Can Italy and Spain survive rates of 6-7%? CEPS Policy Brief No. 279, 27 July 2012

The sentiment that the euro is now in real danger is based in large part on the widespread conviction that interest rates of 6-7% are simply unsustainable for both Italy and Spain., After taking a closer look at the fundamentals, however, Daniel Gros concludes in this new Policy Brief that both countries should be able to live with this level of interest rates for quite some time, but only if they mobilize domestic savings, which remain strong in both countries. For Spain, some debt/equity swaps are also needed.

The use of innovative financial instruments for financing EU policies and objectives: Implications for EU and national budgets. CEPS Special Report, October 2012

This CEPS Special Report analyses the proposed expansion of innovative financial instruments in the EU Multiannual Financial Framework for the 2014–20 period. It presents the economic rationale, governance principles and criteria that these instruments should follow and compares these with proposals from the European Commission. Based on this assessment, it makes recommendations for the proposed instruments.

Performance of long-term care systems in Europe. ENEPRI Policy Brief No. 13, December 2012

The evaluation of long-term care (LTC) systems carried out in Work Package 7 of the ANCIEN project shows which performance criteria are important and – based on the available information – how European countries score on those criteria. This paper summarises the results and discusses the policy implications. An overall evaluation was carried out for four representative countries: Germany, the Netherlands, Spain and Poland. Of the four countries, the Dutch system has the highest scores on quality of life of LTC users, quality of care and equity of the LTC system, and it performs the secondbest after Poland in terms of the total burden of care (consisting of the financial burden and the burden of informal caregiving). The German system has somewhat lower scores than the Dutch on all four dimensions. The Polish system excels in having a low total burden of care, but it scores the lowest on quality of care and equity. The Spanish system has few extreme scores. Some important lessons are the following. The performance of a LTC system is a complex concept where many dimensions have to be included. Specifically, the impact of informal caregiving on the caregivers and on society should not be forgotten. The role of the state in funding and organising LTC versus individual responsibilities is one of the most important differences among countries. Choices concerning private funding and the role of informal care have a large effect not only on the public expenditures but also on the fairness of the system. International research into the relative preferences for the different performance criteria could produce a sound basis for the weights used in the overall evaluation.

Application of the Lighthill-Ford theory of spontaneous imbalance to clear-air turbulence forecasting

A new method of clear-air turbulence (CAT) forecasting based on the Lighthill–Ford theory of spontaneous imbalance and emission of inertia–gravity waves has been derived and applied on episodic and seasonal time scales. A scale analysis of this shallow-water theory for midlatitude synoptic-scale flows identifies advection of relative vorticity as the leading-order source term. Examination of leading- and second-order terms elucidates previous, more empirically inspired CAT forecast diagnostics. Application of the Lighthill–Ford theory to the Upper Mississippi and Ohio Valleys CAT outbreak of 9 March 2006 results in good agreement with pilot reports of turbulence. Application of Lighthill–Ford theory to CAT forecasting for the 3 November 2005–26 March 2006 period using 1-h forecasts of the Rapid Update Cycle (RUC) 2 1500 UTC model run leads to superior forecasts compared to the current operational version of the Graphical Turbulence Guidance (GTG1) algorithm, the most skillful operational CAT forecasting method in existence. The results suggest that major improvements in CAT forecasting could result if the methods presented herein become operational.

Financial protection in the UK building industry: bonds, retentions and guarantees

Financial Protection in the UK Building Industry provides comprehensive treatment of a complex aspect of construction management which is increasingly important in modern construction contracts. The term 'Financial Protection' refers to refers to the various mechanisms by which funds are made available to ensure the due performance of a partys contractual obligations. This book is based on material written for a research project funded by the Reading Construction Forum. Financial Protection in the UK Building Industry looks at the legal and economic background to the problem of providing financial protection to clients to guard against poor performance and or the insolvency of contractors, consultants and sub-contractors. The inclusion of practical guidance notes and summaries makes this a valuable guide for the construction professional as well as for the researcher. * provides in-depth analysis of financial protection measures * explores the ways in which financial protection can increase efficiency in the industry * financial protection in construction is beset with problems - this book points toward practical solutions

Contemporary organizational theory in the management of construction projects

The level of insolvencies in the construction industry is high, when compared to other industry sectors. Given the management expertise and experience that is available to the construction industry, it seems strange that, according to the literature, the major causes of failure are lack of financial control and poor management. This indicates that with a good cash flow management, companies could be kept operating and financially healthy. It is possible to prevent failure. Although there are financial models that can be used to predict failure, they are based on company accounts, which have been shown to be an unreliable source of data. There are models available for cash flow management and forecasting and these could be used as a starting point for managers in rethinking their cash flow management practices. The research reported here has reached the stage of formulating researchable questions for an in-depth study including issues such as how contractors manage their cash flow, how payment practices can be managed without damaging others in the supply chain and the relationships between companies" financial structures and the payment regimes to which they are subjected.

Cash flow management in construction firms

The level of insolvencies in the construction industry is high, when compared to other industry sectors. Given the management expertise and experience that is available to the construction industry, it seems strange that, according to the literature, the major causes of failure are lack of financial control and poor management. This indicates that with a good cash flow management, companies could be kept operating and financially healthy. It is possible to prevent failure. Although there are financial models that can be used to predict failure, they are based on company accounts, which have been shown to be an unreliable source of data. There are models available for cash flow management and forecasting and these could be used as a starting point for managers in rethinking their cash flow management practices. The research reported here has reached the stage of formulating researchable questions for an in-depth study including issues such as how contractors manage their cash flow, how payment practices can be managed without damaging others in the supply chain and the relationships between companies’ financial structures and the payment regimes to which they are subjected.

Ensemble-based data assimilation and the localisation problem

The “butterfly effect” is a popularly known paradigm; commonly it is said that when a butterfly flaps its wings in Brazil, it may cause a tornado in Texas. This essentially describes how weather forecasts can be extremely senstive to small changes in the given atmospheric data, or initial conditions, used in computer model simulations. In 1961 Edward Lorenz found, when running a weather model, that small changes in the initial conditions given to the model can, over time, lead to entriely different forecasts (Lorenz, 1963). This discovery highlights one of the major challenges in modern weather forecasting; that is to provide the computer model with the most accurately specified initial conditions possible. A process known as data assimilation seeks to minimize the errors in the given initial conditions and was, in 1911, described by Bjerkness as “the ultimate problem in meteorology” (Bjerkness, 1911).

Cone model-based SEP event calculations for applications to multipoint observations

The problem of modeling solar energetic particle (SEP) events is important to both space weather research and forecasting, and yet it has seen relatively little progress. Most important SEP events are associated with coronal mass ejections (CMEs) that drive coronal and interplanetary shocks. These shocks can continuously produce accelerated particles from the ambient medium to well beyond 1 AU. This paper describes an effort to model real SEP events using a Center for Integrated Space weather Modeling (CISM) MHD solar wind simulation including a cone model of CMEs to initiate the related shocks. In addition to providing observation-inspired shock geometry and characteristics, this MHD simulation describes the time-dependent observer field line connections to the shock source. As a first approximation, we assume a shock jump-parameterized source strength and spectrum, and that scatter-free transport occurs outside of the shock source, thus emphasizing the role the shock evolution plays in determining the modeled SEP event profile. Three halo CME events on May 12, 1997, November 4, 1997 and December 13, 2006 are used to test the modeling approach. While challenges arise in the identification and characterization of the shocks in the MHD model results, this approach illustrates the importance to SEP event modeling of globally simulating the underlying heliospheric event. The results also suggest the potential utility of such a model for forcasting and for interpretation of separated multipoint measurements such as those expected from the STEREO mission.

Global scale water stages from SAR imagery (GlosSARi) to support global flood forecasting

Despite the success of studies attempting to integrate remotely sensed data and flood modelling and the need to provide near-real time data routinely on a global scale as well as setting up online data archives, there is to date a lack of spatially and temporally distributed hydraulic parameters to support ongoing efforts in modelling. Therefore, the objective of this project is to provide a global evaluation and benchmark data set of floodplain water stages with uncertainties and assimilation in a large scale flood model using space-borne radar imagery. An algorithm is developed for automated retrieval of water stages with uncertainties from a sequence of radar imagery and data are assimilated in a flood model using the Tewkesbury 2007 flood event as a feasibility study. The retrieval method that we employ is based on possibility theory which is an extension of fuzzy sets and that encompasses probability theory. In our case we first attempt to identify main sources of uncertainty in the retrieval of water stages from radar imagery for which we define physically meaningful ranges of parameter values. Possibilities of values are then computed for each parameter using a triangular ‘membership’ function. This procedure allows the computation of possible values of water stages at maximum flood extents along a river at many different locations. At a later stage in the project these data are then used in assimilation, calibration or validation of a flood model. The application is subsequently extended to a global scale using wide swath radar imagery and a simple global flood forecasting model thereby providing improved river discharge estimates to update the latter.

Singular vector ensemble forecasting systems and the prediction of flow dependent uncertainty

The ECMWF ensemble weather forecasts are generated by perturbing the initial conditions of the forecast using a subset of the singular vectors of the linearised propagator. Previous results show that when creating probabilistic forecasts from this ensemble better forecasts are obtained if the mean of the spread and the variability of the spread are calibrated separately. We show results from a simple linear model that suggest that this may be a generic property for all singular vector based ensemble forecasting systems based on only a subset of the full set of singular vectors.

Commercial management in project-based organisations

The term commercial management has been used for some time, similarly the job title commercial manager. However, as of yet, little emphasis has been placed on defining. This paper presents the findings from a two-year research initiative that has compared and contrasted the role of commercial managers from a range of organisations and across industry sectors, as a first step in developing a body of knowledge for commercial. It is argued that there are compelling arguments for considering commercial management, not solely as atask undertaken by commercial managers, but as a discipline in itself: a discipline that, arguably, bridges traditional project management and organisational theories. While the study has established differences in approach and application both between and within industry sectors, it has established sufficient similarity and synergy in practice to identify a specific role of commercial management in project-based organisations. These similarities encompass contract management and dispute resolution; the divergences include a greater involvement in financial and value management in construction and in bid management in defence/aerospace.

Variable selection for financial distress classification using a genetic algorithm

This paper is concerned with the use of a genetic algorithm to select financial ratios for corporate distress classification models. For this purpose, the fitness value associated to a set of ratios is made to reflect the requirements of maximizing the amount of information available for the model and minimizing the collinearity between the model inputs. A case study involving 60 failed and continuing British firms in the period 1997-2000 is used for illustration. The classification model based on ratios selected by the genetic algorithm compares favorably with a model employing ratios usually found in the financial distress literature.