Ben Golub 🇺🇦 Profile picture
Sep 17, 2021 16 tweets 6 min read Read on X
Hard to convey my excitement at seeing an argument by @ojblanchard1 for a networks perspective on three seemingly distinct kinds of fragility.

This is something that I have worked on for a few years now, and I hope that network theory can really help.

1/
I think it's right that there are commonalities between the fragility of

(i) production when institutions are shocked;
(ii) financial systems when asset values are shocked;
(iii) supply when shipping technology is shocked.

2/
One perspective that network theorists have been especially interested in is that there is something qualitative about some collapses: it's not just a matter of some things working worse, but the whole system entering a crisis.

3/
In two papers published in 2014-15, some network theory was brought to bear on the financial crisis. Acemoglu, Ozdaglar, and Tahbaz-Salehi showed that the same structures that are robust to normal shocks are especially bad for the rare large shocks.

citeseerx.ist.psu.edu/viewdoc/downlo…

4/
That is the large shocks trigger a crisis.

Simultaneously, Elliott, @JacksonmMatt and I looked at large stochastic financial networks, and found that diversification and integration can both exacerbate the network linkages that make a network susceptible to crises.

5/
Link mfm.uchicago.edu/wp-content/upl…

Blanchard emphasizes a similarity between domino effects in financial networks and dominoes of failure in real production. Though the economics is different, this analogy seems potentially fruitful!

6/
A key ingredient in the analogy is the high complementarity in production memorably discussed by Kremer (QJE 93). Complementarities in production are a huge deal! In finance, a few counterparties failing can destroy you. In production, it might take one small missing part.

7/
Blanchard and Kremer traced the implications of this when there are large institutional changes. But the aggregation of O-ring production has important implications in crises like the present one, with shortages everywhere.

8/
Of course, firms optimize against these risks. They maintain inventories and maintain multiple suppliers. What are the aggregate implications? There are two literatures that are relevant here. One is from operations -- e.g.,

pubsonline.informs.org/doi/abs/10.128…
There can be severe externalities, and it may not be in firms' interest to make themselves more robust: by correlating the kinds of shocks they are exposed to, they might make more profits but make the system more fragile in the aggregate.

10/
There are two threads one can follow from this point. One of them incorporates some of these forces into the production functions of a canonical networked production model and analyzes its reaction to (formally small) TFP shocks.

onlinelibrary.wiley.com/doi/abs/10.398…

11/
An exciting, growing literature using standard macro models to explore these themes is surveyed by Carvalho and Tahbaz-Salehi

annualreviews.org/doi/full/10.11…

12/
Another thread is more focused on network theory and investigates when we see very large cascades of shutdown. This is more analogous to the financial networks modeling via graph theory, and is studied in this recent paper:

bengolub.net/SNFF

13/
Supply network contagions can look quite different from financial contagions. This is because real complementarities are different: you need *all* inputs to produce (but you can have multiple options for sourcing each of them).

14/
Seoarately, Matt and have just finished the first draft of a survey trying to trace the commonalities Blanchard emphasized through a network theory lens.

(We're not quite ready to circulate, but I'll tweet soon!)

15/
We have a hope (which we articulate systematically in the survey) that network theory can help in unifying our understanding of the forces behind sudden, systemic disruptions.

15/15

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More from @ben_golub

Sep 24
Free disposal thought for theoretically inclined young economists:

Thinking through what AI means for the economy has a lot of upside.

Our toolbox is very powerful at structuring imaginative thinking about the big changes coming. Few others have these tools.

1/
Imagine a 2055 retrospective on economic thought over the past 30 years.

Seems very likely that a field called (roughly )"the economics of artificial intelligence" is the main character.

2/
Let's backward induct: many the big ideas in that field are going to be had roughly 2025-30.

It's unlikely that the really interesting questions will first be addressed with mainly empirical methods...

simply because empirical economics is fundamentally backward-looking.

3/
Read 8 tweets
Sep 23
This lovely paper by @SNageebAli, Mihm, and Siga — just revised for Econometrica — proposed a really striking theory of when voters rationally, but wrongly, think that policies are bad for them if they're good for others.



1/2 sites.psu.edu/nageebali/file…
Image
The paper has had a long childhood — I remember first seeing it in 2017 and finding the core adverse selection mechanism remarkable and compelling.

(Check out this study in abstract length, @ShengwuLi ! )

Hope it gets the attention it deserves in political economy.

2/2 Image
PS/

Scott Aaronson once defined an important theoretical idea as one that is hard to ignore in future discussions of the issue (in this case, zero-sum thinking), and I think by that standard, this is an important idea.
Read 4 tweets
Aug 7
In the WSJ, Steven Landsburg proudly used this brain teaser to make an argument about where economics teaching is going wrong.

Instead he illustrates what’s wrong with his way of doing price theory: sloppy economic thinking, way more impressed with itself than it deserves to be. Image
It's worth thinking through the "answer" he expects, which you can guess based only on knowing his personality (never great):

marginal cost of the fruit is lower for the monopolist. He writes, "In a competitive industry, prices are a pretty good indicator of resource costs."
Let's forgive the obvious incoherence of “in a competitive industry.” His answer is very bad even so.

What will happen to the profit of the monopoly? In the actual world, some of it will be invested in the capital markets, where it might support resource-intensive production.
Read 9 tweets
Apr 27
Small observation on research trajectory in economic theory.

When you first try to do it, most projects you propose are
(i) ridiculous/uninteresting to experts or
(ii) trivial
or, often, both!

This phase is very difficult and it's a big thrill to escape it.

1/
To escape, you have to sense

(i) what directions other scholars consider substantively interesting/promising;
(ii) what experts consider non-obvious.

Judging (i) and (ii) and doing well by these standards is pragmatically what makes young theorists successful
Succeeding at these is a fun, challenging sport.

So fun and challenging that it permanently reshapes how we direct our research.

I think perhaps because failing on these metrics is so painful in youth, once you can do well on them, you really prioritize that.

3/
Read 7 tweets
Jan 28
The notion that amazing papers should not get rejected is an odd one.

Any genuinely important idea is more likely to be strongly disliked. (Some reasons below in a short thread.)

To publish important work, editors have to be bold and overrule some negative experts.
Non-exhaustive list of reasons

1. The first technical work in a new paradigm is often crude and simple relative to the sophisticated and elaborate papers written late in a paradigm, when methods are being polished by a large community of experts in those methods.
2. Good ideas are often counterintuitive and have obvious drawbacks. They often prove valuable mainly through their later consequences.

Experts see the reasons not to pursue the counterintuitive paths: often, they have thought about and rejected these paths themselves before.
Read 7 tweets
Nov 23, 2023
I generally recommend

1. Constructing an n-by-m matrix whose rows are people and columns are issues (or dimensions of issues).

2. Finding the largest few and smallest few singular values.

3. Looking at the corresponding singular vectors in issue space.

(cont.)

1/
The top few singular vectors in issue space will tell you about "bundles" of issues along which there are considerable distances in the group.

(If these have high singular values, that corresponds to those differences explaining a lot of the group's variation in opinions.)
For example, you might find an axis of disagreement between Buttigieg and Warren-inclined democrats, visible across issues.

Buttigieg people would be in favor of things like market-rate housing, while the Warren people would focus on poking Jeff Bezos with a sharp stick.

3/
Read 11 tweets

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