No, it’s not another review of Colander and Kupers (but I wonder what he would think of it). He writes,
One feature of complexity economics is that recessions can be caused not merely by shocks but rather by interactions between companies. Tens of thousands of firms fail every year. Mostly, these failures don’t have macroeconomic significance. But sometimes – as with the Fukushima nuclear power plant or Lehman Brothers – they do. Why the difference? A big part of the answer lies in networks. If a firm is a hub in a tight network, its collapse will cause a fall in output elsewhere. If, however, the network is loose, this will not happen; the loss of the firm is not so critical. Daron Acemoglu has formalized this in an important paper, and there are some good surveys of network economics in the latest JEP.
Read the whole thing. Pointer from Mark Thoma. My thoughts:
1. From a PSST perspective, the importance of a highly-connected firm makes sense. The more connected a firm is, the more patterns of specialization and trade depend on that firm. Also, this may help to explain why shocks in the economy do not average out. A shock that suddenly destroys a highly-connected firm is not going to simultaneously create an equal a highly-connected firm somewhere else. My guess is that dense networks of connection are both difficult to create and difficult to destroy, but they can be destroyed more rapidly than they can be created.
2. Note that complexity economics attracts some attention from heterodox economists on both the left and the right.
3. Dillow thinks that complexity economics deserves more attention. I agree that one reason it tends to be overlooked is that it does not provide the clarity of prediction and tidyness of results that is sought by mainstream economists.
4. Mainstream economists and complexity economists would agree that the world is complex and that models are simplifications. Mainstream economists emphasize the virtues of simple models, while heterodox economists emphasize the vices.
4. Is there a simple way to mathematize PSST? Otherwise I figure mainstream economics will absorb the heterodox bit by bit because you can’t have an academic research program become dominant that depends upon critiquing the dominant form from the sidelines.
You could argue that the reason we don’t have more complexity models is due to computing power. You have to do an ‘agents-based’ / particle model that takes a strong processor or even supercomputer to yield useful results. Back in the 80s, and even today, it’s easier to adopt a ‘representative agent’ and work top down, rather than bottom up with interacting agents. The Rational Expectation crowd is simply hemmed in by lack of a discrete model due to lack of computing power, so they chose a top-down closed form solution and/or ‘fudge factors’ like “Confidence fairy” (you can explain anything by varying your fudge factors, Keynes did the same thing too).