Network analysis of correlation strength between the most developed countries

TL;DR

This paper introduces a novel network analysis algorithm based on power law classification and percolation threshold to study correlations among the GDP per capita time series of the world's most developed countries, revealing key insights into economic convergence and stability.

Contribution

It presents a new correlation analysis algorithm combining PLCS and NPT, applied to economic data, providing a novel approach to understanding economic relationships.

Findings

Identified key countries with strong correlation and convergence.

Compared correlation network with ultrametric distance matrix.

Analyzed stability of correlations over different periods.

Abstract

A new algorithm of the analysis of correlation among economy time series is proposed. The algorithm is based on the power law classification scheme (PLCS) followed by the analysis of the network on the percolation threshold (NPT). The algorithm was applied to the analysis of correlations among GDP per capita time series of 19 most developed countries in the periods (1982, 2011), (1992, 2011) and (2002, 2011). The representative countries with respect to strength of correlation, convergence of time series and stability of correlation are distinguished. The results are compared with ultrametric distance matrix analysed by NPT.