Complete Markets Strikes Back: Revisiting Risk Sharing Tests under Discount Rate Heterogeneity

Recent risk sharing tests strongly reject the hypothesis of complete markets, because in the data: (1) the individual consumption comoves with income and (2) the consumption dispersion increases over the life cycle. In this paper, I revisit the implications of these risk sharing tests in the context of a complete market model with discount rate heterogeneity, which is extended to introduce the individual choices of effort in education. I .nd that a complete market model with discount rate heterogeneity can pass both types of the risk sharing tests. The endogenous positive correlation between income growth rate and patience makes the individual consumption comove with income, even if the markets are complete. I also show that this model is quantitatively admissible to account for both the observed comovement of consumption and income and the increase of consumption dispersion over the life cycle.

Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas

We study the asymmetric and dynamic dependence between financial assets and demonstrate, from the perspective of risk management, the economic significance of dynamic copula models. First, we construct stock and currency portfolios sorted on different characteristics (ex ante beta, coskewness, cokurtosis and order flows), and find substantial evidence of dynamic evolution between the high beta (respectively, coskewness, cokurtosis and order flow) portfolios and the low beta (coskewness, cokurtosis and order flow) portfolios. Second, using three different dependence measures, we show the presence of asymmetric dependence between these characteristic-sorted portfolios. Third, we use a dynamic copula framework based on Creal et al. (2013) and Patton (2012) to forecast the portfolio Value-at-Risk of long-short (high minus low) equity and FX portfolios. We use several widely used univariate and multivariate VaR models for the purpose of comparison. Backtesting our methodology, we find that the asymmetric dynamic copula models provide more accurate forecasts, in general, and, in particular, perform much better during the recent financial crises, indicating the economic significance of incorporating dynamic and asymmetric dependence in risk management.

Prospective validation of the Pulmonary Embolism Severity Index. A clinical prognostic model for pulmonary embolism

Practice guidelines recommend outpatient care for selected patients with non-massive pulmonary embolism (PE), but fail to specify how these low-risk patients should be identified. Using data from U.S. patients, we previously derived the Pulmonary Embolism Severity Index (PESI), a prediction rule that risk stratifies patients with PE. We sought to validate the PESI in a European patient cohort. We prospectively validated the PESI in patients with PE diagnosed at six emergency departments in three European countries. We used baseline data for the rule's 11 prognostic variables to stratify patients into five risk classes (I-V) of increasing probability of mortality. The outcome was overall mortality at 90 days after presentation. To assess the accuracy of the PESI to predict mortality, we estimated the sensitivity, specificity, and predictive values for low- (risk classes I/II) versus higher-risk patients (risk classes III-V), and the discriminatory power using the area under the receiver operating characteristic (ROC) curve. Among 357 patients with PE, overall mortality was 5.9%, ranging from 0% in class I to 17.9% in class V. The 186 (52%) low-risk patients had an overall mortality of 1.1% (95% confidence interval [CI]: 0.1-3.8%) compared to 11.1% (95% CI: 6.8-16.8%) in the 171 (48%) higher-risk patients. The PESI had a high sensitivity (91%, 95% CI: 71-97%) and a negative predictive value (99%, 95% CI: 96-100%) for predicting mortality. The area under the ROC curve was 0.78 (95% CI: 0.70-0.86). The PESI reliably identifies patients with PE who are at low risk of death and who are potential candidates for outpatient care. The PESI may help physicians make more rational decisions about hospitalization for patients with PE.

Risk Attitude And Wage Growth: Replication And Reconstruction

We replicate Shaw (1996) who found that individual wage growth is higher for individuals with greater preference for risk taking. Expanding her dataset with more American observations and data for Germany, Spain and Italy, we find mixed support for the earlier results. We present and estimate a new model and find that in particular the wage level is sensitive to attitudes towards risk taking. Comments given at the Labour Economics Conference in honour of Niels Westergaard (Nyborg, August 2008) and EALE 2008 (Amsterdam) and at seminars in Maastricht,Reus and Essen (RWI) are gratefully acknowledged. The authors also acknowledge financial support from the Spanish Ministry of Science and Innovation (grant number SEJ2007-66318) and from the Barcelona Economics Program of CREA. JEL code: J24; J30. Key words: wage growth, risk, post-school investment.

Predictors of early hospital readmission after acute pulmonary embolism.

BACKGROUND: Risk factors for early mortality after pulmonary embolism (PE) are widely known. However, it is uncertain which factors are associated with early readmission after PE. We sought to identify predictors of readmission after an admission for PE. METHODS: We studied 14 426 patient discharges with a primary diagnosis of PE from 186 acute care hospitals in Pennsylvania from January 1, 2000, to November 30, 2002. The outcome was readmission within 30 days of presentation for PE. We used a discrete proportional odds model to study the association between time to readmission and patient factors (age, sex, race, insurance, discharge status, and severity of illness), thrombolysis, and hospital characteristics (region, teaching status, and number of beds). RESULTS: Overall, 2064 patient discharges (14.3%) resulted in a readmission within 30 days of presentation for PE. The most common reasons for readmission were venous thromboembolism (21.9%), cancer (10.8%), pneumonia (5.2%), and bleeding (5.0%). In multivariable analysis, African American race (odds ratio [OR], 1.19; 95% confidence interval [CI], 1.02-1.38), Medicaid insurance (OR, 1.54; 95% CI, 1.31-1.81), discharge home with supplemental care (OR, 1.40; 95% CI, 1.27-1.54), leaving the hospital against medical advice (OR, 2.84; 95% CI, 1.80-4.48), and severity of illness were independently associated with readmission; readmission also varied by hospital region. CONCLUSIONS: Early readmission after PE is common. African American race, Medicaid insurance, severity of illness, discharge status, and hospital region are significantly associated with readmission. The high readmission rates for venous thromboembolism and bleeding suggest that readmission may be linked to suboptimal quality of care in the management of PE.

Risk factors for Trypanosoma cruzi infection among blood donors in Central Brazil

Characteristics and possible risk factors associated with Trypanosoma cruzi infection among blood donors were assessed within a routine screening programme in blood banks in an endemic area of Chagas disease. 6,172 voluntary blood donors were interviewed and tested for anti-T. cruzi antibodies by Haemagglutination and Complement Fixation tests in six blood banks in Goiânia-Central Brazil from October 1988 to April 1989. An overall prevalence of 2.3% for T. cruzi infection was obtained, being 3.3% for first-time blood donors, and 1.9% for regular ones (p < 0.01). Considering this seropositivity among regular blood donors, selection of candidates relying only on the history of previous donation was found to be inadequate. The risk of infection increased inversely with the degrees of education and monthly income. There was a 9.2 risk of infection (95% CI 3.8-22.6) for those who had lived more than 21 years in an endemic area compared to subjects who had never lived in rural settings, after multivariate analysis. These informations may help to review the criteria of selection of donors in order to improve quality of blood products in endemic areas.

A general model to predict individual exposure to solar UV by using ambient irradiance data

Excessive exposure to solar ultraviolet (UV) is the main cause of skin cancer. Specific prevention should be further developed to target overexposed or highly vulnerable populations. A better characterisation of anatomical UV exposure patterns is however needed for specific prevention. To develop a regression model for predicting the UV exposure ratio (ER, ratio between the anatomical dose and the corresponding ground level dose) for each body site without requiring individual measurements. A 3D numeric model (SimUVEx) was used to compute ER for various body sites and postures. A multiple fractional polynomial regression analysis was performed to identify predictors of ER. The regression model used simulation data and its performance was tested on an independent data set. Two input variables were sufficient to explain ER: the cosine of the maximal daily solar zenith angle and the fraction of the sky visible from the body site. The regression model was in good agreement with the simulated data ER (R(2)=0.988). Relative errors up to +20% and -10% were found in daily doses predictions, whereas an average relative error of only 2.4% (-0.03% to 5.4%) was found in yearly dose predictions. The regression model predicts accurately ER and UV doses on the basis of readily available data such as global UV erythemal irradiance measured at ground surface stations or inferred from satellite information. It renders the development of exposure data on a wide temporal and geographical scale possible and opens broad perspectives for epidemiological studies and skin cancer prevention.

First Report of a Newborn Rat Ventilation Model for Bronchopulmonary Dysplasia Permitting Evaluation of Long-Term Outcome

Background: Bronchopulmonary dysplasia (BPD) remains the leading cause of chronic pulmonary morbidity among preterm neonates. However, the exact pathophysiology is still unknown. Here we present the first results from a new model inteAbstracts, 25th International Workshop on Surfactant Replacement 400 Neonatology 2010;97:395-400 grating the most common risk factors for BPD (lung immaturity, inflammation, mechanical ventilation (MV), oxygen), which allows long-term outcome evaluation due to a non-traumatic intubation procedure. Objectives: To test the feasibility of a new rat model by investigating effects of MV, inflammation and oxygen applied to immature lungs after a ventilation-free interval. Methods: On day 4, 5, or 6 newborn rats were given an intraperitoneal injection of lipopolysaccharides to induce a systemic inflammation. 24 h later they were anesthetized, endotracheally intubated and ventilated for 8 h with 60% oxygen. After weaning of anesthesia and MV the newborn rats were extubated and returned to their mothers. Two days later they were killed and outcome measurements were performed (histology, quantitative RT-PCR) and compared to animals investigated directly after MV. Results: Directly after MV, histological signs of ventilator-induced lung injury were found. After 48 h, the first signs of early BPD were seen with delayed alveolar formation. Expression of inflammatory genes was only transiently increased. After 48 h genes involved in alveolarization, such as matrix metalloproteinase-9 and tropoelastin, showed a significant change of their expression. Conclusion: For the first time we can evaluate in a newborn rat model the effects of MV after a ventilation-free interval. This allows discrimination between immediate response genes and delayed changes of expression of more structural genes involved in alveolarization.

Binding under Conflict Conditions: State-Space Analysis of Multivariate EEG Synchronization.

Real-world objects are often endowed with features that violate Gestalt principles. In our experiment, we examined the neural correlates of binding under conflict conditions in terms of the binding-by-synchronization hypothesis. We presented an ambiguous stimulus ("diamond illusion") to 12 observers. The display consisted of four oblique gratings drifting within circular apertures. Its interpretation fluctuates between bound ("diamond") and unbound (component gratings) percepts. To model a situation in which Gestalt-driven analysis contradicts the perceptually explicit bound interpretation, we modified the original diamond (OD) stimulus by speeding up one grating. Using OD and modified diamond (MD) stimuli, we managed to dissociate the neural correlates of Gestalt-related (OD vs. MD) and perception-related (bound vs. unbound) factors. Their interaction was expected to reveal the neural networks synchronized specifically in the conflict situation. The synchronization topography of EEG was analyzed with the multivariate S-estimator technique. We found that good Gestalt (OD vs. MD) was associated with a higher posterior synchronization in the beta-gamma band. The effect of perception manifested itself as reciprocal modulations over the posterior and anterior regions (theta/beta-gamma bands). Specifically, higher posterior and lower anterior synchronization supported the bound percept, and the opposite was true for the unbound percept. The interaction showed that binding under challenging perceptual conditions is sustained by enhanced parietal synchronization. We argue that this distributed pattern of synchronization relates to the processes of multistage integration ranging from early grouping operations in the visual areas to maintaining representations in the frontal networks of sensory memory.

Canakinumab Reduces The Risk Of Acute Gouty Arthritis Flares During Initiation Of Allopurinol Therapy: Results Of A Double-blind, Randomised Study

RATIONALE: This study assessed the efficacy and safety of canakinumab, a fully human anti-interleukin-1beta monoclonal antibody, for prophylaxis against acute gouty arthritis flares in patients initiating uratelowering therapy.METHODS: In this double-blind, double-dummy, dose-ranging study, 432 patients with gouty arthritis initiating allopurinol therapy were randomised 1:1:1:1:1:1:2 to receive: a single dose of canakinumab, 25, 50, 100, 200, or 300 mg subcutaneously (sc); four 4-weekly doses of canakinumab (50150125125 mg sc); or daily colchicine 0.5 mg orally for 16 weeks. Patients recorded details of flares in diaries. The study aimed to determine the canakinumab dose having equivalent efficacy to colchicine 0.5 mg at 16 weeks.RESULTS: A dose-response for canakinumab was not apparent with any of the four pre-defined dose-responsemodels. The estimated canakinumab dose with equivalent efficacy to colchicinewas belowthe range of doses tested.At 16 weeks, therewas a 62-72% reduction in themean number of flares per patient for canakinumab doses >50 mg vs colchicine based on a negative binomial model (rate ratio: 0.28-0.38, p50.0083), and the percentage of patients experiencing >1 flarewas significantly lower for all canakinumab doses (15- 27%) vs colchicine (44%, p<0.05). Therewas a 64-72%reduction in the risk of experiencing >1 flare for canakinumab doses >50 mg vs colchicine at 16 weeks (hazard ratio: 0.28-0.36, p50.05). The incidence of adverse events was similar across treatment groups.CONCLUSIONS: Single canakinumab doses >50 mg or four 4-weekly doses provided superior prophylaxis against flares compared with daily colchicine 0.5 mg.

A model for intra-familial distribution of an infectious disease (Chagas' disease)

A probabilistic model for intra-familial distribution of infectous disease is proposed and applied to the prevalence of positive serology for Trypanosoma cruzi infection in Northeastern Brazilian sample. This double with one tail excess model fits satisfactorily to the data and its interpretation says that around 51% of these 982 families are free of infection risk; among those that are at risk, 3% have a high risk (0.66), probably due to high domestic infestation of the vector bug; while 97% show a small risk (0.11), probably due to accidental, non-domestic transmission.

Multivariate contemporaneous-threshold autoregressive models

This paper proposes a contemporaneous-threshold multivariate smooth transition autoregressive (C-MSTAR) model in which the regime weights depend on the ex ante probabilities that latent regime-specific variables exceed certain threshold values. A key feature of the model is that the transition function depends on all the parameters of the model as well as on the data. Since the mixing weights are also a function of the regime-specific innovation covariance matrix, the model can account for contemporaneous regime-specific co-movements of the variables. The stability and distributional properties of the proposed model are discussed, as well as issues of estimation, testing and forecasting. The practical usefulness of the C-MSTAR model is illustrated by examining the relationship between US stock prices and interest rates.

Investor protection and income inequality: risk sharing vs risk taking

This paper studies the relationship between investor protection, entrepreneurial risk taking and income inequality. In the presence of market frictions, better protection makes investors more willing to take on entrepreneurial risk when lending to firms, thereby improving the degree of risk sharing between financiers and entrepreneurs. On the other hand, by increasing risk sharing, investor protection also induces more firms to undertake risky projects. By increasing entrepreneurial risk taking, it raises income dispersion. By reducing the risk faced by entrepreneurs, it reduces income volatility. As a result, investor protection raises income inequality to the extent that it fosters risk taking, while it reduces it for a given level of risk taking. Empirical evidence from a panel of forty-five countries spanning the period 1976-2000 supports the predictions of the model.

Species distribution models for conservation-oriented studies in Switzerland : filling data and tools gaps

SUMMARYSpecies distribution models (SDMs) represent nowadays an essential tool in the research fields of ecology and conservation biology. By combining observations of species occurrence or abundance with information on the environmental characteristic of the observation sites, they can provide information on the ecology of species, predict their distributions across the landscape or extrapolate them to other spatial or time frames. The advent of SDMs, supported by geographic information systems (GIS), new developments in statistical models and constantly increasing computational capacities, has revolutionized the way ecologists can comprehend species distributions in their environment. SDMs have brought the tool that allows describing species realized niches across a multivariate environmental space and predict their spatial distribution. Predictions, in the form of probabilistic maps showing the potential distribution of the species, are an irreplaceable mean to inform every single unit of a territory about its biodiversity potential. SDMs and the corresponding spatial predictions can be used to plan conservation actions for particular species, to design field surveys, to assess the risks related to the spread of invasive species, to select reserve locations and design reserve networks, and ultimately, to forecast distributional changes according to scenarios of climate and/or land use change.By assessing the effect of several factors on model performance and on the accuracy of spatial predictions, this thesis aims at improving techniques and data available for distribution modelling and at providing the best possible information to conservation managers to support their decisions and action plans for the conservation of biodiversity in Switzerland and beyond. Several monitoring programs have been put in place from the national to the global scale, and different sources of data now exist and start to be available to researchers who want to model species distribution. However, because of the lack of means, data are often not gathered at an appropriate resolution, are sampled only over limited areas, are not spatially explicit or do not provide a sound biological information. A typical example of this is data on 'habitat' (sensu biota). Even though this is essential information for an effective conservation planning, it often has to be approximated from land use, the closest available information. Moreover, data are often not sampled according to an established sampling design, which can lead to biased samples and consequently to spurious modelling results. Understanding the sources of variability linked to the different phases of the modelling process and their importance is crucial in order to evaluate the final distribution maps that are to be used for conservation purposes.The research presented in this thesis was essentially conducted within the framework of the Landspot Project, a project supported by the Swiss National Science Foundation. The main goal of the project was to assess the possible contribution of pre-modelled 'habitat' units to model the distribution of animal species, in particular butterfly species, across Switzerland. While pursuing this goal, different aspects of data quality, sampling design and modelling process were addressed and improved, and implications for conservation discussed. The main 'habitat' units considered in this thesis are grassland and forest communities of natural and anthropogenic origin as defined in the typology of habitats for Switzerland. These communities are mainly defined at the phytosociological level of the alliance. For the time being, no comprehensive map of such communities is available at the national scale and at fine resolution. As a first step, it was therefore necessary to create distribution models and maps for these communities across Switzerland and thus to gather and collect the necessary data. In order to reach this first objective, several new developments were necessary such as the definition of expert models, the classification of the Swiss territory in environmental domains, the design of an environmentally stratified sampling of the target vegetation units across Switzerland, the development of a database integrating a decision-support system assisting in the classification of the relevés, and the downscaling of the land use/cover data from 100 m to 25 m resolution.The main contributions of this thesis to the discipline of species distribution modelling (SDM) are assembled in four main scientific papers. In the first, published in Journal of Riogeography different issues related to the modelling process itself are investigated. First is assessed the effect of five different stepwise selection methods on model performance, stability and parsimony, using data of the forest inventory of State of Vaud. In the same paper are also assessed: the effect of weighting absences to ensure a prevalence of 0.5 prior to model calibration; the effect of limiting absences beyond the environmental envelope defined by presences; four different methods for incorporating spatial autocorrelation; and finally, the effect of integrating predictor interactions. Results allowed to specifically enhance the GRASP tool (Generalized Regression Analysis and Spatial Predictions) that now incorporates new selection methods and the possibility of dealing with interactions among predictors as well as spatial autocorrelation. The contribution of different sources of remotely sensed information to species distribution models was also assessed. The second paper (to be submitted) explores the combined effects of sample size and data post-stratification on the accuracy of models using data on grassland distribution across Switzerland collected within the framework of the Landspot project and supplemented with other important vegetation databases. For the stratification of the data, different spatial frameworks were compared. In particular, environmental stratification by Swiss Environmental Domains was compared to geographical stratification either by biogeographic regions or political states (cantons). The third paper (to be submitted) assesses the contribution of pre- modelled vegetation communities to the modelling of fauna. It is a two-steps approach that combines the disciplines of community ecology and spatial ecology and integrates their corresponding concepts of habitat. First are modelled vegetation communities per se and then these 'habitat' units are used in order to model animal species habitat. A case study is presented with grassland communities and butterfly species. Different ways of integrating vegetation information in the models of butterfly distribution were also evaluated. Finally, a glimpse to climate change is given in the fourth paper, recently published in Ecological Modelling. This paper proposes a conceptual framework for analysing range shifts, namely a catalogue of the possible patterns of change in the distribution of a species along elevational or other environmental gradients and an improved quantitative methodology to identify and objectively describe these patterns. The methodology was developed using data from the Swiss national common breeding bird survey and the article presents results concerning the observed shifts in the elevational distribution of breeding birds in Switzerland.The overall objective of this thesis is to improve species distribution models as potential inputs for different conservation tools (e.g. red lists, ecological networks, risk assessment of the spread of invasive species, vulnerability assessment in the context of climate change). While no conservation issues or tools are directly tested in this thesis, the importance of the proposed improvements made in species distribution modelling is discussed in the context of the selection of reserve networks.RESUMELes modèles de distribution d'espèces (SDMs) représentent aujourd'hui un outil essentiel dans les domaines de recherche de l'écologie et de la biologie de la conservation. En combinant les observations de la présence des espèces ou de leur abondance avec des informations sur les caractéristiques environnementales des sites d'observation, ces modèles peuvent fournir des informations sur l'écologie des espèces, prédire leur distribution à travers le paysage ou l'extrapoler dans l'espace et le temps. Le déploiement des SDMs, soutenu par les systèmes d'information géographique (SIG), les nouveaux développements dans les modèles statistiques, ainsi que la constante augmentation des capacités de calcul, a révolutionné la façon dont les écologistes peuvent comprendre la distribution des espèces dans leur environnement. Les SDMs ont apporté l'outil qui permet de décrire la niche réalisée des espèces dans un espace environnemental multivarié et prédire leur distribution spatiale. Les prédictions, sous forme de carte probabilistes montrant la distribution potentielle de l'espèce, sont un moyen irremplaçable d'informer chaque unité du territoire de sa biodiversité potentielle. Les SDMs et les prédictions spatiales correspondantes peuvent être utilisés pour planifier des mesures de conservation pour des espèces particulières, pour concevoir des plans d'échantillonnage, pour évaluer les risques liés à la propagation d'espèces envahissantes, pour choisir l'emplacement de réserves et les mettre en réseau, et finalement, pour prévoir les changements de répartition en fonction de scénarios de changement climatique et/ou d'utilisation du sol. En évaluant l'effet de plusieurs facteurs sur la performance des modèles et sur la précision des prédictions spatiales, cette thèse vise à améliorer les techniques et les données disponibles pour la modélisation de la distribution des espèces et à fournir la meilleure information possible aux gestionnaires pour appuyer leurs décisions et leurs plans d'action pour la conservation de la biodiversité en Suisse et au-delà. Plusieurs programmes de surveillance ont été mis en place de l'échelle nationale à l'échelle globale, et différentes sources de données sont désormais disponibles pour les chercheurs qui veulent modéliser la distribution des espèces. Toutefois, en raison du manque de moyens, les données sont souvent collectées à une résolution inappropriée, sont échantillonnées sur des zones limitées, ne sont pas spatialement explicites ou ne fournissent pas une information écologique suffisante. Un exemple typique est fourni par les données sur 'l'habitat' (sensu biota). Même s'il s'agit d'une information essentielle pour des mesures de conservation efficaces, elle est souvent approximée par l'utilisation du sol, l'information qui s'en approche le plus. En outre, les données ne sont souvent pas échantillonnées selon un plan d'échantillonnage établi, ce qui biaise les échantillons et par conséquent les résultats de la modélisation. Comprendre les sources de variabilité liées aux différentes phases du processus de modélisation s'avère crucial afin d'évaluer l'utilisation des cartes de distribution prédites à des fins de conservation.La recherche présentée dans cette thèse a été essentiellement menée dans le cadre du projet Landspot, un projet soutenu par le Fond National Suisse pour la Recherche. L'objectif principal de ce projet était d'évaluer la contribution d'unités 'd'habitat' pré-modélisées pour modéliser la répartition des espèces animales, notamment de papillons, à travers la Suisse. Tout en poursuivant cet objectif, différents aspects touchant à la qualité des données, au plan d'échantillonnage et au processus de modélisation sont abordés et améliorés, et leurs implications pour la conservation des espèces discutées. Les principaux 'habitats' considérés dans cette thèse sont des communautés de prairie et de forêt d'origine naturelle et anthropique telles que définies dans la typologie des habitats de Suisse. Ces communautés sont principalement définies au niveau phytosociologique de l'alliance. Pour l'instant aucune carte de la distribution de ces communautés n'est disponible à l'échelle nationale et à résolution fine. Dans un premier temps, il a donc été nécessaire de créer des modèles de distribution de ces communautés à travers la Suisse et par conséquent de recueillir les données nécessaires. Afin d'atteindre ce premier objectif, plusieurs nouveaux développements ont été nécessaires, tels que la définition de modèles experts, la classification du territoire suisse en domaines environnementaux, la conception d'un échantillonnage environnementalement stratifié des unités de végétation cibles dans toute la Suisse, la création d'une base de données intégrant un système d'aide à la décision pour la classification des relevés, et le « downscaling » des données de couverture du sol de 100 m à 25 m de résolution. Les principales contributions de cette thèse à la discipline de la modélisation de la distribution d'espèces (SDM) sont rassemblées dans quatre articles scientifiques. Dans le premier article, publié dans le Journal of Biogeography, différentes questions liées au processus de modélisation sont étudiées en utilisant les données de l'inventaire forestier de l'Etat de Vaud. Tout d'abord sont évalués les effets de cinq méthodes de sélection pas-à-pas sur la performance, la stabilité et la parcimonie des modèles. Dans le même article sont également évalués: l'effet de la pondération des absences afin d'assurer une prévalence de 0.5 lors de la calibration du modèle; l'effet de limiter les absences au-delà de l'enveloppe définie par les présences; quatre méthodes différentes pour l'intégration de l'autocorrélation spatiale; et enfin, l'effet de l'intégration d'interactions entre facteurs. Les résultats présentés dans cet article ont permis d'améliorer l'outil GRASP qui intègre désonnais de nouvelles méthodes de sélection et la possibilité de traiter les interactions entre variables explicatives, ainsi que l'autocorrélation spatiale. La contribution de différentes sources de données issues de la télédétection a également été évaluée. Le deuxième article (en voie de soumission) explore les effets combinés de la taille de l'échantillon et de la post-stratification sur le la précision des modèles. Les données utilisées ici sont celles concernant la répartition des prairies de Suisse recueillies dans le cadre du projet Landspot et complétées par d'autres sources. Pour la stratification des données, différents cadres spatiaux ont été comparés. En particulier, la stratification environnementale par les domaines environnementaux de Suisse a été comparée à la stratification géographique par les régions biogéographiques ou par les cantons. Le troisième article (en voie de soumission) évalue la contribution de communautés végétales pré-modélisées à la modélisation de la faune. C'est une approche en deux étapes qui combine les disciplines de l'écologie des communautés et de l'écologie spatiale en intégrant leurs concepts de 'habitat' respectifs. Les communautés végétales sont modélisées d'abord, puis ces unités de 'habitat' sont utilisées pour modéliser les espèces animales. Une étude de cas est présentée avec des communautés prairiales et des espèces de papillons. Différentes façons d'intégrer l'information sur la végétation dans les modèles de répartition des papillons sont évaluées. Enfin, un clin d'oeil aux changements climatiques dans le dernier article, publié dans Ecological Modelling. Cet article propose un cadre conceptuel pour l'analyse des changements dans la distribution des espèces qui comprend notamment un catalogue des différentes formes possibles de changement le long d'un gradient d'élévation ou autre gradient environnemental, et une méthode quantitative améliorée pour identifier et décrire ces déplacements. Cette méthodologie a été développée en utilisant des données issues du monitoring des oiseaux nicheurs répandus et l'article présente les résultats concernant les déplacements observés dans la distribution altitudinale des oiseaux nicheurs en Suisse.L'objectif général de cette thèse est d'améliorer les modèles de distribution des espèces en tant que source d'information possible pour les différents outils de conservation (par exemple, listes rouges, réseaux écologiques, évaluation des risques de propagation d'espèces envahissantes, évaluation de la vulnérabilité des espèces dans le contexte de changement climatique). Bien que ces questions de conservation ne soient pas directement testées dans cette thèse, l'importance des améliorations proposées pour la modélisation de la distribution des espèces est discutée à la fin de ce travail dans le contexte de la sélection de réseaux de réserves.

Work, risk and health: differences between immigrants and natives in Spain

We analyze the impact of working and contractual conditions, particularly exposure to job risks, on the probability of acquiring a disability. We postulate a model in which this impact is mediated by the choice of occupation, with a level of risk associated to it. We assume this choice is endogenous, and that it depends on preferences and opportunities in the labour market, both of which may differ between immigrants and natives. To test this hypothesis we use data from the Continuous Sample of Working Lives of the Spanish SS system. It contains individual, job and firm information of over a million workers, including a representative sample of immigrants. We find that risk exposure increases the probability of permanent disability by 5.3%; temporary employment also influences health. Migrant status -with differences among regions of origin- significantly affects both disability and the probability of being employed in a risky occupation. Most groups of immigrants work in riskier jobs, but have lower probability of becoming disabled. Nevertheless, our theoretical hypothesis that disability and risk are jointly determined is not valid for immigrants: i.e. for them working conditions is not a matter of choice in terms of health.