Information Aggregation in Decentralized Markets

去中心化市场的信息聚合

• 批准号: 1061831
• 负责人: Stephan Lauermann
• 金额: $ 26.71万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1061831&HistoricalAwards=false
• 关键词: Information; Aggregation; Decentralized; Markets

Economists have long argued that markets play a key role in aggregating information; what individuals know affects the prices they will pay and charge. How this process works varies from market to market. For example, by analyzing auction markets economists have been able to develop a strategic foundation for information aggregation. In many markets, however, trading is not conducted through centralized auctions. Instead, prices are often determined through local interactions between a small number of agents, for example, in decentralized markets such as those for labor and over-the-counter securities. This award funds research in economic theory with a goal of understanding how decentralized markets aggregate information that is dispersed among market participants. Decentralized markets are modeled with a search framework. Pairs of traders bargain over prices and search for other traders if they do not reach an agreement. The analysis shows that information aggregation in decentralized markets differs fundamentally from information aggregation in auctions. The PI is building and analyzing two different models of this process.In the first, there is a decentralized setting with a single buyer. The buyer seeks to procure a service, repair or cure, and contacts sellers for price offers. The cost of the service depends on private characteristics of the buyer, such as the complexity of the repair or the health status. The number of sellers contacted is endogenous and depends on the private information of the buyer. Moreover, being contacted reveals information to the seller. Sellers also receive noisy information about the buyer's characteristics through inspection or diagnosis. While each individual seller's information is imperfect, all sellers jointly posses sufficient information to determine the buyer's characteristics. Whether and how this dispersed information is aggregated is the question examined. Preliminary results show that information aggregation in the decentralized market is much harder (in a sense made precise later) than in standard auctions. This continues to be true even when the standard auction setting is extended to permit the buyer to solicit bidders.The second model analyzes the flow of information in decentralized settings with many buyers and sellers who trade a single type of good. Aggregate demand for the good (scarcity) is unknown. Buyers and sellers learn individually about the true market condition by interacting with other traders. As in the first sub-project, the focus of the analysis is on the transmission and aggregation of dispersed information. If information is aggregated, the price reflects the true scarcity of the good, that is, the price reflects the good's true economic value.The broader impacts include graduate student training and a better understanding of key features of important markets like the job market.

经济学家长期以来一直认为，市场在汇总信息方面发挥着关键作用；个人所知道的会影响他们支付和收费的价格。这个过程的运作方式因市场而异。例如，通过分析拍卖市场，经济学家已经能够开发出信息聚合的战略基础。然而，在许多市场中，交易不是通过集中拍卖进行的。相反，价格通常是通过少数代理人之间的本地互动决定的，例如，在劳动力和场外证券等分散市场中。该奖项为经济理论研究提供资金，目的是了解分散的市场如何聚集分散在市场参与者之间的信息。去中心化市场是用搜索框架建模的。一对对交易者在价格上讨价还价，如果他们不能达成协议，就寻找其他交易者。分析表明，分散市场中的信息聚合与拍卖中的信息聚合有着根本的区别。PI正在构建和分析该过程的两个不同模型。在第一种情况下，有一个分散的环境，只有一个买家。买方寻求获得服务、修理或治疗，并与卖方联系以获得价格报价。服务的费用取决于买方的私人特征，例如修理的复杂程度或健康状况。联系的卖家数量是内生的，取决于买家的私人信息。此外，被联系也向卖方透露了信息。通过检查或诊断，卖方还会收到有关买方特征的嘈杂信息。虽然每个单独的卖方的信息是不完善的，但所有卖方共同拥有足够的信息来确定买方的特征。是否以及如何将这些分散的信息聚合是研究的问题。初步结果表明，在去中心化市场中，信息聚合比在标准拍卖中要困难得多（在某种意义上，稍后才会变得精确）。即使标准的拍卖设置被扩展到允许买家征求竞标者，这仍然是正确的。第二个模型分析了分散环境下的信息流，许多买卖双方交易一种商品。商品的总需求（稀缺性）是未知的。买家和卖家通过与其他交易者的互动，各自了解真实的市场状况。和第一个子项目一样，分析的重点是分散信息的传递和聚合。如果信息是聚合的，价格反映了商品的真正稀缺性，也就是说，价格反映了商品的真正经济价值。更广泛的影响包括研究生培训和对重要市场（如就业市场）关键特征的更好理解。