Using Random nth Price Auctions to Value Non-market Goods and Services
Public policy decision making often requires balancing the benefits of a policy with the costs. While regulators in the United States and abroad rely heavily on benefit-cost analysis, critics contend that hypothetical bias precludes one of the most popular benefit estimation techniques--contingent surveys--from providing reliable economic values for nonmarket goods and services. This paper explores a new methodology to obtain the total value of nonmarket goods and services--random nth price auctions. The empirical work revolves around examining behavior of 360 participants in a competitive marketplace, where subjects naturally buy, sell, and trade commodities. The field experiment provides some preliminary evidence that hypothetical random nth price auctions can, in certain situations, reveal demand truthfully. Copyright 2003 by Kluwer Academic Publishers
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