In dieser Dissertation werden neue Methoden zur Erfassung zweier Risikoarten entwickelt. Markrisiko ist definiert als das Risiko, auf Grund von Wertrückgängen in Wertpapierportfolios Geld zu verlieren. Systemisches Risiko bezieht sich auf das Risiko des Zusammenbruchs eines Finanzsystems, das durch die Notlage eines einzelnen Finanzinstituts entsteht. Im Zuge der Finanzkrise 2007–2009 realisierten sich beide Risiken, was weltweit zu hohen Verlusten für Investoren, Unternehmen und Steuerzahler führte. Vor diesem Hintergrund besteht sowohl bei Finanzinstituten als auch bei Regulierungsbehörden Interesse an neuen Ansätzen für das Risikomanagement. Die Gemeinsamkeit der in dieser Dissertation entwickelten Methoden besteht darin, dass unterschiedliche Quantilsregressionsansätze in neuartiger Weise für das Finanzrisikomanagement verwendet werden. Zum einen wird nichtparametrische Quantilsregression mit Extremwertmethoden kombiniert, um extreme Markpreisänderungsrisiken zu prognostizieren. Das resultierende Value at Risk (VaR) Prognose- Modell für extremeWahrscheinlichkeiten wird auf internationale Aktienindizes angewandt. In vielen Fällen schneidet es besser ab als parametrische Vergleichsmodelle. Zum anderen wird ein Maß für systemisches Risiko, das realized systemic risk beta, eingeführt. Anders als bereits existierende Messgrößen erfasst es explizit sowohl Risikoabhängigkeiten zwischen Finanzinstituten als auch deren individuelle Bilanzmerkmale und Finanzsektor-Indikatoren. Um die relevanten Risikotreiber jedes einzelnen Unternehmens zu bestimmen, werden Modellselektionsverfahren für hochdimensionale Quantilsregressionen benutzt. Das realized systemic risk beta entspricht dem totalen Effekt eines Anstiegs des VaR eines Unternehmens auf den VaR des Finanzsystems. Anhand von us-amerikanischen und europäischen Daten wird gezeigt, dass die neue Messzahl sich gut zur Erfassung und Vorhersage systemischen Risikos eignet. / This thesis develops new methods to assess two types of financial risk. Market risk is defined as the risk of losing money due to drops in the values of asset portfolios. Systemic risk refers to the breakdown risk for the financial system induced by the distress of individual companies. During the financial crisis 2007–2009, both types of risk materialized, resulting in huge losses for investors, companies, and tax payers all over the world. Therefore, considering new risk management alternatives is of interest for both financial institutions and regulatory authorities. A common feature of the models used throughout the thesis is that they adapt quantile regression techniques to the context of financial risk management in a novel way. Firstly, to predict extreme market risk, nonparametric quantile regression is combined with extreme value theory. The resulting extreme Value at Risk (VaR) forecast framework is applied to different international stock indices. In many situations, its performance is superior to parametric benchmark models. Secondly, a systemic risk measure, the realized systemic risk beta, is proposed. In contrast to exististing measures it is tailored to account for tail risk interconnections within the financial sector, individual firm characteristics, and financial indicators. To determine each company’s relevant risk drivers, model selection techniques for high-dimensional quantile regression are employed. The realized systemic risk beta corresponds to the total effect of each firm’s VaR on the system’s VaR. Using data on major financial institutions in the U.S. and in Europe, it is shown that the new measure is a valuable tool to both estimate and forecast systemic risk.

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

La croissance économique et ses moteurs représentent le principal sujet préoccupant les chercheurs en macroéconomie depuis longtemps. Investir en capital humain à travers le système éducatif joue un rôle important pour stimuler la croissance et le développement économique, cette accentuation a pris place depuis la naissance innovante de la théorie de la croissance endogène. L'attention et les efforts dévoués à l'investissement dans le capital humain peuvent être déstabilisés par le retour global et récent de la crise de la dette souveraine dans plusieurs pays, dette qui poursuit son ascension depuis 2007, et les politiques d'ajustement nécessaires d'après-crise. Des judicieuses politiques de redressement devraient être composées d'un mélange des activités encourageant la croissance économique, y compris l'investissement dans le capital humain, l'austérité et le long terme. L'objectif principal de cette thèse est de fournir des nouvelles évidences empiriques sur la relation dette-croissance économique et leurs externalités sur la formation de capital humain, les estimations sont réalisées sur un jeu de données récent et complet couvrant 22 années et 76 pays dans le monde. L'ensemble des variables utilisées englobe de nombreux agrégats macroéconomiques tel que : taux de croissance annuel du PIB, la dette publique en % de PIB, les dépenses publiques d'éducation en % de PIB, le moyen d'année de scolarité, le taux d'inflation, et d'autres. En utilisant une technique d'estimation semi-paramétrique appropriée qui offre des solutions pour de nombreux problèmes concernant les données, les résultats empiriques suggèrent un impact négatif et hétérogène de dette et des dépenses d'éducation publiques sur la croissance du PIB. Là où, l'utilisation des dépenses d'éducation dans l'ensemble de l'échantillon est inefficace, les décideurs politiques devraient ajuster et bien gérer la fonction de ces dépenses en même temps de viser des efforts publics pour réduire les niveaux élevés d'endettement et d'augmenter la croissance économique. Nous montrons également que l'utilisation des outils d'analyse textuelle en économie, offre une lecture rapide et globale des courants de recherche contenus dans la littérature empirique et théorique de la croissance économique. / Economic growth and its driving forces have been the maintopic preoccupying economic researchers since long time in macroeconomic branch. Public investment in human capital through educational system plays an ultimate role in boosting economic growth and development, this role has taken a place since the innovative dawn of endogenous growth theory. The focus and efforts of investing in human capital could be destabilized by the global and recent return of sovereign debt crisis in several countries, which continues its rise since theearly 2007, and the after-crisis necessary adjusting policies. Getting back wise policies should be composed of mixture of growth fostering activities, including the investment in human capital, austerity and forbearance.The main purpose of this thesis is to provide new empirical inferences on debt-growth relationship and its interaction with human capital formation. Estimates are carried on a recent and complete data set that spans over 22 years and involves 76 countries worldwide. The range of invested variables encompasses many macroeconomic aggregates such as : GDP annual growthrates, public debt to GDP ratio, and public education expenditure to GDP ratio, average schooling years, inflation rate, and others. Using a superior estimation semi-parametric technic which accounts for some data issues, the empirical results suggest a heterogeneous impact of public debt and education expenditures levels on GDP growth rates. Henceforth, the use of education expenditure in the whole sample is inefficient,where policy makers should adjust and well manage the function of these expenditure in line with the public efforts to reduce debt high levels and rise economic growth. We also show that the use of textual analysis tools in economic studies, such in growth literature, offers a rapid and total lecture of the hidden research trends embodied in the huge empirical and theoretical literature of economic growth.

L'Analyse des Données Fonctionnelles est un domaine important et dynamique en statistique. Elle offre des outils efficaces et propose de nouveaux développements méthodologiques et théoriques en présence de données de type fonctionnel (fonctions, courbes, surfaces, ...). Le travail exposé dans cette thèse apporte une nouvelle contribution aux thèmes de l'apprentissage statistique et des quantiles conditionnels lorsque les données sont assimilables à des fonctions. Une attention particulière a été réservée à l'utilisation de la technique Support Vector Machines (SVM). Cette technique fait intervenir la notion d'Espace de Hilbert à Noyau Reproduisant. Dans ce cadre, l'objectif principal est d'étendre cette technique non-paramétrique d'estimation aux modèles conditionnels où les données sont fonctionnelles. Nous avons étudié les aspects théoriques et le comportement pratique de la technique présentée et adaptée sur les modèles de régression suivants. Le premier modèle est le modèle fonctionnel de quantiles de régression quand la variable réponse est réelle, les variables explicatives sont à valeurs dans un espace fonctionnel de dimension infinie et les observations sont i.i.d.. Le deuxième modèle est le modèle additif fonctionnel de quantiles de régression où la variable d'intérêt réelle dépend d'un vecteur de variables explicatives fonctionnelles. Le dernier modèle est le modèle fonctionnel de quantiles de régression quand les observations sont dépendantes. Nous avons obtenu des résultats sur la consistance et les vitesses de convergence des estimateurs dans ces modèles. Des simulations ont été effectuées afin d'évaluer la performance des procédures d'inférence. Des applications sur des jeux de données réelles ont été considérées. Le bon comportement de l'estimateur SVM est ainsi mis en évidence. / Functional Data Analysis is an important and dynamic area of statistics. It offers effective new tools and proposes new methodological and theoretical developments in the presence of functional type data (functions, curves, surfaces, ...). The work outlined in this dissertation provides a new contribution to the themes of statistical learning and quantile regression when data can be considered as functions. Special attention is devoted to use the Support Vector Machines (SVM) technique, which involves the notion of a Reproducing Kernel Hilbert Space. In this context, the main goal is to extend this nonparametric estimation technique to conditional models that take into account functional data. We investigated the theoretical aspects and practical attitude of the proposed and adapted technique to the following regression models.The first model is the conditional quantile functional model when the covariate takes its values in a bounded subspace of the functional space of infinite dimension, the response variable takes its values in a compact of the real line, and the observations are i.i.d.. The second model is the functional additive quantile regression model where the response variable depends on a vector of functional covariates. The last model is the conditional quantile functional model in the dependent functional data case. We obtained the weak consistency and a convergence rate of these estimators. Simulation studies are performed to evaluate the performance of the inference procedures. Applications to chemometrics, environmental and climatic data analysis are considered. The good behavior of the SVM estimator is thus highlighted.

住宅本身特性和鄰里環境為影響住宅價格價格高低之主要因素，環境特徵通因素常透過公共設施反映，設施越完善表示鄰里生活機能及可及性越高，產生正面效應使得住宅價格提升；鄰避設施產生的負面外部性導致居住品質下降，造成住宅價格降低。然現有文獻多數偏向針對特定的公共設施類型分析，相對少見到同時針對多樣設施進行全面性研究，缺乏生活設施面向的實證及設施服務水準衡量。 本研究運用特徵價格理論結合地理資訊系統，界定多項重大設施與生活設施；以等級衡量生活設施服務水準，並建構最小平方及分量迴歸模型自動分群探討設施之量增趨勢對住宅總價影響，以對設施作全面性研究。本研究採用臺北市2011年7月至2015年9月不動產交易實價登錄樣本與設施資料為對象。實證結果顯示，住宅總價主要受交通便利性和開放空間效益影響，生活設施水準對總價為正向影響，顯示生活機能具有正面效益。設施影響係數依序為捷運站0.0774、主題公園0.0307、餐飲0.0283、大專院校0.0219、大型醫院0.0193、殯葬設施-0.0190、學校0.0124、市場0.0057、鄰里公園0.0042及便利商店-0.0018。本研究進而探討不同總價下的設施影響效果發現，隨著住宅總價從低到高，各項生活設施的影響下降，低總價住宅主要受到生活機能和開放空間等鄰里環境影響，設施的便利性大於可及性效益；高總價住宅以負面外部性、文教及開放空間效益和就醫便利為主要影響，設施的便利效益不顯著。 / House pricing is strongly affected by its characteristics and neighborhood environment. Neighborhood characteristics are usually reflected by public facilities. The better the facilities are, the higher quality and convenience of the life results in a positive effect on housing price. The negative externalities of the NIMBY (not-in-my-back-yard) facilities lead to a decline in the quality of living and a reduction in housing prices. However, most of the existing literatures tend to focus on specific types of public facility. In this paper, more detailed study on the effects of overall facilities is proposed. In this research, the overall influence of facilities service level on house pricing is the focus. The proposed regression models are based on Hedonic price theory combined with geographic information system (GIS) to automatically cluster (or quantize) the facility numbers. The clustering is used for evaluating the relationships between facility number and housing price. Those overall facilities are categorized into two groups, important and community facilities. The provided different service levels of community facilities are defined. The real estate sales database in Taipei City from July 2012 to Sept. 2015 along with facilities is used for the evaluations. The evaluated results show that the total price is mainly affected by the convenience of transport and open space benefits, the service levels of community facilities have a positive effect. The impacts of the facilities are in the order of MRT, theme parks, restaurants, Universities, large hospitals, funeral facilities, schools, markets, neighborhood parks and convenience stores. Theme parks, the service level of community facilities and universities have higher impacts on those low-priced property while. funeral facilities, theme parks and large hospitals have higher impacts on high-priced one. One more finding is that the impacts of the service level of community facilities has declined with the increase in total housing prices. Low-priced property is mainly affected by the neighborhood environment and open space because facilities convenience is greater than the accessibility. High-priced property is mainly affected by the negative externalities, education, open space and access to medical care.

O objetivo primordial deste trabalho é analisar se a democracia é uma instituição política que produz resultados econômicos menos desiguais do que os regimes autoritários. A importância deste tema reside no fato que a própria promoção da democracia na agenda da política internacional tornou-se fundamental por inúmeras razões entre as quais sua suposta propensão em reduzir estas disparidades econômicas. Em primeiro lugar apresentamos no Capítulo 1 um balanço da discussão teórica e empírica a partir da qual constatamos que, a despeito do senso comum de que a democracia está relacionada a uma cidadania mais igualitária, os seus efeitos sobre a desigualdade ainda são discutíveis. Mesmo existindo um razoável consenso teórico de que os regimes democráticos devem, de alguma forma, produzir uma melhor distribuição de bens, os resultados empíricos são inconclusivos e contraditórios. Em seguida, diante de tal impasse empírico, propomos no Capítulo 2 uma reformulação da argumentação na qual entendemos que os efeitos da democracia sobre a desigualdade devem ser reinterpretados. A principal contribuição da tese reside na constatação, tanto teórica quanto empírica, de que estes efeitos são heterogêneos e interagem com o próprio nível de desigualdade, e, por conseguinte, é equivocado o suposto de que esses efeitos são homogêneos e independentes do contexto sócio-econômico da desigualdade. No Capítulo 3 apresentamos os dados e os conceitos de democracia e desigualdade. Assumimos que democracia se caracteriza como o regime político no qual os líderes competem entre si por meio de eleições e verificamos se os seus efeitos variam ao longo da própria distribuição de desigualdade econômica mensurada pelo coeficiente de GINI. Para tal análise, realizamos uma série de modelos de regressão quantílica, a metodologia adequada para avaliar o debate sobre a heterogeneidade versus homogeneidade dos efeitos. O argumento teórico, a partir do qual elabora-se a hipótese dos efeitos heterogêneos, refere-se à necessidade de uma convergência entre os interesses eleitorais dos partidos o lado da oferta e as clivagens sobre as quais uma potencial maioria dos eleitores tem interesse em ser atendido o lado da demanda por políticas públicas e plataformas. Isto posto, é 9 necessário discutir as condições que estimulam as lideranças políticas a utilizarem o problema da desigualdade econômica como argumento eleitoral e as condições nas quais surge uma demanda dos cidadãos por redistribuição via ação estatal. Somente nas sociedades mais desiguais tanto os partidos políticos têm interesse em ofertar políticas redistributivas, quanto tende a surgir no seio da cidadania uma demanda por redistribuição por parte de uma maioria de eleitores. No Capítulo 4 comprovamos empiricamente que os efeitos da competição democrática em sociedades mais desiguais são diferentes seus efeitos em sociedades mais iguais; e estes efeitos estão em direção à maior redução da desigualdade apenas nas sociedades mais desiguais. Os resultados são robustos às mais diferentes especificações dos modelos estatísticos, dados e formas de mensuração, tanto de democracia quanto de desigualdade, em diferentes cortes temporais e horizontes históricos de análise. Inclusive quando estendemos o recorte temporal para antes do pós-2ª Guerra Mundial utilizando dados que abrangem o período de surgimento dos primeiros regimes representativos democráticos no século XIX, a veracidade das hipóteses dos efeitos heterogêneos e de que há maior contundência da democracia em direção à redução da desigualdade nas sociedades mais desiguais permanece. Por fim, além deste problema teórico e empírico de crucial importância, também controlamos a análise para a potencial relação recíproca entre democracia e desigualdade. Enquanto parte da literatura discute os potenciais efeitos igualitários da democracia, outra importante literatura debate se o aumento da desigualdade aumenta ou reduz a probabilidade de um país tornar-se ou manter-se democrático. Posto isto, apresentamos uma lista de variáveis instrumentais para estimar validamente os efeitos da democracia sobre a desigualdade independente da relação entre desigualdade e democracia / The primary aim of this study is to analyze whether democracy is a political institution that produces less unequal economic outcomes than authoritarian regimes. The importance of this issue lies in the fact that the very promotion of democracy in the international political agenda has become essential for many reasons, including its supposed propensity to reduce economic disparities. First, at Chapter 1 we overview the theoretical and empirical discussion from which we find that despite the common sense that democracy must be related to a more egalitarian citizenship, its effects on inequality is still debatable. Even with a reasonable theoretical consensus that democracies must somehow produce a better distribution of goods; the empirical results are inconclusive and contradictory. After that, facing such empirical impasse, we propose at Chapter 2 a reformulation about the rationale to explain and analyze the effects of democracy on inequality. The main contribution of this thesis lies in both the theoretical and the empirical claim that these effects are heterogeneous and should interact with the level of inequality and, therefore, the assumption that these effects are homogeneous and independent of the socio-economic context of inequality is wrong. In Chapter 3, we present the data and concepts of democracy and inequality. We assume that democracy is characterized as a political regime in which leaders compete through elections and we test whether the effects vary along the distribution of economic inequality measured by the Gini coefficient. To do that, we conducted a series of quantile regression models, appropriate to evaluate the alternative hypothesis whether the effects are heterogeneous or homogenous. The theoretical argument, from which we elaborate the hypothesis of heterogeneous effects, refers to the need for a convergence between the electoral interests of the parties - the supply side - and the political cleavages on which a majority of voters have potential interest being played - the demand side for other public policies and platforms. Hence, it is necessary to discuss the conditions that lead the political leadership to use the problem of economic 11 inequality as an electoral argument and the conditions under which a demand by citizens for redistribution via state action rises. Only at the most unequal societies the political parties have an interest in offering redistributive policies, as well as there is a higher propensity for a redistribution demand by a majority of voters. In Chapter 4, we proved empirically that the effects of democratic competition at more unequal societies are different from the effects of democracy in more equal societies; and these effects tend to be greater toward inequality reduction only at more unequal societies. These results are robust to different statistical model specifications, data and measurement methods, about both democracy and inequality, and to the use of different time horizons. Even when we extend the time frame of the analysis to the period before World War II - using new data that covers XIX century, the veracity of the hypotheses about the heterogeneous effects and that these effects of democracy toward the reduction of inequality are larger at the most unequal societies remains intact. Finally, beyond this theoretical and empirical issue of crucial importance, we also control the analysis for potential reciprocal relationship between democracy and inequality. This is because while much of the literature discusses the potential effects of egalitarian democracy, another important literature debate discusses whether greater inequality increases or reduces the probability of a country become or remain democratic. Hence, we present a list of valid instrumental variables to estimate the effects of democracy on inequality independent of the relationship between inequality and democracy

Σκοπός της παρούσας διατριβής είναι η μελέτη της επίδρασης των εφαρμοζόμενων διδακτικών στρατηγικών για την διδασκαλία της Χρηματοοικονομικής στη διαμόρφωση των μαθησιακών στρατηγικών των φοιτητών και στην ανάπτυξη των δεξιοτήτων κριτικής σκέψης, με την χρησιμοποίηση της οικονομετρικής τεχνικής της quantile regression (QR). Η επισκόπηση της διεθνούς βιβλιογραφίας καθώς και η έρευνα για την παρούσα διατριβή δείχνουν, αφενός ότι στους συγγενείς επιστημονικούς χώρους της Οικονομικής, της Χρηματοοικονομικής και της Λογιστικής εφαρμόζονται διδακτικές στρατηγικές που βασίζονται στη μέθοδο των διαλέξεων και φαίνεται να επηρεάζουν την διαμόρφωση των μαθησιακών στρατηγικών και αφετέρου ότι η χρησιμοποίηση διδακτικών στρατηγικών ενεργού εμπλοκής των φοιτητών στην μάθηση μπορεί πράγματι να επηρεάζει τη διαμόρφωση των μαθησιακών στρατηγικών και να συμβάλλει στην ανάπτυξη δεξιοτήτων κριτικής σκέψης. Από την ως άνω επισκόπηση έχει καταφανεί ότι η στατιστική ανάλυση των ως άνω επιδράσεων στηρίζεται, κατά το πλείστον, σε υπολογισμό συντελεστών συσχέτισης, σε ανάλυση της διακύμανσης καθώς και στην χρησιμοποίηση της κλασικής παλινδρόμησης. Η διαμόρφωση των μαθησιακών στρατηγικών εκτιμάται μέσα από την διαμόρφωση των τρόπων και τύπων μάθησης των φοιτητών, με τη χρησιμοποίηση του Learning Style Inventory (LSI) του Kolb και του Learning Styles Questionnaire (LSQ) των Honey και Mumford. Με το LSI (που χρησιμοποιήθηκε και στις δυο φάσεις της έρευνας) εκτιμάται η προτίμηση προς τέσσερεις τρόπους μάθησης (Απτή Εμπειρία, Στοχαστική Παρατήρηση, Αφηρημένη Αντίληψη Εννοιών και Ενεργός Πειραματισμός), με βάση τους οποίους προκύπτουν τέσσερεις τύποι μάθησης (Αποκλίνων, Αφομοιωτικός, Συγκλίνων και Διευκολύνων). Για την εκτίμηση του επιπέδου ανάπτυξης των δεξιοτήτων κριτικής σκέψης των φοιτητών, χρησιμοποιείται το California Critical Thinking Skills Test (CCTST), δημιουργημένο από τον Peter Facione με βάση τα συμπεράσματα της Delphi Report (American Philosophical Association). Το CCTST εκτιμά πέντε επιμέρους δεξιότητες κριτικής σκέψης (Ανάλυση, Αξιολόγηση, Συμπερασμός, Επαγωγικός και Απαγωγικός Συλλογισμός) καθώς και την συνολική ικανότητα στις δεξιότητες κριτικής σκέψης. Η έρευνα δια την συγκέντρωση παρατηρήσεων διενεργήθηκε σε δυο φάσεις: στην πρώτη εκτιμήθηκαν μόνο οι τρόποι και τύποι μάθησης με τη χρήση των LSQ και LSI και στην δεύτερη εκτιμήθηκαν οι τρόποι και τύποι μάθησης με τη χρήση μόνο του LSI καθώς και οι δεξιότητες κριτικής σκέψης με τη χρήση του CCTST. Η στατιστική ανάλυση των δεδομένων της έρευνας στηρίζεται στη χρησιμοποίηση του οικονομετρικού μοντέλου της quantile regression (QR), με το οποίο μπορούν να υπολογιστούν συντελεστές ακόμη και για τα 99 εκατοστημόρια της κατανομής της εξαρτημένης μεταβλητής, αυξάνοντας θεαματικά την αντλούμενη πληροφόρηση, έναντι της κλασικής παλινδρόμησης. Προκύπτει έτσι ένα σημαντικό ερμηνευτικό πλεονέκτημα, το οποίο φωτίζει την επίδραση που ασκείται σε όλο το εύρος της κατανομής και συμβάλλει στην εκτενέστερη και βαθύτερη κατανόηση των ασκούμενων επιδράσεων. Αυτή η δυνατότητα έχει κατ’ εξοχήν σημασία στην ερμηνεία της αλλαγής της προτίμησης από τον έναν τρόπο μάθησης στον διαμετρικά αντίθετό του και την ενδιάμεση κατάσταση της ισορροπημένης μάθησης, για κάθε μια από τις δυο διαστάσεις μάθησης του μοντέλου Εμπειρικής Μάθησης του Kolb. Η QR χρησιμοποιείται επίσης για την έρευνα της επίδρασης των διαμορφωμένων τρόπων και τύπων μάθησης στην ανάπτυξη των δεξιοτήτων κριτικής σκέψης. Θεωρητικά υποστηρίζεται ότι ο Συγκλίνων μαθήτυπος του μοντέλου του Kolb υπερτερεί στην επίδοση στις δεξιότητες κριτικής σκέψης, υπόθεση που δεν τεκμηριώνεται στην περίπτωση που αναπτύσσεται ισορροπημένη προτίμηση προς τους τέσσερεις τρόπους μάθησης. Οι εν λόγω επιδράσεις τεκμηριώνονται με την ανάλυση των δεδομένων από την πειραματική εφαρμογή διδακτικού μοντέλου ενεργού εμπλοκής των φοιτητών στην διαδικασία διδασκαλίας-μάθησης της Χρηματοοικονομικής με τη χρήση της QR. Τα βασικά συμπεράσματα της παρούσας διατριβής είναι τα εξής: α) Το μαθησιακό περιβάλλον που διαμορφώνεται από την εκάστοτε εφαρμοζόμενη διδακτική στρατηγική επιδρά διαφορετικά σε κάθε τμήμα της κατανομής της εξαρτημένης μεταβλητής. β) Η ανάπτυξη ισορροπημένης προτίμησης προς τους τρόπους μάθησης είναι επωφελέστερη, έναντι της επιλεκτικής προτίμησης, για την ανάπτυξη δεξιοτήτων κριτικής σκέψης. γ) Η διάδραση που αναπτύσσεται μεταξύ των φοιτητών σε ομάδες που απαρτίζονται από διαφορετικούς τύπους μάθησης ασκεί σημαντική επίδραση στην ανάπτυξη ισορροπημένης μάθησης και στη βελτίωση του επιπέδου των δεξιοτήτων κριτικής σκέψης. δ) Η εκτίμηση πολλών συντελεστών παλινδρόμησης με την χρήση της QR διευρύνει σημαντικά την ερμηνεία των επιδράσεων των ανεξάρτητων στις εξαρτημένες μεταβλητές, έναντι άλλων απλών στατιστικών μέτρων καθώς και της κλασικής παλινδρόμησης. ε) Στον τομέα της διδασκαλίας στον επιστημονικό χώρο της Χρηματοοικονομικής στην Ελλάδα, η παρούσα εργασία είναι μοναδική και πρωτότυπη και η συμβολή της είναι καθολική, αναδεικνύοντας ταυτόχρονα ένα οικονομετρικό μοντέλο – την QR – σε ερμηνευτικό εργαλείο των σχέσεων που αναπτύσσονται στην διδακτική πράξη. / The aim of this dissertation is the study of the effect of the implemented teaching strategies in Finance teaching on the formation of students’ learning strategies and development of critical thinking skills, by using the econometric model of quantile regression (QR). The review of the relevant literature, as well as the research for this dissertation show that on the one hand the implemented teaching strategies in the related disciplines of Economics, Finance and Accounting are mainly based on the use of the lecture method and seem to affect the formation of students’ learning strategies and on the other hand the use of teaching strategies that involve students in the teaching-learning process may affect the formation of students’ learning strategies and contribute to the development of critical thinking skills as well. The literature review also shows that statistical analysis of effects is mostly based on correlation coefficients and analysis of variance, as well as the use of traditional regression. The formation of students’ learning strategies is estimated through student learning styles and types, by the use of Kolb’s Learning Style Inventory (LSI) and Honey & Mumford’s Learning Styles Questionnaire (LSQ). By the use of the LSI (which has been used in both phases of the relative research), student preferences towards four learning styles (Concrete Experience, Reflective Observation, Abstract Conceptualization and Active Experimentation) are estimated. Based on the relevant preference for two consecutive learning styles, in the order depicted above, four learning types may occur: Divergers, Assimilators, Convergers, and Accommodators. The California Critical Thinking Skills Test (CCTST) is used for estimating the level of development of students’ critical thinking skills. This instrument has been developed by Peter Facione and is based on the results and recommendations of the Delphi Report of the American Philosophical Association. The CCTST estimates five discrete critical thinking skills, namely Analysis, Evaluation, Inference, Induction and Deduction and the overall critical thinking skills ability as well. The research for the collection of data has been carried out in two phases. In the first phase the LSQ and LSI instruments have been used for the estimation of students’ learning styles and types and in the second phase the LSI has been used for the estimation of students’ learning styles and types and the CCTST for the estimation of students’ critical thinking skills. The statistical analysis of the research data is based on the use of the econometric model of the quantile regression (QR), by which coefficients for as many as 99 percentiles of the dependent variable can be computed. In this way derived information is extremely richer than that derived by using traditional regression. This renders a significant explanatory advantage, which sheds light of the impact on the whole distribution of the dependent variable and thus it contributes to the more comprehensive and deeper understanding of the caused effect. This capability is especially important for explaining the change in the preference from one learning style to its diametrically opposite one and the interim situation of balanced learning, for each of the two dimensions of learning of Kolb’s Experiential Learning Model. QR is also used for the exploration of the impact of the formed learning styles and types on the development of critical thinking skills. Theory suggests that the Converging learning type of Kolb’s model beats the other three in critical thinking skills performance, but this suggestion is not corroborated in the case that a balanced preference towards all four learning styles is developed. The aforementioned impact is documented by the analysis of data rendered by the experimental implementation of a teaching strategy of active engagement of students in the teaching-learning process in Finance teaching, by using the QR. Basic results of this dissertation are as follows: a) The learning environment develop by the implemented teaching strategy has a different impact on each segment of the distribution of the dependent variable. b) The development of balanced preference towards the learning styles is more beneficial for critical thinking skills development than selective preference. c) The developed interactivity between students in groups made up by different learning types has a significant effect on developing balanced learning and on the improvement of the level of critical thinking skills development. d) The use of the Quantile Regression and the computation of many regression coefficients expands significantly the explanatoty potential about the impact of the independent variables on the dependent ones, against other simple statistical metres as well as traditional regression. e) Regarding the teaching endeavors of instructors in the area of Finance in Greece, this dissertation is unique and original and contributes in a total sense, while it simultaneously highlights the advantages of an econometric model – the QR – as an hermeneutic instrument for the relationships development in the teaching process.

In the present doctoral thesis, we estimated Mincer's (1974) semi logarithmic wage function for the French and Pakistani labour force data. This model is considered as a standard tool in order to estimate the relationship between earnings/wages and different contributory factors. Despite of its vide and extensive use, simple estimation of the Mincerian model is biased because of different econometric problems. The main sources of bias noted in the literature are endogeneity of schooling, measurement error, and sample selectivity. We have tackled the endogeneity and measurement error biases via instrumental variables two stage least squares approach for which we have proposed two new instrumental variables. The first instrumental variable is defined as "the average years of schooling in the family of the concerned individual" and the second instrumental variable is defined as "the average years of schooling in the country, of particular age group, of particular gender, at the particular time when an individual had joined the labour force". Schooling is found to be endogenous for the both countries. Comparing two said instruments we have selected second instrument to be more appropriate. We have applied the Heckman (1979) two-step procedure to eliminate possible sample selection bias which found to be significantly positive for the both countries which means that in the both countries, people who decided not to participate in labour force as wage worker would have earned less than participants if they had decided to work as wage earner. We have estimated a specification that tackled endogeneity and sample selectivity problems together as we found in respect to present literature relative scarcity of such studies all over the globe in general and absence of such studies for France and Pakistan, in particular. Differences in coefficients proved worth of such specification. We have also estimated model semi-parametrically, but contrary to general norm in the context of the Mincerian model, our semi-parametric estimation contained non-parametric component from first-stage schooling equation instead of non-parametric component from selection equation. For both countries, we have found parametric model to be more appropriate. We found errors to be heteroscedastic for the data from both countries and then applied adaptive estimation to control adverse effects of heteroscedasticity. Comparing simple and adaptive estimations, we prefer adaptive specification of parametric model for both countries. Finally, we have applied quantile regression on the selected model from mean regression. Quantile regression exposed that different explanatory factors influence differently in different parts of the wage distribution of the two countries. For both Pakistan and France, it would be the first study that corrected both sample selectivity and endogeneity in single specification in quantile regression framework

This thesis investigates the determinants of the use of debt and leasing in the UK using a comprehensive measure of debt and leases, in recognition of the link between lease and debt-type financing decisions, based on financial contracting theory and the tax advantage hypothesis. The design of the study takes account three lacunae in our current understanding of this topic. Firstly, despite the fact that the capital structure literature is voluminous, it is perhaps surprising that relatively little research has been carried out on lease finance, given its significant role as a major source of finance for many firms. Secondly, the role of tax in the capital structure decision is unclear. Empirically testing for tax effects is challenging because spurious relationships may exist between the financing decision and many commonly used tax proxies. More importantly, our understanding of the impact of taxes on UK financing decisions is far from complete, especially since several major corporate tax reforms have taken place in the last decade. Thirdly, empirical evidence on capital structure determinants is also voluminous but far from conclusive. Notably, contradictory signs and significance levels are commonly observed. Using the standard regression approach invariably involves identification of the average behaviour of firms, and therefore does not measure diversity across firms. In response to these three major issues, this study employs empirical research methods, namely cross-sectional pooled regression, static and dynamic panel data regression, and quantile regression to analyse a large sample of 361 non-financial firms, drawn from the FTSE 350 and FTSE All-Small indices over the tax years 1995 through 2003. The operating lease data are estimated using the constructive capitalisation method while the simulated before-financing marginal tax rate is used to proxy for the firms’ tax status. The endogeneity of corporate tax status is evident since the use of simple tax proxy, the effective tax rate, leads to a spurious negative relation between debt usage and tax rates. The problem was avoided with a better measure of tax variable that is the simulated before-financing marginal tax rate where it is found that the empirical relationships between the tax factor and debt and leasing are consistent with those theoretical predictions. Furthermore, there is a clear distinction between the effect of taxes on debt and leasing where the firm’s marginal tax status is only relevant when managers make decisions on debt financing. The use of quantile regression method in the present study represents a novel approach in investigating the determinants of the use of debt and leasing. The results reveal that the determinants of debt and leasing are heterogeneous across the whole distribution of firms, consistent with the notion of heterogeneity as promoted by Beattie et al. (2006), but contradicting their claim that the large-scale regression approach cannot measure firms’ diversity. This finding implies that average model results (e.g., from OLS or panel data models) may not apply to the tails of debt and leasing levels, and hence assuming that the determinants of debt and leasing decisions are the same for all firms in the economy is clearly unrealistic. Using the dynamic panel data model, this thesis confirms that debt and leasing are substitutes rather than complements, and that the degree of substitutability is more pronounced among smaller firms, where the degree of information asymmetry is greater. More importantly, the use of a joint specification for debt and leasing improves our understanding of the determinants of the two fixed-claim financing instruments. There is also significant evidence to support the view that firm characteristics affect contracting costs which in turn impact on the choice between alternative forms of finance, namely equity, debt and leasing.

This doctoral thesis is a collection of four papers on the analysis of the term structure of interest rates with a focus at the intersection of macroeconomics and finance. "Risk in Macroeconomic Fundamentals and Bond Return Predictability" documents that factors related to risks underlying the macroeconomy such as expectations, uncertainty and downside (upside) macroeconomic risks are able to explain variation in bond risk premia. The information provided is found to be, to a large extent, unrelated to that contained in forward rates and current macroeconomic conditions. "Out-of-sample bond excess returns predictability" provides evidence that macroeconomic variables, risks in macroeconomic outcomes as well as the combination of these different sources of information are able to generate statistical as well as economic bond excess returns predictability in an out-of-sample setting. Results suggest that this finding is not driven by revisions in macroeconomic data. The term spread (yield curve slope) is largely used as an indicator of future economic activity. "Re-examining the predictive power of the yield curve with quantile regression" provides new evidence on the predictive ability of the term spread by studying the whole conditional distribution of GDP growth. "Modeling and forecasting the yield curve by extended Nelson-Siegel class of models: a quantile regression approach" deals with yield curve prediction. More flexible Nelson-Siegel models are found to provide better fitting to the data, even when penalizing for additional model complexity. For the forecasting exercise, quantile-based models are found to overcome all competitors. / <p>Diss. Stockholm :  Stockholm School of Economics, 2014. Introduction together with 4 papers.</p>