Exploring the Time-Series Implications of Dynamic Models in Economics and Finance

该项目就与以下三个专题有关的工作开展工作： 各种动态模型的时间序列含义， 经济和金融。 第一个主题的研究目的是 开发和应用新的估算方法， 非线性连续时间过程的推理 这些方法 将用于研究资产的替代连续时间模型 定价 第二个主题下的研究将评估 各种随机贴现因子模型的性能 资产定价 动态资产定价模型的新诊断 将开发，规格的大小新的措施 将提供各种此类模型的错误，以及新的 将探讨确定和估计的方法。 的 第三个主题将继续发展模型的解决方法 对一类丰富的递归线性 动态经济模型。 在这些模型的范围内， 将会有关于最优动态税收的调查， 季节性、随时间的聚集和收入分配。 这一项目对实证研究的方式产生了巨大影响 研究是在经济学中进行的。 调查员在 与其他人合作，开发了新的方法， 数据来严格估计动态经济关系， 在经济学的实证研究中占据主导地位。 这个项目 在过去研究成果的基础上， 在资产等研究领域研究动态的方法 定价、税收和收入分配。 项目 从事非线性模型的新研究， 连续时间过程。 这一点很重要，因为计量经济学 和统计方法，旨在估计或测试 关于这些模型的大量理论研究已经被 发展缓慢。 该项目将扩大现有的一套 方法，并使用它们来获得重要的新的实质性见解 证券市场的表现。

This project carries out work on three topics pertaining to the time series implications of a variety of dynamic models in economics and finance. Research under the first topic is aimed at developing and applying new methods of estimation and inference for nonlinear continuous time processes. These methods will be used to study alternative continuous time models of asset pricing. Research under the second topic will assess the performance of a variety of stochastic discount factor models of asset pricing. New diagnostics for dynamic asset pricing models will be developed, new measures of the magnitude of specification errors for a variety of such models will be provided, and new methods of identification and estimation will be explored. The third topic will continue development of model solution methods for and quantitative analysis of a rich class of recursive linear models of dynamic economies. Within the context of these models, there will be investigations of optimal dynamic taxation, seasonality, aggregation-over-time and income distribution. This project has had an enormous influence on the way empirical research is conducted in economics. The investigator, in collaboration with others, has developed new methods for using data to rigorously estimate dynamic economic relationships that now dominate most empirical research in economics. This project builds on the results of past research by developing better methods for studying dynamics in such areas of research as asset pricing, taxation and income distribution. The project undertakes a new line of research on nonlinear models of continuous time processes. This is important because econometric and statistical methods designed for estimating or testing the extensive body of theoretical research on these models have been slow to develop. This project will expand the existing set of methods and use them to obtain important new substantive insights into the performance of security markets.