Nonlinearity in Economics and Finance

这个项目的目标是整合混沌的方法 理论和非线性动力学现在用于自然和 物理科学与计量经济学 该项目以一种 为宏观经济学开发有用的新工具， 财政 构建工具的策略是， 实际数据的真实性，实际的计量经济学实践，以及 应用程序--在这个过程中放弃抽象的一般性。 具体方案包括：（1）将 将确定性混沌的残差诊断转化为“残差 测试“确定性混沌”。 (2)统计出 维数分布理论，Kolmogorov熵， Lyapunov指数 比较和对比大小和功率 零的Brock开发的测试的特性 独立性假设与其他测试，如 特征函数检验、分布函数检验，以及 Cramer/ Von Mises形式的测试。 (4)构建通用测试 并比较其尺寸和功率特性 对于诸如双谱偏度测试的其他非线性测试， 双线性试验、双线性和甘精胰岛素试验以及半线性试验 非线性的非参数检验 (5)将这些测试应用于 宏观经济和金融数据。 (6)建立宏观经济 模型和均衡资产定价模型，解释了 发现非线性模式。

The objective of this project is to integrate methods of chaos theory and nonlinear dynamics now used in the natural and physical sciences with econometrics. The project does this in a way that develops useful new tools for macroeconomics and finance. The strategy for building tools is to stay close to the realities of actual data, actual econometric practice, and the applications-- giving up abstract generality in the process. The specific projects consist of the following: (1) turn the residual diagnostic for deterministic chaos into a "residual test" for deterministic chaos. (2) Work out statistical distribution theory for dimension, Kolmogorov entropy, and Lyapunov exponents. Compare and contrast the size and power characteristics of a test developed by Brock of the null hypothesis of independence with other tests such as characteristic function tests, distribution function tests, and Cramer/ Von Mises forms of the tests. (4) Build a general test for nonlinearity and compare its size and power characteristics to other nonlinearity tests such as the bispectral skewness test, tests for bilinearity, tests for ARCH and GARCH, and semi- nonparametric tests for nonlinearity. (5) Apply these tests to data in macroeconomics and finance. (6) Build macro economic models and equilibrium asset pricing models that explain the pattern of nonlinearity found.