MODELING INVESTMENT UNCERTAINTY IN THE COSTS OF GLOBAL CO2 EMISSION POLICY

This paper investigates the effect that explicit modeling of stochastic returns to investment has on the CO2 abatement policy returned by a large scale macroeconomic model of the United States economy. We find that a policy derived from the mean value deterministic model in which the random variables of the stochastic model have been replaced by their expected value poorly approximates the optimal policy returned by solving the stochastic programming model. We measure this nonoptimality by determining the value of the stochastic solution and investigating the different evolutionary paths that various macroeconomic variables follow. Macroeconomic variables which stray far from their optimal paths when derived under the assumption of a certain mean valued future are as follows: the level of carbon taxation, investment in new energy production technologies, exploration for nonrenewable resources and investment in improved macroeconomic efficiency.