Wednesday, November 2, 2016

A list of valid and not so valid complaints about economics

There was a paper from NBER that Noah Smith tweeted last night that showed that log-linearization wasn't really a big deal in a nonlinear New Keynesian DSGE model. Since this was essentially an explicit example of where a common complaint about economics and Taylor series approximations wasn't really valid, I was inspired to construct a (potentially growing) list of complaints about economics when it comes to science and mathematics based on my many posts on the subject.

In constructing this list, I found that several of these posts are in the top 5 most viewed posts (namely, #1, #3, and #5) making me realize that I am probably mostly seen out in the econoblogosphere as a physicist critiquing various approaches to economics rather than as the crackpot developer of the information transfer framework. This may bode well for my forthcoming book which is more critique than information theory. 

Update 4 November 2016: I want to emphasize that this is a list of complaints about economic methodology with emphasis on scientific method and mathematics. It is not supposed to be a list of effects economics includes/excludes or complaints about specific models. They might appear as examples (e.g. I mention DSGE below), but are not the primary complaint. It is primarily intended as a corrective to many complaints in the econoblogosphere that "economics is unscientific because of X" written by a scientist, where the X's are the top line complaints below.

Update 13 March 2017: I am adding some popular books critiquing economics where they might fall with the complaints below.

We'll start with the invalid complaints ...

* * *

Not so valid complaints about economics

"Economics keeps only the linear terms of Taylor approximations"
As mentioned above, I wrote an entire post on this. Keeping linear terms in Taylor series is usually fine, so this doesn't work as a general criticism. It could potentially work against a specific model.

"Economics ignores nonlinear models"
Part of this is captured in the post on Taylor approximations and the new NBER article. However, I also wrote a post (that is now the 5th most viewed post on my blog, with follow-up) addressing one of the better empirical arguments against using nonlinear models. As Roger Farmer's beautifully concise post puts it, without hundreds of years of data we can't meaningfully tell the difference between a nonlinear model and a linear model with stochastic shocks.

"Economics makes unrealistic assumptions"
In science, unrealistic assumptions are made all the time. What matters is the end result of those assumptions. This is how physics operates all the time and it is called "effective theory", and "effective field theory" (what Weinberg called phenomenological Lagrangians) is a formalization of the idea for advanced theoretical physics.

I wrote two posts (here, here) about this subject in response to someone making this claim.

"Economics has too much math"
My background is in physics, but I've been studying economics and finance for over 10 years. My experience is that the level of math being applied is generally appropriate to the problem at hand. Some aspects of economics appropriately aren't very mathematical. Development economics comes to mind.

However, this complaint tends to be made about macroeconomics and the study of the business cycle. These are two things that we would not even know exist without mathematics. For example, no single person can see all the output or all the employed and unemployed people at once. This data must be compiled, which generates numerical quantities. Additionally, prices are numerical. How does one deal with the rise and fall of interest rates without mathematics?

I've written three posts (here, here, and here) on this in which I've tried to understand this charge -- what is it really trying to say? There seem to be many different reasons that range from genuinely feeling left out of a field that has an important effect on people's lives to avoiding testing one's theory against empirical data.

Added 5pm PT. There is a possibly valid version of this in that a lot of economics is written too mathematically; I address this below.

Paul Romer made his big debut in the econoblogosphere with a paper on what he called "mathiness": the lack of technical rigor (Romer used the words 'tight links') in mathematical arguments in economics.

I read through his paper and his specific claims make no economic sense from the standpoint of dealing with the reality of economic systems. It's now my 3rd most-viewed post. I think Romer has touched on something, however, and the issue is really about domains of validity (scope), scales, and limits (see below).

Added 5pm PT. Some people have different interpretations of what "mathiness" is (Romer himself felt misunderstood on this subject [also, Romer's response to my post]). Some people consider "mathiness" to be writing economics with overly formal mathematical symbols, which I address below.

"Macro is like string theory (in a bad way)"
Paul Romer's second big splash was with a devastating critique of macroeconomics. Many of the critiques are valid. However, he uses an analogy with string theory to say macro is unscientific that really misunderstands string theory.

* * *

Complaints that depend on framing

"Economics is bad at forecasting"
This really depends on a lot of factors. Long run or short run? Does the theory actually say the result is forecastable?

DSGE models are designed to forecast over the short run, but appear to be unable to do so -- or do so worse than simple stochastic models. That's a valid complaint!

"Economics can't predict recessions"
Following the complaint about forecasting, we look specifically at recessions. Are recessions random, or are they predictable?

Science can't predict earthquakes, but can predict where earthquakes might occur and levels of strain building up in faults.

Some economic theories predict recessions to be quasi-periodic. But much like the problem with validating the forecasting abilities of presidential election models, we don't have a lot of recessions to work with in the time series. Even a model that predicted the past 3 or 4 recessions (meaning it would have had to have been built in the 80s) could have done so out of luck (although if it matched the severity and duration of those 4 recessions, that might be a real thing).

One should probably hold judgement until we have some evidence that recessions are predictable.

"Economics is unscientific"
Which aspect?

This is not a binary condition, but rather a continuum. String theory in physics could be considered unscientific in the sense that it has little connection to data. However, it's a very scientific extension of standard quantum field theory (you could call it the quantum field theory of strings instead of string theory, and in fact that is the title of a string theory book). So something can really be unscientific in one way, but scientific in another.

As I wrote about here, some aspects of economics appear unscientific (to me) while other aspects don't.

"Economics is not empirical"
Again, this depends on what you are talking about. VAR models are entirely based on empirical data. Sometimes DSGE models aren't compared to data. Sometimes they are.

"Economic quantities are phlogiston"
Added 4 Nov 2016. I remembered this one from Paul Romer's paper, but I think Matthew Yglesias was the source of my own usage with regard to total factor productivity. Phlogiston was originally thought to be the substance contained by combustible materials that made them burn. You can see the obvious circularity in the definition.

Economics introduces many different quantities when describing economic data. Utility, total factor productivity, technology shocks. Some are unmeasurable (utility). Some of these are dangerously close to phlogiston (TFP).

However, introducing new and possibly unmeasurable quantities has long been a part of science. Sometimes they end up being phlogiston. Sometimes they end up being momentum ("quantity of motion" per Newton). It may be true that utility is unobservable. However the quantum wave function is also unobservable.

Therefore, this should be considered on a case by case basis. It is hard to say whether TFP or utility will end up being useful quantities. I personally don't think so, but I also can't rule it out.

* * *

Valid complaints

The identification problem
I think Paul Romer did a delightful job explaining the identification problem. Basically the idea is that any system with m equations in m unknowns will have way too many parameters. Expectations and nonlinear models make this worse.

"Economics does not appear to treat limits properly"
In looking at Romer's mathiness complaint (above), I realized that the way that economists treat limits (taking variables to zero or infinity) is, in a word, sloppy. This can lead to some serious problems such as producing contradictory results or nonsense. The issue can be related to dimensional analysis and understanding the scales of the theory (Romer cedes that he -- and therefore likely other economists -- ignore scaling).

The basic idea is that 1) 0 and infinity are effectively related by 1/∞ ~ 0, and 2) both zero and infinity are dimensionless (have no units). This means you can never take the limit as time t goes to infinity t → ∞ because one has units (time has units of seconds, quarters, or generic time periods). The same goes for t → 0.

Therefore, if you ever want to take limits, you need to understand what your fundamental time scale t₀ (with units of seconds, etc) is so that you can take the limit t/t₀ → ∞. In physics, we tend to write this as t/t₀ >> 1 (the double greater than signs read as "much greater").

The practical result of this is that there are a ridiculous number of undefined (or implicitly defined) time scales like t₀ hiding in economic theory.

Romer's mathiness complaint ends up being wrong because he didn't realize that his double limit makes zero sense because he effectively takes both t → ∞ and t₀ → ∞ in different orders and (as would be expected) ends up with nonsense.

Now you don't have to actually take the limits in order to have these implicit scales in your model. To my chagrin, I pointed this out about stock-flow consistent models (what is by far my #1 most-viewed post), and received a barrage of comments saying that I didn't understand what I was talking about from people suffering from the Dunning-Kruger effect.

"Economics does not deal with domains of validity (scope)"
Every theory, every model, has a range of inputs over which it is valid. In physics, we call it domain of validity (e.g. Sean Carroll uses the term here and here), but Noah Smith appears to think we call it scope conditions (which I think is actually a sociology term). Regardless of what you call it, economics doesn't address it much. Noah says: "I have not seen economists spend much time thinking about domains of applicability (what physicists usually call 'scope conditions'). But it's an important topic to think about."

It is. It is very important. It is closely linked to the scales and limits mentioned above.

Newtonian physics for example is valid for speeds v where v/c << 1 (the scope) where c is the speed of light (the scale [1]). When v ~ c, then Einstein's theory of relativity becomes important.

Because economic theories have implicit scales floating around, and does't take limits properly, one ends up with a confused mess when one tries to understand the scope of any particular model or formula. For example, I looked at the present value formula (more accounting than economics) in this light.

In a more interesting example, utility maximizing rational agents clearly fail when you have N = 1 agent as shown by many experiments. However, they appear to be a decent approximation when N ~ 20 agents in at least one experiment. As Gary Becker showed, you get the same results from an ensemble of irrational agents as you do from a single rational agent. I made the case that rational agents with many of the properties economists assume (but do not appear to be true of individual agents) could emerge in systems with a large number of agents.

What if there was a group scale of N₀ people (say, 100) [2] which told us that when N/N₀ >> 1 we can assume rational utility maximizing agents? This would make sense of the failure of individual (N = 1) human behavior to appear rational. The rational agent model is out of scope for individual humans.

I am not saying that is definitely true; it is just a possible resolution. It's also a possible resolution that would be clearer to understand if economics treated scopes and scales more rigorously.


Dani Rodrik's Economics Rules (although I don't necessarily agree with the solution)

"Economics is written too mathematically"
Added 5pm PT. I think some people see this as "mathiness" or "physics envy", but the following snippet (flagged by Duncan Black, himself an economist) is a not-uncommon paragraph from an academic economics paper:

I wrote about this here. I think writing papers in this style obscures more than it illuminates. As I wrote at the link: "There is quite literally no reason for an economist to refer to the real numbers as or even refer to real numbers at all. To say x ϵ ℝ+ is pretentiousness compared to x > 0." Overall, this is a superficial complaint; the mathematics underlying the terse symbols is usually relevant. It could just be written in simpler, less symbolic language. It really is just an academic culture of writing papers like this (something that "looks like an economics paper").

"Economics accepts stories too easily"
Added 5 Nov 2016. This is probably more a human failing than one specific to economics, but macroeconomic theories are used to produce narratives that are proffered with a certainty that far exceeds their empirical success at describing macroeconomies. I've compiled a list here.

I'm not endorsing the rest of his book or ideas, but Nassim Nicholas Taleb writes about this calling it the narrative fallacy.

Science is primarily as a defense against fooling yourself (Feynman), and narratives constructed by your left brain interpreter are a very seductive way to fail. Data first, story later.


James Kwak's Economism (although he makes the distinction that what he calls "economism" isn't really economics)



[1] For those interested, c comes from the Latin for "quickness": celeritas

[2] For example in physics, when the number of "agents" (atoms) N >> Nₐ (Avogadro's number ~ 10²³), chemistry and thermodynamics are the valid effective theories of Newtonian and quantum mechanics -- that differ from them quite extensively. Maybe something like this happens in macroeconomics?


  1. ""Economics does not deal with domains of validity (scope)""

    You don't think the macroeconomics/microeconomics distinction covers sufficiently the scope issues in economics?

    1. Individual micro or macro models will have their own domains of validity.

      Dani Rodrik actually says the scope of any model is limited to the problem it was designed to study.

      A really good example though is the ISLM model. Although it is not stated in its assumptions, the ISLM model is limited to low inflation.

      According to David Glasner (and something that I see as plausible) microeconomics requires you to be in or near a macroeconomic equilibrium (macrofoundations of micro).

      So there can be a lot more to scope than just separating the economics of nations from microeconomics.

    2. "Dani Rodrik actually says the scope of any model is limited to the problem it was designed to study."

      Generally, the problems are either macroeconomic (inflation, employment, growth) or microeconomic.

      There appears to be an IS/LM model for everybody that has something to say about the matter.

      "...macrofoundations of micro...

      The standard microeconomic model assumes full employment equilibrium.

      I can't see any distinctions beyond macro and micro and everything you said above is in keeping with that view.

    3. "Dani Rodrik ...

      Generally, the problems are either macroeconomic (inflation, employment, growth) or microeconomic.

      I see that you aren't familiar with Dani Rodrik. I can assure you that there are e.g. multiple macroeconomic models (hundreds of DSGE models that are NK or RBC, Smets-Wouters, AD-AS, IS-LM, Kydland-Prescott, IS-MP, Mundell-Fleming). Rodrik says that these different models have different scope (IS-LM for the Depression, RBC for the Great Moderation).

      There appears to be an IS/LM model for everybody that has something to say about the matter.

      It is well known that the IS-LM model (please read about IS-LM) treats inflation as exogenous. Economists don't state this as meaning it is restricted to low inflation, but that is effectively what it means to ignore inflation within the model.

      The standard microeconomic model assumes full employment equilibrium.

      Yes, full employment is exactly the macroeconomic equilibrium I was talking about.

      I can't see any distinctions beyond macro and micro and everything you said above is in keeping with that view.

      No, it isn't, and to quote Yoda, "That is why you fail." Let me illustrate with two concrete examples that I'll walk through step by step.

      First, let's start with macro ...

      1. You're dealing with a macroeconomic system
      2. This sets part of your scope to macro (vs micro)
      3. At this stage, you say there is no more scope to set
      4. However, there are multiple macroeconomic models
      5. Which model?
      6. Depends on scope of the model. Some models were made to understand the Great Depression low inflation/deflation. Other models deal with high inflation.
      7. Do you have low inflation or high inflation?
      8. Say it's low inflation
      9. We now have additional scope: 1) macro, 2) low inflation

      Now let's start with a micro model...

      1. Scope = micro
      2. Let's start with a typical utility optimizing agent model with sticky information
      3. The equations for sticky information become singular for stickiness parameter λ = 1.
      4. Therefore our scope is: 1) micro and 2) λ < 1.

    4. We are saying the same thing, only that, you again, with your penchant for creating straw men and condescension, embellish on what I have said. :-)

    5. We are saying the same thing

      We are explicitly not saying the same thing. You have said there is no distinction besides macro/micro:

      "You don't think the macroeconomics/microeconomics distinction covers sufficiently the scope"

      "I can't see any distinctions beyond macro and micro"

      I explicitly showed that there are distinctions beyond macro and micro (low inflation, sticky information/λ < 1).

      You say two categories encompass all scopes:


      I explicitly showed that this does not exhaust possible different scope with four categories:

      macro, low inflation
      macro, high inflation
      micro, sticky information
      micro, full information

      And 2 ≠ 4.

      Your statement is objectively wrong.
      It is not condescending to tell you that you are wrong.
      It is not a straw man argument to tell you that you are wrong.

      You also apparently don't know what a straw man argument is. I am literally contradicting a statement you explicitly made (you said macro/micro exhausts scope possibilities -- it does not).

    6. "I explicitly showed..."

      You didn't show anything.

      You made assertions.

      "You also apparently don't know what a straw man argument is."

      All the distinctions you made are within the the distinction macro/micro - that's all I said. The rest are assertions made by you.

    7. Ha! So now you're saying these are "within the distinction macro/micro". First off, this is still wrong.

      The distinction between low inflation/high inflation (or sticky vs flexible prices, or any number of modeling choices) in macro models is entirely contained in macro side of your original distinction. The macro/micro distinction does not contain as a subset the sticky/flexible price, high/low inflation, or stick/full information distinctions.

      You also did not say this originally. You originally said

      macroeconomics/microeconomics distinction covers sufficiently the scope issues

      And I showed that there are scope considerations that are not simply macro/micro. For example high/low inflation. This cannot be covered by a macro/micro distinction (i.e. macro/micro does not tell me whether I should use a low or high inflation model).

    8. ". macro/micro does not tell me whether I should use a low or high inflation model"

      Maybe not, but it is contained within the realm of macroeconomics.

      And you only assert that ISLM is a low inflation model because of the empirical relationships you say exist.

      Anyway, what I am saying is that there is a multitude of interpretations of the ISLM model. So your assertion may or may not apply to all of them, if at all to any.

    9. But that means there are more scope distinctions than just macro/micro. Macr

      Who cares about ISLM; it was just a concrete example. You are obviously stuck on a detail that is irrelevant to the argument. Could be sticky/flexible prices. Prices have been shown to become more flexible in recessions, for example. Could be other models that are high/low inflation.

      There are multiple variables involved in a macroeconomic model, therefore there are potentially multiple different possible domains of validity that the macro distinction tells me nothing about.

      Saying macro tells me nothing about whether interest rates, inflation, output growth, etc are high or low.

      Therefore your claim that the macro/micro distinction covers the scope issue is completely wrong.

    10. "But that means there are more scope distinctions than just macro/micro."

      Yes, but they are all within the distinction called macroeconomics.

    11. Nope.

      The aforementioned sticky information is a scope distinction within microeconomics.

      Pwned again.

    12. "The aforementioned sticky information is a scope distinction within microeconomics."

      Exactly. I have no problem with you saying this.

      Everything you've mentioned fits in with the macro/micro distinction.

      Thank you.

    13. You do realize that you can still be wrong even if you don't want to admit being wrong, right?

    14. "You do realize that you can still be wrong even if you don't want to admit being wrong, right?"

      Yes of course. But do you?

    15. How does the error in something you said reflect on me?

    16. It's only your assertion I made an error.

      You still haven't answered the question.

    17. I suggest you read this thread again. Your question was:

      You don't think the macroeconomics/microeconomics distinction covers sufficiently the scope issues in economics?

      My answer is no, and I gave several examples. It is not my fault if you don't understand why you are wrong.

      What you are doing is abusive and is called sealioning. People like you is part of the reason why many blogs get rid of comment sections.

    18. " People like you is part of the reason why many blogs get rid of comment sections."

      Personally, I don't think you're up to taking questions and dealing with differences of opinion.

      You're not very good at making your points intelligible. You brook no dissent.

      You think you're always right and everyone else is wrong - why bother having a comments section?

      You can pontificate in your blogs to your heart's content and not have to worry about dealing with the hoi polloi. :-)

    19. "People like you is part of the reason why many blogs get rid of comment sections."

      Hahah agreed. We all must be able to have reasonable and productive discussions.

      I don't think that things like that are productive: "only that, you again, with your penchant for creating straw men and condescension, embellish on what I have said"

      But who I am to say anything...

    20. Anonymous, you are still sealioning.

      You say you want discussion and say I just don't consider your points. However, if you look at the thread above, I have engaged with your questions. That I think you are incorrect does not mean I am not engaging with you or refusing to answer your questions. Again, evidence = these long comment threads,

      You on the other hand do not seem to be engaging in good faith. Simply repeating your point over and over is not arguing in its favor.

      If you've come to a point where you just repeat yourself over and over, the civilized way to proceed is to simply say "I disagree" and let it go.

      If I was trying to crush dissent, as the owner of this blog, I could just delete all your comments. I have not done so.

      That should be evidence enough that I am not operating from a position of arrogance or unable to withstand criticism.


      Cheers. I'm actually doing a bit of research on the Phillips curve, which is why I haven't gotten back to your comment below. I think you may be right in how the PC is treated today.

    21. "...."I don't think that things like that are productive: "only that, you again, with your penchant for creating straw men and condescension, embellish on what I have said"..."

      But this is what Jason does repeatedly.

      Look at this:

      "...If I was trying to crush dissent..."

      Where did I say he was trying to crush dissent?

      "...I could just delete all your comments. I have not done so..."

      I'll give Jason that much.

      "You on the other hand do not seem to be engaging in good faith. Simply repeating your point over and over is not arguing in its favor."

      Jason does the same.

    22. You said I "brook no dissent"; that you think that is different from "trying to crush dissent" is a bad faith argument.

      This demonstrates my point again that you are a sealioning troll, and not interested in genuine discourse.

    23. "You said I "brook no dissent"; that you think that is different from "trying to crush dissent" is a bad faith argument."

      By "brook no dissent" I don't mean you disallow or prevent discussion. What I mean is, when you are not getting your way, you will engage in various devices to divert attention away from the main argument, generally by creating all manner of straw men.

      Then it becomes ridicule, condescension and hubris.

      At least you are good for a wisecrack that is worthy of a chuckle. :-)

  2. I may be wrong, but I think people have a dfferent interpretation for the "mathiness" and "too much math" critics.

    For what I have read, people usually do not criticize the mathematics itself, but the way it is used.

    A lot of economists believe that, just because they have written a theory in the formal language of mathematics, then that theory is automatically true and its validity does not need to be supported by empirical evidence.

    Also, they believe that, if a theory was not written in the formal language of mathematics, it's automatically a bad theory that is unable to explain the economic phenomena.

    I, myself, believe that the mathematical language is excellent for communicating complex models. And I have trouble in understanding models that are not written in the mathematical form.

    But I'm sure that a mathematical proof is not enough to guarantee empirical validity and most economists ignore this somple fact. So I side with the "mathiness" critics.

    1. Hi André,

      First, I do want to say that these things are not what Paul Romer meant by "mathiness". Paul Romer was referring to slipping back and forth between mathematical and natural language in ways that make the math incorrect. My claim about "mathiness" above is that Romer's complaint is an invalid complaint.

      However, I do acknowledge that Romer's term has taken on a life of its own.

      The complaint you are offering would partially fall under the "written too mathematically" complaint, which I said is a valid one. However, I have never seen the "formalized iff true" (not a typo) version.

      This is similar to what hardline Austrian economists believe, but hardline Austrians actually reject most mathematics (appealing to just logic) and modern economics does not take them seriously.

      I am not aware of any example of a specific case where someone has said either "math makes something true" or "lack of math makes something false". Happy to be corrected!

      Regarding the latter, I tend to believe a lack of math makes something vague and potentially useless as e.g. a macroeconomic model, but it doesn't make it wrong. A good example is the whole "market monetarist" approach. It isn't mathematical.

      Unlike Darwinian evolution, most macroeconomic data consists of numerical time series, so it should be easy to produce a mathematical model. It may not be empirically accurate, but it should be easy. Why people don't go this extra step could have lots of answers. But I'd go with Paul Krugman here:

      First of all, whenever somebody claims to have a deeper understanding of economics (or actually anything) that transcends the insights of simple models, my reaction is that this is self-delusion. Any time you make any kind of causal statement about economics, you are at least implicitly using a model of how the economy works. And when you refuse to be explicit about that model, you almost always end up – whether you know it or not – de facto using models that are much more simplistic than the crossing curves or whatever your intellectual opponents are using.

    2. "....I tend to believe a lack of math makes something vague....."

      Math doesn't necessarily make an argument not vague either.

      I assert maths can be used to engender undeservedly an air of validity or completeness.

    3. "First, I do want to say that these things are not what Paul Romer meant by 'mathiness'."

      Well, maybe that's not exacly what he meant, I don't know. As you said, Romer's term has taken on a life of its own. But what I said is my interpretation about the general critics of the economic opinions/blogs I read about the theme economics & mathematics.

      I will repeat Noah Smith words, because maybe he is better than me to express things:

      "Personally, I think that what’s odd about econ isn’t that it uses lots of math -- it’s the way it uses math. In most applied math disciplines -- computational biology, fluid dynamics, quantitative finance -- mathematical theories are always tied to the evidence. If a theory hasn’t been tested, it’s treated as pure conjecture.

      Not so in econ. 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 if they don’t make sense in the context of leading theories."
      (I will not post the URL because I don't know if there is some sort of filter against external links, but that's easy to find in google)

      Also, a quote from Bill Mitchell:

      "A host of important real world production realities are assumed away (using a Cobb-Douglas production function approach) because they get in the way of a tractable mathematical solution. This is a standard problem in mainstream economics – the maths wags the dog!"

      I believe that kind of criticsm is legitim.

      "However, I have never seen the 'formalized iff true' (not a typo) version."

      The "not formalize -> false" part of the story is much more subtle. You don't see something like that stated explicity. But, if you are an academic, it's easy to observe general disregard to theories that do not have enough math. There is a certain mockery and profound prejudice against this kind of theory, as if they were inferior or useless. Actually, there are entire papers that are not even read by some scholars, because they think it's not real economics, it's just anthropology or something (as if anthropology was not a science)...

    4. *I meant "entire journals"

    5. Anonymous:

      "I assert maths can be used to engender undeservedly an air of validity or completeness."

      Assert away.

      I am not sure who (if anyone) is swayed by math in that way. Are you swayed by math? If you'd like an example of a straw man argument, you've provided an excellent example. The straw man in this case is someone who was swayed to believe something was valid simply because it was expressed mathematically.


      I completely agree with Noah's Bloomberg View piece. However, Noah is talking about ignoring empirical data -- a criticism that I did say was legitimate (at least depending on framing).

      The example I gave was DSGE models that aren't compared to data, but there are VAR models that are entirely based on data. Regardless, this is a complaint about the weight of empirical data, and not math per se. I believe economic theories are too mathematically complex, but that's really about being too mathematically complex given the data, and not the math itself.

      Also, I agree that sometimes certain ansatzes (like Cobb Douglas) or simplifications are used to make models tractable. However, this happens all the time in physics and nobody thinks physics is unscientific because of it. For example, I give you the quenched lattice approximation.

      If someone had come up to me in 2005 and said I was just neglecting real world fermion loop diagrams because it made the calculation tractable, I probably would have laughed. That is exactly the point of making the quenched lattice approximation.

      "Economists are not awesome enough to solve everything without simplifications" is not really a valid complaint and expects too much of human beings. It can be a complaint about a specific model and a specific approximation, but not a general complaint against economics.

    6. "However, Noah is talking about ignoring empirical data -- a criticism that I did say was legitimate"

      That's fair enough. I guess that's really my main point. But things are interrelated. Maybe it's impossible to separate them.

      I do believe that more frequently than not, the CAUSE for the lack of regard of empirical data is related to "mathematical confidence". It's a kind of ignorance, when the economist believes that, just because there is math in it, the theory is sound and valid.

      Also, I would add that I have nothing against simplifications. But I have a lot against simplifications that kill a model and make it unable to be useful to predict the real world. And I don't like when economists employ this oversimplified poor models to support strong claims.

      So, for example, when an economist claims that there is a trade off between employment and inflation (a claim that is present in most introductory books), he will evoke a mathematical construct called "Phillips Curve", and both naive students and "full grown" economists will give him legitimacy because of the formal mathematical construct. Because if mathematics says so, then it's true. It's proved mathematically. And the model even has a fancy name, "Phillips Curve". How can it be a bad model?

      But that model is at least a very poor oversimplification. The economist ignored not just evidence that tell us that there is actually no trade off, but he ignored all other very important aspects of the economy that are probably much more important to predict inflation or unemployment. Like, I don't know, fiscal and monetary policy, exchange rates, demography, politics, and so on.

    7. Andre,

      The Phillips Curve is not a mathematical construct, but was originally an observed empirical relationship.

      I think you might mean something more like the Euler equation (or see here). The Euler equation is a mathematical construct -- it's proven from a set of assumptions about rational agents using math. However, some economists have shown that the Euler equation does not seem to be true -- but some have said it is impossible to estimate (measure). Noah Smith writes about it here.

      But this story is evidence against your argument. People don't just accept the Euler equation because it was proven mathematically. They try to measure it and compare it to data.

      Unfortunately, the most over-simplified model, that things are simply random (AR, ARIMA, etc processes), is actually one of the best at forecasting inflation. Nihilism may be the best theory; there may not be any important aspects of the economy that are relevant to predict inflation.

    8. "The Phillips Curve is not a mathematical construct, but was originally an observed empirical relationship."

      It was originally an observed empirical relationship in a very restricted time period and geographical region. It was such a small sample that it amuses me how anyone tried to take any conclusions about the data. I guess it could be initially framed in what you call a valid complaint named "economics is unscientific".

      But now we have a lot of data and the claim "there is a tradeoff between employment and inflation" can no longer be sustained by evidence. There are some times that employment moves togheter with inflation, and there are times that it's the opposite, and the relationship is not clear.

      Why does introductory economics books keep supporting this claim? I believe that, although there may not not a single cause, one factor may be the reliance on the mathematical model, just because it seems a formal fancy thing.

      It's actually a very simple construct. It's presented as an equation or graph that shows a curve where unemployment has an inverse relation to inflation. But that suffices to blind a lot of people. After all, If there is a mathematical construct with a fancy name like "Philips Curve", than it must be valid. Who am I to defy it?

      I don't know, that's just my feeling... I could be wrong. In my understanding, equations have an dangerous powerful effect on economists... And "mathiness" is related to this sort of thing...

    9. I'd agree that equations can have a powerful psychological effect. However, I am not sure the most damaging ideas in economics are the result of equations. The EMH and rational expectation aren't really equation-based.

      And while you are right that the Phillips curve has become more of a mathematical construct, that hasn't prevent economists from questioning it e.g. here: