Quick Note on Complex Systems

In the comment section of this post, Mattheus and I come to exactly opposite conclusions on how to gain knowledge about complex systems (well, not exactly opposite since I see the utility of both a priori and a posteriori knowledge). I start by writing:

"See, I think you turn the issue on its head. If economics were a simple, clean science like math you could use pure a priori. Some mathematicians now use quasi-empirical methods for tougher problems where the issues at hand aren't as clean-cut, but obviously most of it is a priori knowledge. When you get into more complicated phenomena that the human mind simply can't capture, more empiricism is introduced - like in chemistry or physics. The science of truly complex systems: biology, and the study of human society - have to rely even more heavily on empiricism because the processes are just too complex to faithfully render with a priorism."

Mattheus responds:

"If the human mind can’t capture it, then we shouldn’t be bothering with elucidating the truth of its claims. After all, in order to process empiricism, you NEED a theory behind it otherwise you’re just looking at a lot of data with no way to interpret it. And of we can’t understand it at all, then both modalities are worthless and we’ll never come to terms with it.

The better way to understand complex systems is not by directly observing millions of variables interacting in unknown ways, but to understand each component logically. Mises creates his evenly rotating economy as a thought creation – to understand the difference between profit and interest – because he knows that the economy is far too complex to understand at face value."

For me, "complex system" means a system with relatively simple components or constituents that interact to form a very complicated whole. The concept of complexity is very closely related to that of chaos, which should shed some light on my hesitation to rely exclusively on a priorism to understand any complex system. The agents may be simple. Man may act, as Mises says, and we may be able to derive an awful lot from that. In fact, in Mattheus's initial post which I was responding to, he describes what Mises derived from "man acts" as subjective preferences, time preferences, and the division of labor. For all the back and forth over Mises here, I'm not aware of a single economist that challenges these three fundamental characteristics of economic agents. And that's not surprising. In a complex system, agents are relatively simple and probably could be understood just lying on a couch thinking about them. It's not the only way to do it, but a lot of people do economics that way. There are considerably fewer disagreements among microeconomists than macroeconomists. The disagreements that do exist are largely empirical disputes: the magnitude of certain elasticities, etc. This is to be expected, because agent behavior is (relatively) simple.

The problem comes in when those agents start interacting in the complex system that is human society (both the market, the state, and any variety of other institutions). This is where my understanding of what a "complex system" is is important. Relatively simple agents that on their own have predictable behavior can produce alternatively erratic, structured, or evolutionary group behavior. Or they can fall victim to a sudden cascade of collapse. The interaction of billions of simple agents can have complex and unpredictable results that can leave a priorists high and dry simply because we aren't smart enough to think through all the contingencies on our couch.

This isn't to say that theorizing about complex systems is unfruitful by any means. We need to think through the possible contingencies and the possible complex interactions. But you can't expect to be able to report back on how the economy works after a good couch-sit the way that Mises does. At best you've come up with some ideas on how it could work, and even probably how it does work under certain circumstances.

So what does empiricism have to offer? Well, at the very least it can test theories. The nature of complex systems gives us reason to doubt our a priorism, but presumably we can still observe the system to see if our predictions hold true. Mattheus references "millions of variables", asserting the problems with empirical work on complex systems. I'm not quite sure what millions he is referencing. You can look at just a couple variables to see if they behave the way you expected them to behave. The point is it's an iterative process. We have some ideas about how the system as a whole behaves, but the complexity of the system gives us serious doubt about how much faith to put in those ideas. So we look to see which ideas best match up with reality, we look for interesting trends that are left unexplained and then we try to go back to the drawing board and explain them. This is more the scientific method than it is Kant's "pure reason" at this point, but that's ultimately what the problem requires.

The nature of complex systems also speaks to a common critique you hear of macroeconomics, that because they are in such stark disagreement it is somehow bogus science. Russ Roberts calls macroeconomics "ex post story telling". I think this critique is wrong-headed. We know complex systems act in unpredictable ways. They can form spontaneous order and then suddenly collapse. Or they can reorder into something else. Robust systems are best, but you don't always get robustness. Why would you expect one macroeconomic theory to be able to describe all of this. As I've said before, most macroeconomic theories and models are "necessary but not sufficient". The question usually isn't "is this one right?". Often the models are thoughtfully constructed and tested and usually do hold under certain circumstances. The right question is "is it right under this circumstance?". If you think of things in that sense, what you have isn't a self-contradictory science of the macroeconomy. What you have is a fairly insightful science of one of the most complex systems around, but a science where all the scientists are bizarrely combative. Macroeconomics sometimes feels like a cardiologist telling a pulmonologist that pulmonology is "wrong" because their patient died of a heart attack. If doctors explained illness the way economists explained recessions - trying to find a single cause rather than a mix of causes that are more or less important in a given circumstance - our health care system would fall apart. But the point is, the problem isn't with macroeconomics. The problem is with macroeconomists.

Although all those thoughts of mine are based in my understanding of the macroeconomy as a complex system, I'm getting a little far afield and I have to start getting ready for the day. So I want to end with some links.

First, the work of the Santa Fe Institute shaped a lot of how I think about complex systems. They do a lot of interesting work across a lot of fields. Notable economists working at the Institute are Rajiv Sethi (often cited by Krugman and Thoma) and Sam Bowles (spoiler alert because I'm sure it will come up in the comment section - Bowles is a Marxist).

There is a New England Complex Systems Institute as well. I've glanced through their work before but I'm not as familiar with it.

George Mason University has a Center for Social Complexity.

Two books that see the economy as a complex system that I recommend are Paul Krugman's The Self Organizing Economy, and Thomas Schelling's classic Micromotives and Macrobehavior. Of course, Hayek is great for these insights as well, and has done more than most at looking into the mechanisms that organize simple agents into complex systems, namely the uses of knowledge in society. I think it's probably fair to say that Hayek emphasizes the order of these systems, whereas Krugman and Schelling give a hearing to both the order and the disorder (or at least sub-optimality) of complex systems. All three men are Nobel laureates and all are very good.

And finally, here's a complex systems journal.