Nonparametric Identification, Estimation, and Testing of Auction Models

[409569] Vuong拍卖是现实世界市场中许多价格形成的机制。进一步了解拍卖有助于设计更有效的定价机制，从而改善社会的资源配置。在今天的公共政策领域，拍卖设计问题在金融证券市场（美国国库券的拍卖）、环境（排放配额的拍卖）和电信（无线电/个人通信频谱的拍卖）中具有真正的重要性。尽管拍卖的重要性和对拍卖的大量理论研究，但由于拍卖模型的结构估计存在严重的计算困难，对拍卖经济学的严格实证研究很少。该项目建立在研究者最近取得的突破性进展的基础上，在结构方法中获得了可计算的识别、估计和测试理论拍卖模型的方法。更具体地说，本项目的目标是解决拍卖模型在真实数据上的结构估计面临的以下挑战：(1)以前的结构分析完全依赖于理论拍卖模型的结构元素的一些参数规范。该项目开发了不需要此类参数信息的结构方法；(2)众所周知，基于参数分析的经济政策结论可能对结构要素的错误说明不具有鲁棒性。该项目开发了一种两步非参数程序，该程序不受此问题的影响，计算非常简单，并且对于拍卖数据集中典型的样本量表现令人满意。

9409569 Vuong Auctions are the mechanisms by which many prices in real world markets are formed. Further understanding of auctions can help design more efficient pricing mechanisms and thereby improve society's allocation of resources. In the public policy arena today, auction design questions are of real importance in financial securities markets (auctions of U.S. Treasury bills), the environment (auctions of emission's allowances), and telecommunications (auctions for radio/personal communications spectrum). Despite the importance of auctions and the huge body of theoretical research on auctions, there has been little rigorous empirical research on the economics of auctions because of severe computational difficulties with the structural estimation of auction models. This project builds on recent breakthroughs by the investigator in obtaining computationally tractable methods of identifying, estimating, and testing theoretical auction models within a structural approach. More specifically, the objective of this project is to address the following challenges to structural estimation of auction models on real data: (1) Previous structural analyses have exclusively relied upon some parametric specification of the structural elements of the theoretical auction model. This project develops structural methods that do not require such parametric information; and (2) It is known that economic policy conclusions based on parametric analyses may not be robust to misspecification of the structural elements. The project develops a two-step nonparametric procedure that is not subject to this problem, is quite simple computationally and behaves satisfactorily for sample sizes typically found in auction data sets.