Database

Export database (goods only)

The reference database in the classical Economic Complexity analysis is the international trade database. We reconcile and regularize it starting from the UN-COMTRADE data. Our database covers the external flows of physical goods between 200+ countries in the World with a very detailed classification, collecting more than 5000 distinct products. 

Available for download

Integrated (goods + services) export database

Published in Nature Scientific Data .  In order to provide a better representation of countries' export profiles, we reconcile two databases: the UN-COMTRADE goods-only export database and IMF BOP data regarding the export of services. The so-called Integrated database includes 160+ countries and a total of 124 sectors, providing the largest set of common nations and sectors available from both the IMF BOP and the 2digits UN-COMTRADE datasets. 

Patent database

Innovation activity of countries, tracked by the publication of patents. The dataset is constructed from a collection of regional patent statistics organized in a coherent and uniform structure, collected from the REGPAT database from the OECD. 

The regional patent counts are organized in matrices that specify the territorial level (TL1 or TL2) and the technology sector (using the three-digit or the four-digit CPC classification). The matrices encode whether a region is relatively more active in a technology class compared to the global average, producing yearly bipartite networks of technological competitiveness. The temporal span of the dataset runs from 1978 to 2017, offering four decades of evidence on the evolution of regional technological capabilities.

Available for download

Science database

The scientific activity of countries, reconstructed from published papers.

The dataset is built from the Open Academic Graph (OAG v2), a large-scale academic database created in 2018 by merging Microsoft Academic Graph and AMiner. It contains publication records across journals, books, conference proceedings, reviews, and other scholarly outputs, together with author affiliations, Fields of Study (FoS), and citation counts, starting from the 60s. Author affiliations are used to map documents to locations, with headquarters assigned when institutions span multiple sites.

The FoS classification provides a hierarchical taxonomy of research domains, including a top layer of 19 major sectors and deeper layers with hundreds to tens of thousands of subfields. For each year, the dataset organizes scientific output in tables reporting both the volume of publications and their accumulated citations at the level of geographic areas and fields. 

From these processed data, we construct annual matrices describing the scientific competitiveness of each geographic area. These binary matrices form the Scientific Bipartite Network (SBN), representing the evolving structure of regional scientific specialization over the period from 1960 to the OAG 2018 snapshot.

Available for download

Fitness database

Starting from the export, technology, and science outputs of countries, we compute an assessment of their complexity by using the Fitness algorithm.

Economic Fitness - download here

Technology Fitness - download here

Scientific Fitness - download here

Green Fitness - download here

Green readiness database

The green readiness is a machine-learning-based evaluation of the export relatedness in renewable energy supply chains and, more generally, the green economy. We measured countries’ readiness for the green transition across five renewable-energy supply chains (wind, solar, hydro, geothermal, biofuel) by introducing a machine-learning metric derived from product-level trade data. 

Available for download

Green fingerprints

The green technology fingerprints of products are the statistically validated links between green technology classes and exported products. Green technologies are identified through the Y02 CPC classification in patent data, while products are identified through the Harmonized System (HS) trade classification.

The links are obtained by looking at the co-occurrence, across countries, of green technological specialisation and product export specialisation, and by validating the resulting associations with suitable statistical null models.

Available for download

GDP predictions database

Economic Fitness is an effective indicator of how good the capability structure of an economic actor is. Despite being quite concise (i.e. it consists of a single number), it provides an accurate estimation of the potential for economic growth, especially when used in combination with more traditional indicators of economic performance such as GDP per capita.  The idea is that the economic dynamics of countries can be modelled as a dynamical system. When used at the country level to describe industrial capabilities, Fitness delivers very accurate forecasts that improve on the accuracy of mainstream approaches by up to 25%.