In last weekend’s Thoughts from the Frontline, I talked about how the economics profession in general and central bankers in particular have consistently failed with their economic projections, and I pointed to the need to deepen our understanding of complex systems behavior. I said that we need to marry complex systems theory and information theory in order to establish a new basis for analyzing the economy and creating economic policy.
I couldn’t have been happier, then, when the new issue of Michael Lewitt’s The Credit Strategist popped into my inbox this morning and I found him addressing the same issue. Michael leads off with a discussion of the views of William White, formerly with the Bank for International Settlements (BIS) and now chairman of the Economic and Development Review Committee at the OECD in Paris. (He also spoke at our Strategic Investment Conference last year.)
White, too, has argued that “the fundamental analytical mistake has been to model the economy as an understandable and controllable machine rather than as a complex, adaptive system,” and Lewitt certainly concurs.
OK, so we all agree. But I have to confess, I wasn’t quite satisfied with my own attempt last week to point to a new path forward for economics. It’s one thing to say the economy is complex and nonlinear and another to translate that fundamental understanding into actionable analysis. And in today’s Outside the Box, I find both Lewitt and White struggling similarly.
Consider these sentences from Lewitt, for instance:
The failure to recognize markets as complex systems led policymakers to adopt the wrong approach to healing the global economy after the crisis. Giving credence to the adage that a hammer views every problem like a nail, they clung to the misguided belief that “growth and job creation deemed to be inadequate are solely due to inadequate demand and that this can always be remedied with expansionary monetary policy.”
Notice how he has immediately jumped from his prescription for complex systems thinking to an entirely mundane statement about the failings of Keynesian economics. You may have found me copping out the same way last weekend! Lewitt does this more than once. Here’s another example:
Understanding what to look for requires the proper intellectual frame of reference, which Mr. White correctly argues requires an understanding of complex systems, which require digital not analogue and non-linear rather than linear thinking. The global economy lacks a common anchor of value, leading the value of all financial instruments to be based on a structure of reference rather than relation; in other words, assets are valued based not on their inherent characteristics but on their relative worth compared to other assets.
Well, in the first place, what the heck does it mean to engage in “digital not analogue” thinking? How exactly is digital thinking more nonlinear or better aligned with complexity? What I suspect is going on here is that all of us – Lewitt, White, me, and many others – are just beginning to come to terms with this complexity business. We start to talk about it, and then two seconds later we’re using same tired old economics language we have used for decades. It’s the only language we have! Complexity economics, at this stage, is just very fancy algorithms in very fast computers; it’s not something we can fruitfully chew over and do anything with in our daily work as analysts and investors.