Economics Must Reflect Complexity

Posted by Alex in Complexity, Economics on September 15th, 2009 | View Comments

A wonderful historic analysis of economics (as a struggling social science) giving a huge shoutout to complexity:

“This recognition that the economy is complex is not a new discovery. Earlier economists, such as John Stuart Mill, recognized the economy’s complexity and were very modest in their claims about the usefulness of their models. They carefully presented their models as aids to a broader informed common sense. They built this modesty into their policy advice and told policy makers that the most we can expect from models is half-truths.”

 Unfortunately the more productive part of the post went into the notes:

“NOTES
[1] Some approaches working outside this Walrasian general equilibrium framework that I see as promising includes approaches using adaptive network analysis, agent based modeling, random graph theory, ultrametrics, combinatorial stochastic processes, cointegrated vector autoregression, and the general study of non-linear dynamic models.”

It’s definitely worth a read.

Related posts:

  1. Complexity Economics
  2. The Quandaries of Quantifying Complexity
  3. “Social Entrepreneurship has Complexity Written All Over It”
  4. Complex Systems Symposium
  5. Stability Through Instability

  • Rafe Furst
    BTW, if you replace the word "economy" with "cancer" in Colander's testimony, it reads surprisingly accurately :-)
  • Rafe Furst
    I agree, fantastic analysis and I'm really glad this was part of the testimony before Congress. Also part of it was Taleb (of Black Swan fame) as seen here.

    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.
  • Alex Golubev
    ABM looks promising for exposing assymetry, feedback, and dangers of leverage which plague the current systems. Not that our system is that bad.
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