Forecasting China's current account with EEMD-AWNN ensemble learning approach

被引:0
作者
Liu Y. [1 ,2 ]
Xie L. [1 ,2 ]
Wang S. [1 ,2 ,3 ]
Sun S. [4 ]
机构
[1] Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing
[2] School of Economics and Management, University of Chinese Academy of Sciences, Beijing
[3] Center for Forecasting Science, Chinese Academy of Sciences, Beijing
[4] School of Management, Xi'an Jiaotong University, Xi'an
来源
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | 2021年 / 41卷 / 05期
基金
中国国家自然科学基金;
关键词
Adaptive wavelet neural network; Current account; Empirical mode decomposition; Ensemble learning; Forecasting;
D O I
10.12011/SETP2018-0744
中图分类号
学科分类号
摘要
With the development of China's foreign trade and economic structure reform, it is necessary to explore the evolution of the balance of payments for the macroeconomic regulation, but China is faced with uncertainty of the current account due to the changeable international environment. Based on this background, The EEMD-AWNN model is proposed to predict the current account, including debit and credit. Traditional econometric model can give economic explanation, but it is difficult to adapt to the rapid change of domestic and international economic structure. In addition, the single-variable machine learning algorithm can overcome this problem, but it is not sensitive enough to the external economic variables. Therefore, this paper learns from TEI@I and proposes EEMD-AWNN model to predict the current account. In EEMD-AWNN, the empirical mode decomposition (EEMD) is first used to decompose the variables, and then required exogenous variables are added according to economic significance. Finally, the synthesized adaptive wavelet neural network (AWNN) is used to predict the current account, which obtains higher accuracy and better forecasting performance than econometric models. Based on the proposed model, the results showed that both debit and credit of the current account will grow. However, the debit growth rates of trade in goods and service trade will be higher than their credit growth rate. What's more, the surplus of commodity trade will narrow and travel trade deficit will increase. Therefore, China's current account will continue to run a surplus but the surplus will narrow in next two years. © 2021, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
引用
收藏
页码:1240 / 1251
页数:11
相关论文
共 24 条
[1]  
Tian K L, Yang C H., Analysis of the impact of Sino-European PV trade disputes on the economic profit and loss of both sides, Systems Engineering-Theory & Practice, 36, 7, pp. 1652-1660, (2016)
[2]  
Duan W Q, Liu B Q, Ji J H., The evolution of topological structure of international trade network, Systems Engineering-Theory & Practice, 28, 10, pp. 71-81, (2008)
[3]  
Liu W, Zhang G X., Empirical analysis of FDI and China's current account, Research on Financial Issues, 2, pp. 68-73, (2010)
[4]  
Li X., Research on the change of China's current account balance[D], (2014)
[5]  
Yang WL., A study on the imbalance of China's trade structure-from the perspective of trade balance, Economic Forum, 3, pp. 32-36, (2011)
[6]  
Wang Y R., The application of ARIMA model in the prediction of China's export trade, Decision Reference, 4, pp. 33-34, (2004)
[7]  
Zhang J W, Chen X, Wang S Y., A new spatial weight matrix and its application in China's provincial foreign trade, Systems Engineering-Theory & Practice, 29, 11, pp. 84-91, (2009)
[8]  
Chen J C., The application of GMDH network in the prediction of import and export trade, Information Technology, 8, pp. 199-201, (2014)
[9]  
Chen W., Forecast of import and export trade based on the combination model of linear ARIMA and nonlinear BP neural network, Statistics and Decision Making, 22, pp. 47-49, (2015)
[10]  
Bai S., Prediction algorithm of import and export trade based on PSO optimized hybrid RVM model, Computer and Modernization, 8, pp. 110-118, (2014)