Necessities and problems of coupling climate and socioeconomic models for integrated assessments studies from an economist's point of view

This presentation has two parts. The first part is more theoretical. We will examine the definition of Integrated Assessment Models of Climate Change and identify their main aims. We will also have look at the differences between climate and socioeconomic models. The second part will be applied. We present the Dynamics of Inertia and Adaptability Model (DIAM). That model will be used to study some of the fundamentals economic parameters of IAMs: the discount rate, the technical progress rate, the flexibility of energy systems, uncertainty and the final concentration target. We won\'t try to be exhaustive, see Weyant1 leading author of the corresponding IPCC chapter for that. Our goal is simply to convince the reader that these non realistic models can profitably be used to analyse real issues.climate change, integrated assessment

Transparency and control in engineering integrated assessment models.

Better software engineering such as archiving releases with version control, writing portable code, publishing documentation and results closely tied to the code improves integrated assessment models' transparency and control. A case study of four climate change policy analysis models found that source code and data was generally available, but for largermodels licenses were more restrictive with respect to modification and redistribution. It is suggested that Free software licenses such as the GNU GPL would improve transparency and control. Moreover, opening the source allows opening the development process, a potentially important tool to improve collaboration, data sharing and models integration.

Scenarios, probability and possible futures

This paper provides an introduction to the mathematical theory of possibility, and examines how this tool can contribute to the analysis of far distant futures. The degree of mathematical possibility of a future is a number between O and 1. It quantifies the extend to which a future event is implausible or surprising, without implying that it has to happen somehow. Intuitively, a degree of possibility can be seen as the upper bound of a range of admissible probability levels which goes all the way down to zero. Thus, the proposition `The possibility of X is Pi(X) can be read as `The probability of X is not greater than Pi(X).Possibility levels offers a measure to quantify the degree of unlikelihood of far distant futures. It offers an alternative between forecasts and scenarios, which are both problematic. Long range planning using forecasts with precise probabilities is problematic because it tends to suggests a false degree of precision. Using scenarios without any quantified uncertainty levels is problematic because it may lead to unjustified attention to the extreme scenarios.This paper further deals with the question of extreme cases. It examines how experts should build a set of two to four well contrasted and precisely described futures that summarizes in a simple way their knowledge. Like scenario makers, these experts face multiple objectives: they have to anchor their analysis in credible expertise; depict though-provoking possible futures; but not so provocative as to be dismissed out-of-hand. The first objective can be achieved by describing a future of possibility level 1. The second and third objective, however, balance each other. We find that a satisfying balance can be achieved by selecting extreme cases that do not rule out equiprobability. For example, if there are three cases, the possibility level of extremes should be about 1/3.Futures, futurible, scenarios, possibility, imprecise probabilities, uncertainty, fuzzy logic

Quasi-option value and climate policy choices

In the climate change issue, the environmental irreversibility (risk of an acceleration of mitigation policies if the worse happen) has to be balanced with the investment irreversibility (risk of over-cautious policies). To explore this balance, we define an option value for a precautionary climate policy. Using the simplest decision-making model, we expose how option value relates to the expected value of future information. Using quantitative data from an integrated as sessment model, we find that most of the times the environmental irreversibility dominates the investment irreversibility. For all cases explored here, the order of magnitude of the option value was significant, about 50% of the opportunity cost.Option value, Climate change, Irreversibility

The real option with an absorbing barrier.

Ce papier analyse l'option réelle avec barrière inférieure. C'est le modèle d'un investissement irréversible soumis au risque de perdre l'option d'investir si on attend trop. La valeur critique pour investir décroit lorsque la barrière se rapproche, ou lorsque la volatilité augmente. L'incertitude a un effet ambigu sur le temps espéré de décision et sur la probabilité de résolution après N années. Les résultats numériques et analytiques s'appliquent aussi à une option financière aéricaine avec une "down-and-out barrier" sur un support payant des dividendes.option réelle, incertitude, irréversibilité

A hierarchical fusion of expert opinion in the TBM

This is an abridged version of http://halshs.archives-ouvertes.fr/halshs-00112129/fr/We define a hierarchical method for expert opinion aggregation that combines consonant beliefs in the Transferable Belief Model. Experts are grouped into schools of thought, then opinions are aggregated using the cautious conjunction operator within groups and the non-interactive disjunction across. This method is illustrated with a real-world dataset including 16 experts

Introduction aux approches économiques de l'incertitude

This paper introduces a few words used by economists studying uncertainty, climate policy and integrated assessment models. Section one uses two pedagogical examples to define risk, uncertainty, surprise and contingent strategy. Regarding uncertainty that is not risk, subjective probabilities with safety-first criteria and value at risk; Shackle-Zadeh possibilities; Dempster-Shafer evidence theory as well as imprecise probabilities are discussed. Section two exposes how uncertainty is treated in integated assessment models applied to climate policy analysis. It deals first with risk analysis, exposing sensitivity analysis, Monte Carlo methods and scenario building. Then the principles of bounding analysis are developped with viability theory. Finaly, the stochastic dynamic optimisation approach is illustrated.Cette communication définit quelques mots au sens où les entendent les économistes étudiant l'incertitude, les politiques climatiques et la modélisation intégrée. La première partie expose deux exemples pédagogiques définissant d'abord risque, incertitude, surprise, stratégie contingente. Pour l'incertitude qui n'est pas du risque, les probabilités subjectives et les critères safety first avec la valeur exposée au risque, les possibilités à la Shackle-Zadeh, le modèle de Dempster-Shafer ainsi que les probabilités imprécises dites aussi non-additives sont discutés. La seconde partie expose l'approche de l'incertitude dans les modèles: analyse de risque, sensitivité, Monte-Carlo et scénarios, puis analyse des bornes et viabilité et enfin l'optimisation dynamique stochastique

Risk aversion, intergenerational equity and climate change.

The paper investigates a climate-economy model with an iso-elastic welfare function in which one parameter gamma measures relative risk-aversion and a distinct parameter rho measures resistance to intertemporal substitution. We show both theoretically and numerically that climate policy responds differently to variations in the two parameters. In particular, we show that higher gamma but lower rho leads to increase emissions control. We also argue that climate-economy models based on intertemporal expected utility maximization, i.e. models where gamma = rho, may misinterpret the sensitivity of the climate policy to risk-aversion.risk aversion; equity; discounting; climate change

Recursive Intergenerational Utility in Global Climate Risk Modeling

This paper distinguishes relative risk aversion and resistance to intertemporal substitution in climate risk modeling. Stochastic recursive preferences are introduced in a stylized numeric climate-economy model using preliminary IPCC 1998 scenarios. It shows that higher risk aversion increases the optimal carbon tax. Higher resistance to intertemporal substitution alone has the same effect as increasing the discount rate, provided that the risk is not too large. We discuss implications of these findings for the debate upon discounting and sustainability under uncertainty. Ce texte étudie la différence entre l'aversion relative au risque et la résistance à la substitution intertemporelle dans la modélisation du risque climatique. Les préférences récursives stochastiques sont utilisées dans un modèle numérique stylisé utilisant les scénarios préliminaires GIEC 1998 sur l'économie et le climat. On montre qu'une aversion au risque plus forte conduit à augmenter le niveau optimal de taxation de l'énergie. Augmenter la résistance à la substitution intertemporelle a le même effet qu'augmenter le taux d'actualisation, tant que le risque n'est pas trop grand. Nous discutons les implications de ces résultats pour le débat sur l'actualisation et la durabilité sous incertitude.Recursive utility, risk, discounting, sustainability, climate, Utilité récursive, risque, actualisation, durabilité, climat

Hierarchical fusion of expert opinion in the Transferable Belief Model, application on climate sensitivity

International audienceThis paper examines the fusion of conflicting and not independent expert opinion in the Transferable Belief Model. Regarding procedures that combine opinions symmetrically, when beliefs are bayesian the non-interactive disjunction works better than the non-interactive conjunction, cautious conjunction or Dempster's combination rule.Then a hierarchical fusion procedure based on the partition of experts into schools of thought is introduced, justified by the sociology of science concepts of epistemic communities and competing theories. Within groups, consonant beliefs are aggregated using the cautious conjunction operator, to pool together distinct streams of evidence without assuming that experts are independent. Across groups, the non-interactive disjunction is used, assuming that when several scientific theories compete, they can not be all true at the same time, but at least one will remain. This procedure balances points of view better than averaging: the number of experts holding a view is not essential.This is illustrated with a 16 experts real-world dataset on climate sensitivity from 1995. Climate sensitivity is a key parameter to assess the severity of the global warming issue. Comparing our findings with recent results suggests that, unfortunately, the plausibility that sensitivity is small (below 1.5C) has decreased since 1995, while the plausibility that it is above 4.5C remains high.Ce texte examine la fusion des opinions d'experts en situation de controverse scientifique, à l'aide du Modèle des Croyances Transférables.Parmi les procédures qui combinent les experts symétriquement, nous constatons que lorsque les croyances sont bayésiennes (une modélisation classique s'appuyant sur les probabilités), l'opérateur de disjonction non-interactif donne de meilleurs résultats que les autres (conjonction prudente, la conjonction non-interactive, règle de Dempster).Puis nous proposons une procédure de fusion hiérarchique. En premier lieu, une partition des experts en écoles de pensée est réalisée à l'aide des méthodes de sociologie des sciences. Puis les croyances sont agrégées à l'intérieur des groupes avec l'opérateur de conjonction prudente: on suppose que tous les experts sont fiables, mais pas qu'ils constituent des sources d'information indépendantes entre elles. Enfin les groupes sont combinés entre eux par l'opérateur de disjonction non-interactive: on suppose qu'au moins l'une des écoles de pensée s'imposera, sans dire laquelle. Cette procédure offre un meilleur équilibre des points de vue que la simple moyenne, en particulier elle ne pondère pas les opinions par le nombre d'experts qui y souscrivent.La méthode est illustrée avec un jeu de données de 1995 obtenu en interrogeant 16 experts à propos de la sensibilité climatique (le paramètre clé exprimant la gravité du problème du réchauffement global). La comparaison de nos résultats avec la littérature récente montre que, hélas, la plausibilité que ce paramètre soit relativement faible (moins que 1.5C) a diminué depuis 1995, alors que la plausibilité qu'il soit au delà de 4.5C n'a pas décru