One of the biggest problems that has plagued economics has been its reliance on a theory that lies at the very core — that of human behavior. As you may surmise, macroeconomic phenomena is the emergent result of micro-interactions between markets, businesses, and ultimately, people. By now, you may have guessed that I’m talking about perfect rationality.
Economists have relied on perfect rationality — and it’s permutation: bounded rationality — since as long as there have been models of the macroeconomy. The reason for that some assumption of forward-looking rationality is required to create a computationally efficient equilibrium model. Of course, even a ten-year old child could demolish the theory of perfect rationality. Here, Arnold Kling makes the case against (popular) modelling of rationality:
I think that my least favorite Sumnerian proposition is that the Fed can affect the economy by announcing a long-term target for a nominal variable. I think that in order for this to work, you have to assume that people are forward-looking and focused on future monetary policy. On the other hand, his mechanism by which monetary policy works is the conventional story in which nominal wages are sticky, so that with higher aggregate demand you get lower real wages and more real output. But for nominal wages to be sticky, workers cannot be forward-looking and focused on monetary policy. So, on the one hand, for targets to matter, people have to be forward-looking. On the other hand, for monetary policy to matter, people cannot be forward-looking. I cannot past what I see as a basic contradiction. For what it’s worth, in case you cannot tell already, I do not think that people are forward-looking. I think that they are habit-driven and backward-looking.
Because I believe that people are habit-driven and backward-looking, I think it is possible for real wages to fluctuate. However, I do not think that real wage movements have been very important in post-war economic fluctuations.
This is important, because Kling is right. Very few people are forward-looking in a way that makes a lot of difference in the macroeconomy. I’ll return to this later. However, this type of theory of human behavior lies at the core of complexity economics. The CE theory states that humans think inductively, have highly-incomplete information, are subject to numerous errors and biases, learn to adapt over time using trial-and-error “deductive tinkering”, and are highly heterogeneous in preferences, and only work to “satisfice” a vague notion of utility.
In reality, many types of economic problems turn out to have no perfectly rational solution at all — in theory or practice. Take the Bar Problem:
A popular bar offers live music on Thursday nights. It is not a large bar, however, so you have a comfortable and pleasant evening if no more than sixty people show up. More than that, and it becomes crowded and uncomfortable. You decide that you wish to go, only if there are fewer than sixty people planning on attending, otherwise you will stay home. Obviously you have no way of communicating with the large mass of potential patrons, and let’s assume that the bar has no interest in giving you an (accurate) average turnout. All potential patrons make their own decision in the same way. Do you go or stay home? How do you decide?
As with many things in life, there is no rational solution. There is an infinite circularity problem — what you do depends on what you expect me to do, which in turn depends on what I expect to you to do, and so on. So how do people make their decisions? Well, they look at their past visits to the bar, try to identify a pattern, and then make their choice. There is a strong path-dependency, where positive and negative experiences are reinforced (and result in a greater probability that you will or will not go to the bar, respectively).
Brian Arthur has run computer simulations* of agents following such “rules of thumb” and has found that the bar never settles into an equilibrium.
Cognitive science has gone a long way in showing that human beings are capable of incredible feats of information processing, but do so in a way that is entirely different than the picture painted by rationality in economic models. Humans are bad at math, but excellent at storying-telling and listening. As it turns out, storytelling and listening are vital to the way we process information: through induction; or reasoning by pattern recognition. Anyone who has watched an episode of CSI or Law and Order has born witness to the depth of skill humans possess to work their way through patterns, remember long-term trends, and adjust behavior quickly to adapt to newly arising informational patterns. There are two ways humans excel at performing these activities:
- Relating new experiences to old patterns through metaphors and analogies. Take a moment to listen to people on the news talk, you’ll hear things like “this is the worst recession since the Great Depression“, or “this reminds me of Seattle”, etc. What is the internet like? Well, there are numerous books trying to define it as “like” or “unlike” television, radio, magazines, etc. Just go back and read about the Dave Wiegel fiasco…
- Second, we are excellent pattern completers. We fill in missing information using a mix between induction (past experience) and deduction (crude probability) to arrive at a conclusions that are “correct enough” (ostensibly to keep us alive!). This was obviously an essential skill in our ancestral environment.
Just take a look at the gambler’s fallacy, or sports “hot streaks”, or people looking at clouds…we see patterns literally everywhere! Of course, this behavior is also has bearing on how power law distributions are formed in economies (and in nature, which is also “satisficing”).
Now, why am I still an AS/AD guy after everything? Well, because it is important to note that there are people who spend a lot of time trying to compute deductively to bring supply and demand in line. In fact, it is likely that supply would never meet demand in the macroeconomy if not for these agents. In financial markets, these “people” are, of course, referred to as “market makers“…but of course virtually all markets are (perhaps unconsciously?) designed around the expectation of disequilibrium…we have inventories, order backlogs, slack production capacity, middlemen, and supply chains to smooth out transactions. Car dealerships, for example, do not have empty lots — but they do have some cars that you will need to be put on a waiting list for….
The interaction of this “market making” activity in the greater economy is what, I believe, keeps some of the more sensible forward-looking theories of money afloat.