The International Postal Network and Other Global Flows As Proxies for National Wellbeing

TL;DR

This study explores how physical and digital flow networks, including the novel international postal network, can serve as proxies for assessing countries' socioeconomic status and wellbeing.

Contribution

It introduces a multiplex network approach combining six international flow networks to infer socioeconomic indicators and analyze global community structures.

Findings

Network positions correlate with GDP per capita and HDI.

A global connectivity measure effectively proxies national wellbeing.

Community analysis reveals countries with similar socioeconomic profiles share network communities.

Abstract

The digital exhaust left by flows of physical and digital commodities provides a rich measure of the nature, strength and significance of relationships between countries in the global network. With this work, we examine how these traces and the network structure can reveal the socioeconomic profile of different countries. We take into account multiple international networks of physical and digital flows, including the previously unexplored international postal network. By measuring the position of each country in the Trade, Postal, Migration, International Flights, IP and Digital Communications networks, we are able to build proxies for a number of crucial socioeconomic indicators such as GDP per capita and the Human Development Index ranking along with twelve other indicators used as benchmarks of national wellbeing by the United Nations and other international organisations. In this context, we have also proposed and evaluated a global connectivity degree measure applying multiplex theory across the six networks that accounts for the strength of relationships between countries. We conclude with a multiplex community analysis of the global flow networks, showing how countries with shared community membership over multiple networks have similar socioeconomic profiles. Combining multiple flow data sources into global multiplex networks can help understand the forces which drive economic activity on a global level. Such an ability to infer proxy indicators in a context of incomplete information is extremely timely in light of recent discussions on measurement of indicators relevant to the Sustainable Development Goals.