河南工业大学学报:社会科学版
河南工業大學學報:社會科學版
하남공업대학학보:사회과학판
Journal of Henan University of Technology:Social Science Edition
2011年
4期
73~81
,共null页
非正常波动 修匀 向量自回归 协整检验
非正常波動 脩勻 嚮量自迴歸 協整檢驗
비정상파동 수균 향량자회귀 협정검험
abnormal fluctuations ; smoothing; VAR ; cointegration
统计数据经常会受到定期或不定期的非正常波动因素的影响,因此而扭曲的时间序列短期的基本变动,使得我们难以深入研究和正确解释经济规律。如果利用科学的方法将这些非正常波动因素从经济时间序列中测定、分离、抵消和调整,对这些非正常波动统计数据进行修匀,则能更好地反映其基本的发展趋势。以福建省社会消费零售总额指标和相对指标为例,对其进行了修匀处理和并进行修匀前后的对比分析,发现修匀后的曲线较平滑,修匀效果比较合理。进行外推预测和模拟,得到模型的动态模拟结果以及静态预测结果,得到的环比CPI的动态模拟结果较好地反映了CPI的走势,静态预测较好地显示出短期波动情况。
統計數據經常會受到定期或不定期的非正常波動因素的影響,因此而扭麯的時間序列短期的基本變動,使得我們難以深入研究和正確解釋經濟規律。如果利用科學的方法將這些非正常波動因素從經濟時間序列中測定、分離、牴消和調整,對這些非正常波動統計數據進行脩勻,則能更好地反映其基本的髮展趨勢。以福建省社會消費零售總額指標和相對指標為例,對其進行瞭脩勻處理和併進行脩勻前後的對比分析,髮現脩勻後的麯線較平滑,脩勻效果比較閤理。進行外推預測和模擬,得到模型的動態模擬結果以及靜態預測結果,得到的環比CPI的動態模擬結果較好地反映瞭CPI的走勢,靜態預測較好地顯示齣短期波動情況。
통계수거경상회수도정기혹불정기적비정상파동인소적영향,인차이뉴곡적시간서렬단기적기본변동,사득아문난이심입연구화정학해석경제규률。여과이용과학적방법장저사비정상파동인소종경제시간서렬중측정、분리、저소화조정,대저사비정상파동통계수거진행수균,칙능경호지반영기기본적발전추세。이복건성사회소비령수총액지표화상대지표위례,대기진행료수균처리화병진행수균전후적대비분석,발현수균후적곡선교평활,수균효과비교합리。진행외추예측화모의,득도모형적동태모의결과이급정태예측결과,득도적배비CPI적동태모의결과교호지반영료CPI적주세,정태예측교호지현시출단기파동정황。
Statistical data are often subject to the influence of regular or irregular fluctuations caused by abnor-mal factors, thus distorting the fundamental changes in short-term time series and making it difficult to conduct in-depth study and correct interpretation of the economic laws. Provided that scientific methods are used to revise and smooth these statistical data of abnormal fluctuations by determining, separating, offsetting and adjusting these abnormal factors in economic time series can the basic development trends be better reflected. The paper takes for example the indicators of the total retail sales of social consumption in Fujian Province and relative indicators, conducts a comparative analysis before and after revising and smoothing them. It is found that the curve has been smoother and the effect more reasonable. By extrapolation prediction and simulation, dynamic simulation model and static prediction results come out, the dynamic simulation model of the chain CPI emerges, which better reflects the trend of the static forecasts and shows better short-term fluctuations.