CSpace
Foreign Trade Survey Data: Do They Help in Forecasting Exports and Imports?
Bai Yun1,2; Wang Shouyang1,3; Zhang Xun1,3
2022-06-20
发表期刊JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY
ISSN1009-6124
页码24
摘要Business survey, which starts from the microeconomic level, is a widely used short-term forecasting tool in practice. In this study, the authors examine whether foreign trade survey data collected by China's Ministry of Commerce would provide reliable forecasts of China's foreign trade. The research procedure is designed from three perspectives including forecast information test, turning point forecast, and out-of-sample value forecast. First, Granger causality test detects whether survey data lead exports and imports. Second, business cycle analysis, a non-model based method, is performed. The authors construct composite indexes with business survey data to forecast turning points of foreign trade. Third, model-based numerical forecasting methods, including the Autoregressive Integrated Moving Average Model with Exogenous Variables (ARIMAX) and the artificial neural networks (ANNs) models are estimated. Empirical results show that survey data granger cause imports and exports, the leading composite index provides signal for changes of trade cycles, and quantitative models including survey data generate more accurate forecasts than benchmark models. It is concluded that trade survey data has excellent predictive capabilities for imports and exports, which can offer some priorities for government policy-making and enterprise decision making.
关键词ARIMAX artificial neural network composite index forecasting foreign trade Granger causality test survey data
DOI10.1007/s11424-022-1015-x
收录类别SCI
语种英语
资助项目National Natural Science Foundation of China[71422015] ; National Natural Science Foundation of China[71988101] ; National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences
WOS研究方向Mathematics
WOS类目Mathematics, Interdisciplinary Applications
WOS记录号WOS:000813601100006
出版者SPRINGER HEIDELBERG
引用统计
文献类型期刊论文
条目标识符http://ir.amss.ac.cn/handle/2S8OKBNM/61212
专题中国科学院数学与系统科学研究院
通讯作者Bai Yun
作者单位1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Ctr Forecasting Sci, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Bai Yun,Wang Shouyang,Zhang Xun. Foreign Trade Survey Data: Do They Help in Forecasting Exports and Imports?[J]. JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY,2022:24.
APA Bai Yun,Wang Shouyang,&Zhang Xun.(2022).Foreign Trade Survey Data: Do They Help in Forecasting Exports and Imports?.JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY,24.
MLA Bai Yun,et al."Foreign Trade Survey Data: Do They Help in Forecasting Exports and Imports?".JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY (2022):24.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Bai Yun]的文章
[Wang Shouyang]的文章
[Zhang Xun]的文章
百度学术
百度学术中相似的文章
[Bai Yun]的文章
[Wang Shouyang]的文章
[Zhang Xun]的文章
必应学术
必应学术中相似的文章
[Bai Yun]的文章
[Wang Shouyang]的文章
[Zhang Xun]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。