The effect of uncertainty on decision making about climate change mitigation: a numerical approach of stochastic control

We apply standardized numerical techniques of stochastic optimization (Judd [1998]) to the climate change issue. The model captures the feature that the effects of uncertainty are different with different levels of agent's risk aversion. A major finding is that the effects of stochasticity differ even in sign as to emission control with varying parameters: introduction of stochasticity may increase or decrease emission control depending on parameter settings, in other words, uncertainties of climatic trends may induce people's precautionary emission reduction but also may drive away money from abatement.