
Milton Friedman's Thermostat - cousin_it
http://worthwhile.typepad.com/worthwhile_canadian_initi/2012/07/why-are-almost-all-economists-unaware-of-milton-friedmans-thermostat.html
======
klochner
Am I the only one who read Friedman's paper? [1] The answer to OP's question
[2] - "why are economists unaware of milton friedman's thermostat" - is
because the OP is misinterpreting Friedman's paper, and therefore has
misattributed this nonexistent "theory".

Friedman just said that the Fed acts like a thermostat, and in the linked
paper, claimed that the period subsequent to 1985 had increased price
stability owing to improvements in their understanding of inflation and it's
relation to the quantity of money, hence their "better thermostat".

AFAICT, the OP has made up this "Friedman's Thermostat" insofar as it relates
to economic forecasting, and now he wants to know why no one has heard of it.

As an aside, "exception that proves the rule" is an almost universally
misapplied phrase, that should only be used if you're really really sure you
know what it means (kind of like "begs the question").

[1]
[http://online.wsj.com/article/0,,SB106125694925954100,00.htm...](http://online.wsj.com/article/0,,SB106125694925954100,00.html)

[2] OP = Nick Rowe -
[http://worthwhile.typepad.com/worthwhile_canadian_initi/abou...](http://worthwhile.typepad.com/worthwhile_canadian_initi/about-
nick-rowe.html)

~~~
j2labs
The delivery is so emotionally charged too. It took several paragraphs of "I
can't believe no one gets this!" before we even got to Milton's theory.

~~~
gweinberg
It's worse than that. He rambles on, and then immediately shifts the metaphor
to a more complicated and less clear one. He should have just stuck with the
thermostat: if the temperature inside a house is determined by a thermostat,
the outside temperature has no correlation with the inside temperature.

~~~
salvadors
I suspect this is because he's already written several other posts (linked at
the bottom) with the thermostat example, so is trying a different example
here, in the hope that people might pay more attention this time.

------
rayiner
The level of discourse in policy-oriented economics papers is shockingly low.
My pet policy issue is spectrum management (allocation of radio frequency
ranges). Its a subject that lends itself to "neat" economic arguments. Ronald
Coase wrote an instrumental paper in 1959 suggesting we should propertize
spectrum and allow trading, which would lead to efficient allocations. It
saddens me how many policy papers I see from "think tanks" that completely
ignore the second part of that paper, as well as Coase's earlier work: the
efficient allocation assumes that trading spectrum has negligible transaction
costs. This works for say big TV stations in a city, not so much for say
allocating spectrum for personal wireless devices. In my research for a
seminar paper, I came across people who really should know better who ignored
crucial features of the problem domain, ignored transaction costs, ignored
considerations of lock-in, etc.

I'm tremendously skeptical of economics-based policy papers. A biologist works
on a paper for years, and concludes that this kind of gene expression might be
linked to this kind of nutrient deficiency. An economist at a "think tank"
works on a paper for a fraction of that time and gives advice on how to
structure a tens of billions of $ industry...

~~~
nickik
I like the saying, the economy does not need economist, just like evolution
does not need biologists.

The things we talk about today are not really that diffrent from what Adam
Smith argued for/against a couple hundert years ago. Today you have people
like Stigliz arguing against markets with much more sophisticated models then
the people that argued against Adam Smith. The people that argue against
Stigliz use much better models too. So where does that leave us?

I conclude that we should let the market be the market and not try to
influence it, its a far more complex thing then economist understand. Trying
to influence in to one direction will probebly just cause ten more things that
are unexpected. The market is not perfect, not even close, read Stigliz as a
good example of this but I highly doute that the goverment can improve the end
result in most cases. If you look at the pridictions of TOP economist at every
time X, the are almost always wrong and you get some other people that get it
right, these people are then wrong the next time.

I barly trust the goverment to do the easy things write, tweek a huge economy
is far from easy.

~~~
rayiner
I agree we shouldn't try to tweek the economy with government, but the
corrolary to this is that we shouldn't then raise up economic arguments to
keep the government from solving real problems.

Also, the knee-jerk cynicism about the effectiveness of government is
misplaced. E.g. government funds about 1/3 of all R&D in this country (and it
was as high as 2/3 in 1964). It is definitely not the least productive third
of the R&D expenditures. We crow about all these advances in medical
technology, etc, but many of those advances are the direct result of enormous
NIH funding. Our world-leading universities get well over half their R&D
funding from the government.

~~~
twoodfin
_but the corrolary [sic] to this is that we shouldn't then raise up economic
arguments to keep the government from solving real problems._

I disagree: The economic argument against price controls is a very good one,
and it's completely valid and useful to raise against the idea when
governments try to use them to "solve real problems".

~~~
nickik
Its kind of funny how even the few say 99% of economist agree on get
disregared in politics. Sure price controls are not that common anymore but
once a storm comes they are back. Ifs funny as economist would argue that,
especially in situation like that a flexible price system is imprtend.

Seams to me the goverment does what it does and if the can find economist that
agree with them then they are just happe they can clame that 'economist' agree
with what there doing. They are not actually listening to them.

------
eykanal
OK, I think I'm missing something. To quote the article:

> And no, you can not get around this problem by doing a multivariate
> regression of speed on gas pedal and hill. That's because gas pedal and hill
> will be perfectly colinear.

This is one of the reasons why you check for multicollinearity [1] when
performing multivariate linear regressions; aside from introducing significant
instability into the model, if your predictors are correlated, then you're
essentially measuring the same thing twice. The stated problem is actually a
good example as to why you should _avoid_ having highly correlated predictors
in a multivariate model; by blindly pursuing the regression despite the inputs
being correlated, we miss out on the fact that there is a relationship present
(i.e., the dependent variable (speed) is actually a factor of _both_ of the
independent variables (pedal height and hill slope)).

[1]: <http://en.wikipedia.org/wiki/Multicollinearity>

~~~
cynicalkane
You aren't missing anything. The author's article isn't about the optimal ways
to do statistics, it's a criticism of the informal economic discussion that
dominates policy, blogs, and pop-economics--and, according to the post, an
unfortunate number of actual econ papers--that says things like "economic plan
X doesn't work because there hasn't been a change".

The criticism generalizes to any statistical methods, though. You always need
to think about the underlying model before doing any kind of statistics in any
science.

~~~
chimeracoder
Yes, but I wouldn't say that "almost all" economists don't understand the
principle (as in the title). I would be more likely to say that "almost all"
reporters don't understand basic economics & statistics.

~~~
babblingdweeb
THIS. The problem lies with reporters lacking the basic econmic and
statistical background to either report the news and/or challange others they
are interviewing.

We are often surrounded by "armchair specialists" who know little about what
they are talking about, yet carry large opinions about said topic. I'm all for
constructive discourse, but that seems like a rare thing when talking about
hot topics.

------
kevin_morrill
Really interesting. Biggest complaint is the author takes a long time to
explain the thermostat model. Here is the definition:

Everybody knows that if you press down on the gas pedal the car goes faster,
other things equal, right? And everybody knows that if a car is going uphill
the car goes slower, other things equal, right?

But suppose you were someone who didn't know those two things. And you were a
passenger in a car watching the driver trying to keep a constant speed on a
hilly road. You would see the gas pedal going up and down. You would see the
car going downhill and uphill. But if the driver were skilled, and the car
powerful enough, you would see the speed stay constant.

So, if you were simply looking at this particular "data generating process",
you could easily conclude: "Look! The position of the gas pedal has no effect
on the speed!"; and "Look! Whether the car is going uphill or downhill has no
effect on the speed!"; and "All you guys who think that gas pedals and hills
affect speed are wrong!"

~~~
1337biz
I'm really looking forward to the comments on this one. Overall it is a
variation on the "correlation is not causation" theme and that defining
variables in a social setting is super tricky, if not to say impossible.

~~~
cousin_it
It seems to me that when people say "correlation is not causation", they
typically mean you can't learn about a causal relationship by just looking at
the correlation. The article makes the converse statement: you can't infer the
_absence_ of a causal relationship from the absence of correlation, or
equivalently (contrapositive), even when you know there is a causal
relationship, it won't necessarily lead to a visible correlation in the data.

~~~
endersshadow
Well, more to the point: The data analysis game changes entirely once you've
introduced an intelligent actor (in this case the driver).

~~~
cousin_it
Feedback processes don't have to be intelligent, e.g. the thermostat mentioned
in the title.

------
pdeuchler
I think the better question is why are (almost all) economists unaware of
basic economic theory?

Not to go off topic, but it's hard to take any "economist" talking head
seriously these days. I'm currently re-reading _The Road to Serfdom_ by F.A.
Hayek (highly recommend) and it's scary to see that even 60 years ago we
understood cycles and events that are still being ignored today.

The sad fact remains that real economic policy is no longer in vogue in
Washington or the L.A. TV sets. What _is_ popular these days is hand wavy
gestures that seem to please the most amount of people... the science be
damned.

Rather scary stuff.

~~~
Symmetry
I'm not sure why you think that the lessons of _The Road to Serfdom_ are being
ignored. Does anybody in the halls of power seriously think that Soviet style
central planning is a good idea anymore?

But the real reason that nobody pays too much attention to Hayek is that the
way countries recovered from the Great Depression worked entirely counter to
Hayek's predictions. Going off the gold standard worked. It worked _really
well_ for every country that tried it! The way that the events of the 1970s
conclusively disproved paleo-Keynesianism.

So now we have neo-Keyesianism as endorsed by people like Krugman and
Monetarism from people like Friedman and they agree about a lot more stuff
than Hayek and Keynes did. Now, they use different terms and have different
ideas about the transmission mechanism by which monetary and fiscal policy
influences aggregate demand, but everybody these days thinks of aggregate
demand as the thing that drives fluctuations in the business cycle. That's
progress, maybe in another 100 years economics will be a real science.

And please don't take the talking heads that show up on TV seriously.
Mainstream reporting of economics is just as bad as it is of every other
technical field.

~~~
pdeuchler
Hayek addresses redistribution of wealth as well as central style planning. He
even specifically notes that while they may differ at (sometimes important)
points, the general cycles have very similar results. So while not many people
still believe in central planning, they seem to have grasped the new theory du
jour of "spread it around", and in the end that is just as dangerous. Even so,
to ignore the lessons in the book simply because of a superficial difference
in ideologies probably isn't wise.

I think you're rather over simplifying things. I'm no economist, but I make it
my business to be at the least knowledgable about such things, and I feel
recovery from the Great Depression was more of a combination of New Deal
infrastructure, WWII profiteering and the resultant increase of wealth in US
that was then transferred to Europe to aid in the rebuilding. But then again,
that's probably one of the most complex economic time periods in modern
history so I don't pretend to know everything.

To address the gold standard, there are indicators that removing the gold
standard may have benefitted in the short term, but will hurt us in the long
term.

~~~
nickik
You have very strang opinions. One the one hand you speak well of hayke on the
other point you use the exact opposit of what hayek belived to explain the
recovery from the great depression.

I dont want to go into the hold Great Depression discussion, I just wanted to
point out that hayek would have made the argument that the New Deal made the
GD much longer, same with the WW2. The idea that a war can help the economy
would made hayek cry.

Watch this modern Rap-Video of Hayek vs. Keynes and listen closly when the
talk about the war.

<https://www.youtube.com/watch?v=GTQnarzmTOc>

------
mathattack
A similar problem happened at Harvard Business School. In the mid 80s they
found no correlation between GMAT scores and success at the school, so they
stopped requiring applicants to submit scores. This was a thermostat-unaware
view.

The real answer was that they were giving it the right amount of weight. If
they were overweighting the GMAT, unqualified people with high GMATs would get
in. If they were not underweighting it, the opposite.

Approximately 10 years later they did a correlation of student GMATs (which
weren't used for admissions purposes) and school success, and found that there
was indeed now a correlation.

The lesson was that if you're properly managing a factor, you won't see it in
the outcome. Or in the thermostat example, if you're properly managing the
thermostat, you won't see the changes.

------
dbecker
I am an econometrician... exactly the sub-population that the author faults
most for not knowing about Friedman's thermostat.

We haven't heard of the thermostat because it does not introduce new ideas to
us. If the data includes hill height, this is an example of multicollinearity.
If your data does not include hill height, this is an example of endogeneity.

Both concepts are taught in considerable depth in an undergraduates first
course in econometrics. It's a nice examples, but the author's claim that
these phenomena are outside are awareness shows a striking ignorance of basic
econometrics.

~~~
ScottBurson
Okay, fine, but then what do you think of the Casey Mulligan column that the
author links to (third paragraph)? It certainly seems at first glance to
contain instances of the error the author is describing.

(I am not an economist and have no position on this; just curious.)

~~~
dbecker
That's a great question, and I'm afraid I'm not going to do it justice. But
the place where I think you see the thermostat concern is in the paragraph:

 _A 1983 study by Lars Peter Hansen of the University of Chicago and Kenneth
Singleton of Stanford showed that short-term rates on Treasury bills and
short-term returns on stocks traded on the New York Stock Exchange had very
little correlation with consumer spending. Many empirical studies have
confirmed this sort of result (this comparison of inflation-adjusted Treasury
bill returns and business sector profitability is a recent example)._

This summarizes "many empirical studies" in a single sentence. Unfortunately,
it doesn't include citations.

There are a number of ways to address the "thermostat" problem. Each potential
solution only works in specific circumstances. I'd hope the underlying
research adequately addresses this concern, but it's hard to say without
seeing the research.

In general, summarizing "many" 40 page papers in a paragraph is inherently
difficult, and Mulligan seems to be especially vague here. If the claims here
have any credibility, it would only be through an "appeal to authority," which
most of us won't find very compelling.

So to answer your question, I'm unimpressed with the Mulligan column... in
part because we have no indication what problems there are in the underlying
analysis.

------
eavc
>And no, you can not get around this problem by doing a multivariate
regression of speed on gas pedal and hill.

I'm no expert on statistics, but this seems like a pretty basic scenario for a
statistical analysis to provide insight into. These two phenomena would be
perfectly correlated in both the time of appearance and the degree.

You wouldn't be able to derive anything about the effect of hills or gas
pedals on speed, but you'd be given a powerful clue as to what's going on.

The second there's even a tiny imbalance between the two, you're given the
relationship to speed.

~~~
simonster
Well, in this contrived scenario, you can't tell what would happen if the
driver _didn't_ push down on the gas pedal while going up the hill. The
relationship between the gas pedal and the speed of the car is entirely
obscured.

However, in a real world system, the chance that there is zero imbalance is
also nearly infinitesimal. You could take the most skilled driver in the world
and you would still be able to pull out the relationship between gas pedal and
speed out of his driving pattern. Similarly, with the right variables and
enough data, you could pull a relationship like the one described here out of
economic data.

(As a side note, I think the way in which this article is written is pretty
obnoxious. The first 500 words are dedicated to the author congratulating
himself for being aware of an idea that he hasn't even explained yet.)

------
DannyBee
As a meta-comment, this article dances around and only after an entire page of
text, does it get to the actual idea.

------
nhebb
It sounds like the problem boils down to the difference between understanding
a scalar (speed) and a vector (velocity). So economics would need a way to
represent economic forces similar to the way a free body diagram is used in
engineering and physics. And in order to do that, you would need an economics
coordinate system. And therein lies the problem of economists building models
without known or absolute reference points. Economics != Physics, QED.

~~~
alanctgardner2
Nope, absolutely not. The problem is that they have a feedback system which is
attempting to maintain a constant value. This could be a driver pressing the
gas, a thermostat (as listed below), or the Fed trying to modify interest
rates to achieve a result. The problem is, if you do everything right, and
there's no economic collapse, people wonder why you need to exist. If there
is, you're clearly useless.

I fall into this a lot, but I really hate the attitude of engineers and
scientists believing that everything can be solved by approaching a problem a
certain way. We have this idealized, fetishized approach that if you define
all your axioms and have a rigid framework in place, you can solve anything.
Of course, as soon as you try it in real life, especially in a field like
sociology or economics (which, of course, we deride as not being scientific
enough), it all goes to hell.

I would recommend that anyone who is of this opinion - that economics,
psychology, linguistics, et al are not scientific enough - actually take a
course in that area. What you find are: people who are experts in a field are
really smart, yes, they have thought of that already, no, it didn't work. It's
a very humbling experience.

~~~
cousin_it
> _The problem is, if you do everything right, and there's no economic
> collapse, people wonder why you need to exist. If there is, you're clearly
> useless._

Interesting. Can we come up with some general method of answering questions
like "does institution X really play a part in keeping parameter Y stable?"

~~~
alanctgardner2
The problem is: the only way to detect this, as the article points out, is for
them to stop doing their job well intentionally. You either wreck the
perfectly good situation you have locally, or you find some other place where
everything is terrible, and you compare the two. This is one of the reasons
why scientific methods are hard to apply in non-experimental situations: you
can't necessarily destroy the national economy 'to see if it would really
work'. It's the same as informed consent in medical experiments, just on a
larger scale.

------
pseut
I have no idea if the author describes "friedman's thermostat" correctly, but
to say that Economists are unaware of the phenomenon he describes is beyond
absurd (disclosure: I'm an Economist!).

There's another way to find the relationship between the gas pedal, slope, and
speed that the author did not mention (but is somewhat related to some of his
suggestions): write down a model of the driver that assumes he or she uses the
gas pedal to try to keep speed constant:

E_{t-1} speed(gas_t, slope_t, parameters) = const (eq1)

where E_{t-1} is the conditional expectation of the period-t term, given the
information available in period t-1. Maybe speed should be nonparametric, but
that will introduce some new problems in estimation; maybe you know enough
about physics to write down a parametric formula for speed; whatever, the
exact details of speed(.,.) are kind of beside the point for the author's
argument.

Now,

speed(gas_t, slope_t, parameters) - E_{t-1} speed(gas_t, slope_t, parameters)
(eq2)

is a martingale difference sequence when "parameters" is set to their true
value, so the sequence equals zero in expectation for all t, assuming the
model is true, and that can be the basis for estimation through, say,
Generalized Method of Moments. Because combining (eq1) and (eq2) gives us

E speed(gas_t, slope_t, parameters) = const,

so you can estimate the parameters as

\hat parameters = argmin (average_over_t speed(gas_t, slope_t, parameters) -
const)^2

Everything I laid out is an extreme simplification of the DOMINANT STRATEGY in
applied macro (with, in all likelihood, some errors due to sloppiness). Now,
for any realistic economy, it's going to be hard as hell to write down a
sensible formula for "speed(.,.,.)" and since there aren't that many years
since WWII (which is kind of seen as the beginning of the "modern" economy)
there isn't a lot of data to estimate the model, but neither of those issues
have anything to do with the author's "critique" and are basically the
direction of almost all research in macro.

~~~
Nick_Rowe
pseut: "so you can estimate the parameters as

\hat parameters = argmin (average_over_t speed(gas_t, slope_t, parameters) -
const)^2"

No you can't.

Think about it.

1\. If the driver has as much information as the econometrician, setting both
parameters on slope and gas equal to 0 will fit the data equally well.

2\. If the econometrician observes slope and gas and speed with error (as will
almost always be the case), then GMM will estimate both parameters on slope
and gas as zero (if those 3 errors are independent of each other), even if the
true parameters aren't.

3\. If the driver observes gas or slope with error, and the econometrician
doesn't, then the econometrician can indeed actually estimate the parameters.

How likely is 3? Only a stupidly arrogant econometrician would assume a priori
that he knows better how to drive the car than the guy actually driving it.
(OK, maybe the econometrician has final revised data, and the driver has only
real time data, and the final revised data is better than the real time data.
But even then the driver will be observing other indicators that the
econometrician doesn't have data on, so the econometrician will interpret the
driver's response to those omitted variables as "gas pedal shocks", and will
screw up the estimation royally.

Yep, all that Sims VAR stuff is wrong. Here, read this.

[http://worthwhile.typepad.com/worthwhile_canadian_initi/2011...](http://worthwhile.typepad.com/worthwhile_canadian_initi/2011/10/james-
hamilton-on-christopher-sims-and-identifying-monetary-policy-shocks.html)

You have just proved my point: economists don't understand Milton Friedman's
thermostat.

Forget your fancy stuff. Just STOP AND THINK about what you are really doing
when you try to estimate parameters.

~~~
pseut
I should have been a little more specific; the approach I described assumes
that the driver makes some errors, so the speed is not actually constant in
practice. That can be because the driver slightly errs in seeing the slope or
gas, or because of other sources of error (gusts of wind, maybe). Without that
variation, you're right, the system is unidentified. The larger the variation,
the better the identification. But none of this is news to economists, and
none fundamentally requires the econometrician to have better information than
the driver (although measurement error can matter in some circumstances, it
matters in a different way).

As I'm sure you know, these arguments (i.e. mainstream Economics is wrong and
ignorant!) are more convincing when they're accompanied by a model. DSGE
models have a lot of limitations, but they're pretty good for demonstrating
failure of identification. Monetary policy is tricky to identify, and I'd be
sympathetic to an argument showing that deviations from a Taylor-rule are bad
for identifying the effects of monetary policy shocks (lots of people would
agree with this, the interesting question is whether they're bad in
empirically important ways or just conceptually bad) but your car+driver
analogy seems like it's aiming to be broader than that.

~~~
Nick_Rowe
Thanks psuet. I'm not one of those guys who goes around saying "mainstream
economics is wrong and ignorant". Well, OK, we are often wrong and ignorant,
but people who aren't in mainstream economics are usually even more wrong and
ignorant!

This is just a particular beef I have. Because I keep on seeing examples where
economists make mistakes by missing this point. Like when economists try to
test whether headline or core inflation is better at forecasting future
inflation, and use those results to give policy advice on whether inflation-
targeting central banks should respond to core, headline, or both indicators.
All they are modelling is the central bank's mistakes, in responding too
strongly or too weakly to those indicators.

I think proper identification _does_ require the econometrician be (in some
sense) a "better" driver than the driver. If you can see the hills better than
the driver can, then you can see the effects of a hidden hill that you know he
doesn't see.

------
danielweber
Why does it 11 paragraphs repeating himself about how important this idea is?
I thought this was some set-up for a joke in which he never tells us about the
thermostat.

------
tomrod
In addition to klochner's comment, this is why economists rely on exogenous
variation. Any applied econometrician worth his or her salt would not say "the
gas pedal has no effect", but that the data doesn't rule out the hypothesis
that it does.

------
ignostic
I thought he was never going to get to the point. This entire post should be
about 1/5th the size.

------
baddox
There are exactly 500 words before a single bit of substance in this article.

------
vavoida
find that explanation shorter & faster, although polsci

[http://themonkeycage.org/blog/2012/07/31/milton-friedmans-
th...](http://themonkeycage.org/blog/2012/07/31/milton-friedmans-thermostat/)

------
wissler
This is a subset of David Hume's analysis of causality, see his "An Enquiry
Concerning Human Understanding."

------
SeanLuke
> And no, you can not get around this problem by doing a multivariate
> regression of speed on gas pedal and hill. That's because gas pedal and hill
> will be perfectly colinear.

Um, what? For a constant speed, which is this person's example, this claim is
completely false.

~~~
drunkpotato
When the incline increases, the driver pushes the gas pedal harder. Inline up
correlates with gas pedal up. It's a statement of relation between gas pedal
and hill incline. The claim is correct.

