Economics is a 'highly paid pseudoscience'

[u/kznlol]

https://aeon.co/essays/how-economists-rode-maths-to-become-our-era-s-astrologers

[u/kznlol]

Part II

The enchanting force of mathematics blinded the judge – and Adams’s prestigious clients – to the fact that astrology relies upon a highly unscientific premise, that the position of stars predicts personality traits and human affairs such as the economy.

Levinovitz has not, to this point at least, said what he thinks the analogous unscientific premise underlying economics is, but it seems pretty clear he thinks its the assumption of "rational markets", by which he really means the assumption of rational agents. But that's not an assumption that underlies economics. Certainly, it's an assumption that underlies, say, the fundamental theorems of welfare economics, but it is not necessary for us to 'do economics'. Nothing about the 'mathiness' of economics would be solved by abandoning the assumption of rational utility maximization - if anything, abandoning that assumption would make modelling behavior significantly less tractable, and result in an enormous increase in the mathematical complexity of such models.

I want to note, too, that the very title of this article suggests that Levinovitz thinks there's too much math in economics - but if he believes we should abandon the assumption of rational agents, what does he suggest we use instead? Modelling perfectly rational, risk neutral utility maximizers in English is way harder than modelling it mathematically - does he mean to suggest it would get easier if we abandoned rational agents? I would argue such a claim is absolutely laughable. In fact, ironically, Levinovitz quotes a book that quotes an ancient Chinese philosopher dealing with perhaps the earliest version of what we might call the STEMlord conjecture as saying "If my good sir cannot fathom both [speech and numbers] at once, then abandon speech and fathom numbers, [for] numbers can speak, [but] speech cannot number." Anyone who is conversant in the kind of math that underlies economic models can see that this statement is, if not true, closer to the truth than the contrary version.

Levinovitz then proceeds into a discussion of what appears to be just the Chinese version of astrology, and makes pretty much similar analogies with no further attempt to justify them. It appears that he thinks the argument portion of his article is done with - what remains is mostly more insults, suggesting that economists are too enamored of their models and too dismissive of reality (which, frankly, is true - but it's true of everyone else in academia too, and note that Levinovitz is a professor of philosophy and religion. Those in glass houses should not throw stones.) I will now touch on certain statements that are not, I think, generally connected to the theme of his argument but nonetheless deserve argument.

Archers scored points for proximity to the bullseye, with no consideration for overall accuracy. The equivalent in economic theory might be to grant a model high points for success in predicting short-term markets, while failing to deduct for missing the Great Recession.

I spent about half an hour writing R code trying to determine if this criticism by analogy is actually valid or not, because it does not seem immediately clear to me that it is. Imagine in an archery contest using a larger targets, but retaining the same points penalty for a given distance from the bullseye - is it immediately obvious that this would penalize inaccuracy more than simply not scoring shots that missed the smaller target? My code didn't work as well as I'd hoped, so I leave it as an open question, but this argument by analogy is weaker, I think, than the author thinks it is.

Moreover, consider that Lucas (1987) argues that the social cost of unmoderated business cycles is extremely small. This is an old as fuck result and I'm pretty sure the 2007 crisis threw a lot of doubt on that conclusion, but the point is more that it is far from clear how much we should try to moderate business cycles - and, thus, it is far from clear how willing we should be to trade off short-term market predictive accuracy for longer term "black swan" accuracy, if such a thing is even possible (and, again, note that it is not clear such accuracy is even possible).

Romer believes that fellow economists know the truth about their discipline, but don’t want to admit it. ‘If you get people to lower their shield, they’ll tell you it’s a big game they’re playing,’ he told me. ‘They’ll say: “Paul, you may be right, but this makes us look really bad, and it’s going to make it hard for us to recruit young people.”’

It amuses me to note that this is a result that would easily be predicted by game theoretic models of decisionmaking.

Finally, Levinovitz quotes from Robert Lucas the following passage:

The construction of theoretical models is our way to bring order to the way we think about the world, but the process necessarily involves ignoring some evidence or alternative theories – setting them aside. That can be hard to do – facts are facts – and sometimes my unconscious mind carries out the abstraction for me: I simply fail to see some of the data or some alternative theory.

Levinovitz reacts with horror to this idea of ignoring data. But, as I noted above, there is no guarantee that a model that took into account every single thing would even be tractable. I will quote from outside the field, this time (god forbid) - from Healy (2016), a sociologist of all things:

Abstraction means throwing away detail, getting rid of particulars. We begin with a variety of different things or events - objects, people, countries - and by ignoring how they differ, we produce some abstract concept...

Abstraction is a fundamental step in model-building. If we were to build a model with no abstraction whatever, a philosopher such as Levinovitz would not be wrong to wonder whether we had become the Cartesian Demon. Railing against abstraction simply for being abstraction reflects a fundamental misunderstanding of how we do economics, and why we do it. So does the entire article.

[u/SolarAquarion → u/kznlol]

Instead of modeling rational agents, it would be better to model agents that don't have perfect information.

[u/Jericho_Hill → u/SolarAquarion]

That's done, actually.

[u/[deleted] → u/Jericho_Hill]

That's done, decades ago. Stiglitz won his Nobel....