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Research on Seasonal Adjustment of Economic Time Series

经济时间序列季节调整研究

基本信息

批准号：
08045018
负责人：
KITAGAWA Genshiro
金额：
$ 2.56万
依托单位：
The Institute of Statistical Mathematics
依托单位国家：
日本
项目类别：
Grant-in-Aid for international Scientific Research
财政年份：
1996
资助国家：
日本
起止时间：
1996 至 1998
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-08045018/
关键词：
Time Series Analysis State space model Nonlinear Non-Gaussian model Kalman filter Monte Carlo filter Smoothing Software for Web 平滑化経済データモデル選択トレンド季節成分情報量規準

项目摘要

The objective of this research was to render the theoretical considerations to the various problems in statistical seasonal adjustment, and to develop new methods based on the state-of-art techniques in modern time series analysis. The summary of our research report follows.(1)Development of new proceduresSeasonal adjustment methods based on Monte Carlo filter and smoother, and on dynamical system approach were proposed. Dynamic X-11 model successfully gives explicit model form to X-11, which is defined in an essentially non-parametric way. Monte Carlo filter/smoother deals with higher-dimensional seasonal adjustment problem allowing non-linearity and non-Gaussianity, which was next to impossible by the existing statistical methods. Thsi method was applied to the seasonal adjustment of small count data which seemingly contains quasi-periodic components.(2)Enhancement and characterization of seasonal modelsMacroeconomic system was estimated based on the multivariate seasonal adjustment. These kind of composite seasonal adjustment could be more important in the near future. Extension of seasonal models to time-space data was also considered. Finally, the research on the characterization of linear Gaussian model based seasonal adjustment was done in terms of the optimality of seasonal adjustment. Comparative study between DECOMP and X-12 ARTMA was also performed through simulations.(3)Software developmentThe most successfull software product is Web-DECOMP.Users are free from instaling softwares on local disks or free from recompilation of software codes, but they simply can execute seasonal adjustment program DECOMP through internet browsers. On the other hands, U.S.Bureau of the Census almost completed their new version of software, X-12-ARIMA.The most updated version and its documentation (but not the official release yet at present) can be downloaded via their ftp site (ftp.census.gov).

这项研究的目的是对统计季节调整中的各种问题进行理论思考，并基于现代时间序列分析的最新技术开发新的方法。提出了基于蒙特卡罗滤波和平滑的季节平差方法和基于动力系统方法的季节平差方法。动态X-11模型成功地给出了本质上非参数定义的X-11的显式模型形式。蒙特卡罗滤波/平滑处理允许非线性和非高斯性的高维季节调整问题，这在现有的统计方法中几乎是不可能的。将这一方法应用于似乎含有准周期分量的小计数数据的季节调整。(2)季节模型的增强和表征基于多变量季节调整的宏观经济系统估计。在不久的将来，这种综合的季节性调整可能会变得更加重要。还考虑了将季节性模型扩展到时空数据。最后，从季节调整的最优性出发，研究了基于线性高斯模型的季节调整的特征。软件开发最成功的软件产品是WEB-DECOMP，用户不需要在本地磁盘上安装软件，也不需要重新编译软件代码，只需通过网络浏览器就可以执行季节性调整程序分解。另一方面，美国人口普查局即将完成他们的新版本软件X-12-ARIMA。最新版本及其文档(但目前还没有正式发布)可以通过他们的ftp网站(ftp.percus.gov)下载。