This Article examines scenario analysis, a disruptive argumentation technique used by the German Federal Constitutional Court (GFCC) in recent high-profile cases, such as the so-called climate protection case (Klimaschutz) and other decisions on the fundamental right to intergenerational justice (Grundrecht auf Generationengerechitgkeit). After explaining the basic argumentative steps involved in scenario analysis, for example designing scenarios, identifying stakeholders, relating scenarios to strategies, determining the main driving forces, estimating scenario probabilities, the Article sketches a normative model for rational scenario design. The normative model is used as a lens for evaluating the arguments developed by the GFCC in the climate protection case. Such evaluation also builds on game-theoretic insights and points out some weaknesses in the Court’s argument. Finally, the Article observes that, as scenario analysis is used to assess the future impact of legislative decisions, it has the effect of imposing greater constraints on legislatures.

The model uncertainty issue is pervasive in virtually all applied fields but especially critical in insurance and finance. To hedge against the uncertainty of the underlying probability distribution, which we refer to as ambiguity, the worst case is often considered in quantifying the underlying risk. However, this worst-case treatment often yields results that are overly conservative. We argue that, in most practical situations, a generic risk is realized from multiple scenarios and the risk in some ordinary scenarios may be subject to negligible ambiguity so that it is safe to trust the reference distributions. Hence, we only need to consider the worst case in the other scenarios where ambiguity is significant. We implement this idea in the study of the worst-case moments of a risk in the hope to alleviate the over-conservativeness issue. Note that the ambiguity in our consideration exists in both the scenario indicator and the risk in the corresponding scenario, leading to a two-fold ambiguity issue. We employ the Wasserstein distance to construct an ambiguity ball. Then, we disentangle the ambiguity along the scenario indicator and the risk in the corresponding scenario, so that we convert the two-fold optimization problem into two one-fold problems. Our main result is a closed-form worst-case moment estimate. Our numerical studies illustrate that the consideration of partial ambiguity indeed greatly alleviates the over-conservativeness issue.

There have been important developments in the measurement of farm animal welfare in recent years. Measuring animal welfare is one thing, implementing a farm animal welfare assessment system another. The implementation of such a system occurs in an environment that is influenced by economic, political, technological and socio-cultural factors which interact with each other. This creates enormous complexity, generates a huge number of different potential ‘futures’, and makes the eventual impact that the system will have on the welfare of farm animals uncertain. This article draws upon strategic management literature to apply scenario analysis as a technique to help understand the variance of the uncertainty associated with the implementation of an animal welfare assessment scheme. Specifically, it develops two extreme scenarios based on a theoretical European-wide implementation: one scenario in which all uncertain factors influence the implementation of the assessment system in a negative way, and one scenario in which all these factors have positive impacts. These scenarios provide insight into the variance of possible futures in which the system may have to function. Although consumers are an important stakeholder group, their role in creating uncertainty for the system may be overestimated; it is apparent that the roles of companies, brands and certification organisations deserve significant attention, as well as any relevant institutional structure.

This paper examines the economic implications of the tariff increases by the United States and by China during the Trump era trade dispute and the gains from their potential removal. The increases were dramatic, with the US raising tariffs on industrial products by a factor of six – with particularly large tariff increases on intermediate and capital goods – and China increasing its tariffs on US agricultural products more than five-fold. These changes distort trade and production decisions in both countries and undercut the global trading system. They resulted in substantial economic losses to each country, with import volumes reduced by 4.9% in China and 4.5% in the USA, and bilateral trade patterns were massively distorted. Their cost to the United States rose at the end of 2021, when the import expansion provisions of the Trump era Phase One Agreement expired. Negotiating the abolition of these costly and disruptive tariffs would generate substantial real income gains for both countries and help lower US consumer prices.

This paper illustrates the potential impacts of climate change on financial markets, focusing on their long-term significance. It uses a top-down modelling tool developed by Ortec Finance in partnership with Cambridge Econometrics that combines climate science with macro-economic and financial effects to examine the possible impacts of three plausible (not extreme) climate pathways. The paper first considers the impact on gross domestic product (GDP), finding that GDP is lower in all three pathways, with the most severe reduction in the Failed Transition Pathway where the Paris Agreement climate targets are not met. The model then translates these GDP impacts into financial market effects. In the Failed Transition Pathway, cumulative global equity returns are approximately 50% lower over the period 2020–2060 than in the climate-uninformed base case. For the other two pathways where the Paris Agreement targets are met, the corresponding figures are 15% and 25% lower returns than in the base case. Results are provided for other asset classes too. These demonstrate that climate change represents a significant market risk, with implications for financial planning, modelling and regulation.

This paper demonstrates how climate scenario analysis can be used for forward-looking assessment of the risks and opportunities for financial institutions, using a case study for a UK defined benefit pension scheme. It uses a top-down modelling tool developed by Ortec Finance in partnership with Cambridge Econometrics to explore the possible impacts of three plausible (not extreme) climate pathways of the scheme’s assets and liabilities. It finds that the funding risks are greater under all three climate pathways than under the climate-uninformed base scenario. In the absence of changes to the investment strategy or recovery plan, the time taken to reach full funding is increased by three to nine years. Given that most models currently used by actuaries do not make explicit adjustments for climate change, these modelled results suggest it is quite likely that pension schemes are systematically underestimating the funding risks they face.

This paper presents Parallel World Framework as a solution for simulations of complex systems within a time-varying knowledge graph and its application to the electric grid of Jurong Island in Singapore. The underlying modeling system is based on the Semantic Web Stack. Its linked data layer is described by means of ontologies, which span multiple domains. The framework is designed to allow what-if scenarios to be simulated generically, even for complex, inter-linked, cross-domain applications, as well as conducting multi-scale optimizations of complex superstructures within the system. Parallel world containers, introduced by the framework, ensure data separation and versioning of structures crossing various domain boundaries. Separation of operations, belonging to a particular version of the world, is taken care of by a scenario agent. It encapsulates functionality of operations on data and acts as a parallel world proxy to all of the other agents operating on the knowledge graph. Electric network optimization for carbon tax is demonstrated as a use case. The framework allows to model and evaluate electrical networks corresponding to set carbon tax values by retrofitting different types of power generators and optimizing the grid accordingly. The use case shows the possibility of using this solution as a tool for CO2 reduction modeling and planning at scale due to its distributed architecture.

Distributed models and a good knowledge of the catchment studied are required to assess mitigation measures for nitrogen (N) pollution. A set of alternative scenarios (change of crop management practices and different strategies of landscape management, especially different sizes and distribution of set-aside areas) were simulated with a fully distributed model in a small agricultural catchment. The results show that current practices are close to complying with current regulations, which results in a limited effect of the implementation of best crop management practices. The location of set-aside zones is more important than their size in decreasing nitrate fluxes in stream water. The most efficient location is the lower parts of hillslopes, combining the dilution effect due to the decrease of N input per unit of land and the interception of nitrate transferred by sub-surface flows. The main process responsible for the interception effect is probably uptake by grassland and retention in soils since the denitrification load tends to decrease proportionally to N input and, for the scenarios considered, is lower in the interception scenarios than in the corresponding dilution zones.

The Western diet is characterized by high meat consumption, which negatively affects the environment and human health. Transitioning toward eating more plant-based products in Western societies has been identified as a key instrument to tackle these problems. However, one potential concern is that radically reducing meat in the current diet might lead to deficiencies in nutritional intake. In this paper, we explore a scenario in which meat consumption in Sweden is reduced by 50% and replaced by domestically grown grain legumes. We quantify and discuss the implications for nutritional intake on population level, consequences for agricultural production systems and environmental performance. The reduction in meat consumption is assumed to come primarily from a decrease in imported meat. We use data representing current Swedish conditions including the Swedish dietary survey, the Swedish food composition database, Statistics Sweden and existing life cycle assessments for different food items. At population level, average daily intake of energy and most macro- and micro-nutrients would be maintained within the Nordic Nutrition Recommendations after the proposed transition (e.g., for protein, fat, zinc, vitamin B12 and total iron). The transition would also provide a considerable increase in dietary fiber and some increase in folate intake, which are currently below the recommended levels. The transition scenario would increase total area of grain legume cultivation from 2.2% (current level) to 3.2% of Swedish arable land and is considered technically feasible. The climate impact of the average Swedish diet would be reduced by 20% and the land use requirement by 23%. There would be a net surplus of approximately 21,500 ha that could be used for bioenergy production, crop production for export, nature conservation, etc. Implementation of this scenario faces challenges, such as lack of suitable varieties for varying conditions, lack of processing facilities to supply functional legume-based ingredients to food industries and low consumer awareness about the benefits of eating grain legumes. In sum, joint efforts from multiple actors are needed to stimulate a decrease in meat consumption and to increase cultivation and use of domestically grown grain legumes.

This paper seeks to establish good practice in setting inputs for operational risk models for banks, insurers and other financial service firms. It reviews Basel, Solvency II and other regulatory requirements as well as publicly available literature on operational risk modelling. It recommends a combination of historic loss data and scenario analysis for modelling of individual risks, setting out issues with these data, and outlining good practice for loss data collection and scenario analysis. It recommends the use of expert judgement for setting correlations, and addresses information requirements for risk mitigation allowances and capital allocation, before briefly covering Bayesian network methods for modelling operational risks.

The U.S. export share in the world peanut market has decreased due to heavy competition. In this paper, the Latin American peanut industry is modeled using seemingly unrelated regression (SUR). Based on these estimations, a scenario analysis was conducted. The results show that the Latin American demand is not affected dramatically by either domestic or world price shocks. The effects of price changes on net trade are noticeable. However, the world price does not significantly affect the Latin American peanut supply. The results imply that Latin American peanut farmers are more sensitive to changes in domestic prices than world price changes.

Changes in landscape composition and structure may impact the conservation and management of protected areas. Species that depend on specific habitats are at risk of extinction when these habitats are degraded or lost. Designing robust methods to evaluate landscape composition will assist decision- and policy-making in emerging landscapes. This paper describes a rapid assessment methodology aimed at evaluating land-cover quality for birds, plants, butterflies and bees around seven UK Natura 2000 sites. An expert panel assigned quality values to standard Coordination of Information on the Environment (CORINE) land-cover classes for each taxonomic group. Quality was assessed based on historical (1950, 1990), current (2000) and future (2030) land-cover data, the last projected using three alternative scenarios: a growth-applied strategy (GRAS), a business-as-might-be-usual (BAMBU) scenario, and sustainable European development goal (SEDG) scenario. A quantitative quality index weighted the area of each land-cover parcel with a taxa-specific quality measure. Land parcels with high quality for all taxonomic groups were evaluated for temporal changes in area, size and adjacency. For all sites and taxonomic groups, the rate of deterioration of land-cover quality was greater between 1950 and 1990 than current rates or as modelled using the alternative future scenarios (2000–2030). Model predictions indicated land-cover quality stabilized over time under the GRAS scenario, and was close to stable for the BAMBU scenario. The SEDG scenario suggested an ongoing loss of quality, though this was lower than the historical rate of c. 1% loss per decade. None of the future scenarios showed accelerated fragmentation, but rather increases in the area, adjacency and diversity of high quality land parcels in the landscape.

This paper overviews a practical approach to the assessment of operational risk in life insurance companies. It considers how actuaries, working in conjunction with risk management professionals and senior management, can develop a framework to assess the capital requirements relating to operational risk, taking into account the capital requirements of other risks and their interaction.

This paper recognises that we do not live in an ideal world, and that a lot of the data which one might want for operational risk assessment are not, and in some cases never will be, available. Consequently, the approach outlined in this paper takes into account the fact that management and assessment of operational risk is at an early stage of development in the life industry. In addition, it outlines some of the areas where development is necessary or desirable in the coming years.

There is a section on the operational risks against which it is appropriate to hold capital. As this is a new area for insurance companies, and given the governance requirements for Individual Capital Assessments, it is important to explain the results effectively to senior management. Therefore, a brief review of techniques for reporting the results of the assessment is provided.

The paper concludes with some thoughts on how operational risk management can be embedded more in the business, and then considers what future work will help develop the framework. To echo the thoughts of the authors of the general insurance paper on this topic (Tripp et al., 2004), we hope that the paper will sow seeds for the development of best practice in dealing with operational risk, and will raise the awareness and increase the interest of actuaries in this emerging topic.

This paper represents the views of the individuals in the working party, and not necessarily the views of their employers or the Actuarial Profession.

The paper overviews the application of existing actuarial techniques to operational risk. It considers how, working in conjunction with other experts, actuaries can develop a new framework to monitor/review, establish context, identify, understand and decide what to do in terms of the management and mitigation of operational risk. It suggests categorisations of risk to help analyses and proposes how new risk indicators may be needed, in conjunction with more normal quantification approaches.

Using a case study, it explores the application of stress and scenario testing, statistical curve fitting (including the application of extreme value theory), causal (Bayesian) modelling and the extension of dynamic financial analysis to include operational risk. It suggests there is no one correct approach and that the choice of parameters and modelling assumptions is critical. It lists a number of other techniques for future consideration.

There is a section about how ‘soft issues’ including dominance risk, the impact of belief systems and culture, the focus of performance management systems and the psychology of organisations affect operational risk. An approach to rating the people aspects of risk in parallel with quantification may help give a better overall assessment of risk and improve the understanding for capital implications.

The paper concludes with a brief review of implications for reporting and considers what future work will help develop the actuarial contribution. It is hoped the paper will sow seeds for the development of best practice in dealing with operational risk and increase the interest of actuaries in this emerging new topic.

Identification of latent or unarticulated customer and other stakeholder needs has been a significant barrier to improving the efficiency and effectiveness of the front-end phase of new product development processes. In-depth determination of stakeholder needs entails analysis of their intentions; the overall aim of the work reported in this article is to establish a framework of intentional analysis, and its associated methods and techniques for improving traceability of design practice during the early phases of the design process. The specific aim of this article is to present a conceptual framework for design rationale systems. The framework built upon the cross-fertilization of approaches and methods drawn from systems engineering and philosophy, focussing on the notions of antecedence and consequence. It was developed in the course of tackling design problems originating in industrial contexts. The methods developed were thus evaluated, updated, and refined in real applications. Two application cases are described that have been drawn from the aerospace and power sectors, respectively. The applications showed that the framework's central antecedent/consequent scheme provides a cell from which to develop either a history of actual successive changes, or a tree of alternative possible projected designs.

Objectives: In the next decades, the number of stroke patients is expected to increase. Furthermore, organizational changes, such as stroke services, are expected to be implemented on a large scale. The purpose of this study is to estimate the future healthcare costs by taking into account the expected increase of stroke patients and a nationwide implementation of stroke services.

Methods: By means of a dynamic multistate life table, the total number of stroke patients can be projected. The model calculates the annual number of patients by age and gender. The total healthcare costs are calculated by multiplying the average healthcare costs specified by age, gender, and healthcare sector with the total number of stroke patients specified by age and gender.

Results: In the year 2000, the healthcare costs for stroke amounted to €1.62 billion. This amount is approximately 4.4 percent of the total national healthcare budget. Projections of the total costs of stroke based on current practice result in an increase of 28 percent (€2.08 billion) in the year 2020. A nationwide implementation of stroke services in 2020 would result in a substantial reduction of the costs of stroke (€1.81 billion: 13 percent cost reduction) compared with the regular care scenario.

Conclusions: A nationwide implementation of stroke services is a strong policy tool for cost containment of health care in an aging population like that in the Netherlands. Policy makers should optimize the organization of stroke care.