We consider the case of a non-infinitely-altruistic social planner who does not know the true climate and economic parameters of the DICE model and who, because of political or social constraints, cannot act optimally. We find that the impact of parameter uncertainty on economic outcomes is much more pronounced away from optimality than along an optimal path. We also find that for this non-omniscient and politically constrained social planner the most desirable of the ‘feasible’ courses of actions depends strongly on which quantity is known with uncertainty. A gradual ramp-up is preferred to a steep (‘Stern-like') abatement schedule when we consider (symmetric) uncertainty in the growth rate of the economy, or in the cost of abatement. This result is extremely robust to the choice of a number of non-expected-utility-maximization decisional criteria that do not make use of probabilities: minimax, maximax and maximin all give the same recommendation. Ambiguity aversion does not change these results. However, when uncertainty in the damage function is considered, a steeper abatement schedule becomes a strong contender, and is preferred by some decisional criteria. This suggests that researching this aspect of climate modelling would have the greatest policy relevance. Finally, we note that a gradual (‘Nordhaus-like') ramp-up of the abatement efforts abatement schedule is always preferred to a slower (‘business-as-usual') schedule of abatement even in the case of much stronger future economic growth or much milder climate damage than the central estimates of the DICE model.
JEL Codes: D58, D81, Q28, Q54, Q58