Essentially it's like pre-Enlightenment Natural Philiosophy, in that it's a discipline that claims to explain the way the world works, but actually explains who has the most sway in getting their ideas accepted.

> ...should provide ample data to develop "real" models of economic behavior against, and I think that many researchers actually already make use of this data.

I suspect reality will get about as much traction against idealogues of e.g. the Chicago School as actual climate science does agains useful idiots like Bjørn Lomborg. It's about providing views that happen to be useful to moneyed interests, not reality.

This is an odd criticism. I could see it applied to Chicago's cousin, the Austrian school, which clearly relies more on ideas (viz. the work of Hayek and Mises, both of whom considered themselves political philosophers as much as economists).

But Chicago is just the opposite. It's been criticized for being too tied up in the mathematics of it all. Chicagoans love numbers.

Larry Summers said of RBC models

1. RBC models use parameter values that are almost certainly wrong,

2. RBC models make predictions about prices that are completely, utterly wrong, and

3. The "technology shocks" that RBC models assume drive the business cycle have never been found. (They assume that during recessions we just forget how to be efficient.)

That's a fair criticism, as far as it goes: it's been said (of Austrians, anyway) that they've predicted 8 of the last 3 recessions.

The thing is, qualitatively, we can say that "old school Keynesian-style aggregate models" are just as bad. The difference is that, rather than modeling based on coldly-rational actors, they're modeling based on (and I quote) "animal spirits". And those models told us that the end of WWII and curtailing war spending was going to usher in a new depression worse than the Great Depression; and that the Sequester and "fiscal cliff" were going to plunge us back into the depths of 2008.

The fact is that both approaches like to pretend that they understand what's happening, but neither really do. Anybody claiming they have an accurate model of macroeconomics is trying to sell you something.

HOWEVER, this is all talk about Macro.

If you take a look at the Micro world, you'll see that Chicago really are the winners. Microeconomics is a solved problem, at least to a first approximation. And the progenitor of that was pretty much Gary Becker - from University of Chicago.

So it's not fair to criticize Chicago when (a) in the micro world, they really have been triumphant; and (b) in the macro world, they're just a different kind of wrong than Keynesianism.

Thank you. Simple and true.

It would be more accurate to say that the framework within which microeconomic phenomena is pretty well understood. While there's still plenty of room for research to fill out all the details, there's very broad consensus about how the answers tend to look. Concepts like price elasticity are well understood and non-controversial.

That stands in sharp contrast to macroeconomics, where even when talking about the same stuff, say, ZIRP, there's fundamental disagreement about what factors we should be researching. (and when I say "we", I mean people that aren't me, 'cause I'm not an economist)

Empiricism often uses numbers and math, to be sure, but love of numbers and math is not love of empiricism: you can use math to tease out implications of your abstract, first-principles, non-empirical model as well as you can use apply it to real world observation in an attempt to confirm or refute an empirical model.

A criticism I've seen of the Chicago school has certainly been that it is more concerned with the mathematical implications of idealized assumptions and less concerned with how well those implications reflect real-world results.

It's possible to love numbers and still not be interested in empirical data. One thing you may notice about much raw economic data is that it was selected because (a) it was easy to collect, or (b) it gives "reasonable results" according to the accepted theory.

See also How To Lie With Statistics.

As a layperson with a bit of an interest in economics I don't really see how, as the article says "econ is now a rogue branch of applied math". More like economics uses applied maths, or something like that. It's a 'social science', we can't reveal the laws (let's call them 'habits') of economics like we do The Laws of Nature, because circumstances change -both globally and locally (macro / micro)- and new economic phenomenon emerge.

It'd be interesting to see what future historians have to say about present day economics.

Funny - you could say the same about physics. For example, knowing that the coming car may kill a person causes the human behaviour to change, namely the driver will stop the car. Does that invalidate Newton's laws?

Yes we probably cannot predict universe totally. But we can do scenarios (of complex emergent systems of interacting agents with bounded rationality), just like in physics. In fact the whole point of doing that analysis is to change behaviour of people, one way or another.

The difference is that whether a person will try to move out of the way of an oncoming car is not considered within the domain of physics (so them using their knowledge of physics to predict that a car is a danger may change their behavior, but not the accuracy of what physics predicts within its domain), but whether or not a person will try to move their money out of the path of a predicted stock market collapse is within the domain of economics.

This doesn't actually make empiricism any less applicable to economics, but it does compound problems in the empirical study of economics.

1. Car continues and hits the person / investor won't move money out before stock market crashes

2. Car is stopped / investor will move the money out

In both cases, the physics or economics is no less applicable whatever the circumstances of the actual decision. And just like physics cannot tell you whether the car stops, economics cannot tell you whether investors will actually move the money out. But what economics can tell you, under certain assumptions, say, investors want to make money with this and this horizon, whether or not are they likely to move out.

Let me give another example. Water flows downhill due to gravity. Yet, people can decide to build water pump and aqueduct to get water uphill. In doing so, they didn't break any physical laws. But if you ignore the pump, it may seem that the water flow downhill anymore and so the laws are incorrect. What happened is that now our model of the situation should include the pump, and within the expanded model, physical laws are again preserved.

Similarly for instance, if the society decides to regulate markets, the behaviour of the people can be changed, but they don't necessarily have to break some universal economic law. The new behaviour can have a perfect economic explanation, it's just that the frame of the model changed.

It seems that this "infinite regress" confusion (also called Lucas critique, if I am not mistaken) is caused by ignoring the fact that every model of reality only includes a portion of it and is never a perfect description (for example we ignore the physics of human brain when we model the car hitting the pedestrian).

Also, you should note there are situations where knowing more doesn't actually change the behaviour (under assumption of certain rationality) - for example, getting to know the exact odds of casino wins won't entice me to play.

So what I'm saying is that a theory that cannot be falsified experimentally is not very useful.

The real danger here is that these theories -most of which are supported by no or very slim experimental evidence- are used by governments to formulate economic policies, which in turn affect the life of millions or billions of people. For me, this is a bit like developing an "idealized" theory of nuclear physics and then trying to build a nuclear power-plant based on it. I, personally, would not want to live near one of these ;)

Suppose governments did not formulate economic policies with these imperfect models. What would they do instead?

Edit: this isn't a comment about economics but how economics is used in a political context.

"Observation and only observation" is how you build an inchoate collection of useless factoids, it's not how you do science.

Observations are a very important part of the scientific method and you have to be either rooted or anchored in it, but it's only one part of science, and it's by no means the most important product of it. Observations are seeds (from which patterns are recognised and hypotheses formed) and filters (data gathered to test the predictive power of hypotheses).

We call it phenomenology. The very base of any proper science. The rest is just a mechanical work of eliminating the noise from this data.

Science should never produce any knowledge which is not found in the original data (either passive observations or controlled experiments - does not really matter). The scientific method is all about techniques of extracting the most compact representation (i.e., the information) hidden inside this massive data sets. It turns out that the axiomatic theories are very common and compact representations for many areas of science, but not necessarily the universal representation.

What you disregard as 'just a mechanical work' is nothing of the sort. It has required all the ingenuity of the greatest genius in history to get modern science out of the data, and any future advances will require even greater insights.

If anything, the data gathering is the 'mechanical work' part of science.

Then, some decades later someone finds the practical application, and the data that matches the model.

Mere observations give no interesting and no useful results. Basically, you'll end up with an ever-growing list of facts.

Science, essentially, is nothing but a process of extracting information (as in the algorithmic information theory, not in Shannon sense) from the data. Reasoning is just a tool, one of the ways of representing this information.

Traditionally, economists have put the facts in a subordinate role and theory in the driver’s seat. Plausible-sounding theories are believed to be true unless proven false, while empirical facts are often dismissed

The error is the assumption that facts are, well, facts. In real life, it's not nearly so black-and-white. Remember back in high school physics, when we did experiments with Newtonian physics, but our answers never quite worked with the theory - not just because of Einstein, but mostly because of (a) measurement error and (b) we were (knowingly or not) assuming point-masses on frictionless planes, etc.

As long as we were willing to write off our errors against those two sources, we could never discover that Newton's theories were incomplete, and we needed relativity to explain differences. We only got to that conclusion via models.

The way that you choose to measure fundamentally drives what your measurements are. And you can only decide what and how to measure if you start off with some model of the world.

So, the corrected wording for that paragraph should be the following:

Plausible-sounding theories are believed to be true as long as their numeric predictions conform to all of the experimental facts within this theory supposed range, up to this theory supposed precision.

And a theory falsified by a new set of facts does not become immediately "false". It just get its range cut down to that range of facts where it is still giving an acceptable prediction precision.

Back to physics analogy, the phlogiston theory is still correct and true, as long as it is applied within the range of the phenomenological thermodynamics. But this does not happen in the classic economics - all those crazy theories are coming from the depths of an insane mind, not from any particular set of facts. They never had any specific range where they were known to be applicable. Therefore, phlogiston is science, and economic theory is not.

I mean, it is possible to measure the effect. But you need to first design the experiment in order to make the measurement. It was necessary for Einstein to sit and think for a long time, to come up with the idea, which others were able to design experiments around.

You can't just say that somebody would have noticed the discrepancy sooner or later. Really, doing experimentation that way is a statistical error, of the sort that's really plaguing the sciences these days.

General relativity is an application of a well known extrapolation heuristics - the simplest possible generalisation of a model. The other possible generalisations were much more complex, and the nature for some reason tend to favour simplicity, so it was reasonable to go that way (as well as it is very reasonable now to go out and test all the possible extensions of the Standard Model, starting with the simplest ones).

Observation is useful to develop a theory (induction, or "educated guessing"). However, having a theory guides us towards newer, often subtler observations as we attempt to falsify it. Karl Popper called this the theory-ladeness of observation [1]

[1] http://plato.stanford.edu/entries/popper/

Of course. But it's merely some heuristics helping to cut down the search space, not an inherent, fundamental property of the universe.

In order to test a model, it is useful to collect new data.

The mistake is in thinking it should or could be a hard science like physics.

For example, the financial markets are the most measured markets out there, with the most microscopic details recorded. One interesting thing that happens after financial crashes are crises of theory. For example prior to 1987 American options didn't show [volatility smiles](https://en.wikipedia.org/wiki/Volatility_smile). After the crash the smiles appeared, making the markets a very different place. The same happened after Subprime and the LIBOR scandal, when the notion of a "risk-free rate" suddenly disappeared: governments now had to compensate for their default risk and market quotes were unreliable. Academics still struggle with the whole notion, although it seems that the current practice is settling around OIS discounting and CVA/DVA.

The point is, rules change. Hence in economics you can't just empirically deduce a rule and let it be, you constantly have to recalibrate it.

The fact that some people use astrology to play the markets, and seem to get results that are as good as those of economic theory, says a lot about both.

Economics is entirely a faith-based pseudo-science, which plays the same role in modern culture as the nonsensical theistic "explanations" of the world put out by the Church played in medieval times.

It's a form of political/rhetorical persuasion and social control, with an implied morality that's never seriously questioned. Even if you accept that it's politically descriptive and not politically predictive, it still fails.

It's not a science in any useful way - it simply pretends to be one, because that makes it appear more authoritative.

The real scandal for me is the fact that skeptics and debunkers like the amazing Randi have spent so much time and energy on trivial topics like the paranormal, while leaving the epic intellectual fraud and imposture behind mainstream economic theory unchallenged.

First of all, not a lot of people actually use academic economic theories to "play the markets". Ask a trader how often does (s)he use the General Theory or monetarism in their daily decision making. There are macro-strategies, used mostly by fund managers, but it's not such a big portion of the market.

Secondly, anyone found to use astrology in their market activities would be fired in nanoseconds. Whichever institution. You can do it privately though.

The fact that one can get good results speculating while using astrology as a decision generator (or in fact any other random mechanism, like a monkey throwing darts) is actually known and used in the financial theory. It is called "the random walk hypothesis" and is the foundation of a lot of assumptions. A good introduction to it would be "A Random Walk Down Wall Street" by Burton Malkiel.

So I urge you to actually build an informed opinion before succumbing to an Alex Jones brand of reasoning.

So are the markets.

>First of all, not a lot of people actually use academic economic theories

Maybe not, it you don't consider Black-Scholes and it's endless brood of offspring to be serious academic theories.

Not many people use nation-state Keynesian or other big macro policy theories to play the markets - which is a different point.

But it's a relevant different point, because it highlights the political reality of using macro as a hand-wavey excuse for policy which benefits market operators and the owners of the money behind them at the expense of the rest of the population.

>It is called "the random walk hypothesis" and is the foundation of a lot of assumptions.

Quite. Does it not worry you that this is true, or that even with this insight manic-depressive boom-bust behaviour is apparently still considered a feature, not a bug?

>So I urge you to actually build an informed opinion

I suspect my opinion is at least adequately informed. Perhaps you're mistaking being heterodox for being wrong?

So meteorology isn't a real science either, I assume? Having a perfect model doesn't mean you can predict the behaviour of a system; conversely, not being able to predict the behaviour doesn't mean the model is flawed, or non-scientific.

That said, I do agree that economics is taken way too seriously for its incipient state.

I think this is the most spot on statement on economics I've read.

FYI - I met Randi personally about eleven years ago. He was a wildly charismatic person to talk to. It doesn't show as much when he's on stage or on an interview speaking to an audience.

That depends which theory; under most that can be taken as even semi-plausibly as models of the real world, no, unless you assert some simplifying assumptions (which then make them no longer semi-plausible models of the real world).

The simplifying assumptions are common in intro-level Econ classes, for the same reason that, e.g., assuming the absence of friction is common in many parts of intro-level Physics classes.

The thing is that we don't have as many people in the public media trying to sell policy using explanations of physics that leverage the fact that most people that know anything about the subject do so through hazily-remembered intro-level classes as we do for economics...

Finance != Economics

Economists hardly ever try to use the results of economics to predict the stock market...in fact economics is the field that has theories that no strategy exists that can beat the market reliably.

And there is a proper, scientific approach in the economics: behavioural economics. Instead of hand waving about some "ideal", non-existant agents acting fully rationally upon a 100% correct and impossible information available, as the classic bullshit economics does, the proper, behavioural economics starts with studying the real individuals behaviour (which is very much doable, no matter what the others are saying), and only then drawing conclusions about the herd behaviour in a statistical scale.

In addition to what JupiterMoon says, I'd say that individual behaviour was never a real problem in economics. A lot of the theories are built on stupid assumptions about rational behaviour, but that's just it: you always can change the assumptions and see what happens. Behavioural economics is just that.

The real problem of economics is scale and inability to cleanly experiment on that scale. To imply any kind of large scale "herd" behaviour from individual behaviour would still require a tonne of a priori, non-falsifiable assumptions. Even if the assumptions can be shown to be valid now, it would be impossible to prove that they are stable and valid for a long period of time.

Pure theory has its place in science, as long as one is honest about its limitations.

General relativity is a different thing, it was a pure hypothesis, an extrapolation of the simplest possible generalisation of the special relativity [1]. And it held this hypothesis status up until it was sufficiently confirmed by the incoming experimental data. Before that, a multitude of alternative hypotheses existed which had the same numerical predictions covering the available experimental data (e.g., https://en.wikipedia.org/wiki/Anatoly_Logunov#Relativistic_t...).

So, yes, it's important to distinguish theory from a hypothesis.

[1] this "simplest possible generalisation" method works most of the time, but not always, so it's mostly valid to do so in the hard sciences, and should never be used as a justification for hand waving in the social sciences.

That's not an inherent limitation for applying science. Signal theory has models that represent circuits with feedback loops, where the output ; similar models could be developed to study people who know are being studied.

Also, if you use data collections that were compiled for other purposes, you can study the behavior of people who don't know are participating un such study. Big data is essentially that.

> As you say this all derives from the biggest problem with all the social sciences people are not rational actors and any mathematical model has to encapsulate real human behaviour.

There are theories that don't assume perfect rational agents, and can still predict behavior by studying the common human bias. See the work of behavioral economist Dan Ariely for an academic approach.

That's fair, so far as academic research goes, as there are plenty of academics doing respectable work in in non-scientific fields such as music and poetry.

But it's another matter to decide if and how to ethically apply the results of soft-science research (likewise music and poetry) in ways that affect society.

Competition (or lack of it) is absolutely the number one area where the simplistic models break down, with psychological phenomena being a close second. Even where there is demonstrated and measured irrationality in individual decisions though, in aggregate the distortion effects tend to be minimized.

Outside of these known areas of completixity and modeling deficiency, there have been several major breakthroughs in modeling and understanding other seemingly puzzling factors. Matching problems, search frictions, moral repugnance, game theory, asymmetric information, and discrete choices. There have been huge advances since the 1950's, it just takes some time to catch up with it all.

In the meantime, we still have to do our best. People still want ways to predict the future which suffer less from human interference (which is ideally what a mathematical model will let you do). That's still better than just asking people what they think (in some ways).

A lot of simplifying assumptions have to be made to say anything useful about a system which includes billions of intelligent actors trading trillions of dollars. There's obviously room for improvement, and I think that'll happen once people are given the proper tools to make it happen.

Aside from the technical possibility of doing economic experiments, there is also the ethics of doing them. You are not only involving humans, but doing so on a grand scale. To prove a point, you would not only need to possibly send an economy into a recession, but you would have to do so dozens of times to get significant results. The people you are experimenting upon might get a little murdery.

I think another reason is that in business you need models you can reason about.

One example is from a bank that advises customers on investment. They have to algorithms doing machine learning on the market, a decision tree and a deep neural net. Over time they can see that the neural net outperforms the decision tree, yet they cannot use the results to advise customers because it is a black box.

Why should you buy this investment? "Because the computer said so" isn`t an answer that makes it sound like you know what you are talking about.

And sometimes that's how economics feels. Absolutely agree with your comment. Coincidentally, I was thinking about this yesterday as I watched one of many economists explain the market on TV. At some level I feel they grab onto one of N plausible ideas and go with it. They have to say something, right? After all, they are economists.

I haven't failed to notice that there are very few (not one?) massively wealthy economists. That has to say something. If you look at the people who have made fortunes they are all practitioners, not theorists. In other words, they "touch and feel" the economy every second of the day for years and understand how it moves, at least at the relevant micro level, to gain advantages.

This one thing has always bothered me about economics. Lots of economists publishing books and claiming all sorts of events and effects and none of them have significant financial success to show for their understanding of the economy. Fake Jedi's who talk about the force but can't use it.

I'd like to see an economist on TV who starts their opinion of the economy in a Trump-esque way with: "I am very rich. I understand the economy and because of that I make $400 million per year".

In terms of using models and simulations, well, we do a lot of FEA, mostly for thermal and fluid dynamics. I had a poster printed and hung in the lab. It reads: "The only person who believes the results of these simulations is the one who wrote the code". I stole that from my friends in aero who always talk about how careful you have to be with aero "codes", particularly at the extremes (low and high RN).

Of course, FEA has gotten better and better over the years, yet it is true that you have to be very careful with how you interpret results. That's why we verify expected results experimentally by building a prototype every N variants of a design based on various criteria. I remember thermal management design to cool over 1,000 Watts of high power LED's concentrated within a small surface area. It took eight months of FEA and dozens of prototypes to get it right. Some of the proto's didn't behave anything like the simulation. Some behaved better. It's an art.

And so my point is that we are likely to have a new crop of economists who will base their opinions on simulations without, perhaps, understanding just how imperfect they can be.

An example of an economist who is successful would be Jan Hatzius, Goldman Sach's head economist.

I always go back to when I read "The Big Short" and realized that ALL of these economists missed a herd of elephants in the room. If I remember correctly, the two or three people who called it (and were yelling and screaming about the impending doom) and ultimately shorted the market and made truck-loads of money were not economists but rather intense observers and practitioners. I think one of them had Aspergers (It's been a few years since I read the book).

As for pundits, there's a reason they're pundits... Is Sergey Brin or John Carmack going to host a tech segment on TV? That's silly, as silly as thinking TV economists would be as successful as people like Jan Hatzius (BTW, he did correctly anticipate the crisis of 2008, and GS bet against the market and made a killing during that time).

I recall my family's PhD. economist relating an anecdote about an colleague explaining that he's making the usual set of assumptions like, say, "people live forever", before doing some math for students. :)

Assume a spherical cow: https://en.wikipedia.org/wiki/Spherical_cow

https://en.wikipedia.org/wiki/Foundations_of_Economic_Analys...

I'm a fan of using physics models for predicting behavior of large groups of people, but economics .... they do occasionally come up with nice statistical tools. Sort of like psychological researchers; those fellows whose papers can only be reproduced around 1/3 of the time.