Central corporate control revealed by mathematics

If you haven't already heard about this new study on the network of corporate control, do have a look. The idea behind it was to use network analysis of who owns whom in the corporate world (established through stock ownership) to tease out centrality of control. New Scientist magazine offers a nice account, which starts as follows:

AS PROTESTS against financial power sweep the world this week, science may have confirmed the protesters' worst fears. An analysis of the relationships between 43,000 transnational corporations has identified a relatively small group of companies, mainly banks, with disproportionate power over the global economy.

The study's assumptions have attracted some criticism, but complex systems analysts contacted by New Scientist say it is a unique effort to untangle control in the global economy. Pushing the analysis further, they say, could help to identify ways of making global capitalism more stable.

The idea that a few bankers control a large chunk of the global economy might not seem like news to New York's Occupy Wall Street movement and protesters elsewhere (see photo). But the study, by a trio of complex systems theorists at the Swiss Federal Institute of Technology in Zurich, is the first to go beyond ideology to empirically identify such a network of power. It combines the mathematics long used to model natural systems with comprehensive corporate data to map ownership among the world's transnational corporations (TNCs).

But also have a look at the web site of the project behind the study, the European project Forecasting Financial Crises, where the authors have tried to clear up several common misinterpretations of just what the study shows.

Indeed, I know the members of this group quite well. They're great scientists and this is a beautiful piece of work. If you know a little about natural complex networks, then the structures found here actually aren't terrifically surprising. However, they are interesting, and it's very important to have the structure documented in detail. Moreover, just because the structure observed here is very common in real world complex networks doesn't mean its something that is good for society.