Empirical Applications of Contract Theory: the Case of Insurance Contracts

合同理论的实证应用：保险合同案例

• 批准号: 0096516
• 负责人: Pierre Chiappori
• 金额: $ 16.93万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-07-01 至 2004-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0096516&HistoricalAwards=false
• 关键词: Empirical; Applications; Contract; Theory; Case

In the last twenty years, contract theory has developed at a rapid pace. But, until recently at least, empirical applications have lagged behind. This project is aimed at filling this gap. It is based on the view that insurance provides a nearly ideal field for empirical work on contracts. Individual insurance contracts (automobile, housing, health, life, etc.) are largely standardized. The insurer's information is accessible, and can generally be summarized through a reasonably small number of quantitative or qualitative indicators. The 'performance' - whether it represents the occurrence of an accident, its cost, or some level of expenditure - is very precisely recorded in the firms' files. Finally, insurance companies frequently use data bases containing several millions of contracts, which enables testing of most predictions of contract theory in a detailed way, using standard econometric tools. Three directions will be investigated. The theory has emphasized the role of information asymmetries in the design of optimal contracts, and more specifically the distinction between adverse selection and moral hazard. Adverse selection arises when one party to the contractual relationship - say, the subscriber to an insurance contract - has better information than the other party - say, the insurer - about some parameters that are relevant for the relationship. Moral hazard occurs when the accident probability is not exogenous, but depends on some decision (e.g., effort of prevention) that is made by the subscriber but cannot be monitored by the insurer. In general, different insurance contracts provide different incentives, hence result in different observed accident rates. The empirical distinction between moral hazard and adverse selection is crucial, in particular because the implications in terms of welfare and regulation are totally different. However, in many cases, moral hazard and adverse selection are very difficult to disentangle. The first aim of the present project is to show how the empirical distinction between moral hazard and adverse selection can be implemented when data relative to the dynamics of the relationship are available. A second goal is to study the structure of insurance pricing in the industry. Given the data available, we shall be able to estimate the total risk distribution of each insuree, as a function of her characteristics (age, type of car, location, etc.). This involves not only the probability of an accident, but also its expected severity and the corresponding costs. This regression, in other words, should provide a very accurate description of the 'product' sold by the insurance company. In a second stage, it can be related to the pricing policy. One may check whether the premium charged to a particular consumer only depends on her risk, or whether it may for any given level of risk vary with other characteristics, such as age, sex, etc. Conclusions can be drawn on the industrial organization of the field. The third research direction adopts a more normative viewpoint. A striking feature of modern biology is the increasing ability to identify the genes that either are responsible for or tend to create predispositions to various diseases. This possibility will lead to a spectacular amelioration of prevention and treatments. However, the availability of more precise information on the risk destroys insurance possibilities, which is welfare decreasing. A first task is to obtain a first evaluation of the associated welfare loss. This requires, in particular, an evaluation of the benefit provided by insurance coverage. One purpose of the study (and a quite difficult one) is to provide an preliminary evaluation of this order of magnitude. The most radical solution proposed involves a regulation that would strictly prohibit the use of genetic testing by insurance companies. Such a proposal however requires a thorough investigation. From an economist's point of view, it amounts to introducing a strong adverse selection component. Agents will presumably be informed of their risk, at least if (as it will probably be the case) individuals have free access to genetic testing. The problem, now, is to assess the impact of this asymmetry on the market for health or life insurance. This is a crucial issue, if only because the solution might well reveal worse than the initial problem. If the final outcome is a global collapse of the insurance markets at stake, everybody (including the population at risk) will end up in a much worse situation. The last goal of the project is only to provide some preliminary elements for assessing the scope and

近二十年来，契约理论得到了迅速发展.但是，至少直到最近，实证应用一直落后。该项目旨在填补这一空白。它是基于这样一种观点，即保险为合同的实证工作提供了一个近乎理想的领域。个人保险合同（汽车、住房、健康、人寿等）基本上是标准化的。保险公司的信息是可以获得的，一般可以通过数量合理的少量定量或定性指标进行总结。“业绩”-无论是代表事故的发生、事故的成本，还是某种程度的支出-都非常准确地记录在公司的档案中。最后，保险公司经常使用包含数百万份合同的数据库，这使得使用标准计量经济学工具可以详细地测试合同理论的大多数预测。将从三个方面进行研究。该理论强调了信息不对称在最优契约设计中的作用，更具体地说，强调了逆向选择和道德风险之间的区别。当合同关系的一方--比如说保险合同的签署者--比另一方--比如说保险公司--在与关系相关的某些参数方面拥有更好的信息时，就会出现逆向选择。道德风险发生在事故概率不是外生的，而是取决于某些决策（例如，预防的努力），这是由用户作出的，但不能由保险公司监控。 一般来说，不同的保险合同提供不同的激励，因此导致不同的观察到的事故率。道德风险和逆向选择之间的经验区别是至关重要的，特别是因为福利和监管方面的含义完全不同。然而，在许多情况下，道德风险和逆向选择很难分开。本项目的第一个目的是要说明如何经验的区别道德风险和逆向选择可以实施时，数据相对于动态的关系。第二个目标是研究该行业的保险定价结构。根据现有数据，我们将能够估计每个被保险人的总风险分布，作为其特征（年龄，汽车类型，位置等）的函数。这不仅涉及事故发生的可能性，还涉及其预期的严重程度和相应的成本。换句话说，这种回归应该对保险公司销售的“产品”提供非常准确的描述。在第二阶段，它可能与定价政策有关。人们可以检查向特定消费者收取的保险费是否仅取决于她的风险，或者对于任何给定的风险水平，保险费是否可以随其他特征而变化，例如年龄、性别等。第三个研究方向采用了更规范的观点。现代生物学的一个显著特征是，识别导致或倾向于产生各种疾病易感性的基因的能力越来越强。这种可能性将导致预防和治疗的显著改善。然而，更准确的风险信息的可用性破坏了保险的可能性，这是福利下降。 第一任务是获得相关福利损失的第一评估。 这尤其需要对保险所提供的福利进行评估。这项研究的目的之一（也是相当困难的一个目的）是对这一数量级进行初步评估。最激进的解决方案是制定一项法规，严格禁止保险公司使用基因检测。然而，这一建议需要进行彻底的调查。从经济学家的角度来看，这相当于引入了一个强大的逆向选择成分。代理人大概会被告知他们的风险，至少如果（很可能是这样）个人可以免费获得基因检测。现在的问题是评估这种不对称对健康或人寿保险市场的影响。这是一个至关重要的问题，即使只是因为解决方案很可能比最初的问题更糟糕。如果最终的结果是全球保险市场的崩溃，那么每个人（包括处于风险中的人口）的情况都会变得更糟。该项目的最后一个目标只是为评估范围和