Econometrics of Asymmetric Information Models with Applications to Nonlinear Pricing, Insurance and Compensation

非对称信息模型的计量经济学及其在非线性定价、保险和赔偿中的应用

• 批准号: 1310974
• 负责人: Isabelle Perrigne
• 金额: $ 41.32万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1310974&HistoricalAwards=false
• 关键词: Econometrics; Asymmetric; Information; Models; Applications

Since the nineties, the empirical analysis of auctions has been an active research area to which the PIs contributed with the support of previous NSF grants. Auctions are mechanisms in which buyers compete given their private willingness to pay for an object. The seller's problem is to design auction rules that secure the maximum return. Auctions are asymmetric information models. The PIs propose to analyze new data modeled similarly. As in their previous work, they begin with an economic model, study thoroughly the mapping between it and the data as well as develop quantitative methods drawing from empirical processes, kernel estimation and characteristic functions.First, price discounts (nonlinear pricing) to big buyers are studied. The PIs collect new data on yellow page advertising and cellular phone services. For the latter, they consider a firm proposing two products, namely, voice and SMS. They also address the problem of testing adverse selection by deriving the model restrictions on observables. Second, the research project analyzes insurance in which insurers are heterogeneous in both risk and in attitudes toward risk. Moreover, the PIs consider a finite number of contracts. Both lead to pooling at equilibrium, which represents new challenges. They assess deviations from contract optimality and resulting losses for the insurer. Policy questions are addressed with new data on automobile insurance. Third, this project studies executive compensation and develops models incorporating moral hazard and (i) competition among firms to attract managers and (ii) heterogeneous managers in risk attitudes; utilizing data from S&P ExecuComp.This project further advances the structural analysis of asymmetric information models while addressing fundamental questions. Several new data sets on yellow page advertising, mobile phone service and automobile insurance are collected and will be available to the research community. The methods developed by the PIs will be used by empirical researchers from industrial organization but also from other fields such as health, labor and corporate finance. The results of this project will also assist public institutions in better understanding the impact of regulatory policies on the insurance industry.

自90年代以来，拍卖的实证分析一直是一个活跃的研究领域，私人投资机构在以前国家科学基金会赠款的支持下做出了贡献。拍卖是一种机制，买家在其中竞争，因为他们私人愿意为一件物品买单。卖家的问题是设计能确保最大回报的拍卖规则。拍卖是不对称的信息模型。PI建议分析以类似方式建模的新数据。与以前的工作一样，他们从一个经济模型入手，深入研究了它与数据之间的映射，并利用经验过程、核估计和特征函数发展了定量方法。首先，研究了大买家的价格折扣(非线性定价)。PI收集有关黄页广告和移动电话服务的新数据。对于后者，他们考虑一家公司提出两种产品，即语音和短信。他们还通过推导出对可观测值的模型限制来解决测试逆向选择的问题。其次，研究项目分析了保险公司在风险和对风险的态度上都是异质的保险。此外，私人投资机构考虑的合同数量有限。两者都导致了均衡的汇集，这代表着新的挑战。它们评估对合同最优的偏离以及由此给保险公司带来的损失。政策问题用有关汽车保险的新数据来解决。第三，利用S高管的数据，研究了高管薪酬问题，建立了包含道德风险和(I)公司间竞争以吸引管理者和(Ii)管理者风险态度不同的模型，并进一步推进了信息不对称模型的结构分析，同时解决了基本问题。收集了几个关于黄页广告、移动电话服务和汽车保险的新数据集，并将向研究界提供。PIs开发的方法将被来自产业组织的实证研究人员使用，但也将来自其他领域，如卫生、劳工和公司金融。该项目的成果还将有助于公共机构更好地了解监管政策对保险业的影响。