Abstract
We apply the recently developed reduced Google matrix algorithm for the analysis of the OECD-WTO World Network of Economic Activities. This approach allows to determine interdependencies and interactions of economy sectors of several countries, including China, Russia and the USA, properly taking into account the influence of all the other world countries and their economic activities. Within this analysis, we also obtain the sensitivity of EU countries’ economies to the petroleum activity sector. We show that this approach takes into account the multiplicity of economical interactions between countries and activity sectors, thus providing a richer analysis compared to the usual export-import analysis.
Highlights
The statistical data of UN COMTRADE [1] and the World Trade Organization (WTO) StatisticalReview 2018 [2] demonstrate all the complexity of the international trade and the economic relations between world countries
The reduced Google matrices GR and GR∗ and their three matrix components for PageRank and CheiRank algorithms with Nr = 21 sectors of USA economy activity (s = 1, ..., 21 in Table 1) are shown in Figures 1 and 2 respectively
We apply the reduced Google matrix (REGOMAX) analysis to the World Network of Economic Activities (WNEA) data in order to determine the interdependence of the economy activity sectors for several countries with the main accent on USA, Russia, and China
Summary
The statistical data of UN COMTRADE [1] and the World Trade Organization (WTO) StatisticalReview 2018 [2] demonstrate all the complexity of the international trade and the economic relations between world countries. Developed advanced mathematical tools are required for the scientific analysis of such complex systems. The PageRank algorithm, developed by Brin and Page in 1998 [8] to retrieve information from the WWW, was at the mathematical foundation of the Google search engine (see e.g., [9]). This algorithm constructs the Google matrix G describing Markov chain transitions between the nodes of the WWW network and allows it to rank billions of web pages of the WWW. The efficient applications of the Google matrix analysis to various directed networks have been demonstrated in [10]
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