One amusing feature of math classes at the master's level or above is that they almost take pride in not motivating the subject in external terms. For example, here's a page from a canonical textbook in algebraic geometry.

1/
This does a good job of reminding me of how Lecture 1 in such classes often felt, which is roughly, "The motivation for this class is fuck you. Let k be an arbitrary algebraically closed field. Now..."

Which was not a problem when I had my own motivations!

2/
At some point it stopped being enough. Incidentally, I don't think my economics courses were much better in the way of giving some great external motivation: I just found a cycle of self-reinforcing curiosity that kept me happily studying that subject.

3/
This may even have some efficiency rationale if the purpose of the courses is NOT attracting the marginal student - as it probably shouldn't be in research mathematics, for example. It leaves more time for the hard stuff, and selects for students who have their own reasons

4/
It obviously has big implications in terms of WHO you get - people with a lot of "cultural resources" independent of their academic program. And in less dramatic ways, that seems true in all research subjects, not just math.

5/
(Math blogs improved the situation a lot in math - I found them only later, but it felt like they unlocked a secret code. It felt shocking that the information in them wasn't somehow part of the curriculum, but I guess that's just another way of saying what's above!)

6/
I am idly curious whether research subjects that are growing, whose main challenge is recruitment rather than sorting, are different at the front end. There also doesn't need to be any great economic reason for a subject to be this way - could be just culture!

7/
Anyway, in reminiscing I was struck by the intensity of this quality of math.

It also helps me understand how advanced students in my own subject probably feel when they lose motivation - it's much easier to connect with recalling my "outsider's" experience of math.

8/8
PS/ In defense of alegebraic geometry, it seems like Hartshorne is agreed to be an uninspiring prose stylist? A lapsed algebraic geometer says, "even though I no longer find algebraic geometry particularly interesting, it's more interesting than THAT."

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More from @ben_golub

23 Jan
Ok, my own answer to @JSEllenberg's question.

Here are some important statements that come up in economics:

"Nice estimators are consistent even in complicated models."
"Nice financial markets are informationally efficient."

1/
"Nice markets have price equilibria."
"Nice games have Nash equilibria."

The way these ideas are taught to Ph.D. economists in any field, even in core courses, involve very explicitly and extensively ideas extending ones in basic analysis.

2/
In particular, those ideas are: convergence (in fairly big spaces), integration and probability/martingales, continuity and fixed points.

Though you could get across aspects of these ideas at a high school level, econ grad school doesn't do them that way.

3/
Read 7 tweets
4 Jan
If you think Bean Dad is a symptom of a broken media ecosystem (and it certainly is), may I remind you of the SUMMER OF 2001.

Also known as the SUMMER OF THE SHARK. Networks and print media were *obsessed* with shark attacks.

1/3 Image
An irony is that there were actually relatively few shark attacks, but all I remember playing in the gym on CNN was shark stuff.

I also remember thinking that if this is what they need to amplify, then surely we were due for something bad. (In fact, we were.)

2/3
The old guard media with their vast editorial discretion amplify all sorts of dumb garbage: random kidnapping, shark attack.

Bean Dad type stuff is at least weirder and somewhat more democratic.

So I think critics of new media should recalibrate a little bit on old media.

3/3
Read 5 tweets
4 Jan
Was grateful to share at an #ASSA2021 session today a bit on what I've learned in teaching an undergraduate course on the Economics of Networks.

A short thread to serve as a focal point for any follow-up conversation.

1/
What networks is about (very rough and probably somewhat idiosyncratic description)

2/
I taught several variants of an undergraduate elective on this exciting and growing area. It was at the applied math/econ/CS intersection -- sometimes cross-listed, sometimes just economics but open to (and taken by) applied math, CS, other students.

3/
Read 27 tweets
13 Dec 20
A polite, scathing, and comprehensive reply by @jasndoc and coauthors to the "ergodicity economics" of @ole_b_peters.

@NaturePhysics erred in not finding a referee who would ask these basic questions of the authors, but glad a reply is out there.

nature.com/articles/s4156…

1/
This thread gives my own gloss and expansion of some points Doctor et al. raise.

Peters and co think there is a hidden assumption of economic theory: specifically, they think expected utility theory secretly assumes a mathematical property called ergodicity.

This is false.

2/
Expected utility theory makes 4 assumptions, which are stated precisely and concisely in every graduate textbook. Ergodicity is not among them.

EU is not the kind of theory that can hide assumptions: it is like Newtonian mechanics, not like Freudian analysis.

3/
Read 15 tweets
12 Dec 20
Let me very briefly jot down some notes as I read...

Take a basic static input/output model, and suppose we don't worry about nonlinearities in static equilibrium (as Baqaee and Farhi very productively have done).

Then it's easy to know which shocks matter for welfare...

1/
Just look at the Domar weights of the sectors, which is a fancy way of saying their (suitably defined) size.

All the network stuff boils down to one easily-measured statistic.

Shocks matter more when they hit "bigger" sectors.

2/
Liu and Tsyvinski make the point that this won't hold in an economy with adjustment dynamics.

When input demands increase after a negative shock, it takes time to build/activate capacity.

3/
Read 11 tweets
16 Nov 20
Some networks words
a few more
a few more
Read 4 tweets

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