Valuation on the Frontier: Calibrating Actual and Hypothetical Statements of Value

The lack of robust evidence showing that hypothetical behavior directly maps into real actions remains a major concern for proponents of stated preference nonmarket valuation techniques. This article explores a new statistical approach to link actual and hypothetical statements. Using willingness-to-pay field data on individual bids from sealed-bid auctions for a $350 baseball card, our results are quite promising. Estimating a stochastic frontier regression model that makes use of data that any contingent valuation survey would obtain, we derive a bid function that is not statistically different from the bid function obtained from subjects in an actual auction. If other data can be calibrated similarly, this method holds significant promise since an appropriate calibration scheme, ex ante or ex post, can be invaluable to the policy maker that desires more accurate estimates of use and nonuse values for nonmarket goods and services.