Méthodes sismiques actives adaptées à l'étude de milieux hétérogènes : application aux glissements de terrain

Résumé Les glissements de terrain représentent un des principaux risques naturels dans les régions montagneuses. En Suisse, chaque année les glissements de terrains causent des dégâts qui affectent les infrastructures et ont des coûts financiers importants. Une bonne compréhension des mécanismes des glissements peut permettre d'atténuer leur impact. Celle-ci passe notamment par la connaissance de la structure interne du glissement, la détermination de son volume et de son ou ses plans de glissement. Dans un glissement de terrain, la désorganisation et la présence de fractures dans le matériel déplacé engendre un changement des paramètres physiques et en particulier une diminution des vitesses de propagation des ondes sismiques ainsi que de la densité du matériel. Les méthodes sismiques sont de ce fait bien adaptées à l'étude des glissements de terrain. Parmi les méthodes sismiques, l'analyse de la dispersion des ondes de surface est une méthode simple à mettre en oeuvre. Elle présente l'avantage d'estimer les variations des vitesses de cisaillement avec la profondeur sans avoir spécifiquement recours à l'utilisation d'une source d'onde S et de géophones horizontaux. Sa mise en oeuvre en trois étapes implique la mesure de la dispersion des ondes de surface sur des réseaux étendus, la détermination des courbes de dispersion pour finir par l'inversion de ces courbes. Les modèles de vitesse obtenus à partir de cette procédure ne sont valides que lorsque les milieux explorés ne présentent pas de variations latérales. En pratique cette hypothèse est rarement vérifiée, notamment pour un glissement de terrain dans lequel les couches remaniées sont susceptibles de présenter de fortes hétérogénéités latérales. Pour évaluer la possibilité de déterminer des courbes de dispersion à partir de réseaux de faible extension des mesures testes ont été effectuées sur un site (Arnex, VD) équipé d'un forage. Un profil sismique de 190 m de long a été implanté dans une vallée creusée dans du calcaire et remplie par des dépôts glacio-lacustres d'une trentaine de mètres d'épaisseur. Les données acquises le long de ce profil ont confirmé que la présence de variations latérales sous le réseau de géophones affecte l'allure des courbes de dispersion jusqu'à parfois empêcher leur détermination. Pour utiliser l'analyse de la dispersion des ondes de surface sur des sites présentant des variations latérales, notre approche consiste à déterminer les courbes de dispersions pour une série de réseaux de faible extension, à inverser chacune des courbes et à interpoler les différents modèles de vitesse obtenus. Le choix de la position ainsi que de l'extension des différents réseaux de géophones est important. Il tient compte de la localisation des hétérogénéités détectées à partir de l'analyse de sismique réfraction, mais également d'anomalies d'amplitudes observées sur des cartes qui représentent dans le domaine position de tir - position du récepteur, l'amplitude mesurée pour différentes fréquences. La procédure proposée par Lin et Lin (2007) s'est avérée être une méthode efficace permettant de déterminer des courbes de dispersion à partir de réseaux de faible extension. Elle consiste à construire à partir d'un réseau de géophones et de plusieurs positions de tir un enregistrement temps-déports qui tient compte d'une large gamme de distances source-récepteur. Au moment d'assembler les différentes données une correction de phase est appliquée pour tenir compte des hétérogénéités situées entre les différents points de tir. Pour évaluer cette correction nous suggérons de calculer pour deux tir successif la densité spectrale croisée des traces de même offset: Sur le site d'Arnex, 22 courbes de dispersions ont été déterminées pour de réseaux de géophones de 10 m d'extension. Nous avons également profité du forage pour acquérir un profil de sismique verticale en ondes S. Le modèle de vitesse S déduit de l'interprétation du profil de sismique verticale est utilisé comme information à priori lors l'inversion des différentes courbes de dispersion. Finalement, le modèle en deux dimension qui a été établi grâce à l'analyse de la dispersion des ondes de surface met en évidence une structure tabulaire à trois couches dont les limites coïncident bien avec les limites lithologiques observées dans le forage. Dans celui-ci des argiles limoneuses associées à une vitesse de propagation des ondes S de l'ordre de 175 m/s surmontent vers 9 m de profondeur des dépôts de moraine argilo-sableuse caractérisés par des vitesses de propagation des ondes S de l'ordre de 300 m/s jusqu'à 14 m de profondeur et supérieur ou égal à 400 m/s entre 14 et 20 m de profondeur. Le glissement de la Grande Combe (Ballaigues, VD) se produit à l'intérieur du remplissage quaternaire d'une combe creusée dans des calcaires Portlandien. Comme dans le cas du site d'Arnex les dépôts quaternaires correspondent à des dépôts glacio-lacustres. Dans la partie supérieure la surface de glissement a été localisée à une vingtaine de mètres de profondeur au niveau de l'interface qui sépare des dépôts de moraine jurassienne et des dépôts glacio-lacustres. Au pied du glissement 14 courbes de dispersions ont été déterminées sur des réseaux de 10 m d'extension le long d'un profil de 144 m. Les courbes obtenues sont discontinues et définies pour un domaine de fréquence de 7 à 35 Hz. Grâce à l'utilisation de distances source-récepteur entre 8 et 72 m, 2 à 4 modes de propagation ont été identifiés pour chacune des courbes. Lors de l'inversion des courbes de dispersion la prise en compte des différents modes de propagation a permis d'étendre la profondeur d'investigation jusqu'à une vingtaine de mètres de profondeur. Le modèle en deux dimensions permet de distinguer 4 couches (Vs1 < 175 m/s, 175 m/s < Vs2 < 225 m/s, 225 m/s < Vs3 < 400 m/s et Vs4 >.400 m/s) qui présentent des variations d'épaisseur. Des profils de sismiques réflexion en ondes S acquis avec une source construite dans le cadre de ce travail, complètent et corroborent le modèle établi à partir de l'analyse de la dispersion des ondes de surface. Un réflecteur localisé entre 5 et 10 m de profondeur et associé à une vitesse de sommation de 180 m/s souligne notamment la géométrie de l'interface qui sépare la deuxième de la troisième couche du modèle établi à partir de l'analyse de la dispersion des ondes de surface. Abstract Landslides are one of the main natural hazards in mountainous regions. In Switzerland, landslides cause damages every year that impact infrastructures and have important financial costs. In depth understanding of sliding mechanisms may help limiting their impact. In particular, this can be achieved through a better knowledge of the internal structure of the landslide, the determination of its volume and its sliding surface or surfaces In a landslide, the disorganization and the presence of fractures in the displaced material generate a change of the physical parameters and in particular a decrease of the seismic velocities and of the material density. Therefoe, seismic methods are well adapted to the study of landslides. Among seismic methods, surface-wave dispersion analysis is a easy to implement. Through it, shearwave velocity variations with depth can be estimated without having to resort to an S-wave source and to horizontal geophones. Its 3-step implementation implies measurement of surface-wave dispersion with long arrays, determination of the dispersion curves and finally inversion of these curves. Velocity models obtained through this approach are only valid when the investigated medium does not include lateral variations. In practice, this assumption is seldom correct, in particular for landslides in which reshaped layers likely include strong lateral heterogeneities. To assess the possibility of determining dispersion curves from short array lengths we carried out tests measurements on a site (Arnex, VD) that includes a borehole. A 190 m long seismic profile was acquired in a valley carved into limestone and filled with 30 m of glacio-lacustrine sediments. The data acquired along this profile confirmed that the presence of lateral variations under the geophone array influences the dispersion-curve shape so much that it sometimes preventes the dispersion curves determination. Our approach to use the analysis of surface-wave dispersion on sites that include lateral variations consists in obtaining dispersion curves for a series of short length arrays; inverting each so obtained curve and interpolating the different obtained velocity model. The choice of the location as well as the geophone array length is important. It takes into account the location of the heterogeneities that are revealed by the seismic refraction interpretation of the data but also, the location of signal amplitude anomalies observed on maps that represent, for a given frequency, the measured amplitude in the shot position - receiver position domain. The procedure proposed by Lin and Lin (2007) turned out to be an efficient one to determine dispersion curves using short extension arrays. It consists in building a time-offset from an array of geophones with a wide offset range by gathering seismograms acquired with different source-to-receiver offsets. When assembling the different data, a phase correction is applied in order to reduce static phase error induced by lateral variation. To evaluate this correction, we suggest to calculate, for two successive shots, the cross power spectral density of common offset traces. On the Arnex site, 22 curves were determined with 10m in length geophone-arrays. We also took advantage of the borehole to acquire a S-wave vertical seismic profile. The S-wave velocity depth model derived from the vertical seismic profile interpretation is used as prior information in the inversion of the dispersion-curves. Finally a 2D velocity model was established from the analysis of the different dispersion curves. It reveals a 3-layer structure in good agreement with the observed lithologies in the borehole. In it a clay layer with a shear-wave of 175 m/s shear-wave velocity overlies a clayey-sandy till layer at 9 m depth that is characterized down to 14 m by a 300 m/s S-wave velocity; these deposits have a S-wave velocity of 400 m/s between depths of 14 to 20 m. The La Grand Combe landslide (Ballaigues, VD) occurs inside the Quaternary filling of a valley carved into Portlandien limestone. As at the Arnex site, the Quaternary deposits correspond to glaciolacustrine sediments. In the upper part of the landslide, the sliding surface is located at a depth of about 20 m that coincides with the discontinuity between Jurassian till and glacio-lacustrine deposits. At the toe of the landslide, we defined 14 dispersion curves along a 144 m long profile using 10 m long geophone arrays. The obtained curves are discontinuous and defined within a frequency range of 7 to 35 Hz. The use of a wide range of offsets (from 8 to 72 m) enabled us to determine 2 to 4 mode of propagation for each dispersion curve. Taking these higher modes into consideration for dispersion curve inversion allowed us to reach an investigation depth of about 20 m. A four layer 2D model was derived (Vs1< 175 m/s, 175 m/s <Vs2< 225 m/s, 225 m/s < Vs3 < 400 m/s, Vs4> 400 m/s) with variable layer thicknesses. S-wave seismic reflection profiles acquired with a source built as part of this work complete and the velocity model revealed by surface-wave analysis. In particular, reflector at a depth of 5 to 10 m associated with a 180 m/s stacking velocity image the geometry of the discontinuity between the second and third layer of the model derived from the surface-wave dispersion analysis.

Temporal changes in mRNA expression of the brain nutrient transporters in the lithium-pilocarpine model of epilepsy in the immature and adult rat.

The lithium-pilocarpine model mimics most features of human temporal lobe epilepsy. Following our prior studies of cerebral metabolic changes, here we explored the expression of transporters for glucose (GLUT1 and GLUT3) and monocarboxylates (MCT1 and MCT2) during and after status epilepticus (SE) induced by lithium-pilocarpine in PN10, PN21, and adult rats. In situ hybridization was used to study the expression of transporter mRNAs during the acute phase (1, 4, 12 and 24h of SE), the latent phase, and the early and late chronic phases. During SE, GLUT1 expression was increased throughout the brain between 1 and 12h of SE, more strongly in adult rats; GLUT3 increased only transiently, at 1 and 4h of SE and mainly in PN10 rats; MCT1 was increased at all ages but 5-10-fold more in adult than in immature rats; MCT2 expression increased mainly in adult rats. At all ages, MCT1 and MCT2 up-regulation was limited to the circuit of seizures while GLUT1 and GLUT3 changes were more widespread. During the latent and chronic phases, the expression of nutrient transporters was normal in PN10 rats. In PN21 rats, GLUT1 was up-regulated in all brain regions. In contrast, in adult rats GLUT1 expression was down-regulated in the piriform cortex, hilus and CA1 as a result of extensive neuronal death. The changes in nutrient transporter expression reported here further support previous findings in other experimental models demonstrating rapid transcriptional responses to marked changes in cerebral energetic/glucose demand.

Determination of extreme floods using a distributed hydrological model

Hydrological models developed for extreme precipitation of PMP type are difficult to calibrate because of the scarcity of available data for these events. This article presents the process and results of calibration for a distributed hydrological model at fine scale developed for the estimation of probable maximal floods in the case of a PMP. This calibration is done on two Swiss catchments for two events of summer storms. The calculation done is concentrated on the estimation of the parameters of the model, divided in two parts. The first is necessary for the computation of flow speeds while the second is required for the determination of the initial and final infiltration capacities for each terrain type. The results, validated with the Nash equation show a good correlation between the simulated and observed flows. We also apply this model on two Romanian catchments, showing the river network and estimated flow.

Comparison of the polynomial model against explicit measurements of noise components for different mammography systems.

Given the adverse impact of image noise on the perception of important clinical details in digital mammography, routine quality control measurements should include an evaluation of noise. The European Guidelines, for example, employ a second-order polynomial fit of pixel variance as a function of detector air kerma (DAK) to decompose noise into quantum, electronic and fixed pattern (FP) components and assess the DAK range where quantum noise dominates. This work examines the robustness of the polynomial method against an explicit noise decomposition method. The two methods were applied to variance and noise power spectrum (NPS) data from six digital mammography units. Twenty homogeneously exposed images were acquired with PMMA blocks for target DAKs ranging from 6.25 to 1600 µGy. Both methods were explored for the effects of data weighting and squared fit coefficients during the curve fitting, the influence of the additional filter material (2 mm Al versus 40 mm PMMA) and noise de-trending. Finally, spatial stationarity of noise was assessed.Data weighting improved noise model fitting over large DAK ranges, especially at low detector exposures. The polynomial and explicit decompositions generally agreed for quantum and electronic noise but FP noise fraction was consistently underestimated by the polynomial method. Noise decomposition as a function of position in the image showed limited noise stationarity, especially for FP noise; thus the position of the region of interest (ROI) used for noise decomposition may influence fractional noise composition. The ROI area and position used in the Guidelines offer an acceptable estimation of noise components. While there are limitations to the polynomial model, when used with care and with appropriate data weighting, the method offers a simple and robust means of examining the detector noise components as a function of detector exposure.

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.

Estimation of percentage body fat in 6- to 13-year-old children by skinfold thickness, body mass index and waist circumference.

We evaluated the accuracy of skinfold thicknesses, BMI and waist circumference for the prediction of percentage body fat (PBF) in a representative sample of 372 Swiss children aged 6-13 years. PBF was measured using dual-energy X-ray absorptiometry. On the basis of a preliminary bootstrap selection of predictors, seven regression models were evaluated. All models included sex, age and pubertal stage plus one of the following predictors: (1) log-transformed triceps skinfold (logTSF); (2) logTSF and waist circumference; (3) log-transformed sum of triceps and subscapular skinfolds (logSF2); (4) log-transformed sum of triceps, biceps, subscapular and supra-iliac skinfolds (logSF4); (5) BMI; (6) waist circumference; (7) BMI and waist circumference. The adjusted determination coefficient (R² adj) and the root mean squared error (RMSE; kg) were calculated for each model. LogSF4 (R² adj 0.85; RMSE 2.35) and logSF2 (R² adj 0.82; RMSE 2.54) were similarly accurate at predicting PBF and superior to logTSF (R² adj 0.75; RMSE 3.02), logTSF combined with waist circumference (R² adj 0.78; RMSE 2.85), BMI (R² adj 0.62; RMSE 3.73), waist circumference (R² adj 0.58; RMSE 3.89), and BMI combined with waist circumference (R² adj 0.63; RMSE 3.66) (P < 0.001 for all values of R² adj). The finding that logSF4 was only modestly superior to logSF2 and that logTSF was better than BMI and waist circumference at predicting PBF has important implications for paediatric epidemiological studies aimed at disentangling the effect of body fat on health outcomes.

Determinants of Corporate Disclosure : A Multicountry, Multilevel Model

Abstract The complexity of the current business world is making corporate disclosure more and more important for information users. These users, including investors, financial analysts, and government authorities rely on the disclosed information to make their investment decisions, analyze and recommend shares, and to draft regulation policies. Moreover, the globalization of capital markets has raised difficulties for information users in understanding the differences incorporate disclosure across countries and across firms. Using a sample of 797 firms from 34 countries, this thesis advances the literature on disclosure by illustrating comprehensively the disclosure determinants originating at firm systems and national systems based on the multilevel latent variable approach. Under this approach, the overall variation associated with the firm-specific variables is decomposed into two parts, the within-country and the between-country part. Accordingly, the model estimates the latent association between corporate disclosure and information demand at two levels, the within-country and the between-country level. The results indicate that the variables originating from corporate systems are hierarchically correlated with those from the country environment. The information demand factor indicated by the number of exchanges listed and the number of analyst recommendations can significantly explain the variation of corporate disclosure for both "within" and "between" countries. The exogenous influences of firm fundamentals-firm size and performance-are exerted indirectly through the information demand factor. Specifically, if the between-country variation in firm variables is taken into account, only the variables of legal systems and economic growth keep significance in explaining the disclosure differences across countries. These findings strongly support the hypothesis that disclosure is a response to both corporate systems and national systems, but the influence of the latter on disclosure reflected significantly through that of the former. In addition, the results based on ADR (American Depositary Receipt) firms suggest that the globalization of capital markets is harmonizing the disclosure behavior of cross-boundary listed firms, but it cannot entirely eliminate the national features in disclosure and other firm-specific characteristics.

Heel and toe clearance estimation for gait analysis using wireless inertial sensors.

Tripping is considered a major cause of fall in older people. Therefore, foot clearance (i.e., height of the foot above ground during swing phase) could be a key factor to better understand the complex relationship between gait and falls. This paper presents a new method to estimate clearance using a foot-worn and wireless inertial sensor system. The method relies on the computation of foot orientation and trajectory from sensors signal data fusion, combined with the temporal detection of toe-off and heel-strike events. Based on a kinematic model that automatically estimates sensor position relative to the foot, heel and toe trajectories are estimated. 2-D and 3-D models are presented with different solving approaches, and validated against an optical motion capture system on 12 healthy adults performing short walking trials at self-selected, slow, and fast speed. Parameters corresponding to local minimum and maximum of heel and toe clearance were extracted and showed accuracy ± precision of 4.1 ± 2.3 cm for maximal heel clearance and 1.3 ± 0.9 cm for minimal toe clearance compared to the reference. The system is lightweight, wireless, easy to wear and to use, and provide a new and useful tool for routine clinical assessment of gait outside a dedicated laboratory.

The Impact of Digitization on the Management of Administrative Procedures : The Case of Building Permits

Information and Communication Technologies provide public administrations new ways to meet their users' needs. At the same time, e-Government practices support the public sector in improving the quality of service provision and of its internal operations. In this paper we discuss the impacts of digitization on the management of administrative procedures. The theoretical framework and the research model that we will use in this study help us tackle the question of how digitization transforms administrative procedures as, for example, in terms of time and roles. The multiplicity of institutions involved in issuing building permits led us to consider this administrative procedure as a very interesting case study. An online survey was first addressed to Swiss civil servants to explore the field, and here we present some of its results. We are currently undertaking an in-depth case study of the building permit procedures in three Swiss Cantons, which we will also present in this paper. We will conclude with a discussion and the future steps of this project.

Genetic differentiation in Silene dioica metapopulations: estimation of spatiotemporal effects in a successional plant species

Silene dioica is a diploid, dioecious, perennial, insect-pollinated herb and part of the deciduous phase of primary succession in Skeppsvik Archipelago, Gulf of Bothnia, Sweden. These islands are composed of material deposited and left underwater by melting ice at the end of the last ice age. A rapid and relatively constant rate of land uplift of 0.9 cm per year continually creates new islands available for colonization by plants. Because the higher deposits appear first, islands differ in age. Because it is possible to estimate the ages of islands and populations of plant species belonging to early stages of succession, the genetic dynamics occurring within an age-structured metapopulation can be investigated in this archipelago. Fifty-two island populations of S. dioica of known ages, sizes, and distances from each other were studied through electrophoretic data. A number of factors increase the degree of genetic differentiation among these island populations relative to an island model at equilibrium. Newly founded populations were more differentiated than those of intermediate age, which suggests that colonization dynamics increase genetic variance among populations. The very old populations, which decrease in size as they approach extinction, were more differentiated than intermediate-aged populations. Isolation by distance occurs in this system. Colonizers are likely to come from more than one source, and the migrant pool model best explains colonization events in the archipelago. Degree of environmental exposure also affects population differentiation.

Malaria haplotype frequency estimation.

We present a Bayesian approach for estimating the relative frequencies of multi-single nucleotide polymorphism (SNP) haplotypes in populations of the malaria parasite Plasmodium falciparum by using microarray SNP data from human blood samples. Each sample comes from a malaria patient and contains one or several parasite clones that may genetically differ. Samples containing multiple parasite clones with different genetic markers pose a special challenge. The situation is comparable with a polyploid organism. The data from each blood sample indicates whether the parasites in the blood carry a mutant or a wildtype allele at various selected genomic positions. If both mutant and wildtype alleles are detected at a given position in a multiply infected sample, the data indicates the presence of both alleles, but the ratio is unknown. Thus, the data only partially reveals which specific combinations of genetic markers (i.e. haplotypes across the examined SNPs) occur in distinct parasite clones. In addition, SNP data may contain errors at non-negligible rates. We use a multinomial mixture model with partially missing observations to represent this data and a Markov chain Monte Carlo method to estimate the haplotype frequencies in a population. Our approach addresses both challenges, multiple infections and data errors.

Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data.

Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of biophysical models have been proposed to associate particular patterns observed in the measured signal with specific microstructural properties of the neuronal tissue, such as axon diameter and fiber density. Despite very appealing results showing that the estimated microstructure indices agree very well with histological examinations, existing techniques require computationally very expensive non-linear procedures to fit the models to the data which, in practice, demand the use of powerful computer clusters for large-scale applications. In this work, we present a general framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) and show how to re-formulate this class of techniques as convenient linear systems which, then, can be efficiently solved using very fast algorithms. We demonstrate this linearization of the fitting problem for two specific models, i.e. ActiveAx and NODDI, providing a very attractive alternative for parameter estimation in those techniques; however, the AMICO framework is general and flexible enough to work also for the wider space of microstructure imaging methods. Results demonstrate that AMICO represents an effective means to accelerate the fit of existing techniques drastically (up to four orders of magnitude faster) while preserving accuracy and precision in the estimated model parameters (correlation above 0.9). We believe that the availability of such ultrafast algorithms will help to accelerate the spread of microstructure imaging to larger cohorts of patients and to study a wider spectrum of neurological disorders.

Self-selection and risk selection on the Swiss health insurance market

Abstract This thesis presents three empirical studies in the field of health insurance in Switzerland. First we investigate the link between health insurance coverage and health care expenditures. We use claims data for over 60 000 adult individuals covered by a major Swiss Health Insurance Fund, followed for four years; the data show a strong positive correlation between coverage and expenditures. Two methods are developed and estimated in order to separate selection effects (due to individual choice of coverage) and incentive effects ("ex post moral hazard"). The first method uses the comparison between inpatient and outpatient expenditures to identify both effects and we conclude that both selection and incentive effects are significantly present in our data. The second method is based on a structural model of joint demand of health care and health insurance and makes the most of the change in the marginal cost of health care to identify selection and incentive effects. We conclude that the correlation between insurance coverage and health care expenditures may be decomposed into the two effects: 75% may be attributed to selection, and 25 % to incentive effects. Moreover, we estimate that a decrease in the coinsurance rate from 100% to 10% increases the marginal demand for health care by about 90% and from 100% to 0% by about 150%. Secondly, having shown that selection and incentive effects exist in the Swiss health insurance market, we present the consequence of this result in the context of risk adjustment. We show that if individuals choose their insurance coverage in function of their health status (selection effect), the optimal compensations should be function of the se- lection and incentive effects. Therefore, a risk adjustment mechanism which ignores these effects, as it is the case presently in Switzerland, will miss his main goal to eliminate incentives for sickness funds to select risks. Using a simplified model, we show that the optimal compensations have to take into account the distribution of risks through the insurance plans in case of self-selection in order to avoid incentives to select risks.Then, we apply our propositions to Swiss data and propose a simple econometric procedure to control for self-selection in the estimation of the risk adjustment formula in order to compute the optimal compensations.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Less Risk, More Effort : Demand Risk Allocation in Incomplete Contracts

This article investigates the allocation of demand risk within an incomplete contract framework. We consider an incomplete contractual relationship between a public authority and a private provider (i.e. a public-private partnership), in which the latter invests in non-verifiable cost-reducing efforts and the former invests in non-verifiable adaptation efforts to respond to changing consumer demand over time. We show that the party that bears the demand risk has fewer hold-up opportunities and that this leads the other contracting party to make more effort. Thus, in our model, bearing less risk can lead to more effort, which we describe as a new example of âeuro~counter-incentivesâeuro?. We further show that when the benefits of adaptation are important, it is socially preferable to design a contract in which the demand risk remains with the private provider, whereas when the benefits of cost-reducing efforts are important, it is socially preferable to place the demand risk on the public authority. We then apply these results to explain two well-known case studies.