A lot of attention has been put on “too big to fail,” the idea that big is risky. What really matters in a complex network system, however, is not bigness per se but connection centrality. In a network the liabilities of institution A become the assets of institution B whose own liabilities become the assets of institution C. An institution with high connection centrality can spread distress throughout a large portion of the network.

Inspired by Google’s PageRank, the authors of a new paper create DebtRank, a measure of connection centrality. The vertical axis in the following diagram shows DebtRank (centrality) the horizontal axis asset shows size relative to the total network and the color indicates fragility/leverage. Institutions such as Wachovia, RBS and Barclays were relatively small but because of their centrality and fragility they imposed big risks on the system.

You can find the paper here but do check out the web page of the author group which includes much more material including these animations. Mark Buchanan over at Bloomberg also offers useful comment.

One point to note is that the authors calculated centrality using ex-post data from the Fed. Using this measure, DebtRank clearly signaled danger prior to the crisis and did so earlier than other metrics. In order to do this in real time, however, much more transparent and timely data would be necessary. The fact that centrality doesn’t correlate all that well with bigness, however, indicates that without this data the problem of monitoring risk is even more difficult than it appears.