Collaborative Research: Likelihood Principle Analysis of Economic Time Series

合作研究：经济时间序列似然原理分析

• 批准号: 9005180
• 负责人: David DeJong
• 金额: $ 4.13万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1990
• 资助国家: 美国
• 起止时间: 1990-03-15 至 1992-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9005180&HistoricalAwards=false
• 关键词: Collaborative; Research; Likelihood; Principle; Analysis

The purpose of this research is to develop several applications of the Likelihood Principle for investigating macroeconometric problems that have been difficult to address using classical methods. Further, methods will be devised for evaluating the performance of these procedures in repeated samples, and for illustrating the impact of a broad range of different assumptions on the results. The first consideration is whether macroeconomic time-series-data are best described as integrated or trend- stationary. The performance of Classical integration and co- integration tests will be compared against trend-stationary alternatives. In addition, a method will be devised for examining the performance of macroeconomic models from a Bayesian perspective, and to seek the appropriate interpretation of classically obtained results. Finally, the theory of dynamic games will be extended to models in which the structure of the relevant model is not known with certainty. This research is important because it will provide better methods for analyzing time-series-data, which is the type of data used in much of the empirical research in economics and the other social sciences.

这项研究的目的是开发几个应用程序 研究宏观计量经济学的李克定律 这些问题很难用经典的 方法. 此外，将设计用于评估 在重复样本中执行这些程序，以及 说明各种不同假设的影响 结果。 第一个问题是，宏观经济 时间序列-数据最好描述为综合或趋势- 静止的 经典集成与协同的性能 将积分测试与趋势平稳测试进行比较 替代品. 此外，还将设计一种方法， 从贝叶斯模型中检验宏观经济模型的性能 观点，并寻求适当的解释， 经典的结果。 最后，动态理论 游戏将被扩展到模型，其中的结构， 相关型号尚不确定。 本研究是 重要的是，它将提供更好的方法来分析 时间序列数据，这是在大多数情况下使用的数据类型。 经济学和其他社会科学的实证研究。