Bayesian Inference, Modeling and Forecasting Techniques in Econometrics

计量经济学中的贝叶斯推理、建模和预测技术

• 批准号: 8708571
• 负责人: Arnold Zellner
• 金额: $ 13.49万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-08-01 至 1991-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8708571&HistoricalAwards=false
• 关键词: Bayesian; Inference; Modeling; Forecasting; Techniques

This project extends past and current research on Bayesian inference, econometric modelling and forecasting techniques. In particular, in the area of Bayesian inference further research will be done: (1) to assess the properties of estimates and predictions relative to asymmetric loss functions; (2) to extend and elaborate work on optimal information processing and Bayes' Theorem; (3) to report and extend results on invariant maximal data information prior distributions; and (4) to continue research on minimum expected loss estimates for structural coefficients. In the area of econometric modeling and forecasting techniques, work on Bayesian state-space models have been developed and applied in forecasting annual and quarterly data for the U.S. and eight European countries. These models will be further refined and applied to data from nine additional countries.

该项目扩展了过去和当前对贝叶斯推理的研究， 经济计量模型和预测技术。 特别是 贝叶斯推理领域的进一步研究将做：（1）， 评估估计和预测的性质， 不对称损失函数;（2）扩展和详细说明最佳 信息处理和贝叶斯定理;（3）报告和扩展 不变最大数据信息先验分布的结果; (4)继续研究最低预期损失估计， 结构系数 在计量经济学建模领域， 预测技术，贝叶斯状态空间模型的工作， 开发并应用于预测年度和季度数据， 美国和八个欧洲国家。 这些模型将进一步 完善并应用于另外九个国家的数据。