Valuation on the Frontier: Calibrating Actual and Hypothetical Statements of Value
提出一种统计方法，利用条件价值调查数据校准假设性陈述，使其与实际拍卖中的出价函数无显著差异，为非市场商品的价值评估提供更准确的估计。
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‐topay 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.