A missing error term in benefit-cost analysis

Benefit-cost models are frequently used to inform environmental policy and management decisions. However, they typically omit a random or pure error which biases downward any estimated forecast variance. Ex-ante benefit-cost analyses create a particular problem because there are no historically observed values of the dependent variable, such as net present social value, on which to construct a historically based variance as is the usual statistical approach. To correct this omission, an estimator for the random error variance in this situation is developed based on analysis of variance measures and the coefficient of determination, R(2). A larger variance may affect decision-maker's choices if they are risk averse, consider confidence intervals, exceedance probabilities, or other measures related to the variance. When applied to a model of the net benefits of the Clean Air Act, although the probability of large net benefits increases, the probability that the net present value is negative also increases from 0.2 to 4.5%. A framework is also provided to assist in determining when a variance estimate would be better, in a utility sense, than using the current default of a zero error variance.