Interpreting economic complexity

Penny Mealy, J. Doyne Farmer, Alexander Teytelboym

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Abstract

Two network measures known as the economic complexity index (ECI) and product complexity index (PCI) have provided important insights into patterns of economic development. We show that the ECI and PCI are equivalent to a spectral clustering algorithm that partitions a similarity graph into two parts. The measures are also closely related to various dimensionality reduction methods, such as diffusion maps and correspondence analysis. Our results shed new light on the ECI's empirical success in explaining cross-country differences in gross domestic product per capita and economic growth, which is often linked to the diversity of country export baskets. In fact, countries with high (low) ECI tend to specialize in high-PCI (low-PCI) products. We also find that the ECI and PCI uncover specialization patterns across U.S. states and U.K. regions.

Original languageEnglish
Article numbereaau1705
Number of pages8
JournalScience Advances
Volume5
Issue number1
DOIs
Publication statusPublished - 9 Jan 2019
Externally publishedYes

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