Greenhouse gas policies confront the trade-off between the costs of reducing emissions and the benefits of avoided climate change. The risk of uncertain and potentially irreversible catastrophes is an important issue related to the latter, and one that has not yet been well incorporated into...

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 catastrophic events are characterized by "low frequency and high severity". Nevertheless, during the last decades, both the frequency and the magnitude of these events have been significantly rising worldwide. In 2021, the European Commission adopted a new Strategy on Adaptation to Climate...

In this paper stochastic dynamic programming is used to investigate habitat conservation by a multitude of landholders under uncertainty about the value of environmental services and irreversible development. We study land conversion under competition on the market for agricultural products when...

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...

Uncertainty plays a key role in the economics of climate change, and the discussions surrounding its implications for climate policy are far from settled. We give an overview of the literature on uncertainty in integrated assessment models of climate change and identify some future research...

In a continuous-time framework we study the technology and investment choice problem of a continuous co-digestion biogas plant dealing with randomly fluctuating relative convenience of input factor costs. Input factors enter into the productive process together mixed according to a given initial...

In this paper stochastic dynamic programming is used to investigate land conversion decisions taken by a multitude of landholders under uncertainty about the value of environmental services and irreversible development. We study land conversion under competition on the market for agricultural...

Optimal R&D investment is defined by deep uncertainty that can only partially be addressed through historical data. Thus, expert judgments expressed as subjective probability distributions are seen as an alternative way of assessing the potential of new technologies. In this paper we propose a...

In this paper, we use stochastic dynamic programming to model the choice of a municipality which has to design an optimal waste management program under uncertainty about the price of recyclables in the secondary market. The municipality can, by undertaking an irreversible investment, adopt a...