Nonparametric Inferences from Demand Observations

来自需求观察的非参数推论

• 批准号: 8720596
• 负责人: Rosa Matzkin
• 金额: $ 6.4万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1988
• 资助国家: 美国
• 起止时间: 1988-02-15 至 1990-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8720596&HistoricalAwards=false
• 关键词: Nonparametric; Inferences; Demand; Observations

The purpose of this proposal is to develop methods that use observations about consumer demands to infer properties of consumer preferences. These new methods will require fewer restrictions on the structure of consumer preferences and their utility representations than previous studies have imposed. This research is important because the use of these new approaches will allow researchers to avoid assumptions beyond those directly implied by economic theory and, consequently, to avoid errors that result when models entail possible misspecifications. The project will consider consumers' choices from finite sets of alternatives. For example, from observations on consumer's choices among various means of transportation, it will be possible to study and infer the utility they attach to various attributes, such as time and cost, of alternative means of transportation. In contrast to previous studies, the utility functions and their distribution in the consumer population need to satisfy only weak conditions.

该提案的目的是开发使用 观察消费者的需求来推断消费者的属性 喜好 这些新方法将需要更少的限制 消费者偏好结构及其效用表征 比以前的研究所施加的。 这项研究很重要，因为 这些新方法的使用将使研究人员能够避免 超越经济理论直接暗示的假设， 因此，为了避免模型可能导致的错误， 规格错误 该项目将考虑消费者的选择， 有限的备选方案集。 例如，根据对 消费者在各种交通工具中的选择， 可以研究和推断他们附加到各种效用 时间和成本等属性， 运输 与以前的研究相比，效用函数 以及它们在消费者群体中的分布只需要满足 弱条件。