yes / This note highlights the value of using UQR for addressing the limitations inherent within previous methods involving conditional parameter distributions for spending analysis (QR and OLS). Using unique data and robust analysis using improved methods, our paper clearly demonstrates the over-importance attached to length of stay and the inadequate attention given to business travelers in previous research. There are clear benefits from UQR’s methodological robustness for assessing the multitude of variables related to tourist expenditures, particularly given UQR’s ability to inform across the spending distribution. Given tourism’s importance for the UK it is critical for expensive promotional activities to be targeted efficiently for ensuring effective policy making.

Yes / We employ unconditional quantile regression with region of origin fixed effects, whereby we find that attending live football matches significantly increases expenditures by inbound tourist in the UK, and surprisingly we find that such effects are strongest for those who overall spend the least. Higher spending individuals spend significantly more than those who do not attend football matches, even when such individuals are otherwise similar. We analyse the impact of football attendance across the tourism expenditure distribution which is a relatively neglected aspect within previous research.

Yes / The inbound tourist expenditure generating role of football (soccer), particularly the English Premier League 15 (EPL) is evaluated. An enhanced economic and management understanding of the role of regular sporting fixtures emerges, as well as quantification of their impact. Expenditure on football tickets is isolated to identify local economic spillovers outside the stadium walls. Using the UK International Passenger Survey, unconditional quantile regressions (UQR) is used to evaluate the distributional impact of football attendance on tourist expenditures. Both total expenditure and a new measure which adjusts expenditures for football ticket prices are considered. UQR is a novel technique which is as yet underexploited within sport economics and confers important methodological advantages over both OLS and quantile regressions. Significant cross quantile variation is found. High spending football fans spend more, even after ticket prices are excluded. Surprisingly, spending effects owing to attendance are strongest for those who overall spend the least, confirming the role of sport as a generator of tourist expenditure unlike most others. Though the attendance effect is smaller for higher aggregate spenders, there is nevertheless a significant impact across the distribution. Distributional expenditure impacts highlight clear differentials between attendance by high and low spenders. Similar analysis is applicable to other global brands such as the National Football League (NFL) in the United States (American football) and the Indian Premier (cricket) League. The EPL’s global popularity can be leveraged for achieving enhanced tourist expenditure.

Yes / Using International Passenger Survey (2017) data, this paper employs unconditional quantile regression (UQR) to analyse the determinants of tourist expenditure amongst inbound tourists to the United Kingdom. UQR allows us to estimate heterogeneous effects at any quantile of the distribution of the dependent variable. It overcomes the econometric limitations of ordinary least squares and quantile regression based estimates typically used to investigate tourism expenditures. However, our results reveal that the effects of our explanatory variables change across the distribution of tourist expenditure. This has important implications for those tasked with devising policies to enhance the UK’s tourist flows and expenditures.

This paper applies and extends Machado and Mata's parametric quantile decomposition method and a similar nonparametric technique to explore changes in welfare in Zimbabwe between 1995 and 2001. These methods allow us to construct a counterfactual distribution in order to decompose the shift into the part due to changes in endowments and that due to changes in returns. We examine two subsets of a nationally representative dataset and find that endowments had a positive effect but that returns account for more of the difference. In communal farming areas, the effect of returns was positive while, in urban Harare, it was negative. / Master of Science

No description available.

In this thesis, we introduce a concept of directional quantile envelopes, the intersection of the halfspaces determined by directional quantiles, and show that they allow for explicit probabilistic interpretation, compared to other multivariate quantile concepts. Directional quantile envelopes provide a way to perform multivariate quantile regression: to ``regress contours'' on covariates. We also develop theory and algorithms for an important application of multivariate quantile regression in biometry: bivariate growth charts. We prove that directional quantiles are continuous and derive their closed-form expression for elliptically symmetric distributions. We provide probabilistic interpretations of directional quantile envelopes and establish that directional quantile envelopes are essentially halfspace depth contours. We show that distributions with smooth directional quantile envelopes are uniquely determined by their envelopes. We describe an estimation scheme of directional quantile envelopes and prove its affine equivariance. We establish the consistency of the estimates of directional quantile envelopes and describe their accuracy. The results are applied to estimation of bivariate extreme quantiles. One of the main contributions of this thesis is the construction of bivariate growth charts, an important application of multivariate quantile regression. We discuss the computation of our multivariate quantile regression by developing a fast elimination algorithm. The algorithm constructs the set of active halfspaces to form a directional quantile envelope. Applying this algorithm to a large number of quantile halfspaces, we can construct an arbitrary exact approximation of the direction quantile envelope. In the remainder of the thesis, we exhibit the connection between depth contours and directional regression quantiles (Laine, 2001), stated without proof in Koenker (2005). Our proof uses the duality theory of primal-dual linear programming. Aiming at interpreting halfspace depth contours, we explore their properties for empirical distributions, absolutely continuous distributions and certain general distributions. Finally, we propose a generalized quantile concept, depth quantile, inspired by halfspace depth (Tukey, 1975) and regression depth (Rousseeuw and Hubert, 1999). We study its properties in various data-analytic situations: multivariate and univariate locations, regression with and without intercept. In the end, we show an example that while the quantile regression of Koenker and Bassett (1978) fails, our concept provides sensible answers. / Statistics

Cette thèse de doctorat est une première tentative d'examiner si les réglementations bancaires ont le même impact sur la stabilité et l'efficience des banques islamiques que sur celles des banques conventionnelles. Suite aux nouvelles recommandations de Bâle III, nous étudions l'impact des exigences minimales en matière de fonds propres, de liquidité et de levier financier sur la stabilité et l'efficience des banques islamiques comparativement aux banques conventionnelles. Une première étude exploratoire utilise l'analyse en composantes principales (ACP), les méthodes Logit et Probit et les régressions MCO pour montrer que les banques islamiques disposent d'un capital plus élevé, qu'elles sont plus liquides, plus profitables, mais moins stables que leurs homologues conventionnelles. Une deuxième étude empirique examine la stabilité des banques islamiques et utilise la régression quantile pour montrer que les banques islamiques sont moins stables que les banques classiques. L'étude prouve également que des exigences de fonds propres renforcées améliorent la stabilité des banques islamiques les plus petites et les plus liquides, tandis que le levier financier est négativement associé à la stabilité de ce type de banques. Des contraintes de liquidité plus fortes renforcent la stabilité des grandes banques islamiques alors que l'effet est inverse pour les petites banques. Enfin, nous examinons l'efficience des banques islamiques en utilisant la méthode d'enveloppement des données (DEA). Nous constatons que les banques islamiques sont plus efficientes que les banques conventionnelles. Nous trouvons aussi que des exigences de capital et de liquidité accrues pénalisent l'efficience des petites banques islamiques très liquides, alors que l'inverse est vrai pour le levier financier. Ces résultats montrent notamment qu'en matière de réglementation du capital pour les petites banques islamiques très liquides, un choix est à opérer entre une efficience accrue ou une stabilité renforcée. / This PhD dissertation is the first attempt to examine whether banking regulations have the same impact on the stability and the efficiency of Islamic than for conventional banks. We benefit of Basel III recommendations to investigate the impact of bank capital, liquidity and leverage requirements on the stability and the efficiency of Islamic banks compared to conventional banks. A first exploratory study uses Principal Component Analysis, Logit and Probit methods, and OLS regressions and shows that Islamic banks have higher capital, liquidity, and profitability, but that they are less stable than their conventional counterparts. A second empirical study examines the stability of Islamic banks using conditional quantile regressions and proves that Islamic banks are less stable than conventional banks. It also shows that higher capital and lower leverage improve the adjusted profits of small and highly liquid Islamic banks. Liquidity is positively associated with the stability of large Islamic banks while an opposite effect is detected when small Islamic banks are examined. Finally, we study the efficiency of Islamic banks using Data Envelopment Analysis (DEA) and find that Islamic banks are more efficient than conventional banks. We also find that higher capital and liquidity requirements penalize the efficiency of small and highly liquid Islamic banks, while the opposite is true for financial leverage. These results show that concerning capital requirements for small and highly liquid Islamic banks, a possible trade-off could be found between stability and efficiency.

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

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