Mealy Penny, Farmer J Doyne, Teytelboym Alexander
Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, Oxford OX2 6ED, UK.
Smith School for Enterprise and the Environment, University of Oxford, Oxford OX1 3LP, UK.
Sci Adv. 2019 Jan 9;5(1):eaau1705. doi: 10.1126/sciadv.aau1705. eCollection 2019 Jan.
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.
两种被称为经济复杂度指数(ECI)和产品复杂度指数(PCI)的网络测度为经济发展模式提供了重要见解。我们表明,ECI和PCI等同于一种将相似性图划分为两部分的谱聚类算法。这些测度还与各种降维方法密切相关,如扩散映射和对应分析。我们的结果为ECI在解释人均国内生产总值和经济增长的跨国差异方面的实证成功提供了新的视角,这种差异通常与国家出口篮子的多样性有关。事实上,ECI高(低)的国家往往专门生产高PCI(低PCI)的产品。我们还发现,ECI和PCI揭示了美国各州和英国各地区的专业化模式。