A Influência da teoria da agência na estrutura de capital na indústria do calçado

apresentado ao Instituto de Contabilidade e Administração do Porto para a Dissertação de Mestrado para obtenção do grau de Mestre em Contabilidade e Finanças sob orientação do Mestre Adalmiro Álvaro Malheiro de Castro Andrade Pereira

Response of bat species to sylvo-pastoral abandonment

We assessed the effect of abandonment of sylvo-pastoral practices in chestnut orchards (Castanea sativa) on bats in southern Switzerland to determine practical recommendations for bat conservation. We compared bat species richness and foraging activities between traditionally managed and unmanaged chestnut orchards, testing the hypothesis that managed orchards provide better foraging opportunities and harbour more bat species. Echolocation calls of foraging bats were sampled simultaneously at paired sites of managed and unmanaged orchards using custom made recorders. Vegetation structure and aerial insect availability were sampled at the recording sites and used as explanatory variables in the model. In a paired sampling design, we found twice the number of bat species (12) and five times higher total foraging activity in the managed chestnut orchards compared to the unmanaged ones. Bat species with low flight manoeuvrability were 14 times more common in managed orchards, whereas bats with medium to high manoeuvrability were only 5 times more common than in abandoned orchards. The vegetation structure was less dense in managed orchards. However, management did not affect relative insect abundance. Bats primarily visited the most open orchards, free of undergrowth. As a result of restricted access into the overgrown forests, the abandonment of chestnut orchards leads to a decline in bat species richness and foraging activities. Continued management of chestnut orchards to maintain an open structure is important for the conservation of endangered bat species in the southern Swiss Alps.

Développement et évaluation d’une intervention visant la prise optimale d’un traitement antirétroviral des personnes vivant avec le VIH

La prise optimale d’un traitement antirétroviral est la clé du succès de ces traitements. Cette prise devrait être d’au moins 95 % des médicaments antirétroviraux prescrits afin de supprimer à long terme la réplication virale et donc de restaurer et de préserver la fonction immunologique. Cependant, les personnes vivant avec le virus de l’immunodéficience humaine (PVVIH) éprouvent des difficultés à adopter et à maintenir ce niveau de prise dans le temps. Bien que certaines interventions aient démontré leur capacité à faciliter ce comportement, au Québec il n’y a pas d’intervention systématique pour soutenir ces personnes dans la prise quotidienne de ces traitements. Le but de cette étude était donc de développer et d’évaluer une intervention pour faciliter le comportement de prise optimale d’un traitement antirétroviral chez des personnes vivant avec le VIH. Pour guider le développement de l’intervention, la démarche appelée « intervention mapping » a été suivie. Le cadre théorique proposé par Godin et ses collègues (2005) qui inclut le sentiment d’efficacité personnelle et les attitudes positives face à la prise optimale d’un traitement antirétroviral a été ainsi utilisé non seulement pour prédire et expliquer le comportement de prise, mais aussi pour élaborer l’intervention. Selon ce modèle, le soutien social, la satisfaction envers les professionnels et le fait de ne pas ressentir d’effets indésirables sont autant de facteurs modifiables associés au sentiment d’efficacité personnelle et aux attitudes positives. L’intervention développée visait l’acquisition et la mobilisation des habiletés nécessaires pour influencer ces facteurs en vue de rehausser le sentiment d’efficacité personnelle et les attitudes positives ainsi que pour faciliter ce comportement. Cette intervention comportait quatre rencontres d’une durée de 45 à 75 minutes, s’échelonnant sur 12 semaines, avec une infirmière iii possédant une expertise en VIH. L’évaluation de l’effet de cette intervention sur le comportement et les variables explicatives a été effectuée à l’aide d’un essai clinique avec répartition aléatoire. La principale variable résultat a été mesurée à l’aide d’un questionnaire autoadministré, de la charge virale et du nombre de CD4. Autant la variable résultat principale que les variables explicatives ont été mesurées avant l’intervention et après celle-ci, soit à 12 et 24 semaines. L’échantillon était constitué de 51, personnes vivant avec le VIH et suivies dans une clinique à Montréal : 23 dans le groupe contrôle et 28 dans le groupe expérimental. Des analyses de variance (ANOVA) à mesures répétées ont été réalisées afin d’analyser l’effet de l’intervention sur la prise optimale d’un traitement antirétroviral et les autres variables intermédiaires dans le temps. Les résultats montrent une tendance positive (p = 0,056) quant à l’obtention d’une charge virale indétectable dans le groupe intervention. Ainsi, 43,8 % plus de personnes du groupe expérimental comparativement au groupe contrôle (78,6 % versus 34,8 %) avaient une charge virale indétectable à 12 semaines et 32,8 % de plus à 24 semaines (89,3 % versus 56,5 %). Bien qu’aucun effet significatif ait été trouvé en regard des variables explicatives, probablement à cause d’un manque de puissance statistique, les légères augmentations observées dans le groupe expérimental sont cohérentes avec le modèle théorique utilisé (Godin & al., 2005). Cette étude contribue à l’avancement des connaissances en proposant une intervention pour faciliter la prise optimale d’un traitement antirétroviral chez des personnes vivant avec le VIH.

L’arbre de régression multivariable et les modèles linéaires généralisés revisités : applications à l’étude de la diversité bêta et à l’estimation de la biomasse d’arbres tropicaux

En écologie, dans le cadre par exemple d’études des services fournis par les écosystèmes, les modélisations descriptive, explicative et prédictive ont toutes trois leur place distincte. Certaines situations bien précises requièrent soit l’un soit l’autre de ces types de modélisation ; le bon choix s’impose afin de pouvoir faire du modèle un usage conforme aux objectifs de l’étude. Dans le cadre de ce travail, nous explorons dans un premier temps le pouvoir explicatif de l’arbre de régression multivariable (ARM). Cette méthode de modélisation est basée sur un algorithme récursif de bipartition et une méthode de rééchantillonage permettant l’élagage du modèle final, qui est un arbre, afin d’obtenir le modèle produisant les meilleures prédictions. Cette analyse asymétrique à deux tableaux permet l’obtention de groupes homogènes d’objets du tableau réponse, les divisions entre les groupes correspondant à des points de coupure des variables du tableau explicatif marquant les changements les plus abrupts de la réponse. Nous démontrons qu’afin de calculer le pouvoir explicatif de l’ARM, on doit définir un coefficient de détermination ajusté dans lequel les degrés de liberté du modèle sont estimés à l’aide d’un algorithme. Cette estimation du coefficient de détermination de la population est pratiquement non biaisée. Puisque l’ARM sous-tend des prémisses de discontinuité alors que l’analyse canonique de redondance (ACR) modélise des gradients linéaires continus, la comparaison de leur pouvoir explicatif respectif permet entre autres de distinguer quel type de patron la réponse suit en fonction des variables explicatives. La comparaison du pouvoir explicatif entre l’ACR et l’ARM a été motivée par l’utilisation extensive de l’ACR afin d’étudier la diversité bêta. Toujours dans une optique explicative, nous définissons une nouvelle procédure appelée l’arbre de régression multivariable en cascade (ARMC) qui permet de construire un modèle tout en imposant un ordre hiérarchique aux hypothèses à l’étude. Cette nouvelle procédure permet d’entreprendre l’étude de l’effet hiérarchisé de deux jeux de variables explicatives, principal et subordonné, puis de calculer leur pouvoir explicatif. L’interprétation du modèle final se fait comme dans une MANOVA hiérarchique. On peut trouver dans les résultats de cette analyse des informations supplémentaires quant aux liens qui existent entre la réponse et les variables explicatives, par exemple des interactions entres les deux jeux explicatifs qui n’étaient pas mises en évidence par l’analyse ARM usuelle. D’autre part, on étudie le pouvoir prédictif des modèles linéaires généralisés en modélisant la biomasse de différentes espèces d’arbre tropicaux en fonction de certaines de leurs mesures allométriques. Plus particulièrement, nous examinons la capacité des structures d’erreur gaussienne et gamma à fournir les prédictions les plus précises. Nous montrons que pour une espèce en particulier, le pouvoir prédictif d’un modèle faisant usage de la structure d’erreur gamma est supérieur. Cette étude s’insère dans un cadre pratique et se veut un exemple pour les gestionnaires voulant estimer précisément la capture du carbone par des plantations d’arbres tropicaux. Nos conclusions pourraient faire partie intégrante d’un programme de réduction des émissions de carbone par les changements d’utilisation des terres.

Networks of PhD Students and Academic Performance: A Comparison across Countries

In this article we compare regression models obtained to predict PhD students’ academic performance in the universities of Girona (Spain) and Slovenia. Explanatory variables are characteristics of PhD student’s research group understood as an egocentered social network, background and attitudinal characteristics of the PhD students and some characteristics of the supervisors. Academic performance was measured by the weighted number of publications. Two web questionnaires were designed, one for PhD students and one for their supervisors and other research group members. Most of the variables were easily comparable across universities due to the careful translation procedure and pre-tests. When direct comparison was not possible we created comparable indicators. We used a regression model in which the country was introduced as a dummy coded variable including all possible interaction effects. The optimal transformations of the main and interaction variables are discussed. Some differences between Slovenian and Girona universities emerge. Some variables like supervisor’s performance and motivation for autonomy prior to starting the PhD have the same positive effect on the PhD student’s performance in both countries. On the other hand, variables like too close supervision by the supervisor and having children have a negative influence in both countries. However, we find differences between countries when we observe the motivation for research prior to starting the PhD which increases performance in Slovenia but not in Girona. As regards network variables, frequency of supervisor advice increases performance in Slovenia and decreases it in Girona. The negative effect in Girona could be explained by the fact that additional contacts of the PhD student with his/her supervisor might indicate a higher workload in addition to or instead of a better advice about the dissertation. The number of external student’s advice relationships and social support mean contact intensity are not significant in Girona, but they have a negative effect in Slovenia. We might explain the negative effect of external advice relationships in Slovenia by saying that a lot of external advice may actually result from a lack of the more relevant internal advice

Determinantes de la estructura de capital en Colombia una aproximación de regresión por cuartiles

Con el objetivo de conocer la influencia de los diferentes niveles de apalancamiento en el crecimiento de las empresas colombianas, surge la necesidad de responder la siguiente pregunta: ¿qué determina la elección de estructura de capital de las firmas? La regresión por cuantiles permite examinar toda la distribución de las firmas y no solo una medida de la tendencia central de la distribución de la estructura de capital. De esta manera se puede evaluar la importancia relativa de las diferentes variables explicativas en diferentes puntos de la distribución del apalancamiento de las firmas. Razón por la cual se utilizará esta aproximación; sin embargo también se utilizará el método de regresión para datos de panel (también llamado datos longitudinales) con efectos aleatorios, para comparar resultados, esto teniendo en cuenta que los datos no sólo varían entre observaciones sino también en el tiempo. De esta manera, aplicar el método de regresión por cuantiles, permite darle una mirada más profunda a la elección del nivel de apalancamiento, pues permite discriminar el efecto de las variables entre firmas altamente apalancadas y bajamente apalancadas.

Academic achievement in sciences: the role of preferences and educative assets

This paper provides new evidence on the effect of pupil’s self-motivation and academic assets allocation on the academic achievement in sciences across countries. By using the Programme for International Student Assessment 2006 (PISA 2006) test we find that both explanatory variables have a positive effect on student’s performance. Self-motivation is measured through an instrument that allows us to avoid possible endogeneity problems. Quantile regression is used for analyzing the existence of different estimated coefficients over the distribution. It is found that both variables have different effect on academic performance depending on the pupil’s score. These findings support the importance of designing focalized programs for different populations, especially in terms of access to information and communication technologies such as internet.

Comparing meta-analysis and ecological-longitudinal analysis in time-series studies: a case study of the effects of air pollution on mortality in three Spanish cities

The objective of this paper is to introduce a diVerent approach, called the ecological-longitudinal, to carrying out pooled analysis in time series ecological studies. Because it gives a larger number of data points and, hence, increases the statistical power of the analysis, this approach, unlike conventional ones, allows the complementation of aspects such as accommodation of random effect models, of lags, of interaction between pollutants and between pollutants and meteorological variables, that are hardly implemented in conventional approaches. Design—The approach is illustrated by providing quantitative estimates of the short-termeVects of air pollution on mortality in three Spanish cities, Barcelona,Valencia and Vigo, for the period 1992–1994. Because the dependent variable was a count, a Poisson generalised linear model was first specified. Several modelling issues are worth mentioning. Firstly, because the relations between mortality and explanatory variables were nonlinear, cubic splines were used for covariate control, leading to a generalised additive model, GAM. Secondly, the effects of the predictors on the response were allowed to occur with some lag. Thirdly, the residual autocorrelation, because of imperfect control, was controlled for by means of an autoregressive Poisson GAM. Finally, the longitudinal design demanded the consideration of the existence of individual heterogeneity, requiring the consideration of mixed models. Main results—The estimates of the relative risks obtained from the individual analyses varied across cities, particularly those associated with sulphur dioxide. The highest relative risks corresponded to black smoke in Valencia. These estimates were higher than those obtained from the ecological-longitudinal analysis. Relative risks estimated from this latter analysis were practically identical across cities, 1.00638 (95% confidence intervals 1.0002, 1.0011) for a black smoke increase of 10 μg/m3 and 1.00415 (95% CI 1.0001, 1.0007) for a increase of 10 μg/m3 of sulphur dioxide. Because the statistical power is higher than in the individual analysis more interactions were statistically significant,especially those among air pollutants and meteorological variables. Conclusions—Air pollutant levels were related to mortality in the three cities of the study, Barcelona, Valencia and Vigo. These results were consistent with similar studies in other cities, with other multicentric studies and coherent with both, previous individual, for each city, and multicentric studies for all three cities

Métodos de estadística espacial para evaluar la influencia de factores medioambientales sobre la incidencia y mortalidad por cáncer

Los objetivos de la tesis son: 1.- Estudiar la relación entre la incidencia y mortalidad por cáncer y los factores medioambientales, en particular la contaminación atmosférica, controlando por factores socioeconómicos. 2.- Utilizar aquellos métodos de estadística espacial apropiados para cada tipo de diseño. 3.- Distinguir en los modelos las diferentes fuentes de extra-variabilidad espacial. 4.- Controlar el problema de exceso de ceros inherente a alguna de las neoplasias de interés medioambientales. Conclusiones: - Tanto la incidencia como la mortalidad de las neoplasias, presentaron dos fuentes de extravariación. La extravariaicón espacial, por la que unidades vecinas tienden a presentar razones de incidencia/mortalidad similares, y la heterogeneidad no espacial. En general la extravariabilidad espacial ha resultado ser mucho mayor que la no espacial. - Para suavizar las RIE/RME correspondientes a variables con un porcentaje de ceros superior al40-50% debe utilizarse un modelo que capture este comportamiento. - El mejor modelo en términos de ajuste para recoger el exceso de ceros en las variables de interés ha resultado ser el modelo mixto de riesgo relativo. - Las RIE/RME suavizadas presentan un patrón geográfico claro sólo en algunas neoplasias de interés medioambiental. - Parte de la variabilidad remanente en las RIE/RME suavizadas pudo ser explicada mediante la introducción de variables explicativas, en particular la contaminación atmosférica y variables socioeconómicas. -Como los contaminantes atmosféricos fueron observados en un diseño geoestadístico y las neoplasias de interés mediambiental lo fueron en un diseño en rejilla se modelizó la superficie de exposición. - El efecto del contaminante en cada municipio/sección censal se aproximó introduciendo en el modelo el valor promedio en cada área y la variabilidad intra-área. - El efecto del contaminante se consideró aleatorio, en el sentido de que podría ser diferente en cada una de las áreas. - Las condiciones socioeconómicas fueron otra de las variables que redujeron la variabilidad remanente en las RIE/RME suavizadas. -Las variables explicativas observadas con un diseño en rejilla, como el índice de privación, se introdujeron en el modelo como efectos fijos. - El efecto de la privación sobre la incidencia y/o mortalidad por cáncer de tráquea, bronquios y pulmón, controlando por contaminantes atmosféricos, fue mayor en las mujeres que en los hombres. -Altas concentraciones de contaminantes atmosféricos aumentan el riesgo de padecer neoplasias de interés medioambiental, controlando por condiciones socioeconómicas.

Parametric accelerated failure time models with random effects and an application to kidney transplant survival

Accelerated failure time models with a shared random component are described, and are used to evaluate the effect of explanatory factors and different transplant centres on survival times following kidney transplantation. Different combinations of the distribution of the random effects and baseline hazard function are considered and the fit of such models to the transplant data is critically assessed. A mixture model that combines short- and long-term components of a hazard function is then developed, which provides a more flexible model for the hazard function. The model can incorporate different explanatory variables and random effects in each component. The model is straightforward to fit using standard statistical software, and is shown to be a good fit to the transplant data. Copyright (C) 2004 John Wiley Sons, Ltd.

Field phenotyping of potato to assess root and shoot characteristics associated with drought tolerance

Aims Potatoes are a globally important source of food whose production requires large inputs of fertiliser and water. Recent research has highlighted the importance of the root system in acquiring resources. Here measurements, previously generated by field phenotyping, tested the effect of root size on maintenance of yield under drought (drought tolerance). Methods Twelve potato genotypes, including genotypes with extremes of root size, were grown to maturity in the field under a rain shelter and either irrigated or subjected to drought. Soil moisture, canopy growth, carbon isotope discrimination and final yields were measured. Destructively harvested field phenotype data were used as explanatory variables in a general linear model (GLM) to investigate yield under conditions of drought or irrigation. Results Drought severely affected the small rooted genotype Pentland Dell but not the large rooted genotype Cara. More plantlets, longer and more numerous stolons and stolon roots were associated with drought tolerance. Previously measured carbon isotope discrimination did not correlate with the effect of drought. Conclusions These data suggest that in-field phenotyping can be used to identify useful characteristics when known genotypes are subjected to an environmental stress. Stolon root traits were associated with drought tolerance in potato and could be used to select genotypes with resilience to drought.

Determinants of satisfaction amongst tenants of UK Offices

Purpose – Corporate Occupiers require offices and services which meet their business needs, whilst landlords must attract and retain occupiers in order to maximise occupancy and rental income. The purpose of this research is to help landlords and corporate occupiers understand each other better, in order to achieve a mutually beneficial relationship. Design/methodology/approach - This paper analyses interviews with 1334 office tenants in the UK, conducted over an 11-year period, to investigate determinants of occupier satisfaction, loyalty and advocacy. Structural equation modelling and regressions are performed using respondents’ ratings of satisfaction with many aspects of occupancy as explanatory variables. The dependent variables include satisfaction with property management, value for money, overall occupier satisfaction, lease renewal intentions and occupiers’ willingness to recommend their landlord. Findings - The aspects with most impact on occupiers’ satisfaction are the office building itself, its location and amenities, and also communication with their property manager, a belief that their business needs are understood and the property manager’s responsiveness to occupiers’ requests. Occupiers’ loyalty depends mainly upon feeling that their rent and service charges provide value for money, an amicable leasing process, the professionalism of their property manager and the Corporate Social Responsibility of the Landlord. ‘Empathy’ is crucial to occupiers’ willingness to recommend their landlord, and clear documentation and efficient legal process improve occupiers’ perception of receiving ‘Value for Money’. Research Limitations - The sample is skewed towards occupiers of prime office buildings in the UK, owned by landlords who care sufficiently about their tenants to commission studies into occupier satisfaction. Practical implications - This research should help to improve the landlord – tenant relationship, benefitting the businesses that rent property and helping building managers understand where to focus their efforts to achieve maximum effect on occupier satisfaction, loyalty and advocacy. Originality/value - There has been little academic research into the determinants of satisfaction of occupiers of UK commercial property. This large-scale study enables the most influential factors to be identified and prioritised.

What factors affect the destination choice of Jordanian tourists?A panel data analysis

This paper investigates what factors affect the destination choice for Jordanian to 8 countries (Oman, Saudi Arabia, Syria, Tunisia, Yemen, Egypt, Lebanon and Bahrain) using panel data analysis. Number of outbound tourists is represented as dependent variable, which is regressed over five explanatory variables using fixed effect model. The finding of this paper is that tourists from Jordan have weak demand for outbound tourism; Jordanian decision of traveling abroad is determined by the cost of traveling to different places and choosing the cheapest alternative.

Coordenação entre política fiscal monetária no regime de metas de inflação

Essa dissertação trata da coordenação entre política monetária e política fiscal. O trabalho visa testar a hipótese de que a demanda agregada é afetada pela política fiscal no Brasil entre 1995 e 2006. Com esse intuito, o trabalho estima uma curva IS para o Brasil nesse período, incluindo variáveis fiscais explicativas. O resultado é de que há evidência estatística de que o desvio do produto em relação ao produto potencial (de agora em diante gap do produto) seja dependente (positivamente) do nível de gastos do governo e (negativamente) da arrecadação do setor público. Além disso, conforme a teoria prevê, o gasto do governo tem um efeito (em módulo) mais intenso do que a arrecadação do governo, de modo que tanto o nível do superávit primário, quanto o tamanho do governo em proporção ao PIB têm impacto sobre a demanda agregada. Assim, assumindo que a convergência da taxa de câmbio real via paridade descoberta de taxa de juros tenha sido defasada no período sob análise, a política fiscal pode ter contribuído para manutenção da taxa de juros real acima do nível de equilíbrio no período em questão.

Government policy and private investment in Brazil (1955/82)

The questlon of the crowding-out of private !nvestment by public expenditure, public investment in particular , ln the Brazilian economy has been discussed more in ideological terrns than on empirical grounds. The present paper tries to avoid the limitation of previous studies by estlmatlng an equation for private investment whlch makes it possible to evaluate the effect of economic policies on prlvate investment. The private lnvestment equation was deduced modifylng the optimal flexible accelerator medel (OFAM) incorporating some channels through which public expendlture influences privateinvestment. The OFAM consists in adding adjustment costs to the neoclassical theory of investrnent. The investment fuction deduced is quite general and has the following explanatory variables: relative prices (user cost of capitaljimput prices ratios), real interest rates, real product, public expenditures and lagged private stock of capital. The model was estimated for private manufacturing industry data. The procedure adopted in estimating the model was to begin with a model as general as possible and apply restrictions to the model ' s parameters and test their statistical significance. A complete diagnostic testing was also made in order to test the stability of estirnated equations. This procedure avoids ' the shortcomings of estimating a model with a apriori restrictions on its parameters , which may lead to model misspecification. The main findings of the present study were: the increase in public expenditure, at least in the long run, has in general a positive expectation effect on private investment greater than its crowding-out effect on priva te investment owing to the simultaneous rise in interst rates; a change in economlc policy, such as that one of Geisel administration, may have an important effect on private lnvestment; and reI ative prices are relevant in determining the leveI of desired stock of capital and private investrnent.