Hierarchicality of Trade Flow Networks Reveals Complexity of Products

TL;DR

This paper uses ecological flow analysis to examine global trade networks, revealing that products with higher added value and complexity have more hierarchical trade flow structures, which can be identified solely from trade data.

Contribution

It introduces a novel application of ecological flow analysis to classify trade networks by complexity using the allometric scaling exponent.

Findings

Higher allometric exponents correlate with more complex, hierarchical trade networks.

Trade networks of high-value products like machinery are more hierarchical.

Product complexity and country importance can be inferred from network structure alone.

Abstract

With globalization, countries are more connected than before by trading flows, which currently amount to at least 36 trillion dollars. Interestingly, approximately 30-60 percent of global exports consist of intermediate products. Therefore, the trade flow network of a particular product with high added values can be regarded as a value chain. The problem is weather we can discriminate between these products based on their unique flow network structure. This paper applies the flow analysis method developed in ecology to 638 trading flow networks of different products. We claim that the allometric scaling exponent $\eta$ can be used to characterize the degree of hierarchicality of a flow network, i.e., whether the trading products flow on long hierarchical chains. Then, the flow networks of products with higher added values and complexity, such as machinery&transport equipment with larger exponents, are highlighted. These higher values indicate that their trade flow networks are more hierarchical. As a result, without extra data such as global input-output table, we can identify the product categories with higher complexity and the relative importance of a country in the global value chain solely by the trading network.