A Point Decision for Partially Identified Auction Models
提出一种决策理论方法，利用英语拍卖的交易价格数据，为部分识别拍卖模型（如Haile和Tamer模型）选择一个单一保留价，并通过蒙特卡洛研究显示相比随机点和区间中点能显著提高卖方收益。
This article proposes a decision-theoretic method to choose a single reserve price for partially identified auction models, such as Haile and Tamer (2003), using data on transaction prices from English auctions. The article employs Gilboa and Schmeidler (1989) for inference that is robust with respect to the prior over unidentified parameters. It is optimal to interpret the transaction price as the highest value, and maximize the posterior mean of the seller’s revenue. The Monte Carlo study shows substantial gains relative to the revenues corresponding to a random point and the midpoint in the Haile and Tamer interval.