratie en Afrique plusieurs années après les indépendances. Le chapitre 4 aborde la problématique du changement constitutionnel en Afrique. Il identifie les facteurs qui influencent la tentative et la réussite du changement de l’article constitutionnel sur la limitation du nombre de mandats présidentiels, et montre qu’ils sont d’ordre institutionnel, macroéconomique, culturel et socioculturel. Enfin, le chapitre 5 met en évidence le fait que les déterminants de la corruption varient selon le niveau de développement des pays et selon les zones géographiques. / This thesis is a contribution to the economic analysis of political and economic institutions in developing countries. It is in line with the works of the new institutional economics and the new political economics. Precisely, we are interested in institutions such as constitution, corruption and democracy. This thesis is articulated around five chapters. The first chapter provides a global approach of the analysis of institutions. In this chapter, we define institutions as « rule and constraint », « governance tool » and « game equilibrium ». Then, we discuss the theories of institutional changes. Finally, we identify the key drivers of the institutional quality. In the second chapter, we revisit the modernization theory. The empirical analyses lead to the conclusion that the modernization theory according to which the democracy is mainly driven by the level of education, income, urbanization and the industrialization do not explain the negative dynamic of the democratic process in Africa. In chapter 3, we show that the lack of parliamentary experience at the independence has a negative persistent effect on the current state of democracy in Africa. Chapter 4 adresses the issue of constitutional changes in Africa. It shows that the factors which affect the attempt and the success of the change of the article limiting the number of presidential terms are of institutional, macroeconomic, cultural and sociocultural order. Finally, chapter 5 highlights the fact that the determinants of corruption vary according to the country’s level of development and according to the geographic area.

Apresentamos duas abordagens para obter uma densidade de probabilidades para o preço futuro de um ativo: uma densidade preditiva, baseada em um modelo Bayesiano para série de tempo e uma densidade implícita, baseada na fórmula de precificação de opções de Black & Scholes. Considerando o modelo de Black & Scholes, derivamos as condições necessárias para obter a densidade implícita do preço do ativo na data de vencimento. Baseando-­se nas densidades de previsão, comparamos o modelo implícito com a abordagem histórica do modelo Bayesiano. A partir destas densidades, calculamos probabilidades de ordem e tomamos decisões de vender/comprar um ativo. Como exemplo, apresentamos como utilizar estas distribuições para construir uma fórmula de precificação. / We present two different approaches to obtain a probability density function for the stocks future price: a predictive distribution, based on a Bayesian time series model, and the implied distribution, based on Black & Scholes option pricing formula. Considering the Black & Scholes model, we derive the necessary conditions to obtain the implied distribution of the stock price on the exercise date. Based on predictive densities, we compare the market implied model (Black & Scholes) with a historical based approach (Bayesian time series model). After obtaining the density functions, it is simple to evaluate probabilities of one being bigger than the other and to make a decision of selling/buying a stock. Also, as an example, we present how to use these distributions to build an option pricing formula.

L’évaluation et la gestion des stocks de poissons ont pour objectif d’atteindre une exploitation durable des ressources fournies par les océans. Si les progrès dans ce domaine sont bien réels pour certains stocks de grande importance commerciale, la situation est différente pour les stocks dits à données limitées. Souvent historiquement moins exploités, ces stocks ne bénéficient pas des mêmes ressources, tant économiques qu’humaines, pour réaliser une évaluation de stock permettant par la suite la mise en place de mesures de gestion. Ce travail s’appuie sur deux cas d’étude, le lieu jaune (Pollachius pollachius) et la seiche (Sepia officinalis), afin d’explorer des méthodologies d’évaluation de stocks adaptées aux situations de données limitées. Après une première partie introductive reprenant le contexte de l’évaluation des stocks et présentant les deux cas d’étude, une revue des méthodes d’évaluation de stocks à données limitées est proposée. Une troisième partie compare les résultats d’un modèle de biomasse à deux stades et d’un modèle multi-annuel de déplétion généralisé appliqués au stock de seiche de Manche. Une version améliorée du modèle de biomasse à deux stades codé en Bayésien est également présentée. Le travail se poursuit avec l’application d’un modèle d’analyse intégrée Stock Synthesis au stock de lieu jaune de mer Celtique. Les résultats sont comparés aux résultats de modèles plus simples nécessitant moins de données. Les résultats du modèle Stock Synthesis s’avèrent sensibles aux hypothèses sur la valeur de mortalité naturelle, dont le calcul dépend des paramètres de croissance du stock. La cinquième partie présente l’acquisition et le traitement de nouvelles données qui pourront permettre une meilleure estimation de l’état du stock de lieu jaune. Un modèle hiérarchique Bayésien est construit, permettant un transfert d’information entre trois stocks et la mise à jour des paramètres biologiques du lieu jaune. Le dernier chapitre conclut ce travail en reprenant les principaux résultats obtenus et en élargissant la discussion sur des perspectives de recherche. / The assessment and the management of fish stocks aim at achieving a sustainable exploitation of the resources provided by the oceans. While progress have been made in this field for some stocks of great commercial importance, the situation is different for the so-called “data limited” stocks. Often historically less exploited, these stocks do not benefit from the same economical resources nor workforce to conduct the stock assessments required to set management measures. This work is based on two case studies, pollack (Pollachius pollachius) and cuttlefish (Sepia officinalis). The aim is to investigate the stock assessment methods adapted to data-limited situations. A first introductive part presents the background of fish stock assessment as well as the two case studies. This first chapter is followed by a review of data-limited stock assessment methods. The third part compare the results of a two-stage biomass model with the results of a multi-annual generalized depletion model applied to the English Channel stock of cuttlefish. An improved version of the Bayesian two-stage biomass model is also presented. In the fourth part, a Stock Synthesis model based on integrated analysis methods is applied to the stock of pollack in the Celtic Seas Ecoregion. The results are compared to the results of simpler models which require less data. The Stock Synthesis model results are sensitive to the assumptions on the natural mortality value, which relies on the growth parameters of the stock. The fifth part presents the collection and analysis of new data which will allow a better estimate of pollack stock status. A Bayesian hierarchical model is constructed, allowing information transfer between three stocks and the update of pollack biological parameters. The last chapter concludes this work by summarizing the main results. The discussion is extended to the research perspectives.

People are better able to empathize with others when they are given information concerning the context driving that person’s experiences. This suggests that people draw on prior memories when empathizing, but the mechanisms underlying this connection remain largely unexplored. The present study investigates how variations in episodic information shape the emotional response towards a movie character. Episodic information is either absent or provided by a written context preceding empathic film clips. It was shown that sad context information increases empathic concern for a movie character. This was tracked by neural activity in the temporal pole (TP) and anterior hippocampus (aHP). Dynamic causal modeling with Bayesian Model Selection has shown that context changes the effective connectivity from left aHP to the right TP. The same crossed-hemispheric coupling was found during rest, when people are left to their own thoughts. We conclude that (i) that the integration of episodic memory also supports the specific case of integrating context into empathic judgments, (ii) the right TP supports emotion processing by integrating episodic memory into empathic inferences, and (iii) lateral integration is a key process for episodic simulation during rest and during task. We propose that a disruption of the mechanism may underlie empathy deficits in clinical conditions, such as autism spectrum disorder.

The local false discovery rate (LFDR) is one of many existing statistical methods that analyze multiple hypothesis testing. As a Bayesian quantity, the LFDR is based on the prior probability of the null hypothesis and a mixture distribution of null and non-null hypothesis. In practice, the LFDR is unknown and needs to be estimated. The empirical Bayes approach can be used to estimate that mixture distribution. Empirical Bayes does not require complete information about the prior and hyper prior distributions as in hierarchical Bayes. When we do not have enough information at the prior level, and instead of placing a distribution at the hyper prior level in the hierarchical Bayes model, empirical Bayes estimates the prior parameters using the data via, often, the marginal distribution. In this research, we developed new Bayesian methods under unknown prior distribution. A set of adequate prior distributions maybe defined using Bayesian model checking by setting a threshold on the posterior predictive p-value, prior predictive p-value, calibrated p-value, Bayes factor, or integrated likelihood. We derive a set of adequate posterior distributions from that set. In order to obtain a single posterior distribution instead of a set of adequate posterior distributions, we used a blended distribution, which minimizes the relative entropy of a set of adequate prior (or posterior) distributions to a "benchmark" prior (or posterior) distribution. We present two approaches to generate a blended posterior distribution, namely, updating-before-blending and blending-before-updating. The blended posterior distribution can be used to estimate the LFDR by considering the nonlocal false discovery rate as a benchmark and the different LFDR estimators as an adequate set. The likelihood ratio can often be misleading in multiple testing, unless it is supplemented by adjusted p-values or posterior probabilities based on sufficiently strong prior distributions. In case of unknown prior distributions, they can be estimated by empirical Bayes methods or blended distributions. We propose a general framework for applying the laws of likelihood to problems involving multiple hypotheses by bringing together multiple statistical models. We have applied the proposed framework to data sets from genomics, COVID-19 and other data.