Mathematical Sciences: Dealing with Mixed Levels of Uncertainty

数学科学：处理混合级别的不确定性

• 批准号: 9523602
• 负责人: M Granger Morgan
• 金额: $ 24.06万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-09-01 至 1999-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9523602&HistoricalAwards=false
• 关键词: Mathematical; Sciences; Dealing; Mixed; Levels

This research program revolves around three different but related projects in discrete choice modeling and estimation. The common theme is the modeling of consumer choice behavior, and the estimation of models of consumer behavior on revealed preference data sets. With the availability of electronic scanner panel data, choice models have become very important for understanding consumer behavior. For example, such models may be used to evaluate the impact of the marketing mix on consumer purchasing behavior, and to assess the patterns of competition in the market place. The three research projects in this study involve the use of recently developed simulation estimation techniques. In the model of the first project, consumer choice probabilities are high dimensional integrals over unobserved prices and coupon values, as well as over stochastic preference shocks. Thus, Monte-Carlo methods must be used to simulate the likelihood function in the model. In the second and third projects, both solution of the dynamic programming problem and construction of the likelihood function require high dimensional integrations over stochastic process for prices, preference shocks, etc. In these projects we will use Monte- Carlo methods both to solve consumers' dynamic programming problems and to simulate the likelihood function.

本研究计划围绕三个不同但相关的离散选择建模和估计项目。 共同的主题是消费者选择行为的建模，以及消费者行为模型的估计显示偏好数据集。 随着电子扫描仪面板数据的可用性，选择模型对于理解消费者行为变得非常重要。 例如，这些模型可用于评估营销组合对消费者购买行为的影响，并评估市场竞争的模式。 本研究中的三个研究项目涉及使用最近开发的模拟估计技术。 在第一个项目的模型中，消费者的选择概率是高维积分的未观察到的价格和优惠券的价值，以及随机偏好冲击。 因此，必须使用蒙特-卡罗方法来模拟模型中的似然函数。 在第二个和第三个项目中，动态规划问题的解决方案和似然函数的构建都需要对价格，偏好冲击等随机过程进行高维积分。在这些项目中，我们将使用Monte- Carlo方法来解决消费者的动态规划问题并模拟似然函数。