Deepening interdependence in global financial networks

Pdfout gif 504×504 pixels

International Political Economy blog writing out of the University of North Carolina has a post up displaying an animated version of this very cool network graphic. These are quarterly observations.

I don’t quite understand the model yet, but I am trying to.

Make sure to take a look at the animated gif. It really brings their point home. A great visualization to help us understand what happened in the industry in just a few short years.

3 thoughts on “Deepening interdependence in global financial networks

  1. in the post they explain how they did it and provide a link to the dataset.
    part of the backstory is they show they got some of the code from kieran healy’s post that was a itself a reply to one of my posts asking for help graphing my radio data. funny to think that you can use the same code to explain the international banking system as to explain the popularity of “My Humps.”

  2. I downloaded the paper…usually I wait to post on something until I have read the manuscript and can explain it to non-technies (a lot of younger students read the blog), but the animation got me sooooo excited I haven’t read it yet.

  3. Thanks for showing interest. The paper is still very much a working version — we just distributed it for the first time last week — and parts of it are inside baseball for those working in IPE. (We think it has some fairly wide-ranging conceptual applications, but we’re mostly speaking to folks working in our discipline.)

    The gist of the model is that it isn’t *just* the level of integration in the system that’s important, but how that integration is distributed. Understanding that distribution is a prerequisite for making inferences about the system. The time series in the gif shows that as total integration went up, so did the inequality in the system. Specifically, it shows the increasing importance of the US and UK over the past decade. In the paper we also plot some degree distribution time series that make this even more clear. One implication of this is that a highly unequal system is relatively robust to shocks in the periphery (Argentina 1999-2002) but very fragile to shocks in the core (US subprime 2008-). This isn’t exactly a new insight in terms of network theory, but hasn’t really been applied to international politics and economics in this way before.

    We’d be very interested in comments/suggestions on how to improve the paper if you have any. And if you have any questions post them here or at our place and I’ll try to answer them.

    Gabriel, just goes to show that the power of My Humps is endless. ; ) Thanks for getting Kieran to put that code up.

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