Using complex networks to characterize international business cycles.

ABSTRACT:

Background

There is a rapidly expanding literature on the application of complex networks in economics that focused mostly on stock markets. In this paper, we discuss an application of complex networks to study international business cycles.

Methodology/principal findings

We construct complex networks based on GDP data from two data sets on G7 and OECD economies. Besides the well-known correlation-based networks, we also use a specific tool for presenting causality in economics, the Granger causality. We consider different filtering methods to derive the stationary component of the GDP series for each of the countries in the samples. The networks were found to be sensitive to the detrending method. While the correlation networks provide information on comovement between the

SUBMITTER: Caraiani P 

PROVIDER: S-EPMC3587567 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature