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: 1148149
• 负责人: Isabelle Perrigne
• 金额: $ 41.32万
• 依托单位: Pennsylvania State Univ University Park
• 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: 2012-06-01 至 2013-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1148149&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.

自九十年代以来，拍卖的实证分析一直是一个活跃的研究领域，PI 在之前的 NSF 资助的支持下做出了贡献。拍卖是买家根据个人购买物品的意愿进行竞争的机制。卖方的问题是设计保证最大回报的拍卖规则。拍卖是不对称信息模型。 PI 建议分析类似建模的新数据。与之前的工作一样，他们从经济模型开始，深入研究经济模型与数据之间的映射，并根据经验过程、核估计和特征函数开发定量方法。首先，研究对大买家的价格折扣（非线性定价）。 PI 收集有关黄页广告和手机服务的新数据。对于后者，他们考虑一家公司提出两种产品，即语音和短信。他们还通过推导可观察量的模型限制来解决测试逆向选择的问题。其次，该研究项目分析了保险公司在风险和风险态度方面存在异质性的保险。此外，PI 考虑的合同数量有限。两者都会导致均衡汇集，这代表着新的挑战。他们评估合同最优性的偏差以及由此给保险公司带来的损失。汽车保险的新数据解决了政策问题。第三，该项目研究了高管薪酬并开发了包含道德风险和（i）公司之间吸引管理者的竞争和（ii）风险态度上的异质管理者的模型；利用 S&P ExecuComp 的数据。该项目在解决基本问题的同时进一步推进了不对称信息模型的结构分析。收集了有关黄页广告、移动电话服务和汽车保险的几个新数据集，并将提供给研究界。 PI 开发的方法将被工业组织以及卫生、劳工和公司财务等其他领域的实证研究人员使用。该项目的结果也将有助于公共机构更好地了解监管政策对保险业的影响。