Documenting six facts about the structure and dynamics of the LLM market, from Mert Demirer, Andrey Fradkin, Nadav Tadelis, and Sida Peng www.nber.org/papers/w34608
Posts by Andrey Fradkin
🚨Free data alert!! 🚨 Please share.
Large new dataset of Amazon product reviews, including full text and photos and product characteristics, with individual *reviews labeled as fake reviews*.
I believe this is the first publicly available data of this kind.
github.com/bretthollenb...
Thanks Erik!!!
3. There is substantial multi-homing, with users of the same app employing a mix of models.
This is still very preliminary work, so comments are welcome!
2. New model releases differ in the degree to which they cause substitution from existing models or expand the market.
Through the use of three case studies of model releases (Sonnet 3.7, Gemini 2.0 Flash, Gemini 2.5 Pro), I document three stylized facts:
1. New models are adopted quickly, with increased demand stabilizing within a few weeks.
🚨 New working paper 🚨
Demand for LLMs: Descriptive Evidence on
Substitution, Market Expansion, and Multi-Homing
A key question for the business of AI is the extent to which LLMs are differentiated from each other. I use data from OpenRouter to take a first look.
andreyfradkin.com/assets/deman...
Congratulations to Frank Verboven (@frankverboven.bsky.social) for being appointed as AER coeditor, handling papers in empirical IO and related fields. His term starts on July 1. I’m delighted to have him on our team. @aeajournals.bsky.social #EconSky
A new episode of Justified Posteriors just dropped. We discuss the recent papers of Chad Jones about existential risk and AI safety investment. Check it out!
open.substack.com/pub/empiricr...
Great point from @andreyfradkin.bsky.social: as a movement’s policies become more incoherent and harmful, the quality of “experts” who are willing to publicly defend it decreases precipitously.
It was fun engaging with the EconCS community!
In the latest episode of our podcast, Justified Posteriors, we discuss whether interest rates should rise in anticipation of AGI (as predicted by @basilhalperin.com). Our priors are quite different! Do check it out.
empiricrafting.substack.com/p/if-the-rob...
I'm just using their GUI. The papers submitted to MS are mostly available online already, so am not worried about leakage.
Write a referee report for Management Science based on this paper. Take the perspective of an economist who cares about causal methods.
But what if we're interested in studying AIs?
Can report that Deepseek writes perfectly serviceable referee reports of empirical papers submitted to Management Science. Note, I will still write my own, but you should update accordingly and ask it to provide feedback on your paper prior to submission.
I think your example of the rent curve is great, but doesn't represent much of social science research (based on things I referee). A lot of (most?) empirical papers are driven by hammer and nail thinking (something changed, run a DID), and not by careful descriptive work followed by modeling.
Perhaps the best David Lynch appearance was on Louie.
"Get that belly moving son or you're out."
www.youtube.com/watch?v=HlEJ...
Thanks, right back at ya!
It's a good time to mention that Seth Benzell and I have a podcast called Justified Posteriors discussing the economics of AI and other technologies. Our latest episode considers @timobres.bsky.social's paper on AI and Aggregate Growth.
empiricrafting.substack.com/p/beyond-tas...
EC 2025 will be held at Stanford from July 7-12. Itai Ashlagi and I are the chairs. The abstract deadline is February 3, and the paper deadline is February 10. The scope is inclusive of many topics across CS, economics, and operations research. Submit your best work!
Write down a vague idea of a model and it will write the math. Tell it to translate the math into code. Tell it to make it run quickly and to try other variations. I think the key speedups are actually in steps 2 and 3, which prevented most from using them.
Will be a huge complement to most of it, but the efficiency improvements for tasks in IO for me have been immense. So maybe IO / anything with structural modeling. But also, it might now be cheap to include a structural model in any type of paper, making econ papers even longer.
NBER Digital Economics and AI meeting at Stanford. Deadline December 16. www.nber.org/conferences/...
It's the best time ever to experiment with new coding tools. Coding with o1-preview is very effective for hard research tasks (structural modeling with pyTorch, functions for custom latex tables, computing Hessians). 4o/Claude do well on simpler data cleaning with just a little guidance.
I should mention that I'm a fan of one of the authors, Byrne Hobart, and his newsletter The Diff, which provides interesting analysis at the intersection of tech and finance.
Recently read Boom, the new Stripe book about bubbles. It wasn't a great book, but it did give a lens into what areas of academia influence discourse in Silicon Valley. Research in innovation is influential, but research in macro and finance is not. Any theories for why?
press.stripe.com/boom
This is a nice paper! Explains why home exchange networks can exist in equilibrium.
Why doesn't Boston have any Michelin star restaurants, but Atlanta does?
youtu.be/-ccVaNWow6E?...