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.

Robert Mendelsohn of Yale School of the Environment, Department of Economics, and Yale School of Management reviews “Climate Future: Averting and Adapting to Climate Change” by Robert S. Pindyck. The Econlit abstract of this book begins: “Explores the extent and nature of the uncertainty of climate change's impact on the economy and society, promoting the argument that climate policy should focus on adaptation in preparation for the unlikelihood of sufficiently reducing greenhouse gas emissions.”

This paper demonstrates that the data from a single market with nonlinear prices are consistent with a large set of underlying structural equations. By restricting the permitted functional form of the structural equations, the nonlinearity of marginal prices can be used to identify the price and shift parameters of a single member from the set. The identification approach must be used with great caution, however, because the true shape of supply and demand functions is often unknown and so the necessary restrictions may be unjustified.

Whenever marginal prices are nonconstant, as in most hedonic and household production function markets, ordinary least squares estimates of the price elasticities of structural equations will be biased. A two-stage least squares estimation procedure is developed and applied to estimate hedonic (and potentially household production function) demand functions when price gradients are nonlinear.