Optimal Scheduling of Greenhouse Gas Emissions under Carbon Budgeting and Policy Design

We solve a problem of optimal scheduling of GHG emissions for a climate change policy that is consistent with the COP21 targets and has to be monitored at a fixed time horizon. Our model is dynamic and stochastic where production, and therefore well-being, increase in carbon emissions, but, at the same time, anthropogenic cumulative emissions determine a super-linear impact on the observed stochastic damage. We compare the optimal unconstrained path of emissions and the constrained path of emissions and evaluate when the carbon budget is exhausted. A sensitivity analysis is also developed to examine the effects of resilience, impact of emissions on damage and uncertainty. Our results have direct implications in terms of policy and show that uncertainty and the way we introduce it in the model are likely to influence the efficacy of the climate change policies for the foreseeable future