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\subsubsection{\texorpdfstring{Econophysics}{Econophysics}}
\label{sec:econophysics}


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.

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