Bounds on revenue distributions in counterfactual auctions with reserve prices
研究了在反事实保留价或拍卖形式下，如何在不依赖参数假设的情况下界定收入分布边界，并利用美国市政债券拍卖数据发现最优保留价下的第一价格和第二价格拍卖对收入提升有限，而竞标者数量影响更大。
Measuring auction revenues under counterfactual reserve prices or formats requires knowledge of distributions of bidders' values and private signals. This poses a challenge when bids are observed from first‐price, common‐value auctions. I bound counterfactual revenue distributions without imposing parametric restrictions on the model structure. Using data from U.S. municipal bond auctions, I find first‐price and second‐price auctions under optimal reserve prices lead to little improvement in revenues over existing first‐price formats. The number of bidders has a more significant impact on revenues in optimal auctions. I also find invoking an incorrect assumption of private values in counterfactual analyses results in small errors in predicting revenues from optimal second‐price auctions.