统计研究

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德国BV4.1模型修正与中国CPI季节调整

桂文林 李玉玲   

  • 出版日期:2017-07-15 发布日期:2017-07-18

Correction of Germany BV4.1 and the Seasonal Adjustment of China’s CPI

Gui Wenlin & Li Yuling   

  • Online:2017-07-15 Published:2017-07-18

摘要: 中国的居民消费价格指数(CPI)是衡量通货膨胀程度和经济活动水平的重要指标,通常要剔除季节性因素影响。本文对国际最新的BV4.1季节调整模型进行了系统的研究和软件开发,编写R程序增强了其实用性,首先考虑到了中国的节日因素,交易日因素和异常值,对2001年1月至2015年3月的CPI数据进行了预处理。在分离出季节成分以及日历成分之后,还采用了平滑区间和修正历史法进行了模型诊断的研究。研究得出:CPI的趋势在短期内具有二阶多项式发展特征,节日因素,交易日影响和异常值不显著;实证结果表明BV4.1的季节调整结果与其他模型如X-12-ARIMA和TRAMO/SEATS相比具有很强的稳定性。

关键词: BV4.1, 中国CPI, 修正历史法

Abstract: China's CPI is an important indicator of inflation and economic activity which usually exclude the seasonal factors. Then it is to introduce the latest seasonal adjustment method BV4.1 which is systematically studied with full exploitation. Besides, R programming is applied to increase its practicability. First of all, Chinese holidays, trading day effects and detecting outliers are considered to make a preprocessing for CPI from Jan 2001 to Mar 2015. After separating seasonal and calendar components, sliding span as well as revised history is used for testing adjustment stability. Main conclusions: (1) CPI has a quadratic polynomial trend in the short term, the impact of the Chinese holidays, trading day effects and outliers are not significant. (2) Seasonally adjusted series by BV4.1 has a better stability than X-12-ARIMA and TRAMO/SEATS.

Key words: Seasonal Adjustment, BV4.1, China’s CPI, Revised History