Another great place to learn of the history of economics as well as the rise of “complexity economics” is Beinhocker’s The Origin of Wealth discussed here.

One of the main lessons of complexity economics that I suspect won’t be learned this time around by policy makers is that the very act of trusting in incentives and regulation — no matter how complete and “perfect” they are — creates the conditions for the boom-bust dynamic to repeat. The particulars are always different and the more perfect the incentive/regulation scheme is and the more trust we have in it, the bigger the next crisis will be. Noted complexity researcher, Alfred Hubler, draws a strong correlation to forrest fire dynamics.

For this reason, I think Colander’s suggestions regarding peer review and model interpretation are wise. I also agree with the promising approaches outlined in the Notes, especially agent-based modeling *combined* with adaptive network analysis. Closed form analyses of any sort are ipso facto a bad idea: they lead to the misplaced trust referred to above. Moreover, they create the false dichotomy between the endogenous and the exogenous, which is at the heart of why we are always solving the last crisis (instead of avoiding the future one).

The one thing we know for certain is that the next black swan is coming and by definition we can’t predict when and what it will look like. But we can stop acting so surprised when it shows up, and we can make the system more resilient to its effects by accepting this basic truth and building in some heterogeneity both in terms of our ability to perceive the black swan and our ability to respond to it.