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The global financial crisis of 2008 has shown that the present financial system involves global systemic risks. The dimension of these risks is hard to grasp with the conceptual tools that have been developed to tackle conventional risks like fire or car accidents. While modern societies know quite well how to deal with conventional risks, we have not yet been equally successful at dealing with global systemic risks. For managing this kind of risks, one needs to understand critical features of specific global systems where many human agents interact in ever changing complex networks. Here we apply two specific dimensions of complexity theory for dealing with global systemic risk in an integrated fashion: normal accidents and extended evolution. Both of them have successfully been applied to the analysis of systemic risks. As a paradigmatic example of global systemic risks, we focus on the global financial crisis that began in 2008, and suggest that the future evolution of the financial system could either see a further increase in complexity, or a reversal to a less complex system. We explore and contrast the implications of normal accident theory and extended evolution perspectives and suggest a four‐point research strategy informed by complexity theory for better understanding global systemic risks in financial systems. [ABSTRACT FROM AUTHOR]

Like every major new technology, genetic engineering is affecting the hopes and fears of many people. The risks involved are perceived differently by different groups. One group regards genetic engineering as a simple extension of older techniques with no special risks, e.g. traditional breeding. This conservative denial of special risks is confronted with a different kind of conservatism from a group which, in the name of the preservation of nature, opposes any kind of genetic engineering. A third group, rooted in the liberal tradition, is prepared to accept the risks of genetic engineering as long as they are outweighed by prospective benefits. The liberal as well as the two conservative approaches, however, face serious difficulties in trying to develop a sound ethical argument concerning genetic engineering. In order to avoid these difficulties, an ethical approach focused on paradigmatic examples of good and evil is proposed. Such examples constitute rules of moral description, much as standards of measurement constitute rules of physical description. These rules are elaborated and interpreted in processes of social learning. In the present state of development of genetic engineering, such social learning requires appropriate institutional procedures.

Byline: Bernd Kasemir, Marjolein B.A. van Asselt, Gregor Durrenberger, Carlo C. Jaeger Integrated assessment (IA) is a maturing research approach aiming at providing decision support on complex environment-related problems. Although interdisciplinary research is a pre-condition for IA, in order to reach the goals that IA has set it is necessary to go beyond interdisciplinary research efforts alone. There are two major reasons for this: the nature of democratic decision-making, and the nature of complex issues. The views held by stakeholders and the public at large are an integral part of democratic decision-making processes. Integrated assessments, which aim to support decision-making in an appropriate and relevant way, should therefore synthesise interdisciplinary scientific insights with a wide variety of societal views. Furthermore, this paper argues that the sustainability issues with which IA is concerned are complex problems, in the sense that they cannot be fully described or solved in any unique way. One of the reasons for this is the essentially contested character of the concept 'sustainable development'. Against this background, the search for techniques of articulation and interaction of multiple perspectives is a major challenge for the IA community. Where the nature of democratic processes asks for taking into account views of a diversity of actors, the nature of the issues considered demands that multiple perspectives are included in integrated assessments. Decision support building on a single scientific description is therefore not at all sufficient for addressing complex problems in a democratic decision-making context. To this end, this paper argues that it seems promising to develop techniques that combine scientific assessment tools with public participation methods. In order to contribute to the search for such new IA techniques, this paper discusses some new avenues in IA modelling, and the application of a well-established social scientific tool, namely focus groups, in integrated assessment.

This paper discusses proposals for tabular standards in the late nineteenth and early twentieth centuries. In particular, we focus on Keynes’ proposal for an international tabular standard (ITS) as the gold standard unravelled in the 1930s. The paper explains the origins of Keynes’ ITS proposal which pegged the value of an international reserve to a broad index of primary commodities, weighted in terms of their value in world production. We argue that the ITS should be viewed as an important and enduring component of Keynes’ ideal long-run vision for anchoring the international monetary system, even post-Bretton Woods. [ABSTRACT FROM AUTHOR]

Reaching the Sustainable Development Goals requires a fundamental socio-economic transformation accompanied by substantial investment in low-carbon infrastructure. Such a sustainability transition represents a non-marginal change, driven by behavioral factors and systemic interactions. However, typical economic models used to assess a sustainability transition focus on marginal changes around a local optimum, which--by construction--lead to negative effects. Thus, these models do not allow evaluating a sustainability transition that might have substantial positive effects. This paper examines which mechanisms need to be included in a standard computable general equilibrium model to overcome these limitations and to give a more comprehensive view of the effects of climate change mitigation. Simulation results show that, given an ambitious greenhouse gas emission constraint and a price of carbon, positive economic effects are possible if (1) technical progress results (partly) endogenously from the model and (2) a policy intervention triggering an increase of investment is introduced. Additionally, if (3) the investment behavior of firms is influenced by their sales expectations, the effects are amplified. The results provide suggestions for policy-makers, because the outcome indicates that investment-oriented climate policies can lead to more desirable outcomes in economic, social and environmental terms. [ABSTRACT FROM AUTHOR]

The UN sustainable development goals contain environmental, economic, and social objectives. They may only be reached, or at least it would be easier to reach them, if instead of a trade-off between these objectives that implies a need for balancing them, there are synergies to be reaped. This paper discusses how the structures of economic models typically used in policy analysis influence whether win-win strategies for the environment and the economy can be conceptualised and analysed. With a focus on climate policy modelling, the paper points out how, by construction, commonly used model structures find mitigation costs rather than benefits. This paper describes mechanisms that, when added to these model structures, can bring win-win options into a model's solution horizon, and which provide a spectrum of alternative modelling approaches that allow for the identification of such options. [ABSTRACT FROM AUTHOR]