Why markets fail
George Soros makes the case for economics as a social science using his theory of reflexivity. Below are some thoughts on the issue that lead one to understanding why markets fail.
George Soros penned a must-read piece at Politico that is an important contribution to our thinking about the cause of the credit crisis and necessary remedies. He writes:
In my theory of reflexivity I assert that the thinking of economic agents serves two functions. On the one hand, they try to understand reality; that is the cognitive function. On the other, they try to make an impact on the situation. That is the participating, or manipulative, function.
The two functions connect reality and the participants’ perception of reality in opposite directions. As long as the two functions work independently of each other they produce determinate results. When they operate simultaneously they interfere with each other. That is the case not only in the financial markets but also in many other social situations.
I call the interference reflexivity. Reflexivity introduces an element of unquantifiable uncertainty into both the participants’ understanding and the actual course of events.
This two-way connection works as a feedback loop. The feedback is either positive or negative. Positive feedback reinforces both the prevailing trend and the prevailing bias — and leads to a mispricing of financial assets. Negative feedback corrects the bias. At one extreme lies equilibrium, at the other are the financial “bubbles.” These occur when the mispricing goes too far and becomes unsustainable — boom is then followed by bust.
In the real world, positive and negative feedback are intermingled and the two extremes are rarely, if ever, reached. Thus the equilibrium postulated by the efficient market hypothesis turns out to be an extreme — with little relevance to reality.
Frank Knight was the first to identify the unquantifiable uncertainty inherent in financial markets. John Maynard Keynes and his followers elaborated his insight.
Classical economists, by contrast, sought to eliminate the uncertainty connected with reflexivity from their subject matter.
I suggest you read the whole piece. Here are my thoughts on what Soros had to say.
In American universities, areas of study are often delineated along broad subject lines: the humanities, the social sciences and the sciences. I think this is a pretty good way of thinking about the distinctions in a student’s area of focus. On the one hand, you have subjects like English and Art History that are purely about the human condition "using methods that are primarily analytical, critical, or speculative" as Wikipedia says. On the other hand you have subjects like Biology and Physics which are all about studying the world and universe around us, bound by strict rules, and investigated using the scientific method. In between there are the social sciences, "which use a scientific method to study human behavior and society". That’s where economics lies.
Unfortunately however, there has been a trend in economics toward greater and greater mathematical complexity as if this abstraction only adds value, as if economics were a natural science. The introduction of mathematical complexity has certainly added rigour to economic analysis. Paul Samuelson is the economist most celebrated for bringing more rigorous analysis using mathematical equations into economics. Justin Fox’s book "The Myth of the Rational Market" has a good historical narrative on this, which could be summed up by Ed Glaeser’s comments on Samuelson’s recent passing:
it was Samuelson who gave economists our toolbox — the mathematical methods that define our field — and the magnitude of that gift made him an indispensible economist.
The drawback, however, is that the numbers strip away the role of uncertainty that emanates from the inherent unpredictability of social psychology and the reflexivity that comes from living with and among others in society, sharing thoughts and ideas. That role of uncertainty is central to all social sciences and is exactly what distinguishes those subjects from the natural sciences that are bound by strict rules and laws.
Economists err in not appreciating how large a role this uncertainty plays in generating reflexivity. The reliance on the certainty of mathematical modelling underpinned by the bell curves of the natural sciences and an ideology of rational expectations that strips away the role of emotions and irrationality in human psychology has been a major contributor to the credit crisis.
At the height of the crisis in October 2008 testimony before Congress, Greenspan famously said:
Well, remember that what an ideology is, is a conceptual framework with the way people deal with reality. Everyone has one. You have to — to exist, you need an ideology. The question is whether it is accurate or not.
And what I’m saying to you is, yes, I found a flaw. I don’t know how significant or permanent it is, but I’ve been very distressed by that fact.
I have a conceptual framework too. And it is quite different from the one Alan Greenspan has worked with, involving power laws and reflexivity. I have been meaning to write about this in greater detail. But the gist of it goes back to something I wrote at this time last year regarding bubbles:
[Jeremy] Grantham defines a bubble as a 40-year event. If he knows the price and volatility of an asset, he can work out what a 40-year event is.
My informal working definition for a bubble is a price rise that is at least two standard deviations above trend. My assumption is that prices never follow a random walk. Rather prices are influenced little enough by past price movements below two standard deviations that a Gaussian bell curve is a good approximation of price data.
Above two-standard deviations the psychology of prior price movements starts to dominate price activity and a bubble forms in which power law characteristics come into play.
The psychology of prior price movements can dominate price activity because humans are social animals. When prices go up 5%, you could consider the actions of market participants random because the motivations and psychology of buyers and sellers cancel each other out. However, when prices go up 50%, this is no longer true. It is very important whether my neighbour is making a killing in the housing market or in Internet stocks. That is exactly how bubbles form. And the same is also true on the downside, the principal reason markets that crash tend to overshoot to the downside.
What this means is that future price movements are normally independent of prior price movements. If a stock is down 5%, future prices will largely follow a random walk. Future price movements will appear to be independent of prior price movements. But when we get to that critical state, what I believe is about two standard deviations above trend, the reflexivity of social psychology dominates future price movements. That is what bubbles, manias and crashes are all about. When you hear people talking about ‘fat tails‘, this is the phenomenon at work.
In principal, everyone knows this. All you need to do is look around you and witness the events over the past quarter century to understand the psychology behind these events. But economic modelling strips this out by assuming no reflexivity. When markets reach the critical state, this assumption is catastrophically wrong. That’s why markets fail. If we can understand the centrality of social psychology and reflexivity to crises, we might be able to formulate better policy to prevent or at least mitigate them in the future.