Climate change and extreme events : an assessment of economic implications.

We use a general equilibrium model of the world economy, and a regional economic growth model, to assess the economic implications of vulnerability from extreme meteorological events, induced by the climate change. In particular, we first consider the impact of climate change on ENSO and NAO oceanic oscillations and, subsequently, the implied variation on regional expected damages. We found that expected damages from extreme events are increasing in the United States, Europe and Russia, and Russia, and decreasing in energy exporting countries.

AD-DICE: an implementation of adaptation in the DICE model

Integrated Assessment Models (IAMS) have helped us over the past decade to understand the interactions between the environment and the economy in the context of climate change. Although it has also long been recognized that adaptation is a powerful and necessary tool to combat the adverse effects of climate change, most IAMs have not explicitly included the option of adaptation in combating climate change. This paper adds to the IAM and climate change literature by explicitly including adaptation in an IAM, thereby making the trade-offs between adaptation and mitigation visible.

Adapting and Mitigating to Climate Change: Balancing the Choice under Uncertainty

Nowadays, as stressed by important strategic documents like for instance the 2009 EU White Paper on Adaptation or the recent 2009 “Copenhagen Accord”, it is amply recognized that both mitigation and adaptation strategies are necessary to combat climate change. This paper enriches the rapidly expanding literature trying to devise normative indications on the optimal combination of the two introducing the role of catastrophic and spatial uncertainty related to climate change damages.

Does Ambiguity Aversion Raise the Optimal Level of Effort? A Two-Period Model

The objective of this paper is to analyze the effect the uncertainty about the probabilities has in the decision making process. In particular, I give an answer to the following question: Does the ambiguous nature of an outcome lead an ambiguity averse decision maker to exert more effort than another who does not take this ambiguity into account?

Siblings, not triplets: social preferences for risk, inequality and time in discounting climate change.

Arguments about the appropriate discount rate often start by assuming a Utilitarian social welfare function with isoelastic utility, in which the consumption discount rate is a function of the (constant) elasticity of marginal utility along with the (much discussed) utility discount rate. In this model, the elasticity of marginal utility simultaneously reflects preferences for intertemporal substitution, aversion to risk, and aversion to (spatial) inequality.

Risk Aversion, time preference, and the social cost of carbon

The Stern Review reported a social cost of carbon of over $300/tC, calling for ambitious climate policy. We here conduct a systematic sensitivity analysis of this result on two crucial parameters: the rate of pure time preference, and the rate of risk aversion. We show that the social cost of carbon lies anywhere in between 0 and $120,000/tC. However, if we restrict these two parameters to match observed behavior, an expected social cost of carbon of $60/tC results. If we correct this estimate for income differences across the world, the social cost of carbon rises to over $200/tC.

Discounting for climate change

It is well-known that the discount rate is crucially important for estimating the social cost of carbon, a standard indicator for the seriousness of climate change and desirable level of climate policy. The Ramsey equation for the discount rate has three components: the pure rate of time preference, a measure of relative risk aversion, and the rate of growth of per capita consumption. Much of the attention on the appropriate discount rate for long-term environmental problems has focussed on the role played by the pure rate of time preference in this formulation.

Uncertainty characterization in risk analysis for decision-making practice

This document provides an overview of sources of uncertainty in probabilistic risk analysis. For each phase of the risk analysis process (system modeling, hazard identification, estimation of the probability and consequences of accident sequences, risk evaluation), the authors describe and classify the types of uncertainty that can arise.

Incorporating catastrophes into integrated assessment: science, impacts, and adaptation

Incorporating potential catastrophic consequences into integrated assessment models of climate change has been a top priority of policymakers and modelers alike. We review the current state of scientific understanding regarding three frequently mentioned geophysical catastrophes, with a view toward their implications for integrated assessment modeling. This review finds inadequacies in widespread model assumptions regarding the nature of catastrophes themselves and climate change impacts more generally.

On Modeling and Interpreting the Economics of Catastrophic Climate Change

With climate change as prototype example, this paper analyzes the implications of structural uncertainty for the economics of lowprobability, high-impact catastrophes. Even when updated by Bayesian learning, uncertain structural parameters induce a critical “tail fattening” of posterior-predictive distributions. Such fattened tails have strong implications for situations, like climate change, where a catastrophe is theoretically possible because prior knowledge cannot place sufficiently narrow bounds on overall damages.