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Factsheet
(2010)CRN ReportsDas Factsheet bietet einen Überblick über grundlegende Aspekte der Risikobewertung. Im Rahmen eines integrierten Risikomanagement-Prozesses folgt auf die anfängliche Risikoidentifikation die Bewertung von Risiken, die sodann der Vorbereitung von Massnahmen zur Risikoreduktion dient. Das Factsheet führt aus, dass eine wissenschaftliche Risikobewertung identifizierte Risiken möglichst präzise erfassen, beschreiben und falls möglich ...Report -
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Representation of Gaussian fields in series with independent coefficients
(2010)SAM Research ReportThe numerical discretization of problems with stochastic data or stochastic parameters generally involves the introduction of coordinates that describe the stochastic behavior, such as coefficients in a series expansion or values at discrete points. The series expansion of a Gaussian field with respect to any orthonormal basis of its Cameron--Martin space has independent standard normal coefficients. A standard choice for numerical ...Report -
Innovation, Competition and Incentives for R&D
(2010)KOF Working PapersThis paper analyses the relationship between past innovation output, competition, and future innovation input in a dynamic econometric setting. We distinguish two dimensions of competition that correspond to the concepts of product substitutability and entry barriers due to fixed costs. Based on firm-level panel data for Germany and Switzerland we obtain consistent results for both countries. Innovation output in t-1 as measured by the ...Working Paper -
Economics of endogenous technical change in CGE models - the role of gains from specialization
(2010)Economics Working Paper SeriesWorking Paper -
Multi-Level Monte Carlo Finite Element Method for elliptic PDEs with stochastic coefficients
(2010)SAM Research ReportIt is a well-known property of Monte Carlo methods that quadrupling the sample size halves the error. In the case of simulations of a stochastic partial differential equations, this implies that the total work is the sample size times the discretization costs of the equation. This leads to a convergence rate which is impractical for many simulations, namely in finance, physics and geosciences. With the Multi--level Monte Carlo method ...Report -
Analytic regularity and gpc approximation for parametric and random 2nd order hyperbolic PDEs
(2010)SAM Research ReportInitial boundary value problems of linear second order hyperbolic partial differential equations whose coefficients depend on countably many random parameters are reduced to a parametric family of deterministic initial boundary value problems on an infinite dimensional parameter space. This parametric family is approximated by Galerkin projection onto finitely supported polynomial systems in the parameter space. We establish uniform ...Report -