Emil Verner

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Emil Verner

Emil Verner

@EmilVerner

Professor at @MITSloan working on finance, macroeconomics, international economics, economic history, and other fun stuff

Cambridge, MA Katılım Aralık 2014
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Emil Verner
Emil Verner@EmilVerner·
New paper on bank runs with Correia and Luck: "Bank Runs With and Without Bank Failure" Questions: - What are the determinants of runs? - When do bank runs result in bank failure? - Can runs trigger the failure of healthy banks and amplify small shocks into large crises? - Are runs themselves the initial cause of financial distress or are they a symptom of deeper fundamental solvency problems in the financial system? What we do: - Apply LLMs to historical newspapers to uncover over 4,000 runs on individual banks in the pre-FDIC US banking system from 1863 to 1934. Capture the most famous runs (Bank of the US - Merge data on runs and other bank-level events discussed in newspapers (suspensions, failures) to bank-level fundamentals (harder than it sounds!) What we find: (1) Runs are considerably more likely in weak banks, but can also occur in strong banks, especially in response to negative news about the real economy or the broader banking system. (2) However, runs typically only result in failure for banks with weak fundamentals [see figure below]. Strong banks survive runs through various mechanisms, including interbank cooperation, equity injections, public signals of strength, and suspension of convertibility (3) At the local level, poor fundamentals necessary for runs to translate into large declines in lending. Moreover, bank failures (with and without runs) translate into substantially larger declines in deposits and lending than runs without failures. Overall takeaways: - Poor fundamentals are key for whether runs pass through into failure and have severe consequences for the broader economy. - The findings temper the view that small shocks can result in large jumps to bad equilibria via runs on demandable debt. Full paper here. Comments welcome. Given the methodology and evolving AI tools, we expect to make refinements to the runs database over time. Any input is welcome. static1.squarespace.com/static/58f6b1c…
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Emil Verner
Emil Verner@EmilVerner·
@ProfStefanNagel Unfortunately, it is! When presenting at Chicago, one has the privilege of being invited to set up an application with PaymentWorks and then being added as a UChicago supplier...
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Stefan Nagel
Stefan Nagel@ProfStefanNagel·
(I have no idea how our process looks like for outside speakers. If ours at Chicago Booth is nonsensically burdensome, please let me know!)
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Stefan Nagel
Stefan Nagel@ProfStefanNagel·
Rant of the day: The reimbursement process for seminar visits has really gotten insanely burdensome with universities treating a speaker getting a few hundred bucks reimbursement like a million dollar supplier.
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Bank for International Settlements
Hélène Rey, Professor of Economics at @LBS, is appointed as Economic Adviser and Head of the Monetary and Economic Department, replacing Hyun Song Shin, from 1 September 2026 bit.ly/4skt7zc
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Joe Hazell
Joe Hazell@JADHazell·
When interest rates fall, do people spend more? And if so why? We argue monetary policy affects consumption mostly because house prices rise when rates fall, and households borrow against their homes. With superstar coauthors Angus Foulis, @AtifRMian and Belinda Tracey. 1/5
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Francesco Bianchi
Francesco Bianchi@Francesco_Bia·
I am very happy to announce that Thomas Drechsel @td_econ will be joining @JohnsHopkins econ! A fantastic hire that further strengthens our department. Thomas has a very broad research agenda, spanning Monetary Economics, International Macro, HANK,... Welcome to JHU Thomas!
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Gauti Eggertsson 🇺🇦
Gauti Eggertsson 🇺🇦@GautiEggertsson·
I don’t get the concern: You tell Claude to write about some unspecified estimation on some unspecified dataset and it does that. So what? It’s interesting if there is an interesting idea that lets us understand the world — then great, let AI write more papers and our learning curve steepens. I see no indication of that in this example. Did the paper teach us anything? The author says he did not read it? Must be more specific to be interesting. We can run 1 million regressions and automate them. But will AI produce regressions that answer meaningful questions? If we could automate knowledge creation, cure disease, tame recessions, prevent the climate crisis, send people to Mars — GREAT! This strikes me as asking Claude a question and the answer is like in The Hitchhiker’s Guide to the Galaxy: 42!
Ben Moll@ben_moll

Every journal editor should read this: causalinf.substack.com/p/claude-code-…

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Tomas Williams
Tomas Williams@twilliams8·
New working paper: Demand Shocks in Equity Markets and Firm Responses Institutional investors now allocate huge amounts of global capital. When they mechanically buy/sell stocks, do firms actually change behavior? 🧵
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Emil Verner
Emil Verner@EmilVerner·
@fqroldan In your response, I hope you wrote: "I believe it's referred to as a squiggle, not a wiggle."
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Francisco Roldán
Francisco Roldán@fqroldan·
By far the most important comment I've gotten in referee reports (not joking). I think about it and re-implement it ~once per week.
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David Thesmar
David Thesmar@dthesmar·
seems to me a key point of the Citrini paper was that AI would increase competition (destroy firm margins). what seems missing in these discussion is that this predicts (1) an increase in productivity and (2) a reduction in profits --> this should be good for workers.
Emil Verner@EmilVerner

In all of the discussion of AI, r, and the Citrini post, I have not seen mention of Ricardo Caballero's recent paper on AI, r, and valuations. Some quick thoughts: Ricardo's model captures the second force @ojblanchard1 mentions, namely lower r from wealth concentration. Higher wealth concentration among the wealthy who have a higher propensity to save (as in work by @ludwigstraub, @AtifRMian, @profsufi) leads to a lower required return. Here is the mechanism: Optimism about AI => higher valuations (Tobin's q) => higher investment => higher capital => higher capitalist wealth => lower required return (nonhomothetic preferences over wealth) => high valuations (q) justified A key assumption is that AI capital is "labor-like" and so does not have diminishing returns over some range of capital. Another interesting feature: during the AI deployment, wages and worker consumption stagnate, and the labor share is lower (workers don't own claims to AI). What about a recession? The model doesn't have sticky prices/demand-determined output. But it does highlight the simple point that a recession is more likely if the AI boom crashes (drop in q). If there is no crash and the optimistic AI boom is realized, then (*speculating here*) it depends on whether the rise in investment and consumption of capitalists offsets the stagnant worker wages. But investment demand would likely be strong given the high valuations, which will push against a shortfall of demand. Also, my sense is that a recession would be relative to the rising potential output (a "growth recession"), not the counterfactual without AI. Again, this latter part is speculation... Here's a link to Ricardo's interesting paper: nber.org/papers/w34722

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Basil🧡
Basil🧡@LinkofSunshine·
It’s interesting how it’s common wisdom that boomers built wealth through inflating housing prices, when every dollar they put into stocks instead would have had 4x as big of an increase
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Emil Verner
Emil Verner@EmilVerner·
In all of the discussion of AI, r, and the Citrini post, I have not seen mention of Ricardo Caballero's recent paper on AI, r, and valuations. Some quick thoughts: Ricardo's model captures the second force @ojblanchard1 mentions, namely lower r from wealth concentration. Higher wealth concentration among the wealthy who have a higher propensity to save (as in work by @ludwigstraub, @AtifRMian, @profsufi) leads to a lower required return. Here is the mechanism: Optimism about AI => higher valuations (Tobin's q) => higher investment => higher capital => higher capitalist wealth => lower required return (nonhomothetic preferences over wealth) => high valuations (q) justified A key assumption is that AI capital is "labor-like" and so does not have diminishing returns over some range of capital. Another interesting feature: during the AI deployment, wages and worker consumption stagnate, and the labor share is lower (workers don't own claims to AI). What about a recession? The model doesn't have sticky prices/demand-determined output. But it does highlight the simple point that a recession is more likely if the AI boom crashes (drop in q). If there is no crash and the optimistic AI boom is realized, then (*speculating here*) it depends on whether the rise in investment and consumption of capitalists offsets the stagnant worker wages. But investment demand would likely be strong given the high valuations, which will push against a shortfall of demand. Also, my sense is that a recession would be relative to the rising potential output (a "growth recession"), not the counterfactual without AI. Again, this latter part is speculation... Here's a link to Ricardo's interesting paper: nber.org/papers/w34722
Olivier Blanchard@ojblanchard1

On AI and r* (inspired by the Citrini discussion). Standard effect: If AI leads to higher growth, likely to increase r* (higher investment, lower saving). Non standard effect: If AI leads to more inequality (enormous rents for the owners of AI, unemployment or low wages for those displaced), then likely decrease r* (saving rate of the rich much higher than saving rate of the poor). Which way does r* go?

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NBER
NBER@nberpubs·
A review of the evidence on the causes of bank failures points to a central role for insolvency. Runs often trigger failure of insolvent banks but rarely bring down strong banks, from Sergio A. Correia, @StephanLuck, and @EmilVerner nber.org/papers/w34853
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