Semi-Structural Modeling of Empirical Auction Models

实证拍卖模型的半结构建模

• 批准号: 0136408
• 负责人: Jean-Francois Richard
• 金额: $ 23.42万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-03-01 至 2005-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0136408&HistoricalAwards=false
• 关键词: Semi; Structural; Modeling; Empirical; Auction

Each year billions of dollars of goods and services are acquired through auctions. By analyzing data that are generated in these transactions, key insights can be obtained on critical issues such as auction design. The data also may be used to understand the competitive character of these markets and bring information to bear on possible collusive behavior and market performance as reflected in economic efficiency. "Structural" analysis of auctions traditionally is based on game theoretic models that assume perfect rationality. Yet, the findings from auction experiments are pervasive and consistent: The behavior of auction participant deviates significantly from theory prescriptions. The extent of deviation sharply contradicts the assumption of perfect rationality that is so fundamental to structural analysis. The objective of this proposal is to bridge the gap between experimental economics and empirical auction modeling. We will explicitly allow bidders to deviate from the theoretical solutions of an inherently oversimplified "benchmark" theory model. Such deviations could be non-strategic (mistakes), or they may be strategic in the sense that they reflect real-life factors that are not appropriately captured by the benchmark model. Traditional bid functions, which assign a single bid to a player's valuation, are replaced by a full probability distribution for bids, conditional on valuations.The proposal develops operational numerical procedures for the analysis of bids under this new class of "semi-structural" models and explains their statistical properties. The analytical tools developed in this framework will be applied to several real-life situations: (1) Auction data from timber sales in the Northwest Pacific will be analyzed, with a specific focus on the identification of possible collusive behavior. (2) Data related to school milk procurement in Georgia will be analyzed, where issues of market efficiency may be highlighted. (3) Internet auctions, where observed behavior sharply deviates from standard theory prescriptions, will be used to demonstrate the explanatory power of the techniques developed. These empirical studies are expected to provide critical new insights in the operations of real-life auctions and result in suggestions for corresponding adjustments in their design.

每年都有数十亿美元的商品和服务通过拍卖获得。通过分析这些交易中产生的数据，可以获得拍卖设计等关键问题的关键见解。这些数据还可以用来了解这些市场的竞争特征，并为可能的串通行为和反映在经济效率上的市场表现提供信息。传统的拍卖“结构”分析是基于假设完全理性的博弈论模型。然而，拍卖实验的结果是普遍和一致的：拍卖参与者的行为明显偏离理论处方。这种偏离的程度与对结构分析至关重要的完美理性假设严重矛盾。这一建议的目的是弥合实验经济学和经验拍卖模型之间的差距。我们将明确允许投标人偏离本质上过于简化的“基准”理论模型的理论解决方案。这种偏差可能是非战略性的（错误），也可能是战略性的，因为它们反映了基准模型没有适当捕获的现实生活因素。传统的出价函数（将单个出价分配给玩家的估值）被出价的全概率分布（以估值为条件）所取代。该建议为在这类新的“半结构”模型下分析投标制定了可操作的数值程序，并解释了它们的统计特性。在此框架中开发的分析工具将应用于几个现实情况：(1)将分析西北太平洋木材销售的拍卖数据，特别侧重于识别可能的串通行为。(2)分析格鲁吉亚学校牛奶采购相关数据，突出市场效率问题。(3)互联网拍卖，其中观察到的行为明显偏离标准理论处方，将被用来证明所开发的技术的解释力。这些实证研究有望为现实拍卖的运作提供重要的新见解，并为其设计提供相应的调整建议。