Math, reading, and purpose

Noah Smith recently smashed math in economics (specifically macroeconomics) stating:

Math can also be used as obscurantism; if every paper in a field starts with a dense thicket of formal statements and functional equations, it will be difficult for even very smart outsiders to come in and evaluate what the people in a field are doing with their time. Again, I doubt all but the most cynical macroeconomists would be intentionally obscurantist; they would just be subtly rewarded for doing things that ended up having an obscurantist result.

Paul Krugman then neatly defends maths, stating the following:

mathematical models are useful in economics: used properly, they help you think clearly, in a way that unaided words can’t.


What is true is that all too many economists have lost sight of this purpose; they treat their models as The Truth, and/or judge each others’ work by how hard the math is.

This all reminds me of one of my favourite quotes, by the semi-fictional character Liang Zhuge:

“I consider the pursuit of knowledge to be about what one learns, rather than what one can recall”

But as James has often noted to me in the past, there is as much danger, if not more, from going too far down this line.  Reading books and papers, writing, math, these all have a purpose in terms of helping us try to understand problems.  Having an understanding, and creating knowledge that helps us make decisions is the purpose.

Yes, people can overquote from books, they can use books and math as excessive signals of ability, and they can use these things to obsfucate points and prevent true knowledge being gained.  But this just suggests we need to be more careful about how we use maths and quotations from authority when building arguments and discussing these issues – not that these methods for doing so are inherently bad.

As we often do with economic problems, when we are thinking about communication we should be trying to clearly define what outcome is truly of interest, we should be figuring out how what we observe is related to these outcomes of interest, and the way the “primitives” and things we can control that are involved directly influence the things we observe and are interested in.  This is of course where good old Alfred Marshall had the idea!

  1. Use mathematics as shorthand language, rather than as an engine of inquiry.
  2. Keep to them till you have done.
  3. Translate into English.
  4. Then illustrate by examples that are important in real life
  5. Burn the mathematics.
  6. If you can’t succeed in 4, burn 3. This I do often.

The way economists communicate with each other and the public, and their ability to persuade others and shift priors with the argument they are making, is part of how we can tell if what economists are doing is really “relevant”.  That is why communication is important.  Or maybe an indication that we need to help incorporate price signals into the discipline.

UpdateByran Caplan at Econlog is more cynical, and about math in Econ more generally not just Macro.

I’ve heard such claims a thousand times.  But after enduring four years of Princeton economath, and publishing two pure theory pieces (here and here), I am convinced that most economath badly fails the cost-benefit test.

I believe Paul.  But I have a slightly different interpretation: His seminar audiences needed the economath because their economic intuition was atrophied from disuse.  I can explain Paul’s models to intelligent laymen in a matter of minutes.  Since they know no economath to blind them, they don’t need economath to grasp the obvious-once-you-point-it-out.

I am far from convinced by this – the maths provides both a “burden of proof” and a “conditional” element to the argument that is important for making sure we actually understand the intuition without relying on “common sense”.  At the margin there might be overinvestment in mathematical training – but I fear this is overstating the case!

I have seen “intuitive” arguments abused (namely over reliance on partial equilibrium logic) too often to be quite this cynical about maths.  Of course, the margin I work in is considerably different – I am not an academic, and spend significantly less time trekking the hard yards involved with mathematics.  And in that case, I would note that views on the “over reliance” of maths are then dependent on where you are sitting with reference to arguments – implying that the entire argument that there is “too much” maths must be seen as a statement about a specific area, not on economic debate in general.

Update 2Krugman, Caplan, Waldmann.

Note the selection bias in blogs – bloggers will tend to be people with a comparative advantage in written forms of communication.  I am not sure “economath” will get a fair trial in such a place.  I like Ryan Decker’s tweet in this context (Note, associated post):

And still, in today’s crop of anti-math posts, we see a lot of criticisms of math that also apply to narrative/heuristic theorizing.

3 replies
  1. jamesz
    jamesz says:

    I agreed with Noah and I don’t think it has anything to do with maths. It’s about the core assumptions of choice theory and maximisation being empirically falsified. Which they have been. If your macro theory fits the stylised facts but your microfoundations are empirically false then your model is a poor structural representation of the world. Economists know that and just don’t have anything better yet, but that shouldn’t be a reason to pretend the weaknesses don’t exist.

    • Matt Nolan
      Matt Nolan says:

      “Economists know that and just don’t have anything better yet, but that
      shouldn’t be a reason to pretend the weaknesses don’t exist.”

      Indeed – but I did not interpret the post as just saying this, it appeared to be saying that the use of maths led to this type of outcome. But this isn’t a flaw with the use of maths, this is a flaw with analysts in general – and I fear that even if we pulled the maths out, we would end up with even worse tacit assumptions. That was the point I was trying, poorly, to make 🙂

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