Entropy-Based Analysis and Bioinformatics-Inspired Integration of Global Economic Information Transfer

Jinkyu Kim, Gunn Kim, Sungbae An, Young Kyun Kwon, Sungroh Yoon

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

The assessment of information transfer in the global economic network helps to understand the current environment and the outlook of an economy. Most approaches on global networks extract information transfer based mainly on a single variable. This paper establishes an entirely new bioinformatics-inspired approach to integrating information transfer derived from multiple variables and develops an international economic network accordingly. In the proposed methodology, we first construct the transfer entropies (TEs) between various intra- and inter-country pairs of economic time series variables, test their significances, and then use a weighted sum approach to aggregate information captured in each TE. Through a simulation study, the new method is shown to deliver better information integration compared to existing integration methods in that it can be applied even when intra-country variables are correlated. Empirical investigation with the real world data reveals that Western countries are more influential in the global economic network and that Japan has become less influential following the Asian currency crisis.

Original languageEnglish
Article numbere51986
JournalPloS one
Volume8
Issue number1
DOIs
Publication statusPublished - 2013 Jan 2
Externally publishedYes

ASJC Scopus subject areas

  • General

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