摘要
在国际关系预测领域,目前较多文献集中于经验预测或者回归模型预测。而在计量经济学中,时间序列预测方法是前沿的预测方法。因此,本文将时间序列分析方法引入国际关系预测领域,以中法关系为例,建立了ARIMA模型。根据模型检测,中法关系属于非平稳序列,也就是说中法关系变化不是水平波动,容易出现大起大落的趋势。通过经验事实的检验表明,文中对双边关系的预测具有较高的准确率。
Nowadays a number of literature focus on experimental studies or on regression models in forecasting international relations. As a leading forecasting method frequently used in the econometrics,the time-series analysis is relatively neglected in the IR field,into which the author introduces the time-series analysis and builds an ARIMA model by applying it in forecasting the Sino-French relations. According to the time-series analysis,the relationship between China and France belongs to the non-stationary series which is apt to change.The result proves a relatively high degree of accuracy in forecasting the bilateral relationships.
出处
《欧洲研究》
CSSCI
北大核心
2009年第4期20-32,共13页
Chinese Journal of European Studies
