nep-ene New Economics Papers
on Energy Economics
Issue of 2006‒12‒22
two papers chosen by
Roger Fouquet
Imperial College, UK

  1. Uncertainty In Environmental Economics By Robert S. Pindyck
  2. Unspanned Stochastic Volatility and the Pricing of Commodity Derivatives By Anders B. Trolle; Eduardo S. Schwartz

  1. By: Robert S. Pindyck
    Abstract: In a world of certainty, the design of environmental policy is relatively straightforward, and boils down to maximizing the present value of the flow of social benefits minus costs. But the real world is one of considerable uncertainty -- over the physical and ecological impact of pollution, over the economic costs and benefits of reducing it, and over the discount rates that should be used to compute present values. The implications of uncertainty are complicated by the fact that most environmental policy problems involve highly nonlinear damage functions, important irreversibilities, and long time horizons. Correctly incorporating uncertainty in policy design is therefore one of the more interesting and important research areas in environmental economics. This paper offers no easy formulas or solutions for treating uncertainty -- to my knowledge, none exist. Instead, I try to clarify the ways in which various kinds of uncertainties will affect optimal policy design, and summarize what we know and don't know about the problem.
    JEL: D81 L51 Q28
    Date: 2006–12
  2. By: Anders B. Trolle; Eduardo S. Schwartz
    Abstract: We conduct a comprehensive analysis of unspanned stochastic volatility in commodity markets in general and the crude-oil market in particular. We present model-free results that strongly suggest the presence of unspanned stochastic volatility in the crude-oil market. We then develop a tractable model for pricing commodity derivatives in the presence of unspanned stochastic volatility. The model features correlations between innovations to futures prices and volatility, quasi-analytical prices of options on futures and futures curve dynamics in terms of a low-dimensional affine state vector. The model performs well when estimated on an extensive panel data set of crude-oil futures and options.
    JEL: G13
    Date: 2006–12

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