The SAFE FOODS framework for improved risk analysis of foods

Three main changes to current risk analysis processes are proposed to improve their transparency, openness, and accountability. First, the addition of a formal framing stage would allow interested parties, experts and officials to work together as needed to gain an initial shared understanding of the issue, the objectives of regulatory action, and alternative risk management measures. Second, the scope of the risk assessment is expanded to include the assessment of health and environmental benefits as well as risks, and the explicit consideration of economic- and social-impacts of risk management action and their distribution. Moreover approaches were developed for deriving improved information from genomic, proteomic and metabolomic profiling methods and for probabilistic modelling of health impacts for risk assessment purposes. Third, in an added evaluation stage, interested parties, experts, and officials may compare and weigh the risks, costs, and benefits and their distribution. As part of a set of recommendations on risk communication, we propose that reports on each stage should be made public.

A note on estimating market–based minimum capital risk requirements: a multivariate GARCH approach

Internal risk management models of the kind popularized by J. P. Morgan are now used widely by the world’s most sophisticated financial institutions as a means of measuring risk. Using the returns on three of the most popular futures contracts on the London International Financial Futures Exchange, in this paper we investigate the possibility of using multivariate generalized autoregressive conditional heteroscedasticity (GARCH) models for the calculation of minimum capital risk requirements (MCRRs). We propose a method for the estimation of the value at risk of a portfolio based on a multivariate GARCH model. We find that the consideration of the correlation between the contracts can lead to more accurate, and therefore more appropriate, MCRRs compared with the values obtained from a univariate approach to the problem.

The use of risk registers by project managers

The construction industry is widely recognised as being inherent with risk and uncertainty. This necessitates the need for effective project risk management to achieve the project objectives of time, cost and quality. A popular tool employed in projects to aid in the management of risk is a risk register. This tool documents the project risks and is often employed by the Project Manager (PM) to manage the associated risks on a project. This research aims to ascertain how widely risk registers are used by Project Managers as part of their risk management practices. To achieve this aim entailed interviewing ten PMs, to discuss their use of the risk register as a risk management tool. The results from these interviews indicated the prevalent use of this document and recognised its effectiveness in the management of project risks. The findings identified the front end and feasibility phases of a project as crucial stages for using risk registers, noting it as a vital ingredient in the risk response planning of the decision making process. Moreover, the composition of the risk register was also understood, with an insight into how PMs produce and develop this tool also ascertained. In conclusion, this research signifies the extensive use of the risk register by PMs. A majority of PMs were of the view that risk registers constitute an essential component of their project risk management practices. This suggests a need for further research on the extent to which risk registers actually help PMs to control the risks in a construction project, particularly residual risks, and how this can be improved to minimize deviations from expected outcomes.

Private climate change reporting: an emerging discourse of risk and opportunity?

Purpose – This paper aims to explore the nature of the emerging discourse of private climate change reporting, which takes place in one-on-one meetings between institutional investors and their investee companies. Design/methodology/approach – Semi-structured interviews were conducted with representatives from 20 UK investment institutions to derive data which was then coded and analysed, in order to derive a picture of the emerging discourse of private climate change reporting, using an interpretive methodological approach, in addition to explorative analysis using NVivo software. Findings – The authors find that private climate change reporting is dominated by a discourse of risk and risk management. This emerging risk discourse derives from institutional investors' belief that climate change represents a material risk, that it is the most salient sustainability issue, and that their clients require them to manage climate change-related risk within their portfolio investment. It is found that institutional investors are using the private reporting process to compensate for the acknowledged inadequacies of public climate change reporting. Contrary to evidence indicating corporate capture of public sustainability reporting, these findings suggest that the emerging private climate change reporting discourse is being captured by the institutional investment community. There is also evidence of an emerging discourse of opportunity in private climate change reporting as the institutional investors are increasingly aware of a range of ways in which climate change presents material opportunities for their investee companies to exploit. Lastly, the authors find an absence of any ethical discourse, such that private climate change reporting reinforces rather than challenges the “business case” status quo. Originality/value – Although there is a wealth of sustainability reporting research, there is no academic research on private climate change reporting. This paper attempts to fill this gap by providing rich interview evidence regarding the nature of the emerging private climate change reporting discourse.

Foreign direct investment in high-risk environments: an historical perspective

Since the banking crisis of 2008 the global economy is perceived as riskier than before. Firms that cannot manage risks have withdrawn from countries in which they previously invested. These problems are not new. For centuries firms have invested in risky foreign environments, and many of them have succeeded. This paper reviews the risk management strategies of foreign investors. Using archival evidence and secondary sources it distinguishes the different types of risks that investors face and the different strategies by which risks can be managed. It investigates which strategies are used to manage which types of risk.

Private climate change reporting: a discourse of risk and opportunity

Purpose – This paper aims to explore the nature of the emerging discourse of private climate change reporting, which takes place in one-on-one meetings between institutional investors and their investee companies. Design/methodology/approach – Semi-structured interviews were conducted with representatives from 20 UK investment institutions to derive data which was then coded and analysed, in order to derive a picture of the emerging discourse of private climate change reporting, using an interpretive methodological approach, in addition to explorative analysis using NVivo software. Findings – The authors find that private climate change reporting is dominated by a discourse of risk and risk management. This emerging risk discourse derives from institutional investors' belief that climate change represents a material risk, that it is the most salient sustainability issue, and that their clients require them to manage climate change-related risk within their portfolio investment. It is found that institutional investors are using the private reporting process to compensate for the acknowledged inadequacies of public climate change reporting. Contrary to evidence indicating corporate capture of public sustainability reporting, these findings suggest that the emerging private climate change reporting discourse is being captured by the institutional investment community. There is also evidence of an emerging discourse of opportunity in private climate change reporting as the institutional investors are increasingly aware of a range of ways in which climate change presents material opportunities for their investee companies to exploit. Lastly, the authors find an absence of any ethical discourse, such that private climate change reporting reinforces rather than challenges the “business case” status quo. Originality/value – Although there is a wealth of sustainability reporting research, there is no academic research on private climate change reporting. This paper attempts to fill this gap by providing rich interview evidence regarding the nature of the emerging private climate change reporting discourse.

Informing operational flood management with ensemble predictions: lessons from Sweden.

This paper highlights some communicative and institutional challenges to using ensemble prediction systems (EPS) in operational flood forecasting, warning, and civil protection. Focusing in particular on the Swedish experience, as part of the PREVIEW FP6 project, of applying EPS to operational flood forecasting, the paper draws on a wider set of site visits, interviews, and participant observation with flood forecasting centres and civil protection authorities (CPAs) in Sweden and 15 other European states to reflect on the comparative success of Sweden in enabling CPAs to make operational use of EPS for flood risk management. From that experience, the paper identifies four broader lessons for other countries interested in developing the operational capacity to make, communicate, and use EPS for flood forecasting and civil protection. We conclude that effective training and clear communication of EPS, while clearly necessary, are by no means sufficient to ensure effective use of EPS. Attention must also be given to overcoming the institutional obstacles to their use and to identifying operational choices for which EPS is seen to add value rather than uncertainty to operational decision making by CPAs.

A word of caution on calculating market-based minimum capital risk requirements

This paper demonstrates that the use of GARCH-type models for the calculation of minimum capital risk requirements (MCRRs) may lead to the production of inaccurate and therefore inefficient capital requirements. We show that this inaccuracy stems from the fact that GARCH models typically overstate the degree of persistence in return volatility. A simple modification to the model is found to improve the accuracy of MCRR estimates in both back- and out-of-sample tests. Given that internal risk management models are currently in widespread usage in some parts of the world (most notably the USA), and will soon be permitted for EC banks and investment firms, we believe that our paper should serve as a valuable caution to risk management practitioners who are using, or intend to use this popular class of models.

Paying for long-term performance: restructuring bankers’ pay for risk regulation

The purpose of this paper is to propose hybrid capital securities as a new approach to compensation for senior bank executives and risk-takers instead of cash or equity-based compensation currently adopted by the industry. The global financial turmoil indicated that misaligned pay-for-performance compensation arrangements encouraged management short-termism and rewarded excessive risk-taking behaviour in Anglo-Saxon system. Rather than regulating specific instruments and processes, we believe that it is much more efficient to overhaul the compensation scheme to align it with risk management and governance. This empirical paper investigates the European hybrid market by employing data from the Merrill Lynch Global Index System from 2000 to 2010. Our paper contributes to both literature and practices by designing a structured scheme to tie the executive’s interests to long-term performance of the bank, the goal of regulators and the economy at large which consequently reduce the probability of future bank failures.

Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia

Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging due to reinforcing feedbacks between multiple drivers. We conducted semi-structured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation scenarios in the context of future drier climatic conditions. Scenarios also considered possible failure to respond in time to the emergent risk. This approach proved of great potential to support decision-making for risk management. It helped identify key forcing variables and generate insights into potential risks and trade-offs of different strategies. All scenarios showed increased wildfire risk in the event of more droughts. The ‘Hands-off’ scenario resulted in amplified impacts driven by intensifying trends, affecting particularly the agricultural production. The ‘Fire management’ scenario, which adopted a bottom-up approach to improve controlled burning, showed less trade-offs between wildfire risk reduction and production compared to the ‘Fire suppression’ scenario. Findings highlighted the importance of considering strategies that involve all actors who use fire, and the need to nest these strategies for a more systemic approach to manage wildfire risk. The FCM model could be used as a decision-support tool and serve as a ‘boundary object’ to facilitate collaboration and integration of different forms of knowledge and perceptions of fire in the region. This approach has also the potential to support decisions in other dynamic frontier landscapes around the world that are facing increased risk of large wildfires.

Modelling the hydraulics of the Carlisle 2005 flood event

The performance of a 2D numerical model of flood hydraulics is tested for a major event in Carlisle, UK, in 2005. This event is associated with a unique data set, with GPS surveyed wrack lines and flood extent surveyed 3 weeks after the flood. The Simple Finite Volume (SFV) model is used to solve the 2D Saint-Venant equations over an unstructured mesh of 30000 elements representing channel and floodplain, and allowing detailed hydraulics of flow around bridge piers and other influential features to be represented. The SFV model is also used to corroborate flows recorded for the event at two gauging stations. Calibration of Manning's n is performed with a two stage strategy, with channel values determined by calibration of the gauging station models, and floodplain values determined by optimising the fit between model results and observed water levels and flood extent for the 2005 event. RMS error for the calibrated model compared with surveyed water levels is ~±0.4m, the same order of magnitude as the estimated error in the survey data. The study demonstrates the ability of unstructured mesh hydraulic models to represent important hydraulic processes across a range of scales, with potential applications to flood risk management.

Construction subcontracts: for what we are about to receive

This paper is from a study on specialist and trade contracting in the construction industry. The research was commissioned by CIRIA and undertaken by the University of Reading in conjunction with Sir Alexander Gibb & Partners Ltd. The purpose of the work was to provide guidance for effective and equitable practice in the management of projects where much of the work is executed, and possibly designed, by specialist and trade contractors (STCs). As part of this study, a preliminary investigation into the nature and origins of specialist contracting was undertaken, in conjunction with a survey of the problems confronting STCs. This paper presents that phase of the project.

Evaluating a new LISFLOOD-FP formulation with data from the summer 2007 floods in Tewkesbury, UK

Two-dimensional flood inundation modelling is a widely used tool to aid flood risk management. In urban areas, where asset value and population density are greatest, the model spatial resolution required to represent flows through a typical street network (i.e. < 10m) often results in impractical computational cost at the whole city scale. Explicit diffusive storage cell models become very inefficient at such high resolutions, relative to shallow water models, because the stable time step in such schemes scales as a quadratic of resolution. This paper presents the calibration and evaluation of a recently developed new formulation of the LISFLOOD-FP model, where stability is controlled by the Courant–Freidrichs–Levy condition for the shallow water equations, such that, the stable time step instead scales linearly with resolution. The case study used is based on observations during the summer 2007 floods in Tewkesbury, UK. Aerial photography is available for model evaluation on three separate days from the 24th to the 31st of July. The model covered a 3.6 km by 2 km domain and was calibrated using gauge data from high flows during the previous month. The new formulation was benchmarked against the original version of the model at 20 m and 40 m resolutions, demonstrating equally accurate performance given the available validation data but at 67x faster computation time. The July event was then simulated at the 2 m resolution of the available airborne LiDAR DEM. This resulted in a significantly more accurate simulation of the drying dynamics compared to that simulated by the coarse resolution models, although estimates of peak inundation depth were similar.

Improving flood models using LiDAR: progress and problems

Airborne scanning laser altimetry (LiDAR) is an important new data source for river flood modelling. LiDAR can give dense and accurate DTMs of floodplains for use as model bathymetry. Spatial resolutions of 0.5m or less are possible, with a height accuracy of 0.15m. LiDAR gives a Digital Surface Model (DSM), so vegetation removal software (e.g. TERRASCAN) must be used to obtain a DTM. An example used to illustrate the current state of the art will be the LiDAR data provided by the EA, which has been processed by their in-house software to convert the raw data to a ground DTM and separate vegetation height map. Their method distinguishes trees from buildings on the basis of object size. EA data products include the DTM with or without buildings removed, a vegetation height map, a DTM with bridges removed, etc. Most vegetation removal software ignores short vegetation less than say 1m high. We have attempted to extend vegetation height measurement to short vegetation using local height texture. Typically most of a floodplain may be covered in such vegetation. The idea is to assign friction coefficients depending on local vegetation height, so that friction is spatially varying. This obviates the need to calibrate a global floodplain friction coefficient. It’s not clear at present if the method is useful, but it’s worth testing further. The LiDAR DTM is usually determined by looking for local minima in the raw data, then interpolating between these to form a space-filling height surface. This is a low pass filtering operation, in which objects of high spatial frequency such as buildings, river embankments and walls may be incorrectly classed as vegetation. The problem is particularly acute in urban areas. A solution may be to apply pattern recognition techniques to LiDAR height data fused with other data types such as LiDAR intensity or multispectral CASI data. We are attempting to use digital map data (Mastermap structured topography data) to help to distinguish buildings from trees, and roads from areas of short vegetation. The problems involved in doing this will be discussed. A related problem of how best to merge historic river cross-section data with a LiDAR DTM will also be considered. LiDAR data may also be used to help generate a finite element mesh. In rural area we have decomposed a floodplain mesh according to taller vegetation features such as hedges and trees, so that e.g. hedge elements can be assigned higher friction coefficients than those in adjacent fields. We are attempting to extend this approach to urban area, so that the mesh is decomposed in the vicinity of buildings, roads, etc as well as trees and hedges. A dominant points algorithm is used to identify points of high curvature on a building or road, which act as initial nodes in the meshing process. A difficulty is that the resulting mesh may contain a very large number of nodes. However, the mesh generated may be useful to allow a high resolution FE model to act as a benchmark for a more practical lower resolution model. A further problem discussed will be how best to exploit data redundancy due to the high resolution of the LiDAR compared to that of a typical flood model. Problems occur if features have dimensions smaller than the model cell size e.g. for a 5m-wide embankment within a raster grid model with 15m cell size, the maximum height of the embankment locally could be assigned to each cell covering the embankment. But how could a 5m-wide ditch be represented? Again, this redundancy has been exploited to improve wetting/drying algorithms using the sub-grid-scale LiDAR heights within finite elements at the waterline.