An Experimental Investigation of the Seller Incentives in the EPAs Emission Trading Auction.
通过实验模拟美国环保局排放交易拍卖的逆向版本，发现买方出价高于估值、拍卖结果无效率，且买方数量增加会推高报价；面对人类对手时竞争比风险中性预测更激烈，但面对电脑对手时无显著差异。
The Clean Air Act requires the EPA to conduct annual auctions of emission allowances. Under the discriminative auction rules, sellers with the lowest asking prices receive the highest bids. This paper studies an inverted version of this auction in which buyers face the same incentives as sellers in the EPA auction. Consistent with theoretical predictions, buyers bid above their valuation, auction outcomes are inefficient, and increasing the number of buyers increases bids. Buyers facing human opponents compete more aggressively than the risk-neutral prediction but bids do not differ systematically from this prediction when buyers face computerized Nash 'robots.' Copyright 1995 by American Economic Association.