基于季节调整的CPI统计环比指数研究

本文首先阐述了季节调整与统计环比指数的必要性,简要介绍了X-12-ARIMA与TRAMO/SEATS季节调整原理,然后运用X-12-ARIMA程序对中国1997年1月至2010年5月CPI月度数据进行季节调整,再运用TRAMO/SEATS方法解决季节调整程序中中国春节因素问题。接着由季节调整后的数据计算得到月环比CPI,对月环比CPI和同比增加率进行了比较,结果显示月环比CPI领先同比CPI。最后利用TRAMO/SEATS程序建立ARIMA模型（210）（011）进行了24个月的预测,预测结果显示,未来24个月内我国消费者物价指数温和上升,不会发生大的通货膨胀,但是存在一定的通胀压力。

Research of CPI Chain Index based on Seasonal Adjustment

This paper firstly describs the need for seasonal adjustment and index of statistics chain,and briefly introduces the seasonal adjustment principle of the X-12-ARIMA and TRAMO/SEATS.Then it applies X-12-ARIMA procedure to China＇s monthly CPI from Jan.1997 to May 2010 for seasonal adjustment,uses TRAMO/SEATS solutions to solve the Chinese New Year factor problem in seasonal adjustment process,uses the seasonally adjusted data to calculate monthly chain CPI,and compares the monthly chain CPI with the year-on-year increase rate.Results show that chain CPI is higher than the year-on-year CPI.Finally,the paper uses ARIMA Model（2 1 0）（0 1 1） established by TRAMO /SEATS procedure to predict for the next 24 months.Prediction results show that within the next 24 months,China＇s consumer price index will moderately increase,and there will not be major inflation,but there are some inflation pressures.