Large State Space Issues in Dynamic Models

动态模型中的大状态空间问题

• 批准号: 1124193
• 负责人: Peter Arcidiacono
• 金额: $ 39.11万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1124193&HistoricalAwards=false
• 关键词: Large; State; Space; Issues; Dynamic

The estimation of models of dynamic decision making is complicated by needing to calculate the future payoffs associated with different choice paths. These expected future payoffs from behaving optimally in the future are called the value function. Calculating a value function for a complicated dynamic game is computationally expensive because of the large number of possible choice paths. This award funds research to develop a new method for approximating value functions. The approximation is based on sieve methods, and it has good asymptotic properties as the complexity of the sieve increases.These methods will be useful for models of individual decision making and also useful for dynamic games, where several individuals make decisions over time. The sieve method can be used to solve for the finite horizon Nash equilibrium; it can also be used to test whether this equilibrium is being played by individuals in a particular application. The research team will apply this method to analyzing data from a sample of sixth grade students; the dynamic game here is the establishment of friendships and how students over time form strong peer networks.The new method will potentially advance empirical work in many areas of applied microeconomics. Because the method is computationally less expensive, it may be well suited for use by researchers who wish to estimate dynamic game models at a reasonable cost.

动态决策模型的估计是复杂的，因为需要计算与不同选择路径相关的未来收益。 这些未来最优行为的预期收益称为价值函数。 计算一个复杂的动态博弈的价值函数是计算昂贵的，因为大量的可能的选择路径。 该奖项资助研究开发一种近似值函数的新方法。 近似是基于筛子方法，它具有良好的渐近性质随着筛子的复杂性的增加，这些方法将是有用的个人决策模型，也有用的动态游戏，其中几个人随着时间的推移作出决定。 筛法可以用来求解有限时间纳什均衡，也可以用来测试在特定应用中个人是否在玩这个均衡。 研究小组将运用这种方法分析六年级学生的样本数据;这里的动态游戏是建立友谊以及学生如何随着时间的推移形成强大的同伴网络。新方法将潜在地推进应用微观经济学许多领域的实证工作。 由于该方法是计算成本较低，它可能是非常适合使用的研究人员谁希望以合理的成本估计动态博弈模型。