The complexity of integrated assessment models (IAMs) prevents the direct appreciation of the impact of uncertainty on the model predictions. However, for a full understanding and corroboration of model results, analysts might be willing, and ought to identify the model inputs that influence the...

The paper derives the optimal carbon tax in closed-form from an integrated assessment of climate change. The formula shows how carbon, temperature, and economic dynamics quantify the optimal mitigation effort. The model's descriptive power is comparable to numeric models used in policy advising....

This paper contributes to the normative literature on mitigation and adaptation by framing the question of their optimal policy balance in the context of catastrophic climate risk. The analysis uses the WITCH integrated assessment model with a module that models the endogenous risk of...

The stylized model presented in this paper extends the approach developed by Fischer and Newell (2008) by analysing the optimal policy design in a context with more than one externality while taking explicitly into account uncertainty surrounding future emission damage costs. In the presence of...

We present a modification of the most commonly used integrated assessment model (IAM) of climate change (DICE-2016), AD-DICE2016, which is designed to address three key aspects of climateeconomy models: treatment of uncertainty, the use of more appropriate utility functions, and including...

We propose a novel framework for the economic assessment of climate-change policy. Our main point of departure from existing work is the adoption of a "satisficing", as opposed to optimizing, modeling approach. Along these lines, we place primary emphasis on the extent to which different...

Anthropogenic greenhouse gas emissions are changing the energy balance of our planet. Various climatic feedbacks make the resulting warming over the next decades and centuries highly uncertain. We quantify how this uncertainty changes the optimal carbon tax in a stochastic dynamic programming...