Complexity economics is basically the application of complexity science to economics. It sees economics not as a system in equilibrium but one that is under constant construction.
Measures used in Complexity Economics
“Economic complexity index
Harvard economist Ricardo Hausmann and MIT physicist Cesar A. Hidalgo introduced a spectral method to measure the complexity of a country’s economy by inferring it from the structure of the network connecting countries to the products that they export. The measure combines information of a country’s diversity, which is positively correlated with a country’s productive knowledge, with measures of a product ubiquity (number of countries that produce or export the product). This concept, known as the “Product Space”, has been further developed by MIT’s Observatory of Economic Complexity, and in The Atlas of Economic Complexity in 2011.
The economic complexity index (ECI) introduced by Hausmann and Hidalgo is highly predictive of future GDP per capita growth. In Hausmann, Hidalgo et al., the authors show that the List of countries by future GDP (based on ECI) estimates ability of the ECI to predict future GDP per capita growth is between 5 times and 20 times larger than the World Bank’s measure of governance, the World Economic Forum’s (WEF) Global Competitiveness Index (GCI) and standard measures of human capital, such as years of schooling and cognitive ability.
Metrics for country fitness and product complexity
Pietronero and collaborators have recently proposed a different approach. These metrics are defined as the fixed point of the non-linear iterative map. Differently, from the linear algorithm giving rise to the ECI, this non-linearity is a key point to properly deal with the nested structure of the data. The authors of this alternative formula claim it has several advantages:
- Consistency with the empirical evidence from the export country-product matrix that diversification plays a crucial role in the assessment of the competitiveness of countries. The metrics for countries proposed by Pietronero is indeed extensive with respect to the number of products.
- Non-linear coupling between fitness and complexity required by the nested structure of the country-product matrix. The nested structure implies that the information on the complexity of a product must be bounded by the producers with the lowest fitness.
- Broad and Pareto-like distribution of the metrics.
- Each iteration of the method refines information, does not change the meaning of the iterated variables and does not shrink information.
The metrics for country fitness and product complexity have been used in a report of the Boston Consulting Group on Sweden growth and development perspectives.” Source: https://en.wikipedia.org/wiki/Complexity_economics