Can we fruitfully use the same macroeconomic model to forecast and to perform policy analysis? There is a tension between a model’s ability to forecast accurately and its ability to tell a theoretically consistent story. The aim of this dissertation is to propose ways to soothe this tension, combining structural and reduced-form models in order to have models that can effectively do both. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

La migration internationale d’étudiants est un investissement couteux pour les familles dans beaucoup de pays en voie de développement. Cependant, cet investissement est susceptible de générer des bénéfices financiers et sociaux relativement importants aux investisseurs, tout autant que des externalités pour d’autres membres de la famille. Cette thèse s’intéresse à deux aspects importants de la migration des étudiants internationaux : (i) Qui part? Quels sont les déterminants de la probabilité de migration? (ii) Qui paie? Comment la famille s’organise-t-elle pour couvrir les frais de la migration? (iii) Qui y gagne? Ce flux migratoire est-il au bénéfice du pays d’origine? Entreprendre une telle étude met le chercheur en face de défis importants, notamment, l’absence de données complètes et fiables; la dispersion géographique des étudiants migrants en étant la cause première. La première contribution importante de ce travail est le développement d’une méthode de sondage en « boule de neige » pour des populations difficiles à atteindre, ainsi que d’estimateurs corrigeant les possibles biais de sélection. A partir de cette méthodologie, j’ai collecté des données incluant simultanément des étudiants migrants et non-migrants du Cameroun en utilisant une plateforme internet. Un second défi relativement bien documenté est la présence d’endogénéité du choix d’éducation. Nous tirons avantage des récents développements théoriques dans le traitement des problèmes d’identification dans les modèles de choix discrets pour résoudre cette difficulté, tout en conservant la simplicité des hypothèses nécessaires. Ce travail constitue l’une des premières applications de cette méthodologie à des questions de développement. Le premier chapitre de la thèse étudie la décision prise par la famille d’investir dans la migration étudiante. Il propose un modèle structurel empirique de choix discret qui reflète à la fois le rendement brut de la migration et la contrainte budgétaire liée au problème de choix des agents. Nos résultats démontrent que le choix du niveau final d’éducation, les résultats académiques et l’aide de la famille sont des déterminants importants de la probabilité d’émigrer, au contraire du genre qui ne semble pas affecter très significativement la décision familiale. Le second chapitre s’efforce de comprendre comment les agents décident de leur participation à la décision de migration et comment la famille partage les profits et décourage le phénomène de « passagers clandestins ». D’autres résultats dans la littérature sur l’identification partielle nous permettent de considérer des comportements stratégiques au sein de l’unité familiale. Les premières estimations suggèrent que le modèle « unitaire », où un agent représentatif maximise l’utilité familiale ne convient qu’aux familles composées des parents et de l’enfant. Les aidants extérieurs subissent un cout strictement positif pour leur participation, ce qui décourage leur implication. Les obligations familiales et sociales semblent expliquer les cas de participation d’un aidant, mieux qu’un possible altruisme de ces derniers. Finalement, le troisième chapitre présente le cadre théorique plus général dans lequel s’imbriquent les modèles développés dans les précédents chapitres. Les méthodes d’identification et d’inférence présentées sont spécialisées aux jeux finis avec information complète. Avec mes co-auteurs, nous proposons notamment une procédure combinatoire pour une implémentation efficace du bootstrap aux fins d’inférences dans les modèles cités ci-dessus. Nous en faisons une application sur les déterminants du choix familial de soins à long terme pour des parents âgés. / International migration of students is a costly investment for family units in many developing countries. However, it might yield substantial financial and social return for the investors, as well as externalities for other family members. Furthermore, when these family decisions aggregate at the country-level, they affect the stock of human capital available to the origin country. This thesis addresses primarily two aspects of international student migration: (i) Who goes? What are the determinants of the probability of migration? (ii) Who pays? How does the family organize to bear the cost of the migration? Engaging in this study, one faces the challenge of data limitation, a direct consequence of the geographical dispersion of the population of interest. The first important contribution of this work is to provide a new snowball sampling methodology for hard-to-reach population, along with estimators to correct selection-biases. I collected data which include both migrant and non-migrant students from Cameroon, using an online-platform. A second challenge is the well-documented problem of endogeneity of the educational attainment. I take advantage of recent advances in the treatment of identification problems in discrete choice models to solve this issue while keeping assumptions at a low level. In particular, validity of the partial identification methodology does not rest on the existence of an instrument. To the best of my knowledge, this is the first empirical application of this methodology to development related issues. The first chapter studies the decision made by a family to invest in student. I propose an empirical structural decision model which reflects the importance of both the return of the investment and the budgetary constraint in agent choices. Our results show that the choice of level of education, the help of the family and academic results in secondary school are significant determinant of the probability to migrate, unlike the gender which does not seem to play any role in the family decision. The objective of the second chapter is to understand how agents decide to be part of the migration project and how the family organizes itself to share profits and discourage free riding-behavior. Further results on partial identification for games of incomplete information allow us to consider strategic behavior of family. My estimation suggests that models with a representative individual suit only families which consist of parent and child, but are rejected when a significant extended family member is introduced. Helpers incur a non-zero cost of participation that discourages involvement in the migration process. Kinship obligations and not altruism appears as the main reason of participation. Finally, the third chapter presents the more general theoretical framework in which my models are imbedded. The method presented is specialized to infinite games of complete information, but is of interest for application to the empirical analysis of instrumental variable models of discrete choice (Chapter 1), cooperative and non-cooperative games (Chapter 2), as well as revealed preference analysis. With my co-authors, we propose an efficient combinatorial bootstrap procedure for inference in games of complete information that runs in linear computing time and an application to the determinants of long term elderly care choices.

O objetivo principal do presente trabalho é oferecer métodos alternativos de previsão da arrecadação tributária federal, baseados em metodologias de séries temporais, inclusive com a utilização de variáveis explicativas, que reflitam a influência do cenário macroeconômico na arrecadação tributária, com o intuito de melhorar a acurácia da previsão da arrecadação. Para tanto, foram aplicadas as metodologias de modelos dinâmicos univariados, multivariados, quais sejam, Função de Transferência, Auto-regressão Vetorial (VAR), VAR com correção de erro (VEC), Equações Simultâneas, e de modelos Estruturais. O trabalho tem abrangência regional e limita-se à análise de três séries mensais da arrecadação, relativas ao Imposto de Importação, Imposto Sobre a Renda das Pessoas Jurídicas e Contribuição para o Financiamento da Seguridade Social - Cofins, no âmbito da jurisdição do estado de São Paulo, no período de 2000 a 2007. Os resultados das previsões dos modelos acima citados são comparados entre si, com a modelagem ARIMA e com o método dos indicadores, atualmente utilizado pela Secretaria da Receita Federal do Brasil (RFB) para previsão anual da arrecadação tributária, por meio da raiz do erro médio quadrático de previsão (RMSE). A redução média do RMSE foi de 42% em relação ao erro cometido pelo método dos indicadores e de 35% em relação à modelagem ARIMA, além da drástica redução do erro anual de previsão. A utilização de metodologias de séries temporais para a previsão da arrecadação de receitas federais mostrou ser uma alternativa viável ao método dos indicadores, contribuindo para previsões mais precisas, tornando-se ferramenta segura de apoio para a tomada de decisões dos gestores. / The main objective of this work is to offer alternative methods for federal tax revenue forecasting, based on methodologies of time series, inclusively with the use of explanatory variables, which reflect the influence of the macroeconomic scenario in the tax collection, for the purpose of improving the accuracy of revenues forecasting. Therefore, there were applied the methodologies of univariate dynamic models, multivariate, namely, Transfer Function, Vector Autoregression (VAR), VAR with error correction (VEC), Simultaneous Equations, and Structural Models. The work has a regional scope and it is limited to the analysis of three series of monthly tax collection of the Import Duty, the Income Tax Law over Legal Entities Revenue and the Contribution for the Social Security Financing Cofins, under the jurisdiction of the state of São Paulo in the period from 2000 to 2007. The results of the forecasts from the models above were compared with each other, with the ARIMA moulding and with the indicators method, currently used by the Secretaria da Receita Federal do Brasil (RFB) to annual foresee of the tax collection, through the root mean square error of approximation (RMSE). The average reduction of RMSE was 42% compared to the error committed by the method of indicators and 35% of the ARIMA model, besides the drastic reduction in the annual forecast error. The use of time-series methodologies to forecast the collection of federal revenues has proved to be a viable alternative to the method of indicators, contributing for more accurate predictions, becoming a safe support tool for the managers decision making process.

La migration internationale d’étudiants est un investissement couteux pour les familles dans beaucoup de pays en voie de développement. Cependant, cet investissement est susceptible de générer des bénéfices financiers et sociaux relativement importants aux investisseurs, tout autant que des externalités pour d’autres membres de la famille. Cette thèse s’intéresse à deux aspects importants de la migration des étudiants internationaux : (i) Qui part? Quels sont les déterminants de la probabilité de migration? (ii) Qui paie? Comment la famille s’organise-t-elle pour couvrir les frais de la migration? (iii) Qui y gagne? Ce flux migratoire est-il au bénéfice du pays d’origine? Entreprendre une telle étude met le chercheur en face de défis importants, notamment, l’absence de données complètes et fiables; la dispersion géographique des étudiants migrants en étant la cause première. La première contribution importante de ce travail est le développement d’une méthode de sondage en « boule de neige » pour des populations difficiles à atteindre, ainsi que d’estimateurs corrigeant les possibles biais de sélection. A partir de cette méthodologie, j’ai collecté des données incluant simultanément des étudiants migrants et non-migrants du Cameroun en utilisant une plateforme internet. Un second défi relativement bien documenté est la présence d’endogénéité du choix d’éducation. Nous tirons avantage des récents développements théoriques dans le traitement des problèmes d’identification dans les modèles de choix discrets pour résoudre cette difficulté, tout en conservant la simplicité des hypothèses nécessaires. Ce travail constitue l’une des premières applications de cette méthodologie à des questions de développement. Le premier chapitre de la thèse étudie la décision prise par la famille d’investir dans la migration étudiante. Il propose un modèle structurel empirique de choix discret qui reflète à la fois le rendement brut de la migration et la contrainte budgétaire liée au problème de choix des agents. Nos résultats démontrent que le choix du niveau final d’éducation, les résultats académiques et l’aide de la famille sont des déterminants importants de la probabilité d’émigrer, au contraire du genre qui ne semble pas affecter très significativement la décision familiale. Le second chapitre s’efforce de comprendre comment les agents décident de leur participation à la décision de migration et comment la famille partage les profits et décourage le phénomène de « passagers clandestins ». D’autres résultats dans la littérature sur l’identification partielle nous permettent de considérer des comportements stratégiques au sein de l’unité familiale. Les premières estimations suggèrent que le modèle « unitaire », où un agent représentatif maximise l’utilité familiale ne convient qu’aux familles composées des parents et de l’enfant. Les aidants extérieurs subissent un cout strictement positif pour leur participation, ce qui décourage leur implication. Les obligations familiales et sociales semblent expliquer les cas de participation d’un aidant, mieux qu’un possible altruisme de ces derniers. Finalement, le troisième chapitre présente le cadre théorique plus général dans lequel s’imbriquent les modèles développés dans les précédents chapitres. Les méthodes d’identification et d’inférence présentées sont spécialisées aux jeux finis avec information complète. Avec mes co-auteurs, nous proposons notamment une procédure combinatoire pour une implémentation efficace du bootstrap aux fins d’inférences dans les modèles cités ci-dessus. Nous en faisons une application sur les déterminants du choix familial de soins à long terme pour des parents âgés. / International migration of students is a costly investment for family units in many developing countries. However, it might yield substantial financial and social return for the investors, as well as externalities for other family members. Furthermore, when these family decisions aggregate at the country-level, they affect the stock of human capital available to the origin country. This thesis addresses primarily two aspects of international student migration: (i) Who goes? What are the determinants of the probability of migration? (ii) Who pays? How does the family organize to bear the cost of the migration? Engaging in this study, one faces the challenge of data limitation, a direct consequence of the geographical dispersion of the population of interest. The first important contribution of this work is to provide a new snowball sampling methodology for hard-to-reach population, along with estimators to correct selection-biases. I collected data which include both migrant and non-migrant students from Cameroon, using an online-platform. A second challenge is the well-documented problem of endogeneity of the educational attainment. I take advantage of recent advances in the treatment of identification problems in discrete choice models to solve this issue while keeping assumptions at a low level. In particular, validity of the partial identification methodology does not rest on the existence of an instrument. To the best of my knowledge, this is the first empirical application of this methodology to development related issues. The first chapter studies the decision made by a family to invest in student. I propose an empirical structural decision model which reflects the importance of both the return of the investment and the budgetary constraint in agent choices. Our results show that the choice of level of education, the help of the family and academic results in secondary school are significant determinant of the probability to migrate, unlike the gender which does not seem to play any role in the family decision. The objective of the second chapter is to understand how agents decide to be part of the migration project and how the family organizes itself to share profits and discourage free riding-behavior. Further results on partial identification for games of incomplete information allow us to consider strategic behavior of family. My estimation suggests that models with a representative individual suit only families which consist of parent and child, but are rejected when a significant extended family member is introduced. Helpers incur a non-zero cost of participation that discourages involvement in the migration process. Kinship obligations and not altruism appears as the main reason of participation. Finally, the third chapter presents the more general theoretical framework in which my models are imbedded. The method presented is specialized to infinite games of complete information, but is of interest for application to the empirical analysis of instrumental variable models of discrete choice (Chapter 1), cooperative and non-cooperative games (Chapter 2), as well as revealed preference analysis. With my co-authors, we propose an efficient combinatorial bootstrap procedure for inference in games of complete information that runs in linear computing time and an application to the determinants of long term elderly care choices.

Thesis (MComm)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: As a direct result of having segregated amenities and public services during the Apartheid era where Black individuals were provided with services inferior to those of White individuals, the country is currently challenged by serious and debilitating issues such as a skills shortage across most industry sectors, high unemployment and poverty rates, and inequality in terms of income distribution as well as in terms of racial representation in the workforce. The country is furthermore facing social problems such as high crime rates and high incidence of HIV/AIDS. A discussion is put forward that these challenges are the consequence of a larger problem. The larger problem being the fact that knowledge, skills and abilities are not uniformly distributed across all races. The situation is that in the past, and still now, White South Africans have greater access to skills development and educational opportunities. It is this fundamental cause that must be addressed to in order to create a sustainable solution to the challenges described above. It is therefore argued that a means to overcome the challenges the country faces as a result of Apartheid is through skills development – specifically affirmative action skills development. Affirmative action skills development will entail giving previously disadvantaged Black individuals access to skills development and educational opportunities as to equip them with the currently deficit skills, knowledge, and abilities. It is proposed that affirmative action skills development is one of the most effective mechanisms through which the aforementioned problems facing the country might be alleviated. A need was therefore identified for Industrial Psychology researchers to assist organisations to identify the individuals who would gain maximum benefit from such affirmative action skills development opportunities. To achieve this, an understanding is required of the factors that determine whether or not a learner will be successful if entered into an affirmative action skills development opportunity. Some studies have already been conducted regarding this need. One such study was conducted by de Goede (2007). The primary objective of this study consequently was to expand on De Goede’s (2007) learning potential structural model. Non-cognitive factors were added to the De Goede (2007) learning potential structural model in order to gain a deeper understanding of the complexity underlying learning and the determinants of learning performance. A subset of the hypothesised learning potential structural model was then empirically evaluated. The measurement model was found to have a good fit. However, the first analysis of the structural model failed to produce a good fit to the data. The analysis of the standardised residuals for the structural model suggested the addition of paths to the existing structural would probably improve the fit of the model. Modification indices calculated as part of the structural equation modeling pointed out specific additions to the existing model that would improve the fit. The model was subsequently modified by both adding additional paths. Furthermore, when considering the modification of an initially proposed structural model, the question should not only be whether any additional paths should be added, but should also include the question whether any of the existing paths should be removed. To this end the unstandardised beta and gamma matrices were examined and it pointed to insignificant paths that could be removed. The model was subsequently also modified by removing insignificant paths. The final revised structural model was found to fit the data well. All paths contained in the final model were empirically corroborated. The practical implications of the learning potential structural model on HR and organisations are discussed. Suggestions for future research are made by indicating how the model can be further elaborated. The limitations of the study are also discussed. / AFRIKAANSE OPSOMMING: ‘n Resultaat van Apartheid is dat Suid Afrika dringende uitdagings in die gesig staar soos byvoorbeeld lae vaardigheidsvlakke, hoë vlakke van werkloosheid en armoede, en ongelykheid in terme van inkomste en verteenwordiging in die werksmag. Suid Afrika het onder meer ook die uitdagings van hoë vlakke van misdaad en HIV/VIGS. Hierdie tesis stel voor dat die bogenoemde uitdagings simptome is van ‘n groter probleem, naamlik gebrekkige opleiding en ontwikkeling van vaardighede van Swart Suid Afrikaners. Dit is hierdie gebrek aan vaardighede wat aangespreek moet word om ‘n volhoubare oplossing tot die bogenoemde uitdagings te vind. Die argument word gestel dat ‘n oplossing gevind sal word in regstellende ontwikkeling. Regstellende ontwikkeling behels om voorheen benadeelde Swart Suid Afrikaners toegang te gee tot opleidings en ontwikkelingsgeleenthede. Dit word gestel dat regstellende ontwikkeling die meganisme is waardeur die land se uitdagings aangespreek moet word. ‘n Behoefte is dus geïdentifiseer vir Bedryfsielkundiges om navorsing te doen aangaande die eienskappe van studente wat sal bepaal of hulle suksesvol, al dan nie, sal wees tydens versnelde regstellende ontwikkeling. ‘n Soortgelyke studie is reeds onderneem deur de Goede (2007). Die primêre doelwit van hierdie studie was gevolglik om De Goede (2007) se leerpotensiaal-strukturele model uit te brei. Nie-kognitiewe faktore is tot De Goede (2007) se model toegegevoeg om ’n meer indringende begrip van die kompleksiteit onderliggend aan leer en die determinante van leerprestasie te verkry. ‘n Subversameling van die voorgestelde leerpotensiaal-strukturele model is vervolgens empiries geëvalueer. Dit is gevind dat die metingsmodel die data goed pas. Met die eerste analise van die strukturele model is goeie passing nie verkry nie. ‘n Ondersoek na die gestandardiseerde residue het getoon dat die toevoeging van addisionele bane tot die bestaande strukturele model waarskynlik die passing van die model sou verbeter. Modifikasie-indekse bereken as deel van die strukturele vergelykingsmodellering het spesifieke bane uitgewys wat die passing van die model sou verbeter indien dit bygevoeg word tot die bestaande model. Die strukturele model is dus aangepas deur addisionele bane by te voeg tot die bestaande model. Die strukturele model is ook aangepas deur bane te verwyder wat nie statisties beduidend was nie. Die bevinding was dat die hersiene model die data goed pas. Alle bane in die finale model is empiries bevestig.

O objetivo principal do presente trabalho é oferecer métodos alternativos de previsão da arrecadação tributária federal, baseados em metodologias de séries temporais, inclusive com a utilização de variáveis explicativas, que reflitam a influência do cenário macroeconômico na arrecadação tributária, com o intuito de melhorar a acurácia da previsão da arrecadação. Para tanto, foram aplicadas as metodologias de modelos dinâmicos univariados, multivariados, quais sejam, Função de Transferência, Auto-regressão Vetorial (VAR), VAR com correção de erro (VEC), Equações Simultâneas, e de modelos Estruturais. O trabalho tem abrangência regional e limita-se à análise de três séries mensais da arrecadação, relativas ao Imposto de Importação, Imposto Sobre a Renda das Pessoas Jurídicas e Contribuição para o Financiamento da Seguridade Social - Cofins, no âmbito da jurisdição do estado de São Paulo, no período de 2000 a 2007. Os resultados das previsões dos modelos acima citados são comparados entre si, com a modelagem ARIMA e com o método dos indicadores, atualmente utilizado pela Secretaria da Receita Federal do Brasil (RFB) para previsão anual da arrecadação tributária, por meio da raiz do erro médio quadrático de previsão (RMSE). A redução média do RMSE foi de 42% em relação ao erro cometido pelo método dos indicadores e de 35% em relação à modelagem ARIMA, além da drástica redução do erro anual de previsão. A utilização de metodologias de séries temporais para a previsão da arrecadação de receitas federais mostrou ser uma alternativa viável ao método dos indicadores, contribuindo para previsões mais precisas, tornando-se ferramenta segura de apoio para a tomada de decisões dos gestores. / The main objective of this work is to offer alternative methods for federal tax revenue forecasting, based on methodologies of time series, inclusively with the use of explanatory variables, which reflect the influence of the macroeconomic scenario in the tax collection, for the purpose of improving the accuracy of revenues forecasting. Therefore, there were applied the methodologies of univariate dynamic models, multivariate, namely, Transfer Function, Vector Autoregression (VAR), VAR with error correction (VEC), Simultaneous Equations, and Structural Models. The work has a regional scope and it is limited to the analysis of three series of monthly tax collection of the Import Duty, the Income Tax Law over Legal Entities Revenue and the Contribution for the Social Security Financing Cofins, under the jurisdiction of the state of São Paulo in the period from 2000 to 2007. The results of the forecasts from the models above were compared with each other, with the ARIMA moulding and with the indicators method, currently used by the Secretaria da Receita Federal do Brasil (RFB) to annual foresee of the tax collection, through the root mean square error of approximation (RMSE). The average reduction of RMSE was 42% compared to the error committed by the method of indicators and 35% of the ARIMA model, besides the drastic reduction in the annual forecast error. The use of time-series methodologies to forecast the collection of federal revenues has proved to be a viable alternative to the method of indicators, contributing for more accurate predictions, becoming a safe support tool for the managers decision making process.

Submitted by Marco Antonio Oliveira da Silva (maosilva@ipen.br) on 2016-08-26T11:39:00Z No. of bitstreams: 0 / Made available in DSpace on 2016-08-26T11:39:00Z (GMT). No. of bitstreams: 0 / O presente estudo tem por objetivo geral identificar os critérios utilizados na tomada de decisão do orientador em aceitar ou não um candidato a orientando e analisar as possíveis relações dessa decisão com a sua produção acadêmica e a evasão de seus orientados. Para o cumprimento desses objetivos buscou-se identificar e analisar os critérios de seleção de candidatos para os programas de mestrado e de doutorado em um Programa de Pós-Graduação, no caso do Instituto de Pesquisas Energéticas e Nucleares - IPEN, e mais especificamente, procurou-se estudar semelhanças e diferenças desses critérios entre os orientadores; verificar se existe correlação entre os critérios de seleção e as características (perfil) do orientador; identificar o processo de seleção utilizado pelos orientadores e apontar quais as possíveis motivações que levam à evasão segundo a visão desses orientadores. Para responder a tais desafios, como ponto de partida da pesquisa, foi elaborado um modelo conceitual da pesquisa, que serviu de base para a elaboração do roteiro de entrevistas com questões abertas para a identificação dos critérios de seleção utilizados por um grupo pequeno e com um perfil pré-definido de orientadores. Na sequência, a partir das respostas obtidas nas entrevistas, a pesquisa foi ampliada para todos os orientadores do programa de pós-graduação do IPEN mediante a aplicação de uma pesquisa online por meio do aplicativo Google Docs para coleta de dados. Em seguida, esses dados foram analisados e reorganizados segundo um modelo operacional de pesquisa que orientaria a análise através da Modelagem de Equações Estruturais (MEE) com o uso do software SmartPLS, cujo objetivo é identificar a existência ou não de correlação entre os critérios adotados pelos orientadores e sua produção acadêmica e a Evasão dos orientados, para isso nos apoiamos em nossos estudos em: Bazerman e Moore (2010); Hair Jr. et al (2009); Hansmann e Ringle (2004); Martins (1997); Ringle, C.; Silva e Bido (2014); Sousa (2007); Sousa e Yu (2014); Torres (2014); Yu (2011). A metodologia da pesquisa acima descrita pode ser definida como um estudo exploratório que combina aspectos qualitativos e quantitativos. Como conclusão da pesquisa, constatou-se que existem critérios tanto subjetivos como objetivos de escolha dos orientadores, que estão associados à produção acadêmica, esses se apresentam com média intensidade, e que os orientadores que valorizam mais os critérios subjetivos na seleção dos orientandos estão associados a uma maior produção acadêmica do que aqueles que valorizam mais os critérios objetivos. Dentre os critérios subjetivos, destacou-se o critério da disponibilidade enquanto dentre os critérios objetivos destacou-se a experiência. Com relação à evasão não foi possível neste estudo associar os critérios de seleção a esta variável dependente. Os resultados aqui apresentados sugerem que os critérios de escolha por um orientador de Pós-Graduação podem estar associados à produção acadêmica desse orientador. Por outro lado, vale destacar que esses resultados se encontram limitados ao de um Programa de Pós-Graduação. / Dissertação (Mestrado em Tecnologia Nuclear) / IPEN/D / Instituto de Pesquisas Energéticas e Nucleares - IPEN-CNEN/SP

The main aim of my final thesis is to familiar reader with different ways of measuring credit risk by means of particular structural models of credit risk. This issue has been already described by foreign authors. Though, neither Czech nor Slovak economists have been deeply involved in this topic so far. For this reason, I have decided to focus on those models and both describe them as well as put them into the practice. My final thesis gradually focus on individual detailed model description in each chapter in following sequence: Credit Metrics, Black-School model, Merton model, KMV, Credit Grades. Moreover, it also targets model's construction as well as practical application. Regarding practical model's application, Black-School model is applied on IBM and KMV on Kraft Foods Company. Admittedly, that proves the fact that structural models are not only theoretical models, but also practical models applyable on real companies. Finally, I will compare all above mentioned models in selected parameters.

„Comorbidity“ among mental disorders is commonly observed in both clinical and epidemiological samples. The robustness of this observation is rarely questioned; however, what is at issue is its meaning. Is comorbidity „noise“ – nuisance covariance that researchers should eliminate by seeking „pure“ cases for their studies – or a „signal“ – an indication that current diagnostic systems are lacking in parsimony and are not „carving nature at its joints?“ (Krueger, p. 921). With these words, Krueger started a discussion on the structure of mental disorders, which suggested that a 3-factor model of common mental disorders existed in the community. These common factors were labeled „anxious-misery,“ „fear“ (constituting facets of a higher-order internalizing factor), and „externalizing.“ Along with similar evidence from personality research and psychometric explorations and selective evidence from genetic and psychopharmacologic studies, Krueger suggested that this model might not only be phenotypically relevant, but might actually improve our understanding of core processes underlying psychopathology. Since then, this suggestion has become an influential, yet also controversial topic in the scientific community, and has received attention particularly in the context of the current revision process of the Manual of Mental Disorders (Fifth Edition) (DSM-V) and the International Classification of Diseases, 11th Revision (ICD-11). Focusing on anxiety disorders, this article critically discusses the methods and findings of this work, calls into question the model’s developmental stability and utility for clinical use and clinical research, and challenges the wide-ranging implications that have been linked to the findings of this type of exploration. This critical appraisal is intended to flag several significant concerns about the method. In particular, the concerns center around the tendency to attach wide-ranging implications (eg, in terms of clinical research, clinical practice, public health, diagnostic nomenclature) to the undoubtedly interesting statistical explorations.

Introduction: The current development strategy of population pharmacokinetic models is a complex and iterative process that is manually performed by modellers. Such a strategy is time-demanding, subjective, and dependent on the modellers’ experience. This thesis presents a novel model building tool that automates the development process of pharmacokinetic (PK) structural models. Methods: Modelsearch is a tool in Pharmpy library, an open-source package for pharmacometrics modelling, that searches for the best structural model using an exhaustive stepwise search algorithm. Given a dataset, a starting model and a pre-specified model search space of structural model features, the tool creates and fits a series of candidate models that are then ranked based on a selection criterion, leading to the selection of the best model. The Modelsearch tool was used to develop structural models for 10 clinical PK datasets (5 orally and 5 i.v. administered drugs). A starting model for each dataset was generated using the assemblerr package in R, which included a first-order (FO) absorption without any absorption delay for oral drugs, one-compartment disposition, FO elimination, a proportional residual error model, and inter-individual variability on the starting model parameters with a correlation between clearance (CL) and central volume of distribution (VC). The model search space included aspects of absorption and absorption delay (for oral drugs), distribution and elimination. In order to understand the effects of different IIV structures on structural model selection, five model search approaches were investigated that differ in the IIV structure of candidate models: 1. naïve pooling, 2. IIV on starting model parameters only, 3. additional IIV on mean delay time parameter, 4. additional diagonal IIVs on newly added parameters, and 5. full block IIVs. Additionally, the implementation of structural model selection in the workflow of the fully automatic model development was investigated. Three strategies were evaluated: SIR, SRI, and RSI depending on the development order of structural model (S), IIV model (I) and residual error model (R). Moreover, the NONMEM errors encountered when using the tool were investigated and categorized in order to be handled in the automatic model building workflow. Results: Differences in the final selected structural models for each drug were observed between the five different model search approaches. The same distribution components were selected through Approaches 1 and 2 for 6/10 drugs. Approach 2 has also identified an absorption delay component in 4/5 oral drugs, whilst the naïve pooling approach only identified an absorption delay model in 2 drugs. Compared to Approaches 1 and 2, Approaches 3, 4 and 5 tended to select more complex models and more often resulted in minimization errors during the search. For the SIR, SRI and RSI investigations, the same structural model was selected in 9/10 drugs with a significant higher run time in RSI strategy compared to the other strategies. The NONMEM errors were categorized into four categories based on the handling suggestions which is valuable to further improve the tool in its automatic error handling. Conclusions: The Modelsearch tool was able to automatically select a structural model with different strategies of setting the IIV model structure. This novel tool enables the evaluation of numerous combinations of model components, which would not be possible using a traditional manual model building strategy. Furthermore, the tool is flexible and can support multiple research investigations for how to best implement structural model selection in a fully automatic model development workflow.