The Role of Institutions in Cross-Section Income and Panel Data Growth Models: A Deeper Investigation on the Weakness and Proliferation of Instruments

This paper investigates the role of institutions in determining per capita income levels and growth. It contributes to the empirical literature by using different variables as proxies for institutions and by developing a deeper analysis of the issues arising from the use of weak and too many instruments in per capita income and growth regressions. The cross-section estimation suggests that institutions seem to matter, regardless if they are the only explanatory variable or are combined with geographical and integration variables, although most models suffer from the issue of weak instruments. The results from the growth models provides some interesting results: there is mixed evidence on the role of institutions and such evidence is more likely to be associated with law and order and investment profile; government spending is an important policy variable; collapsing the number of instruments results in fewer significant coefficients for institutions.

International Evidence on the New Keynesian Phillips Curve Using Aggregate and Disaggregate Data

We present a unique empirical analysis of the properties of the New Keynesian Phillips Curve using an international dataset of aggregate and disaggregate sectoral in ation. Our results from panel time-series estimation clearly indicate that sectoral heterogeneity has important consequences for aggregate in ation behaviour. Heterogeneity helps to explain the overestimation of in ation persistence and underestimation of the role of marginal costs in empirical investigations of the NKPC that use aggregate data. We nd that combining disaggregate information with heterogeneous-consistent estimation techniques helps to reconcile, to a large extent, the NKPC with the data.

The new direct oral anticoagulants in special indications: rationale and preliminary data in cancer, mechanical heart valves, anti-phospholipid syndrome, and heparin-induced thrombocytopenia and beyond.

The present review will briefly summarize the interplay between coagulation and inflammation, highlighting possible effects of direct inhibition of factor Xa and thrombin beyond anticoagulation. Additionally, the rationale for the use of the new direct oral anticoagulants (DOACs) for indications such as cancer-associated venous thromboembolism (CAT), mechanical heart valves, thrombotic anti-phospholipid syndrome (APS), and heparin-induced thrombocytopenia (HIT) will be explored. Published data on patients with cancer or mechanical heart valves treated with DOAC will be discussed, as well as planned studies in APS and HIT. Although at the present time published evidence is insufficient for recommending DOAC in the above-mentioned indications, there are good arguments in favor of clinical trials investigating their efficacy in these contexts. Direct inhibition of factor Xa or thrombin may reveal interesting effects beyond anticoagulation as well.

Prevalence of victims of violence admitted to an emergency department.

OBJECTIVE: To collect data on the consultation frequency and demographic profile of victims of violence attending an emergency department (ED) in Switzerland. METHODS: We undertook screening of all admitted adult patients (>16 years) in the ED of the CHUV, Lausanne, Switzerland, over a 1 month period, using a modified version of the Partner Violence Screen questionnaire. Exclusionary criteria were: life threatening injury (National Advisory Committee on Aeronautics score > or =4), or inability to understand or speak French, to give oral informed consent, or to be questioned without a family member or accompanying person being present. Data were collected on history of physical and/or psychological violence during the previous 12 months, the type of violence experienced by the patient, and if violence was the reason for the current consultation. Sociodemographic data were obtained from the registration documents. RESULTS: The final sample consisted of 1602 patients (participation rate of 77.2%), with a refusal rate of 1.1%. Violence during the past 12 months was reported by 11.4% of patients. Of the total sample, 25% stated that violence was the reason for the current consultation; of these, 95% of patients were confirmed as victims of violence by the ED physicians. Patients reporting violence were more likely to be young and separated from their partner. Men were more likely to be victims of public violence and women more commonly victims of domestic violence. CONCLUSIONS: Based on this monthly prevalence rate, we estimate that over 3000 adults affected by violence consult our ED per annum. This underlines the importance of the problem and the need to address it. Health services organisations should establish measures to improve quality of care for victims. Guidelines and educational programmes for nurses and physicians should be developed in order to enhance providers' skills and basic knowledge of all types of violence, how to recognise and interact appropriately with victims, and where to refer these patients for follow up care in their local networks.

Is real GDP stationary? Evidence from a panel unit root test with cross-sectional dependence and historical data

We use historical data that cover more than one century on real GDP for industrial countries and employ the Pesaran panel unit root test that allows for cross-sectional dependence to test for a unit root on real GDP. We find strong evidence against the unit root null. Our results are robust to the chosen group of countries and the sample period. Key words: real GDP stationarity, cross-sectional dependence, CIPS test. JEL Classification: C23, E32

Quantitative integration of geophysical and hydraulic data : from the local towards the regional scale range

Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.

Multiple-scale hydrological and geophysical data integration through non-linear Bayesian sequential simulation

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the scale of a field site represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed downscaling procedure based on a non-linear Bayesian sequential simulation approach. The main objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity logged at collocated wells and surface resistivity measurements, which are available throughout the studied site. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariatekernel density function. Then a stochastic integration of low-resolution, large-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities is applied. The overall viability of this downscaling approach is tested and validated by comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure allows obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Analyzing complex rock slope deformation at Stampa, western Norway, by integrating geomorphology, kinematics and numerical modeling

The unstable rock slope, Stampa, above the village of Flåm, Norway, shows signs of both active and postglacial gravitational deformation over an area of 11 km2. Detailed structural field mapping, annual differential Global Navigation Satellite System (GNSS) surveys, as well as geomorphic analysis of high-resolution digital elevation models based on airborne and terrestrial laser scanning indicate that slope deformation is complex and spatially variable. Numerical modeling was used to investigate the influence of former rockslide activity and to better understand the failure mechanism. Field observations, kinematic analysis and numerical modeling indicate a strong structural control of the unstable area. Based on the integration of the above analyses, we propose that the failure mechanism is dominated by (1) a toppling component, (2) subsiding bilinear wedge failure and (3) planar sliding along the foliation at the toe of the unstable slope. Using differential GNSS, 18 points were measured annually over a period of up to 6 years. Two of these points have an average yearly movement of around 10 mm/year. They are located at the frontal cliff on almost completely detached blocks with volumes smaller than 300,000 m3. Large fractures indicate deep-seated gravitational deformation of volumes reaching several 100 million m3, but the movement rates in these areas are below 2 mm/year. Two different lobes of prehistoric rock slope failures were dated with terrestrial cosmogenic nuclides. While the northern lobe gave an average age of 4,300 years BP, the southern one resulted in two different ages (2,400 and 12,000 years BP), which represent most likely multiple rockfall events. This reflects the currently observable deformation style with unstable blocks in the northern part in between Joasete and Furekamben and no distinct blocks but a high rockfall activity around Ramnanosi in the south. With a relative susceptibility analysis it is concluded that small collapses of blocks along the frontal cliff will be more frequent. Larger collapses of free-standing blocks along the cliff with volumes > 100,000 m3, thus large enough to reach the fjord, cannot be ruled out. A larger collapse involving several million m3 is presently considered of very low likelihood.

Coronary MR angiography: comparison of quantitative and qualitative data from four techniques.

OBJECTIVE: The optimal coronary MR angiography sequence has yet to be determined. We sought to quantitatively and qualitatively compare four coronary MR angiography sequences. SUBJECTS AND METHODS. Free-breathing coronary MR angiography was performed in 12 patients using four imaging sequences (turbo field-echo, fast spin-echo, balanced fast field-echo, and spiral turbo field-echo). Quantitative comparisons, including signal-to-noise ratio, contrast-to-noise ratio, vessel diameter, and vessel sharpness, were performed using a semiautomated analysis tool. Accuracy for detection of hemodynamically significant disease (> 50%) was assessed in comparison with radiographic coronary angiography. RESULTS: Signal-to-noise and contrast-to-noise ratios were markedly increased using the spiral (25.7 +/- 5.7 and 15.2 +/- 3.9) and balanced fast field-echo (23.5 +/- 11.7 and 14.4 +/- 8.1) sequences compared with the turbo field-echo (12.5 +/- 2.7 and 8.3 +/- 2.6) sequence (p < 0.05). Vessel diameter was smaller with the spiral sequence (2.6 +/- 0.5 mm) than with the other techniques (turbo field-echo, 3.0 +/- 0.5 mm, p = 0.6; balanced fast field-echo, 3.1 +/- 0.5 mm, p < 0.01; fast spin-echo, 3.1 +/- 0.5 mm, p < 0.01). Vessel sharpness was highest with the balanced fast field-echo sequence (61.6% +/- 8.5% compared with turbo field-echo, 44.0% +/- 6.6%; spiral, 44.7% +/- 6.5%; fast spin-echo, 18.4% +/- 6.7%; p < 0.001). The overall accuracies of the sequences were similar (range, 74% for turbo field-echo, 79% for spiral). Scanning time for the fast spin-echo sequences was longest (10.5 +/- 0.6 min), and for the spiral acquisitions was shortest (5.2 +/- 0.3 min). CONCLUSION: Advantages in signal-to-noise and contrast-to-noise ratios, vessel sharpness, and the qualitative results appear to favor spiral and balanced fast field-echo coronary MR angiography sequences, although subjective accuracy for the detection of coronary artery disease was similar to that of other sequences.