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Interpreting economic complexity

delete2019-01-04
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OA
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P
Penny Mealy *
J
J. Doyne Farmer
A
Alexander Teytelboym
DOI:10.1126/sciadv.aau1705delete
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摘要

摘要

En 中文
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.
Keyword:
EXPORT DIVERSIFICATION
GROWTH
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期刊

Science Advances 封面图
Science Advances
IF:
12.5
论文数:
2.1W
被引数:
21.3W

机构

U
University of Oxford
学者数:
5.6K
论文数: 2.0K
被引数: 3.0K
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