Trade

The flow of goods and services between geographic regions in an economic system is enabled by supply chains. Supply chains are composed of buyers and suppliers of goods and services interacting with each other to meet the consumption needs or final demand for all products within an economy. When mapped for the entire economy and geographic locations of a country, supply chains form a spatial network of interactions among suppliers and buyers. They are typically characterized by a high connectivity due to trade and complex interdependencies among different economic sectors.

The Google matrix analysis of the world trade network (WTN) allows to probe the direct and indirect trade exchange dependencies between countries (see e.g. [1]). Unlike the simple accounting view obtained from the usual import export balance, relying on the total volumes of exchanged commodities between countries, the PageRank-CheiRank trade balance (PCTB) allows to take account of the long range inter-dependencies between world economies. We present a WTN crisis contagion model [2, 3] built upon the iterative measure of the PCTB for each country.

International trade is based on a set of complex relationships between different countries that can be modelled as a dense network of interconnected agents. A long-standing problem in this field is the detection of communities, as it reveals how the network is internally organized, highlighting the presence of special relationships between nodes, that might not be revealed by direct empirical analyses.

We connect the corporate ownership network to the network of financial instruments that inject money into the ownership network. The ownership network in our data consists of 66 million nodes (i.e., companies and their shareholders) and over 90 million ownership links among them. The previous studies on the network of corporate ownership and control emphasize the importance of roles played by banks and other financial institutions in the network [1-4].