This paper establishes a methodology for valuing the impact of large-scale ecological changes in a market. Given the large capital stocks inherent in most ecological systems, the dynamic nature of most ecological change, and the dynamic response of markets, it is critical to build dynamic models to capture the resulting effects. This paper demonstrates how to construct such a model using the impacts of climate change on U.S. timber markets as an example. Across a wide range of scenarios and models, warming is predicted to expand timber supplies and thus benefit U.S. timber markets.

We measure the economic impact of climate on land prices. Using cross-sectional data on climate, farmland prices, and other economic and geophysical data for almost 3,000 counties in the United States, we find that higher temperatures in all seasons except autumn reduce average farm values, while more precipitation outside of autumn increases farm values. Applying the model to a global-warming scenario shows a significantly lower estimated impact of global warming on U.S. agriculture than the traditional production-function approach and, in one case, suggests that, even without CO_2 fertilization, global warming may have economic benefits for agriculture.

Decision makers performing cost-benefit analysis must often deal with the problem of how to aggregate the benefits across states of nature accruing from an uncertain public investment project.' Option price and the expected value of consumer's surplus are two potential measures of these aggregate benefits.2 The expected value of surplus has been proposed because it is readily measured and because risk pooling (Paul Samuelson, William Vickrey; 1964) and risk spreading (Kenneth Arrow and Robert Lind, 1970) tend to encourage risk neutral behavior. Option price has been favored on the vague notion that people would be willing to pay something extra above expected surplus to preserve the opportunity to purchase a good (Burton Weisbrod, 1964). As Daniel Graham cogently argues in this Review (1981), however, option price is but one of an infinite number of contingent payment schemes. The literature has provided no justification for focusing upon it as an ideal measure of benefits under individual risk. Graham further argues that policymakers ought to adopt the compensating contingent payment plan which maximizes expected revenue. This maximum payment plan, by definition, is never less and will often exceed any other contingent payment scheme. Consequently, Graham argues that both the expected value of surplus and option price are underestimates of the true value of project benefits. Our purpose in this comment is twofold: first, we show the role of project and nonproject insurance in a model of individual risk; and, second, we argue that option price, not the maximum payment plan, is the optimal rule when no fair insurance is available. In Section II, we show that if fair insurance is available against all risks, all contingent payment plans yield identical revenue. A similar result holds if insurance is available for nonproject risks and the effect of the project to an individual is small (the Arrow-Lind model). In Section III, we explore the case where either the project has a large uninsurable effect on the individual, or there is no insurance against even nonproject risks. We argue that the very phenomena (moral hazard, adverse selection, and complexity) that eliminate the market for private insurance also prevent the government from making otherwise desirable contingent payments. If contingent payments are too costly, the government's only remaining choice is to collect payments that are constant across states, which makes option price the relevant measure of benefits.