Economic Complexity Index
The Economic Complexity Index (ECI) is a holistic measure of the productive capabilities of large economic systems, usually cities, regions, or countries. In particular, the ECI looks to explain the knowledge accumulated in a population and that is expressed in the economic activities present in a city, country, or region. To achieve this goal, the ECI defines the knowledge available in a location, as the average knowledge of the activities present in it, and the knowledge of an activity as the average knowledge of the places where that economic activity is conducted. The product equivalent of the Economic Complexity Index is the Product Complexity Index or PCI.
The ECI was developed by Cesar A. Hidalgo, from the MIT Media Lab and Ricardo Hausmann, from Harvard University's Kennedy School of Government. ECI data is available in The Observatory of Economic Complexity. The original formulation of the Economic Complexity Index was published in PNAS in 2009.
In its strict mathematical definition, the ECI is defined in terms of an eigenvector of a matrix connecting countries to countries, which is a projection of the matrix connecting countries to the products they export. Since the ECI considers information on the diversity of countries and the ubiquity of products, it is able to produce a measure of economic complexity containing information about both the diversity of a country's export and their sophistication. For example, Japan or Germany, with high ECIs, export many goods that are of low ubiquity and that are produced by highly diversified countries, indicating that these are diverse and sophisticated economies. Countries with low ECI, like Angola or Zambia, export only a few products, which are of relatively high ubiquity and which are exported by countries that are not necessarily very diversified, indicating that these are countries that have little diversity and that the products that they export are not very sophisticated.
Hidalgo and Hausmann propose the concept of ECI not only as a descriptive measure, but also as a predictive tool for economic growth and income inequality. According to the statistics models presented in their Atlas of Economic Complexity (2011), the ECI is a more accurate predictor of GDP per capita growth than traditional measures of governance, competitiveness (World Economic Forum's Global Competitiveness Index) and human capital (as measured in terms of educational attainment). ECI also shows a strong negative correlation with income inequality, suggesting that more knowledge intense productive structures are more inclusive in terms of income distribution, and providing a statistically more powerful explanation of cross-national variations in income inequality than Kuznets Curve.
- Cesar A. Hidalgo, Ricardo Hausmann (2009). "The Building Blocks of Economic Complexity". Proceedings of the National Academy of Sciences. PNAS. 106 (26): 10570–10575. arXiv:0909.3890. Bibcode:2009PNAS..10610570H. doi:10.1073/pnas.0900943106. PMC 2705545. PMID 19549871.
- Ricardo Hausmann, Cesar Hidalgo; et al. "The Atlas of Economic Complexity". Puritan Press, Cambridge MA. Archived from the original on 18 May 2012. Retrieved 26 April 2012.
- Dominik Hartmann, Miguel Guevara, Cristian Jara-Figueroa, Manuel Aristaran, Cesar Hidalgo (2018), "Linking Economic Complexity, Institutions, and Income Inequality", World Development, 93: 75–93, arXiv:1505.07907, doi:10.1016/j.worlddev.2016.12.020CS1 maint: multiple names: authors list (link)
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