摘要
文章通过对中国国际贸易进口和出口的数据分析,应用自回归滑动平均模型和条件异方差理论,对国际贸易进口的差分数据构建了6月份及8月份的自回归平均移动模型和,并应用进口增长率自回归平均移动-条件异方差模型对国际贸易出口增长率进行了波动率和变化率的拟合估计。根据所拟合的模型,发现在8月份拟合的自回归平均移动-条件异方差模型下的国际贸易进口差分数据更接近实际的国际贸易差分数据,并且国际贸易进口增长率差分对出口增长率差分的波动率具有正向的作用。中国国际贸易进口具有滞后的时间效应,并且中国国际贸易进口差分波动率对出口差分有正向的溢出效应。
Based on the analysis of Chinese international trade import and export data, the application of auto regressive moving average model and conditional variance theory of international trade, and at the same time,applied the differential data of import constructed in June and August the auto regressive moving average model at the same time, the application of auto regressive moving average at the import growth rate- conditional difference variances to the models of the growth of international trade export rate of fitting volatility and rate estimation. According to the fitting model, we can find that in August fitting auto regressive moving average- GARCH model fitting international trade import differential data is more close to the actual international trade difference data, and the discovery rate of international trade import growth of the export growth rate difference volatility has a positive effect promotion. China＇s international trade import has a lag time effects, at the same time, China＇s international trade import difference fluctuation rate has a positive stimulative effects on the export difference.
作者
谢沅潮
Xie Yuanchao(Economics and Management School,Wuhan University 430072,Chin)
出处
《统计与决策》
CSSCI
北大核心
2017年第5期153-156,共4页
Statistics & Decision
