Empirical Study On Seasonal Adjustment Model Based On Time Series Analysis

In the process of steady economic development in our country,the development of different industries or industries have changed.The contrast between new economy and traditional economy has become the most concerned "economic barometer".In order to accurately grasp the economic development trends,it is necessary to monitor macroeconomic indicators in real time.Therefore,the more we carry out the major macroeconomic series,especially the ring-to-ring statistical work of GDP series.It is more and more necessary.On the basis of calculating the year-on-year growth rate of GDP,combined with the annular growth rate to make an analysis of the economic situation,in order to more timely and accurate insight into the trend of economic indicators and provide help for making correct macroeconomic decisions.Firstly,this thesis combines X-11-ARIMA and TRAMO/SEATS models,which are the mainstream models in the world,to seasonally adjust the GDP data of Anhui Province from the first quarter of 2010 to the third quarter of 2017,removes the seasonal factors affecting GDP,calculates its ring-to-ring growth rate,and gives five predictions;then compares the results of the two models,the results show that the ring-to-ring ratio of GDP in Anhui Province has been relatively stable.The growth state is about 6% in the next year.Finally,the seasonal adjustment analysis of X-11-ARIMA model is adopted to analyze the value added by different industries.The direct and indirect methods are used to adjust and compare the seasonal differences of GDP in Anhui Province.At the same time,comparing with the seasonal adjustment results of GDP in Jiangsu Province,we can see that the annular growth rate and the corresponding growth rate of GDP in Anhui Province and Jiangsu Province are comparable.The gap between the rate and Jiangsu is very small,but there is a big gap in volume.