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Economic DNA Explorer (Data, Networks, Analysis)

Economic DNA Explorer (Data, Networks, Analysis) was developed using data from the Asian Development Bank’s 2023 Multiregional "Input-Output" table. It represents a matrix of inter-industry flows at both national and cross-country levels, containing GDP data by both the production (industries) and final consumption methods.

The table contains more than 7.5 million entries for 72 countries, 35 sections of economy.

For a deeper analysis of the global economy, structural indicators were complemented by the following more comprehensive indicators:

  1. output multipliers

  2. countries’ specialisation in industries

  3. economic complexity indices of countries (ECI) and industries (ICI)

  4. intersectoral and intercountry relationships (the concept of spaces).

 

Output multiplier

The dashboard uses the output multiplier (hereinafter referred to as the multiplier), calculated according to W. Leontief’s classical methodology, which reflects the total increase in output in the economy resulting from increases in a particular industry.

 

Specialisation

The Balassa index (RCA) was used to assess specialisation. It is calculated by adjusting the share of a country or industry (amount of production in our case) by its weight in the world. An index greater than 1 means that the country or industry’s performance exceeds its “fair share” in the world, indicating a specialisation.

Complexity

The complexity indicators (ECI and ICI) were calculated using the "Atlas of Economic Complexity" methodology, developed by C. Hidalgo et al. (2011). Compared to the classical method of assessing the economy, based on separate structural analysis of objects, this approach is based on "collective learning" and considers the indicators of “diversity” and "ubiquity" of industries.

 

Cross-country and cross-industry relationships

The analysis of interrelations is based on matrices of country (or industry) proximity coefficients by RCA. Their graphical representation in the form of networks is used for visualisation. They consist of “nodes” (circles) denoting countries or industries, and "edges" (lines) denoting the most significant links between them.

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