Journal of Economic Interaction and Coordination

, Volume 14, Issue 4, pp 835–858 | Cite as

Modeling the impulse response complex network for studying the fluctuation transmission of price indices

  • Qingru Sun
  • Xiangyun GaoEmail author
  • Shaobo Wen
  • Sida Feng
  • Ze Wang
Regular Article


We provide a method for analyzing the transmission of fluctuation among price indices, which combines the complex network method and the impulse response function (IRF). The transmission relationships of price fluctuation among numerous price indices are remarkably complicated, especially under external shocks. In this paper, the empirical data of US, China and Japan are selected as samples, and we analyze the transmission relationships between each two price indices using IRF and construct directed positive and negative impulse response networks of US, China and Japan, respectively. We analyze and compare the price fluctuation transmission characteristics of different countries under external shocks from the aspect of the transmission range, degree, intermediary, clustering and time. The results of the analysis indicate that (1) Positive networks are tighter than negative networks; (2) There is positive correlation between the range and degree of price fluctuation transmission; (3) The intermediation ability of price fluctuation transmission is high; (4) The clustering of networks is different and the transmission probability among clusters are different; (5) The transmission speed of positive networks is faster than that of negative networks. This research could provide some implications for investors in relation to decentralizing investments.


Econophysics Complex network Impulse response function Fluctuation transmission Price index 

JEL Classification

C3 D85 



This research is supported by the Humanities and Social Sciences planning funds project under the Ministry of Education of the PRC (Grant No. 17YJCZH047), Beijing Natural Science Foundation (Grant No. 9174041), the National Natural Science Foundation of China (Grant No. 41871202) and the fund from Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Natural Resources (Grant No. CCA2017.11).

Supplementary material

11403_2018_231_MOESM1_ESM.docx (33 kb)
Supplementary material 1 (DOCX 34 kb)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Economics and ManagementChina University of GeosciencesBeijingChina
  2. 2.Key Laboratory of Carrying Capacity Assessment for Resource and EnvironmentMinistry of Natural ResourcesBeijingChina

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