Does Uncertainty Matter? A Stochastic Dynamic Analysis of Bankable Emission Permit Trading for Global Climate Change Policy

Abstract

Emission permit trading is a centerpiece of the Kyoto Protocol which allows participating nations to trade and bank greenhouse gas permits under the Framework Convention on Climate Change. When market conditions evolve stochastically, emission trading produces a dynamic problem, in which anticipation about the future economic environment affects current banking decisions. In this paper, the author explores the effect of increased uncertainty over future output prices and input costs on the temporal distribution of emissions. In a dynamic programming setting, a permit price is a convex function of stochastic prices of electricity and fuel. Increased uncertainty about future market conditions increases the expected permit price and causes a risk-neutral firm to reduce ex ante emissions so as to smooth out marginal abatement costs over time. The convexity results from the asymmetric impact of changes in counterfactual emissions on the change of marginal abatement costs. Empirical analysis corroborates the theoretical prediction. The author finds that a 1 percent increase in electricity price volatility measured by the annualized standard deviation of percentage price change is associated with an average decrease in the annual emission rate by 0.88 percent. Numerical simulation suggests that high uncertainty could induce substantially early abatements, as well as large compliance costs, therefore imposing a tradeoff between environmental benefits and economic efficiency. The author discusses policy implications for designing an effective and efficient global carbon market.