Macroeconomic data releasing and methodology research on measuring China's business cycle in the real-time

被引：0
|
作者：
Zheng T. [1 ,2 ]
Xia K. [2 ]
机构：
[1] Department of Statistics, School of Economics, Xiamen University, Xiamen
[2] Wang Yanan Institute for Studies in Economics (WISE), Xiamen University, Xiamen
来源：
| 1600年 / Systems Engineering Society of China卷 / 37期
基金：
中国国家自然科学基金;
关键词：
Business cycle; Macroeconomic data releases; Markov-switching dynamic factor model; Realtime ragged-edge data;
D O I：
10.12011/1000-6788(2017)04-0817-14
中图分类号：
学科分类号：
摘要：
To make better use of the new information from macroeconomic data releasing in the realtime, this paper develops a mixed-frequency Markov-switching dynamic factor model for an unbalanced datasets together with its Bayesian estimation procedure. Simulation studies show that the Bayesian method improves the estimation accuracy, and indicators with less noise are more efficient in reducing the measure errors in the real-time. Based on 256 real-time data sets collected on the data releasing dates since 2008, it shows that our model well characterizes China's business cycle since 1992, and its estimation is robust and reliable with respect to GDP data revisions. In addition, there may exist about 2 to 8 month delays in real-time dating business cycle turning points. Furthermore, among all indicators released in turn within every month, export and import total amount is released earlier but with more noise, while the real-time revision impacts of indicators like industrial product, fiscal taxation on the contemporary business cycle fluctuation are substantial and reliable. © 2017, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
引用
收藏
页码：817 / 830
页数：13
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