Pareto's Law of Income Distribution: Evidence for Germany, the United Kingdom, and the United States

We analyze three sets of income data: the US Panel Study of Income Dynamics PSID), the British Household Panel Survey (BHPS), and the German Socio-Economic Panel (GSOEP). It is shown that the empirical income distribution is consistent with a two-parameter lognormal function for the low-middle income group (97%-99% of the population), and with a Pareto or power law function for the high income group (1%-3% of the population). This mixture of two qualitatively different analytical distributions seems stable over the years covered by our data sets, although their parameters significantly change in time. It is also found that the probability density of income growth rates almost has the form of an exponential function.Comment: Latex2e v1.6; 16 pages with 5 figure

The Importance of Trust for Investment: Evidence from Venture Capital

We examine the effect of trust on financial investment and contracting decisions in a micro-economic environment where trust is exogenous. Using hand-collected data on European venture capital, we show that the Eurobarometer measure of trust among nations significantly affects investment decisions. This holds even after controlling for investor and company fixed effects, geographic distance, information and transaction costs. The national identity of venture capital firms' individual partners further contributes to the effect of trust. Education and work experience reduce the effect of trust but do not eliminate it. We also examine the relationship between trust and sophisticated contracts involving contingent control rights and find that, even after controlling for endogeneity, they are complements, not substitutes.

Estimate of a spatially variable reservoir compressibility by assimilation of ground surface displacement data

Abstract. Fluid extraction from producing hydrocarbon reservoirs can cause anthropogenic land subsidence. In this work, a 3-D finite-element (FE) geomechanical model is used to predict the land surface displacements above a gas field where displacement observations are available. An ensemble-based data assimilation (DA) algorithm is implemented that incorporates these observations into the response of the FE geomechanical model, thus re- ducing the uncertainty on the geomechanical parameters of the sedimentary basin embedding the reservoir. The calibration focuses on the uniaxial vertical compressibility c M , which is often the geomechanical parameter to which the model response is most sensitive. The partition of the reservoir into blocks delimited by faults moti- vates the assumption of a heterogeneous spatial distribution of c M within the reservoir. A preliminary synthetic test case is here used to evaluate the effectiveness of the DA algorithm in reducing the parameter uncertainty associated with a heterogeneous c M distribution. A significant improvement in matching the observed data is obtained with respect to the case in which a homogeneous c M is hypothesized. These preliminary results are quite encouraging and call for the application of the procedure to real gas fields

Pentraxin 3 in cardiovascular disease

The long pentraxin PTX3 is a member of the pentraxin family produced locally by stromal and myeloid cells in response to proinflammatory signals and microbial moieties. The prototype of the pentraxin family is C reactive protein (CRP), a widely-used biomarker in human pathologies with an inflammatory or infectious origin. Data so far describe PTX3 as a multifunctional protein acting as a functional ancestor of antibodies and playing a regulatory role in inflammation. Cardiovascular disease (CVD) is a leading cause of mortality worldwide, and inflammation is crucial in promoting it. Data from animal models indicate that PTX3 can have cardioprotective and atheroprotective roles regulating inflammation. PTX3 has been investigated in several clinical settings as possible biomarker of CVD. Data collected so far indicate that PTX3 plasma levels rise rapidly in acute myocardial infarction, heart failure and cardiac arrest, reflecting the extent of tissue damage and predicting the risk of mortality

Towards a Conceptualization of Sociomaterial Entanglement

In knowledge representation, socio-technical systems can be modeled as multiagent systems in which the local knowledge of each individual agent can be seen as a context. In this paper we propose formal ontologies as a means to describe the assumptions driving the construction of contexts as local theories and to enable interoperability among them. In particular, we present two alternative conceptualizations of the notion of sociomateriality (and entanglement), which is central in the recent debates on socio-technical systems in the social sciences, namely critical and agential realism. We thus start by providing a model of entanglement according to the critical realist view, representing it as a property of objects that are essentially dependent on different modules of an already given ontology. We refine then our treatment by proposing a taxonomy of sociomaterial entanglements that distinguishes between ontological and epistemological entanglement. In the final section, we discuss the second perspective, which is more challenging form the point of view of knowledge representation, and we show that the very distinction of information into modules can be at least in principle built out of the assumption of an entangled reality

The World-Trade Web: Topological Properties, Dynamics, and Evolution

This paper studies the statistical properties of the web of import-export relationships among world countries using a weighted-network approach. We analyze how the distributions of the most important network statistics measuring connectivity, assortativity, clustering and centrality have co-evolved over time. We show that all node-statistic distributions and their correlation structure have remained surprisingly stable in the last 20 years -- and are likely to do so in the future. Conversely, the distribution of (positive) link weights is slowly moving from a log-normal density towards a power law. We also characterize the autoregressive properties of network-statistics dynamics. We find that network-statistics growth rates are well-proxied by fat-tailed densities like the Laplace or the asymmetric exponential-power. Finally, we find that all our results are reasonably robust to a few alternative, economically-meaningful, weighting schemes.Comment: 44 pages, 39 eps figure

Reservoir characterization in an underground gas storage field using joint inversion of flow and geodetic data

Characterization of reservoir properties like porosity and permeability in reservoir models typically relies on history matching of production data, well pressure data, and possibly other fluid-dynamical data. Calibrated (history-matched) reservoir models are then used for forecasting production and designing effective strategies for improved oil and gas recovery. Here, we perform assimilation of both flow and deformation data for joint inversion of reservoir properties. Given the coupled nature of subsurface flow and deformation processes, joint inversion requires efficient simulation tools of coupled reservoir flow and mechanical deformation. We apply our coupled simulation tool to a real underground gas storage field in Italy. We simulate the initial gas production period and several decades of seasonal natural gas storage and production. We perform a probabilistic estimation of rock properties by joint inversion of ground deformation data from geodetic measurements and fluid flow data from wells. Using an efficient implementation of the ensemble smoother as the estimator and our coupled multiphase flow and geomechanics simulator as the forward model, we show that incorporating deformation data leads to a significant reduction of uncertainty in the prior distributions of rock properties such as porosity, permeability, and pore compressibility.Eni S.p.A. (Firm