Integrative Noise and Fixed Point Methods as Solution Techniques for Generalized Linear-Quadratic Models of Endogenous Information

综合噪声和不动点方法作为内生信息广义线性二次模型的求解技术

• 批准号: 8721304
• 负责人: Bart Taub
• 金额: $ 2.86万
• 依托单位: Virginia Polytechnic Institute and State 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: 1988-04-01 至 1990-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8721304&HistoricalAwards=false
• 关键词: Integrative; Noise; Fixed; Point; Methods

Rational expectations models of macroeconomics that incorporate asymmetric information typically use a linear-quadratic technical framework because individuals' predictions or decisions are then linear (and hence tractable) functions of observable variables. If individuals have asymmetric information and obtain information by observing endogenous variables -- prices, aggregate output or the like -- then it becomes technically difficult to solve such models for the endogenous aggregates. The standard method, the method of undetermined coefficients, is limited to special cases. The investigator developed two promising new solution methods and in this project he expands them to a more general setting. He will show that all linear rational expectations models with asymmetric information are expressible as special cases of a general structure in which economic, informational, and statistical structure is captured by specifying the dimensions and elements of matrices of analytic functions. Any economic structure can be rigorously modelled and empirically estimated by specifying the details of these matrices. Solving this model requires factoring the matrix. The first approach designs the model so that the matrix is comprised solely of exogenous elements -- which are easily factored -- and then perturbing the model to achieve the solution of the economically interesting model. The second approach uses a contraction mapping fixed point method. The model will integrate the informational externality micro literature with the rational expectations literature. This paves the way for further analysis, particularly of the welfare characteristics of alternative policy regimes, using what we know from the micro literature. The investigator has already shown how informational externalities lead to aggregate fluctuations that mimic business cycles for special cases of stochastic driving processes. This project investigates how the persistence, amplitudes and co-movements of economic aggregates are affected by such externalities when the driving processes are more general.

宏观经济学的理性预期模型， 不对称信息通常使用线性二次技术 因为个人的预测或决定 可观测变量的线性（因此易于处理）函数。 如果个人拥有不对称的信息， 通过观察内生变量--价格、总产出或 那么技术上就很难解决 内生性聚集体的模型。 标准方法， 待定系数法，仅限于特殊情况。 研究人员开发了两种有前途的新解决方案， 在这个项目中，他将它们扩展到一个更一般的环境。 他 将表明，所有线性理性预期模型， 信息不对称可以表述为 经济、信息和 通过指定维度来捕获统计结构 和解析函数矩阵的元素。 任何经济 结构可以严格建模和经验估计， 指定这些矩阵的细节。 求解该模型 需要分解矩阵 第一种方法设计了 模型，使矩阵仅由外源 这些元素很容易分解，然后干扰 模型，以实现经济利益的解决方案 模型 第二种方法使用压缩映射固定 点法 该模型将信息外部性的微观整合 理性预期的文学。 这铺路 进一步分析的方式，特别是福利 替代政策制度的特点，利用我们所知道的 从微观文学。 调查人员已经证实 信息外部性如何导致总体波动 模拟商业周期的特殊随机情况， 驾驶过程。 这个项目调查了 经济总量的持续性、幅度和共同变动 受到这种外部性的影响，当驱动过程是 更一般。