
Mathiness: not just a problem of macro-economics (2015) - jimsojim
http://magic-maths-money.blogspot.com/2015/06/mathiness-not-just-problem-of-macro.html
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matt4077
People have been complaining for 20 years+ that economics chose the wrong
tool. It needs psychology, not math. (Or, more accurately: more and less,
respectively – you'll still need math).

The old joke about physicists starts "Consider a spherical chicken". It's
funny because it gets at the reductionism at the core of physics, and it's
even funny for physicists because they actually have been pretty successful
with that model.

It just doesn't work that way in economics. Even worse, the reductionism in
economics is unethical, because when it registered (somewhere) that humans are
not "objective, utility-maximising spheres" they more or less started
advocating that they /should/ be. That got us to "corporations are people" and
24-step daily checklists to "make better use of your time". It also made fast-
food the superior choice (time is money!), so at least the "spherical" part is
coming along.

After this short rant, which was obviously about microeconomics and therefore
off-topic, something different for macro: While he's right that the "growth"
debate has had more or less the same trajectory as the Grand Unifying Theory
in physics, I wouldn't discount the improvements we've made in other areas.
Inflation, for example, is pretty well under control. People don't appreciate
that too much, but I remember how my Grandmother talked about inflation. It
was basically /the/ catastrophe of her life (Germany in the 20ies – WW2 was
just a result of it).

So we seem to be doing something right – maybe economics, maybe politics, but
certainly better.

I also disagree with the very last paragraph of the article where he seems to
advocate dropping the scientific method for a model closer to that of the
social sciences. An improved discourse would obviously be great, but he seems
to be equating math with the scientific method. We can try to get at the
complexities of economics with new tools and still verify the results.
Ultimately, math should be able to make a comeback when it develops the tools
to describe systems of this complexity. It's a lot like the brain: it is
obviously possible to describe the brain using physics & math (because it's a
physical system). BUT we're not there yet, and until we are, we get better
results with the collection of heuristics called "psychology"

~~~
yummyfajitas
_It just doesn 't work that way in economics. Even worse, the reductionism in
economics is unethical, because when it registered (somewhere) that humans are
not "objective, utility-maximising spheres" they more or less started
advocating that they /should/ be. That got us to "corporations are people" and
24-step daily checklists to "make better use of your time". It also made fast-
food the superior choice (time is money!), so at least the "spherical" part is
coming along._

Some citations are clearly needed here. In particular about the _normative_
claims you believe economics makes - as far as I know the field is very
strictly positive [1]. Economists will say that fast food is better _because
people are choosing to consume it_ , and most of those same economists will
discuss the topic over a lunch of artisinal kale salad locally grown by vegan
hipsters.

[1] There are cases where economists are clearly motivated by normative
concerns to draw a particular positive conclusion - e.g. that the law of
demand doesn't work for low skill labor. But that's a different critique.
[http://cafehayek.com/2016/12/41844.html](http://cafehayek.com/2016/12/41844.html)

~~~
matt4077
I guess the scientific term is
[https://en.wikipedia.org/wiki/Homo_economicus](https://en.wikipedia.org/wiki/Homo_economicus).
The classic experiment is probably the Ultimatum game. And that's so old,
you're tempted to say: see – they did notice the flaws in their theories!

Yes, economists will readily admit to these flaws and encourage you to keep it
in mind when evaluating their predictions and prescriptions. Unfortunately,
people aren't just marginally different from the models. Just yesterday I
violated transitivity of preferences when choosing lunch.

I did an evaluation of GDO growth forecasts for my bachelor thesis. None of
the institutions (Central banks etc.) managed to outperform a well-adjusted
random number generator.

~~~
jernfrost
I don't think economist always are that frank about the limits of their
models. E.g. Milton Friedman I think seemed to think that the world worked
mostly has homo economicus. He had some rather ridiculous examples. E.g. he
was touring a factory in Hong Kong and claimed workers had picked noisy and
hazardous work environments over more pleasant ones, because it paid better.
That strikes me as a guy with the head in the cloud lost his his theories.

Jobs don't exist in endless varieties like that. If I'd rather have a better
health insurance but lower paid job, I can't easily change to an almost
identical job, with just those differences.

I also remember him arguing why it was rational for Ford or GM to install a
cheap fix for dangerous fuel tanks. His straw man argument was that an
infinitely safe car would cost infinitely amounts of money. With such
arguments you can argue in favor of no minimum standards for anything. Never
mind that he failed to see the blindingly obvious problem. It simply didn't
make any economic sense because any car company making such a cynical
calculation would severely damage their reputation and thus their sales. It
only works for companies who manage to cover up.

And Milton Friedman is one of our most celebrated economists. Sure he create
some great theories, but he seemed also to not heed to typical advice of not
taking models too literal. He basically advocated policies based on rather
fundamentalists interpretations of economic models. If he could do that, then
surely lots of other economists would fail in the same manner.

~~~
tenkabuto
> He had some rather ridiculous examples. E.g. he was touring a factory in
> Hong Kong and claimed workers had picked noisy and hazardous work
> environments over more pleasant ones, because it paid better.

How is this a ridiculous example? Did he just invent it or was that indeed the
actual reason why they were working there versus a more pleasant place?

------
jernfrost
Nice to see some focus on this, as I believe so many of the ills of the
present days has been caused by this mathiness. I don't think math or
mathematical models are bad per say, but they have clearly been used in the
wrong way in too many instances. Ones has placed far too much faith in
simplified models of the real world.

We don't like the messy world of human interactions and so we have tried to
turn it all into math, while overstating the utility or applicability of the
models.

It is a bit like trying to create a mathematical models for determining the
quality of a persons character rather than simply relying on people's
subjective characterizations. We forget that humans have brains which are very
good at processing massive amounts of messy data. Instead of relying on human
brains why have outsourced the task to mathematical models which can't easily
deal with messy data, and thus simplify the world to the point where quite
essential characteristics are lost.

Also as a software developer I think we could gain a lot by employing more
agent based simulations to the economics field. I think too much of the
dynamics of a system over time is lost by relying so exclusively on
mathematical equations.

Too much of economic science also seems to have turned into a political
ideology for many on the right. The fact that a mathematical model predicts
inefficiencies from taxation in a free market, seems to make some people
believe it is inherently bad with taxation and it must be limited at all cost.

Such models should always be compared with real world data, where there has
never been found a clear evidence that higher taxes really retards economic
growth the way a simple model predicts. Naturally because an economy is
extremely complicated with many interdependent variables.

Higher taxes might cause worse allocation of resources but it might also allow
for better schools and thus better skills among workers increasing efficiency
more than is lost through distortions of taxations. Not claiming it is like
that, but giving food for thought about the idea that it is hard to look at
these models in isolation.

Mathematical models were used in the late 70s to argue in favor of high CEO
salaries. We know today that there is no empirical evidence that it worked.
Western economies are not growing faster and companies are not better run.
There is no provable difference between highly paid CEOs and lower paid CEOs.

This shows the danger of such mathematical models. They become self fulfilling
prophecies. Once people start using them, they keep using them because of
inertia and the tendency to conform and stick to traditions.

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nerdponx
Glad this issue is getting attention. It's one of the things that got me to
reconsider applying for an economics PhD.

