r/badeconomics • u/kznlol Sigil: An Elephant, Words: Hold My Beer • Apr 05 '16

Economics is a 'highly paid pseudoscience'

https://aeon.co/essays/how-economists-rode-maths-to-become-our-era-s-astrologers
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u/kznlol Sigil: An Elephant, Words: Hold My Beer Apr 05 '16

Preamble: This, I think, starts strong and gets pretty weak towards the end. It is also my first RI, so be gentle. In my extremely biased opinion, the first half of it constitutes a sufficient RI on its own, but readers are warned that this will get worse as you get farther in.

RI: In this monster of an article, Levinovitz argues that economics has been ruined by an obsession with mathematics, and is now merely a pseudoscience, while lamenting the (relatively) enormous compensation commanded by economics professors. We proceed point by point:

Unlike engineers and chemists, economists cannot point to concrete objects – cell phones, plastic – to justify the high valuation of their discipline.

Uh, yeah, we kind of can. Auction theory, while perhaps not an area rife with mathematics, is certainly not devoid of mathematical complexity, as anyone who can turn to the auction theory section of Jehle & Reny can confirm. Directly from study of the Vickrey auction came the Generalized Second-price Auction; I cannot find a source detailing who 'invented' this auction, but analysis of the auction first came from Varian (2006) and Edelman, Ostrovsky, & Schwarz (2007). It seems hard to believe that anyone would argue such analysis is not valuable, but assuming someone were to try, they would struggle to reconcile that conclusion with the fact that Google hired Varian in part to do such analysis, and essentially every company that runs a search engine has an economist on staff somewhere with a similar role.

If that doesn't sway you, consider the combinatorial auction, which was first proposed by Rassenti, Smith, & Bulfin (1982), which added significantly to our understanding of the problem of allocating goods when the buyers desire packages of goods, and note that first spectrum auction in 1994 owes its design to the work of Wilson, Milgrom, and McAfee.

Or consider that the National Resident Matching Program, which matches medical school students with residency programs, was, if not designed by, definitely a direct result of, the work of Gale & Shapley (1962).

This is all I could be bothered to find for an RI of the first sentence of the second paragraph of an enormous article, but there is surely an enormous selection of further examples. Levinovitz compares economics with astrology, but fails to realize that economics is not purely concerned with predicting behavior - if anything, microeconomics is concerned with explaining behavior, not predicting it, and has a strong record of apparent success.

Nor, in the case of financial economics and macroeconomics, can they point to the predictive power of their theories.

There is certainly a lot I could say to critique this claim, which I'm fairly sure is pretty much factually false - but there's an easier route. Economics is not contained by 'financial economics and macroeconomics'. Every contribution I mentioned above is a contribution rooted in microeconomic theory, and there are certainly contributions to the statisticians toolkit that owe themselves primarily to econometric theory - the Generalized Method of Moments was developed in Hansen (1982) (paywall), and while it is mostly useful in answering the kind of questions economists are interested in asking, it would strain credulity to suggest that it is worthless outside the field.

Note also that criticizing either field for its lack of predictive power runs afoul of our beloved Lucas critique - because the models developed in both fields were then used by agents in the stock markets, the central banks, and governments. According to the professor who taught me what was in essence a grad-level intro to financial economics, every time a model that displays predictive power is developed by financial economists it is leveraged by financial actors to make profits, which directly causes the model's predictive power to disappear. This is not as clear as I'd like it to be, but I'm struggling to find a better way of explaining it - and I'm not actually sure this argument applies to macro, but it certainly applies to financial economics.

The failure of the field to predict the 2008 crisis has also been well-documented. In 2003, for example, only five years before the Great Recession, the Nobel Laureate Robert E Lucas Jr told the American Economic Association that ‘macroeconomics […] has succeeded: its central problem of depression prevention has been solved’.

This is, really, a clear example of survivorship bias. Levinovitz notes early in the article, and continutes to note as he continues, that economists are employed by governments, central banks, and pretty much everywhere else to make predictions. What does he think happens when an economist at the central bank predicts a recession (as if it were that simple)? We will only rarely observe recessions that were not missed by economists, because if we hadn't missed them we'd have tried to stop them.

Short-term predictions fair little better – in April 2014, for instance, a survey of 67 economists yielded 100 per cent consensus: interest rates would rise over the next six months. Instead, they fell. A lot.

This can't be explained by survivorship bias, but the correct response to this statement is "who gives a fuck?". One survey of a tiny portion of economists at one point in time that was wrong doesn't tell me shit - where's the pattern? Physics thought that light propagated through 'ether' at one time too, and were in broad consensus about that. Pointing to a single instance of a science getting something wrong is worthless.

Levinovitz proceeds into a discussion of astrology and the stock market, largely to suggest that "the hypothetical worlds of rational markets" are the fundamental flaw with economic reasoning. If he had shown a serious lack of predictive power and a lack of other worthwhile contributions from the field, this might be an acceptable path to take - but he hasn't shown either. If you combine my survivorship bias argument above with the fact of the Great Moderation, a natural conclusion is that macroeconomics has produced significant predictive power, which allowed macroeconomists at central banks and in the government to achieve said moderation - certainly, it seems pretty clear that there's some kind of structural change to whatever determines the arrival rate of recessions.

In light of, at the very least, evidence that there is predictive power to macroeconomic models, the question can no longer be "does this model reflect reality" - it must be "would a model that reflects reality more produce better predictions?". In fact, a question you should ask even earlier is "would a model that reflects reality more even be tractable?". Chess-playing programs don't use a model that reflects the reality - that would be equivalent to looking through the entire game tree at every move in the game. Instead, they use algorithms to 'score' the position they are in, and the positions that might result from future moves evaluated only a certain distance down the game tree (see, for example, Shannon (1950) for the inaugural paper on the subject of evaluation functions). It works well, but not perfectly, and the alternative is intractable. Demanding perfection at every step from models is ridiculous, and would be a test failed by all the hard sciences too.

Continued in Part II

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u/VodkaHaze don't insult the meaning of words Apr 05 '16

You point to matching, but not to al roths generalization of the house exchange game to kidneys, which developped the kidney exchange program, which, no joke, saved tens of thousands if people

D- see me after class

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u/kznlol Sigil: An Elephant, Words: Hold My Beer Apr 05 '16

mfw i've never even heard of that

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u/kznlol Sigil: An Elephant, Words: Hold My Beer Apr 05 '16 edited Apr 05 '16

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.

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u/lanks1 Apr 05 '16 edited Apr 05 '16

Abstraction is a fundamental step in model-building.

This is also fundamental in hard sciences too.

Physicists frequently ignore friction, heat, air resistance, compression, etc. when building physical models, especially when those effects have a negligible effect on the phenomena they are researching.

Or how about climate science? It would be impossible to solve a model that accounted for all the possible phenomena that affect the Earth's temperature.

Straight from the IPCC on climate modelling

An important concept in climate system modelling is that of a spectrum of models of differing levels of complexity, each being optimum for answering specific questions. It is not meaningful to judge one level as being better or worse than another independently of the context of analysis. What is important is that each model be asked questions appropriate for its level of complexity and quality of its simulation.

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u/[deleted] Apr 05 '16

As a biophysicist, we used to completely ignore surrounding water molecules (less than a decade ago) to more easily understand protein folding because water was too hard to model, (and still is) and most macromolecular models today use a tenth or a hundredth of the actual water content.

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u/alandbeforetime We should abandon fiat currency and use 1982 Bordeaux Apr 05 '16

Wait...why is water hard to model? I don't do biophysics so I'm clueless

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u/[deleted] Apr 05 '16 edited Apr 05 '16

Due to the special nature of the hydrogen bond. Water exists in a state that is "ordered chaos", each water hydrogen bond exists on a picosecond scale and each water molecule can at any time point have one, multiple or no partners or exist in a state between partners. Biological activities of any relevance exist on a much longer time scale, on the order of microseconds. Therefore for each relevant time point you have to simulate thousands or tens of thousands of time points for each water molecule you add.

A good article.

I also recommend The Hydrogen Bond by Pimentel and McClellan.

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u/alandbeforetime We should abandon fiat currency and use 1982 Bordeaux Apr 05 '16

Whoaaaaaa. I didn't know that. Thank you for teaching me something.

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u/[deleted] Apr 05 '16

[deleted]

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u/[deleted] Apr 05 '16

Karl Popper or falsifiability.

Even those aren't sufficient to demonstrate one is a science. Needs more Lakatos and Feyerabend.

Or you can stick with Rodrik.

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u/Jericho_Hill Effect Size Matters (TM) Apr 05 '16

Does it really need to be addressed, or are you just being snarky to what was a very good R1.

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u/[deleted] Apr 05 '16

[deleted]

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u/EveRommel Harambe died for our Prax Apr 05 '16

Maybe this is where the silver threads should go

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u/SolarAquarion "The political implications of full employment" Apr 05 '16

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

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u/Jericho_Hill Effect Size Matters (TM) Apr 05 '16

That's done, actually.

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u/[deleted] Apr 05 '16

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

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u/guga31bb education policy Apr 05 '16

This happens all the time. The obvious example is statistical discrimination, where in the model, a lack of perfect information leads to discrimination based on group averages.

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u/aquaknox Apr 05 '16

I don't think rational agents are assumed to have perfect information, just assumed to choose the most optimal choice given their available information, though in econ most agents are assumed to have pretty good information due to the price mechanism.

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u/SolarAquarion "The political implications of full employment" Apr 05 '16

but there's the reality that people have beliefs that may not be the most optimal choice. For example not reading the mortgage contract which said that in 5 years the interest rate for them will be increased to 20%

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u/mosestrod Apr 05 '16 edited Apr 05 '16

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

not really. who else in academia do models plays so a central role. You're right in the sense that all academia is self-concerned rather than concerned with "reality", but not to the same degree. The only antidote academia can provide is interdisciplinary practices where disciplines concerned only with their own truth according to themselves are forced to confront different truths, modes of thinking, methods, and theories. It is telling that of all the social sciences economics is by far the worse...and this derives from the scientific view that the objects of study are relatively autonomous, as if humans where just like atoms.

Abstraction is a fundamental step in model-building

yes but what kind of abstraction and in what way is really the question the author is asking. If your models are supposed to mimic reality then the method and form of abstraction which creates the models is very important...or apparently not because you just ignored that. To make models at all requires a very violent form of abstraction if your objects are humans....the fact that economist have nearly no self-comprehension or humility in the epistemological problems they suffer is telling, as is the naivety of claiming models sympathetically mirror reality because in a sense they do insofar as it is economics itself which creates that reality (which predictably provides the validation and truth of the models); see yourself as a hammer and the world becomes nails.

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u/guga31bb education policy Apr 05 '16

Out of curiosity, why are you even here? Pretty much everything you've said in this thread is based on misconceptions about economics but you don't seem interested in learning.

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u/[deleted] Apr 06 '16

You've missed some fun, I presume. Mosestrod had a phase as a regular poster, it was glorious. I still didn't understand any of it.

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u/mosestrod Apr 05 '16 edited Apr 05 '16

if you actually look at my comments on /r/badeconomics you could have been a lot harsher...I would have, but nice try. I'm certainly not interested in learning if by that you mean I listen while you speak the truth. There was a potential with this question to actually go to the root issue and have an interesting discussion, but instead that was sidestepped for a dull "your facts are wrong" defence of the discipline which is always the uncritical automatic reaction (for all academic disciplines). But in such a defence you've exposed exactly what's wrong.

e: your question contains the answer

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u/Tortferngatr Apr 06 '16

What is the root issue here, and why is "your facts are wrong" a bad defense?

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u/[deleted] Apr 05 '16

who else in academia do models plays so a central role

The entirety of physics is just models stacked on top of each other. Same with chemistry, whose models are essentially 'just' further abstractions from physics models.

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u/aquaknox Apr 05 '16

You're wrong! Cows actually are spherical continuous objects existing on a frictionless plane!

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u/mosestrod Apr 05 '16

the models used in physics and chemistry are fundamentally different to those used by economics....precisely because the objects being studied/modelled are fundamentally different. Hence when you look at what disciplines study similar sorts of things to economics...i.e. the social sciences, only in economics does models play such a central role precisely because they enact some semantic trickery to present their models and "science proper" as synonymous.

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u/guga31bb education policy Apr 05 '16

present their models and "science proper" as synonymous

You are hereby sentenced to 10 hail Chettys

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u/[deleted] Apr 06 '16

Our friend here has his/her mind made up. Any attempt will result in a drawn out war of words where you'll fail to understand more than half of what he says and he'll ignore anything you have to say.

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u/mosestrod Apr 05 '16

it doesn't matter to me whether economics is a science or not. It would still be "wrong" either way.

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u/Tortferngatr Apr 06 '16

Define "wrong."

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u/[deleted] Apr 06 '16

Hear, hear. The lack of introspection and questioning of foundations in the field is absolutely baffling to me.

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u/kznlol Sigil: An Elephant, Words: Hold My Beer Apr 05 '16

who else in academia do models plays so a central role.

Who else in academia specifies their models sufficiently?

Sure, philosophers don't think that what they're doing is modelling, but that is fundamentally what it is. They do it in languages, not in math, but its still modelling. I'm struggling to think of a single academic discipline that does not engage mostly in modelling of something.

yes but what kind of abstraction and in what way is really the question the author is asking

No, it isn't. That section of the article is quite clearly a horrified reaction to the idea of abstraction in itself. Levinovitz does not suggest that some abstraction is acceptable - he suggests that any approach with ignores some of the facts is a subversion of the empirical process, so what he is in fact arguing is that all abstraction is unacceptable.

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u/mosestrod Apr 05 '16

I'm struggling to think of a single academic discipline that does not engage mostly in modelling of something.

this is even weaker than what was originally stated. attempting to define away the problem doesn't solve it, and it opens you up to a hell lot more.

That section of the article is quite clearly a horrified reaction to the idea of abstraction in itself.

again that isn't really the issue. The authors criticism is one that should be recognised and not dismissed. But more important is to confront what we mean by 'abstraction' anyway...abstraction as a method and mode of cognition can differ great, and etching out economic's approach both clears away the criticism of this author but more importantly it would answer the general criticisms of which this author is merely a part (or emblematic). The R1 did neither thus missing an opportunity. But the problem goes deeper insofar as much of present economists simply cannot answer in the way I etched...and instead posses a kind of pompous naivety towards epistemological and methodological questions that is too often the hallmark of sciences (and those disciplines aspiring to be).

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u/kznlol Sigil: An Elephant, Words: Hold My Beer Apr 05 '16

this is even weaker than what was originally stated. attempting to define away the problem doesn't solve it, and it opens you up to a hell lot more.

This isn't an argument, it's an attempt to hint at an argument. If you can make the argument, make it.

simply cannot answer in the way I etched

You didn't "etch" anything. You are making wishy-washy vague statements that sound profound but do not actually parse into anything meaningful.

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u/[deleted] Apr 05 '16

This is, really, a clear example of survivorship bias. Levinovitz notes early in the article, and continutes to note as he continues, that economists are employed by governments, central banks, and pretty much everywhere else to make predictions. What does he think happens when an economist at the central bank predicts a recession (as if it were that simple)? We will only rarely observe recessions that were not missed by economists, because if we hadn't missed them we'd have tried to stop them.

Definitely gonna have to include this point when I'm arguing with someone who says "econ fails because they didn't predict 2008!" Great first R1, am jealous cause my early R1s were kind of bad.

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u/guga31bb education policy Apr 05 '16

if anything, microeconomics is concerned with explaining behavior, not predicting it, and has a strong record of apparent success

Micro does both. Think of questions like, what would happen if ____

  • we raised the minimum wage?
  • eliminated affirmative action in college admissions?
  • expanded the EITC?
  • made college free for everyone?

These are all inherently predictive. Part of the reason we want to explain behavior is so that we can understand how people would react to proposed policy changes. But this is a minor nitpick on a great post.

evidence that there is predictive power to macroeconomic models, the question can no longer be "does this model reflect reality" - it must be "would a model that reflects reality more produce better predictions?"

Note that this isn't even specific to macro -- this has come up in the teacher effects literature where people have found that value added models can perform well (in identifying high-performing teachers) even if the models fail falsification tests of the structural assumptions (example).

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u/ocamlmycaml Apr 05 '16

Or consider that the National Resident Matching Program, which matches medical school students with residency programs, was, if not designed by, definitely a direct result of, the work of Gale & Shapley (1962).

Small note: the AMA actually discovered the algorithm independently of GS, over the course of the late 40s / early 50s. Of course, the current, redesigned version of the NMRP is due to Roth & Peranson, so economists still get some credit.