我国外贸依存度的灰色关联度分析及灰色马尔科夫预测

Grey Correlation Analysis and Grey Markov Prediction of China’s Foreign Trade Dependence

摘要: 本文探究了我国外贸依存度与其影响因素的关联程度以及我国外贸依存度在当前环境政策下的变化情况，利用1990~2017共28年的数据由“总活动”法计算出我国的外贸依存度，并且与经典计算公式所得的名义外贸依存度作比较，针对其影响因素进行了灰色关联度分析，进一步运用灰色马尔科夫模型预测了我国未来三年的外贸依存度。分析结果表明：我国的外贸依存度在修正后没有名义上那么高；对其影响程度较大的是人口总数、CPI、汇率和第三产业占比；马尔科夫修正后的GM(1,1)模型可以预测到我国外贸依存度的细微波动情况，预测精度高达99.33%，较GM(1,1)模型，预测精度提高了约2%。

Abstract: This paper explores the degree of correlation between China’s foreign trade dependence and its influencing factors and the changes of China’s foreign trade dependence under the current policies, calculates China’s foreign trade dependence by the “total activity” method using data for 28 years from 1990 to 2017, and compares it with the nominal foreign trade dependence obtained by the classical formula. A gray correlation analysis is conducted for its influencing factors, and a gray Markov model is further applied to predict China’s foreign trade dependence in the next three years. The results of the analysis show that: China’s foreign trade dependence is not as high as the nominal one after the correction; the influencing factors are total population, CPI, exchange rate and tertiary industry share; the Markov modified GM(1,1) model can predict the slight fluctuation of China’s foreign trade dependence with 99.33% prediction accuracy, which is about 2% higher than the GM(1,1) model.