estimatingmulticountryprosperityindexatwodimensionalsingularspectrumanalysisapproach

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	estimatingmulticountryprosperityindexatwodimensionalsingularspectrumanalysisapproach
	Zhang Jiawei 1; Hassani Hossein 2; Xie Haibin 3; Zhang Xun1
	2014
发表期刊	journalofsystemsscienceandcomplexity
ISSN	1009-6124
卷号	27 期号:1 页码:56
摘要	With the development of the global economy, interaction among different economic entities from one region is intensifying, which makes it significant to consider such interaction when constructing composite index for each country from one region. Recent advances in signal extraction and time series analysis have made such consideration feasible and practical. Singular spectrum analysis (SSA) is a well-developed technique for time series analysis and proven to be a powerful tool for signal extraction. The present study aims to introduce the usage of the SSA technique for multi-country business cycle analysis. The multivariate SSA (MSSA) is employed to construct a model-based composite index and the two dimensional SSA (2D-SSA) is employed to establish the multi-country composite index. Empirical results performed on Chinese economy demonstrate the accuracy and stability of MSSA-based composite index, and the 2D-SSA based composite indices for Asian countries confirm the efficiency of the technique in capturing the interaction among different countries.
语种	英语
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/46400
专题	系统科学研究所
作者单位	1.中国科学院数学与系统科学研究院 2.伯恩茅斯大学 3.对外经济贸易大学
推荐引用方式 GB/T 7714	Zhang Jiawei,Hassani Hossein,Xie Haibin,et al. estimatingmulticountryprosperityindexatwodimensionalsingularspectrumanalysisapproach[J]. journalofsystemsscienceandcomplexity,2014,27(1):56.
APA	Zhang Jiawei,Hassani Hossein,Xie Haibin,&Zhang Xun.(2014).estimatingmulticountryprosperityindexatwodimensionalsingularspectrumanalysisapproach.journalofsystemsscienceandcomplexity,27(1),56.
MLA	Zhang Jiawei,et al."estimatingmulticountryprosperityindexatwodimensionalsingularspectrumanalysisapproach".journalofsystemsscienceandcomplexity 27.1(2014):56.