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

探索经济和金融动态模型的时间序列含义

• 批准号: 9110015
• 负责人: Lars Hansen
• 金额: $ 18.3万
• 依托单位: National Opinion Research Center
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-08-15 至 1995-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9110015&HistoricalAwards=false
• 关键词: Exploring; Time; Series; Implications; Dynamic

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.

该项目开展的工作涉及三个主题，涉及经济和金融中各种动态模型的时间序列含义。第一个主题的研究旨在开发和应用非线性连续时间过程的估计和推理的新方法。这些方法将用于研究资产定价的替代连续时间模型。第二个主题下的研究将评估各种资产定价的随机贴现因子模型的性能。将开发动态资产定价模型的新诊断方法，为各种此类模型提供规格误差大小的新措施，并探索识别和估计的新方法。第三个主题将继续发展模型求解方法，并对一类丰富的动态经济递归线性模型进行定量分析。在这些模型的背景下，将对最优动态税收、季节性、随时间累积和收入分配进行调查。这个项目对经济学中实证研究的方式产生了巨大的影响。这位研究者与其他人合作，开发了使用数据严格估计动态经济关系的新方法，这种方法目前主导着经济学中的大多数实证研究。该项目以过去的研究成果为基础，通过开发更好的方法来研究资产定价、税收和收入分配等研究领域的动态。该项目对连续时间过程的非线性模型进行了新的研究。这一点很重要，因为为估计或检验这些模型的大量理论研究而设计的计量经济学和统计方法发展缓慢。该项目将扩展现有的方法集，并利用它们获得对证券市场表现的重要的新的实质性见解。