宏观经济统计数据结构变化分析及其对中国的实证

The Analyses on Structure Changes in Macroeconomics Data Series and Positive Study on China

对于宏观经济统计数据的结构变化进行分析已成为研究数据质量的核心内容之一。本文从经济系统的角度运用联合估计诊断模型对我国 3 6个宏观经济时间序列的结构变化进行了全面的分析 ,发现了数据异常的特点和规律。研究结论表明 :大部分异常点的出现或多或少都是以聚集成堆的形式出现的 ,它们之间存在深刻的内在联系 ,孤立的异常点不是我国宏观经济时间序列的主要特征 ;几乎所有的原始序列都有显著的偏度 ,过多的峰度也是明显的 ,因此它们被显著地拒绝认为服从正态分布 ;大部分变量的原始序列和异常点修正后序列虽然都呈现出非ARCH特征 ,但是ARCH2、ARCH4、ARCH8的P值却有一定程度的不同。

The study on structures changes has become one of the core contents on macroeconomic data quality. This paper adopts the joint estimation model to deeply analysis 36 Chinese macroeconomic data series from the view of economic system and finds out the features and rules of the outliers. The results show:The most of outliers appear in the cluster forms more or less, and there are deep internal relationships between them, and the isolated outliers are not the major features of Chinese data. Almost all of the original series have obvious skewness and many kurtosis are appear. So it is obviously rejected they obey normal distributions. Most of the original series and the correct series appear non-ARCH features, but the P-value from ARCH2 to ARCH8 are different.