After posting my original entry I thought about whether there might be areas of economics in which physicists would be able to contribute quickly and it occurred to me that perhaps finance – particularly high-frequency trading – might be such an area. Here lots of trades and market patterns might be governed by the technology of trading and could present an environment in which the skills of physicists are particularly valuable. So I was pleased to see that Mark seems to also focus on finance as an area where physicists have found a grip.
He mentions one particular area – distributions of random variables that have “fat tails” – which has specific value in modern economics. Several researchers are using such distributions to analyze economic phenomena. Xavier Gabaix has used power laws to study “granular” business cycles – the idea that random shocks which affect large players might have substantial consequences for the aggregate economy. Robert Barro, Francois Gourio, and others consider the possibility that such distributions place weight on extreme outcomes which in turn influence asset pricing (asset pricing implications of rare disasters). Trade theories, models of urban (spatial) formation, etc. use power laws. If physicists are actually the source of some of the background on fat-tailed distributions then kudos– that’s a point for physicists in economics.
Mark’s post also presents an example of what you might call ‘Deepak Chopra’ mode. This occurs when a writer (or speaker) talks about an issue which is complicated but then takes the opportunity to start hurling around complicated-sounding ideas and jargon with at best tangential relevance to the topic and at worst no relevance to the topic whatsoever. (Deepak Chopra is known to start talking about quantum healing and other new-age concepts that have the word “quantum” attached to them …). Here is Mark veering dangerously close to Deepak Chopra territory:
What the physicists DO believe, however, is that markets and economies are great examples of what scientists have come to call “complex systems” — systems of many elements (people, firms, etc.) with strong interactions between those elements which create webs of non-linear feedback. The elements learn and adapt, their interactions create “emergent” coherent structures and fluctuations at the collective level, and these structures then act back downwards to influence the behavior of the elements.
He quotes a similar sentiment from the essay by Brian Arthur:
It is this recursive loop that connects with complexity. Complexity is not a theory but a movement in the sciences that studies how the interacting elements in a system create overall patterns, and how these overall patterns in turn cause the interacting elements to change or adapt. … Complexity is about formation—the formation of structures—and how this formation affects the objects causing it.
(… and this is why we need physicists?)
OK, the economy is “complex”. There are many players on the stage and they take a variety of actions which together contribute to the aggregate behavior of the economic system. In turn, aggregate outcomes influence individual behavior. This simultaneity is indeed one feature that makes analyzing the economy so difficult. The thing is, this type of two-way feedback is what economists are doing already. We often reduce environments like this to “fixed point problems” – the players take the market conditions as given when they make their decisions and in turn, these decisions generate the perceived market conditions. In fact, we often prove that equilibria exist by appealing to mathematical “fixed point theorems” for exactly this reason. You might think that this rules out learning and adaptation to an environment. It doesn’t. Economists have been analyzing environments with learning for decades. Learning does make things a bit more difficult. In learning models, the market participants start with some subjective beliefs upon which they base their actions. These actions lead to market outcomes and beliefs are refined. The interplay between beliefs, actions and outcomes is analyzed simultaneously (and it plays out over time). A bit more difficult, yes. But not an insurmountable obstacle for the field.
If economists already do this stuff, why do smart outside observers like Mark Buchanan think we do not? Why are we being lobbied by physicists like Eric Weinstein to adopt techniques which are of such speculative value? My guess is that techno-heterodox ideas (Technodox economics?) like gauge theory, agent based models, chaos (or complexity) theory are advocated in the hope that it might either (1) provide outsiders with some authority even though they don’t really know much about the field and (2) because most practicing economists will have to admit (if they are honest) that they know essentially nothing about these techniques – an admission which could deprive them of some authority even though they do know quite a bit about the economy.
Incidentally, the jargon which comes along with a lot of these Technodox ideas allows even those who don’t understand these speculative techniques to masquerade as though they do understand them. Jargon is a very problematic part of academia. Often academic jargon is particularly imprecise on top of the fact that it allows the speaker to try to “pull rank” on the audience.
As an aside, Eric Weinstein commented on my earlier post by arguing that gauge theory was actually valuable. I told him that I was willing to be convinced but I asked him to convey his insights without referring to the mathematics. He hasn’t got back to me yet. (Eric also commented on Noah’s post with a lengthy comment with a bunch of mysterious mathematical notation. I doubt he is going to convince people by taking this route.)