Estimating Recreation Demand Using the Properties of the Implied Consumer Surplus

Consumer surplus estimates are random variables. While they are generally recognized as stochastic, little attention was given to their properties prior to Bockstael and Strand's (1987) evaluation of conventional practices for using recreation demand models in benefit measurement. Their paper, as well as all the research it stimulated, adopted a similar strategy, namely to judge the methods for estimating demand or random utility models based on the properties of their respective consumer surplus estimates.' This paper proposes a different strategy-to define estimators based on the properties of their implied consumer surplus estimates. This type of argument is not new and usually is associated with the rationale offered for Bayesian estimators.2 However, the motivation for the estimator proposed here can be based on minimizing the mean squared error of the consumer surplus estimates. Moreover, it can be constructed from the statistics usually reported with ordinary least squares (OLS) estimates.