Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy. More stringent standards of proofs are demanded from model-based numbers, especially when these numbers represent potential financial losses, threats to human health or the state of the environment. Quantitative sensitivity analysis is generally agreed to be one such standard. Mathematical models are good at mapping assumptions into inferences. A modeller makes assumptions about laws pertaining to the system, about its status and a plethora of other, often arcane, system variables and internal model settings. To what extent can we rely on the model-based inference when most of these assumptions are fraught with uncertainties? Global Sensitivity Analysis offers an accessible treatment of such problems via quantitative sensitivity analysis, beginning with the first principles and guiding the reader through the full range of recommended practices with a rich set of solved exercises. The text explains the motivation for sensitivity analysis, reviews the required statistical concepts, and provides a guide to potential applications. The book: Provides a self-contained treatment of the subject, allowing readers to learn and practice global sensitivity analysis without further materials. Presents ways to frame the analysis, interpret its results, and avoid potential pitfalls. Features numerous exercises and solved problems to help illustrate the applications. Is authored by leading sensitivity analysis practitioners, combining a range of disciplinary backgrounds. Postgraduate students and practitioners in a wide range of subjects, including statistics, mathematics, engineering, physics, chemistry, environmental sciences, biology, toxicology, actuarial sciences, and econometrics will find much of use here. This book will prove equally valuable to engineers working on risk analysis and to financial analysts concerned with pricing and hedging.
Sensitivity analysis should be considered a pre-requisite for statistical model building in any scientific discipline where modelling takes place. For a non-expert, choosing the method of analysis for their model is complex, and depends on a number of factors. This book guides the non-expert through their problem in order to enable them to choose and apply the most appropriate method. It offers a review of the state-of-the-art in sensitivity analysis, and is suitable for a wide range of practitioners. It is focussed on the use of SIMLAB – a widely distributed freely-available sensitivity analysis software package developed by the authors – for solving problems in sensitivity analysis of statistical models. Other key features: Provides an accessible overview of the current most widely used methods for sensitivity analysis. Opens with a detailed worked example to explain the motivation behind the book. Includes a range of examples to help illustrate the concepts discussed. Focuses on implementation of the methods in the software SIMLAB - a freely-available sensitivity analysis software package developed by the authors. Contains a large number of references to sources for further reading. Authored by the leading authorities on sensitivity analysis.
The paper provides an extension to first generation DSGE models with a financial sector -- for which QUEST III would be a typical example -- by explicitly modelling (mortgage) loan demand and supply decisions. We estimate a DSGE model with a housing sector where housing capital is used as collateral against which impatient consumers borrow from more patient lenders. While in existing estimated models with a construction sector the Loan-to-Value (LTV) ratio is imposed exogenously and constant (e.g., Iacoviello and Neri, 2010, In't Veld et al., 2011), we introduce an endogenous LTV ratio by explicitly modelling the riskiness of loans in order to capture changing credit conditions. Using data of the Euro Area, we show that, compared to similar models with an exogenous LTV ratio, the business cycle properties of our model improve. The endogenous default mechanism allows estimating an important amplification mechanism driven by the riskiness of collateral values and propagating, in turn, into the real economy. Housing market-related shocks appear to be the main driver of the pre-crisis growth of mortgage-backed loans and a subsequent reversal of the sentiment on the housing market may have been a trigger that led to a credit crunch, house price bubble burst and a collapse in the construction sector. Shocks on the housing market had also a substantial impact on several demand aggregates, in particular, consumption."--Document home page.
This paper uses an estimated DSGE model to analyse the factors behind the build-up of imbalances in the Spanish economy. Shock decompositions suggest that external imbalances have been able to build up mainly due to the reduction in real interest rates and easier access to credit following the elimination of the exchange rate risk premium. While the reduction in external imbalances has started in the recent period, projections of the estimated model indicate that faster correction to these imbalances will require an adjustment in domestic demand and a significant improvement in the trade balance in the coming years. The correction would be eased in a more favourable and less risk-averse environment.."--Document home page.
This paper proposes a framework for sovereign debt sustainability assessment based on an estimated DSGE model. One advantage of this is that it allows taking into account feedback effects of debt ratios, spreads and fiscal measures on growth and tax bases, and thus capture the impact of changes in the composition of GDP which is pronounced during fiscal consolidation. Unsustainable debt developments may give rise to increasing interest rate spreads which could further reduce growth and tax revenue and worsen debt dynamics, while fiscal austerity measures are likely to reduce growth and lower tax revenues in the short run. Capturing the impact of risk premium on growth and public debt dynamics is crucial to understand current developments and policy trade-offs in euro area periphery countries."--Document home page.
We estimate a three-country model using 1995-2013 data for Germany, the Rest of the Euro Area (REA) and the Rest of the World (ROW) to analyze the determinants of Germany's current account surplus after the launch of the Euro. The most important factors driving the German surplus were positive shocks to the German saving rate and to ROW demand for German exports, as well as German labour market reforms and other positive German aggregate supply shocks. The convergence of REA interest rates to German rates due to the creation of the Euro only had a modest effect on the German current account and on German real activity. The key shocks that drove the rise in the German current account tended to worsen the REA trade balance, but had a weak effect on REA real activity. Our analysis suggests these driving factors are likely to be slowly eroded, leading to a very gradual reduction of the German current account surplus. An expansion in German government consumption and investment would raise German GDP and reduce the current account surplus, but the effects on the surplus are likely to be weak."--Document home page.
Sensitivity analysis should be considered a pre-requisite for statistical model building in any scientific discipline where modelling takes place. For a non-expert, choosing the method of analysis for their model is complex, and depends on a number of factors. This book guides the non-expert through their problem in order to enable them to choose and apply the most appropriate method. It offers a review of the state-of-the-art in sensitivity analysis, and is suitable for a wide range of practitioners. It is focussed on the use of SIMLAB – a widely distributed freely-available sensitivity analysis software package developed by the authors – for solving problems in sensitivity analysis of statistical models. Other key features: Provides an accessible overview of the current most widely used methods for sensitivity analysis. Opens with a detailed worked example to explain the motivation behind the book. Includes a range of examples to help illustrate the concepts discussed. Focuses on implementation of the methods in the software SIMLAB - a freely-available sensitivity analysis software package developed by the authors. Contains a large number of references to sources for further reading. Authored by the leading authorities on sensitivity analysis.
Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy. More stringent standards of proofs are demanded from model-based numbers, especially when these numbers represent potential financial losses, threats to human health or the state of the environment. Quantitative sensitivity analysis is generally agreed to be one such standard. Mathematical models are good at mapping assumptions into inferences. A modeller makes assumptions about laws pertaining to the system, about its status and a plethora of other, often arcane, system variables and internal model settings. To what extent can we rely on the model-based inference when most of these assumptions are fraught with uncertainties? Global Sensitivity Analysis offers an accessible treatment of such problems via quantitative sensitivity analysis, beginning with the first principles and guiding the reader through the full range of recommended practices with a rich set of solved exercises. The text explains the motivation for sensitivity analysis, reviews the required statistical concepts, and provides a guide to potential applications. The book: Provides a self-contained treatment of the subject, allowing readers to learn and practice global sensitivity analysis without further materials. Presents ways to frame the analysis, interpret its results, and avoid potential pitfalls. Features numerous exercises and solved problems to help illustrate the applications. Is authored by leading sensitivity analysis practitioners, combining a range of disciplinary backgrounds. Postgraduate students and practitioners in a wide range of subjects, including statistics, mathematics, engineering, physics, chemistry, environmental sciences, biology, toxicology, actuarial sciences, and econometrics will find much of use here. This book will prove equally valuable to engineers working on risk analysis and to financial analysts concerned with pricing and hedging.
The aim of this monograph is to present a self-contained introduction to some geometric and analytic aspects of the Yamabe problem. The book also describes a wide range of methods and techniques that can be successfully applied to nonlinear differential equations in particularly challenging situations. Such situations occur where the lack of compactness, symmetry and homogeneity prevents the use of more standard tools typically used in compact situations or for the Euclidean setting. The work is written in an easy style that makes it accessible even to non-specialists. After a self-contained treatment of the geometric tools used in the book, readers are introduced to the main subject by means of a concise but clear study of some aspects of the Yamabe problem on compact manifolds. This study provides the motivation and geometrical feeling for the subsequent part of the work. In the main body of the book, it is shown how the geometry and the analysis of nonlinear partial differential equations blend together to give up-to-date results on existence, nonexistence, uniqueness and a priori estimates for solutions of general Yamabe-type equations and inequalities on complete, non-compact Riemannian manifolds.
This book describes very recent results involving an extensive use of analytical tools in the study of geometrical and topological properties of complete Riemannian manifolds. It analyzes in detail an extension of the Bochner technique to the non compact setting, yielding conditions which ensure that solutions of geometrically significant differential equations either are trivial (vanishing results) or give rise to finite dimensional vector spaces (finiteness results). The book develops a range of methods, from spectral theory and qualitative properties of solutions of PDEs, to comparison theorems in Riemannian geometry and potential theory.
The aim of this paper is to analyze some of the relationships between oscillation theory for linear ordinary differential equations on the real line (shortly, ODE) and the geometry of complete Riemannian manifolds. With this motivation the authors prove some new results in both directions, ranging from oscillation and nonoscillation conditions for ODE's that improve on classical criteria, to estimates in the spectral theory of some geometric differential operator on Riemannian manifolds with related topological and geometric applications. To keep their investigation basically self-contained, the authors also collect some, more or less known, material which often appears in the literature in various forms and for which they give, in some instances, new proofs according to their specific point of view.
This book demonstrates the influence of geometry on the qualitative behaviour of solutions of quasilinear PDEs on Riemannian manifolds. Motivated by examples arising, among others, from the theory of submanifolds, the authors study classes of coercive elliptic differential inequalities on domains of a manifold M with very general nonlinearities depending on the variable x, on the solution u and on its gradient. The book highlights the mean curvature operator and its variants, and investigates the validity of strong maximum principles, compact support principles and Liouville type theorems. In particular, it identifies sharp thresholds involving curvatures or volume growth of geodesic balls in M to guarantee the above properties under appropriate Keller-Osserman type conditions, which are investigated in detail throughout the book, and discusses the geometric reasons behind the existence of such thresholds. Further, the book also provides a unified review of recent results in the literature, and creates a bridge with geometry by studying the validity of weak and strong maximum principles at infinity, in the spirit of Omori-Yau’s Hessian and Laplacian principles and subsequent improvements.
Aims to introduce the reader to various forms of the maximum principle, starting from its classical formulation up to generalizations of the Omori-Yau maximum principle at infinity obtained by the authors.
Della Porta has assembled a distinguished group of scholars who have made great strides in illuminating the early phases of the movement. The book includes especially keen analyses of the movement against global capitalism, particularly in its European manifestations." John D. McCarthy, Pennsylvania State University "Della Porta has skillfully coordinated a comparative study in six European countries and the US. Renowned scholars give testimony of the movement in their countries. [This is] the first attempt to document a genuine transnational movement." Bert Klandermans, Vrije Universiteit, Amsterdam You G-8, we 6 billion!" So went the chant at the international parade leading into the summit in Genoa, Italy. The global justice movement has led to a new wave of protest, building up transnational networks, inventing new strategies of action, constructing new images of democracy, and boldly asserting that "another world is possible". This book examines all this and more with case studies drawn from seven different countries, covering transnational networks and making cross-national comparisons. Leading European and American scholars analyze more than 300 organizations and 5,000 activists, looking at mobilizations that bridge old and new movements and bring politics back to the street. Contributors include: Massimiliano Andretta, Angel Calle, Helene Combes, Donatella della Porta, Nina Eggert, Marco Giugni, Jennifer Hadden, Manuel Jimenez, Raffaele Marchetti, Lorenzo Mosca, Mario Pianta, Herbert Reiter, Christopher Rootes, Dieter Rucht, Clare Saunders, Isabelle Sommier, Sidney Tarrow, Simon Teune, Mundo Yang.
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