Enrique Ide

Everyone’s talking about @erikbryn, @econ_b & @RuyuChen’s excellent new paper Canaries in the Coal Mine. It shows entry-level jobs shrinking in AI-exposed occupations. But wait: earlier studies found AI helps novices most. So why are entry-level jobs disappearing? (1/n)

Looking forward to the @nberpubs Organizational Economics Working Group tomorrow. Amazing line up of presenters and discussants, follow the sessions live on YouTube.

I am below 6h every night since January. Is general anxiety and overwork from AI use reducing sleep? A deeply scientific study: Are you sleeping less post Claude Code/Codex adoption?

This is one of the points @ide_enrique and I make in this paper: The fact that digital brains can be scaled makes them fundamentally different. They will transform organizations.

Garicano @lugaricano’s Hierarchies model (2000) is a very interesting and important model in Organizational Economics. Let me explain it👇 Let π ∈ [0, ♾️) be the type of problem a firm faces. We order them by frequency, with a probability distribution F with strictly decreasing density f, which means ▶️low π = common problems ▶️high π = rare problems Workers choose what to learn (at cost c) and can ask other workers (at cost h). They first try to solve the problem themselves. If [0, π̄₀] is the knowledge set of a worker, then if π ≤ π̄₀ → problem solved if π > π̄₀ → the problem is passed to someone more knowledgeable So the probability of a problem being passed up is Pr(passed up) = 1 − F(π̄₀). This extends to multiple hierarchical layers with different knowledge sets, each handling progressively rarer problems. Optimal choice for the firm: handle common problems yourself, send rare ones up ⇒ hierarchy. Source: Garicano, L. (2000). Hierarchies and the Organization of Knowledge in Production. Journal of Political Economy, 108(5), 874–904. doi.org/10.1086/317671

🚨 “Job Transformation, Specialization, and the Labor Market Effects of AI” - new paper with @lukasfmann 💡 AI transforms what tasks we do at work. Our paper shows how, as a result, individuals' wages may rise or fall depending on their skill set. 🧰 We build a framework to quantify the effects of job transformation on wages, and characterize winners & losers in a genAI automation scenario from 3 perspectives. 👉Exposure: Moderate occupational exposure benefits incumbents, on average, while high exposure harms them; but: within any exposed occupation there are both losers and winners. 👉Skills: Value of social and manual-technical skills ⬆️, analytical/information-processing skills ⬇️. 👉Distribution: Low-wage workers gain relatively more than high-wage workers. 🧵 Summary thread & link to paper 👇

@ide_enrique has a really exciting paper Automation, AI, and the Intergenerational Transmission of Knowledge on this theme. He develops a model in which equilibrium automation of early-career work can be excessive, because experts cannot be fully compensated for the tacit knowledge they transfer to novices. By eroding the skills of future cohorts, this mechanism limits long-run growth.

Famously (there is a beautiful Works in Progress piece on this) in 2016, Geoffrey Hinton told an audience in Toronto that medical schools should stop training radiologists, since AI would soon outperform them at reading scans. Ten years later, there are more radiologists than ever, and they earn more than they did then. Hinton was right about the task, but he was wrong (so far!) on the future of the radiology profession. Times have never been better for them. The gap between those two claims, the difference between tasks and jobs, is the subject of a paper I have written with Jin Li and Yanhui Wu, and that we release today: "Weak Bundle, Strong Bundle: How AI Redraws Job Boundaries." (Very relatedly we are also finishing the first draft of our book "Messy Jobs" on AI and Jobs!! You will be the first to hear). We start from the observation that the growing literature on AI and labor markets measures the AI shock by task exposure: people count how many tasks AI can perform in a given occupation AI can perform, and infer that more exposure means more displacement. Eloundou et al. published a paper in Science in 2024 that started this literature, and many follow the same logic. The inference they make is that the more exposed tasks, the worse the outcomes. This is incomplete, because labor markets price jobs, not tasks. A radiologist does not just sell image classification, but does many other jobs: triages cases, communicates with other physicians, trains residents, makes the difficult decisions, and signs a diagnosis. The market buys a bundled service. The question AI poses is not whether it can do one task inside the bundle. The question is whether that task can be pulled out. Thread (1/3) dropbox.com/scl/fo/689u1g7…

Someone has created a gmail account using my first and last name (raffaellasadun@gmail.com) without my consent. If you receive an email from this gmail account please know that it is not me, and please alert me. This is an impersonator using my name to ask for money.

🚨 Calling scholars & practitioners based in Latin America: @ILASColumbia’s Edward Larocque Tinker Visiting Professorship (2027–28) is now open. ✅ 1 semester at Columbia + stipend, office space, housing support, airfare, RA support 📚 Teach/co-teach 1 course + 2 public lectures ⏳ Apply by March 20, 2026 🔗 ilas.columbia.edu/content/edward…

Fantastic post on AI's impact on productivity. In recent @JPolEcon paper building on foundational work by @lugaricano and @HansbergRossi, @ide_enrique and I propose another reason that may explain the disparity in findings about who wins and loses from AI.

Barcelona in June is beautiful. If there is a cool workshop on AI at the same time, even better. Consider submitting your best work on the economy at the other side of AGI.

Link: aeaweb.org/webcasts/2026/…

Fantastic review of the latest AI labor research by Danielle Li at the AEA meetings. She covers everything from micro-evidence (@shakked_noy, @orgRem, @erikbryn) to broader generalizations, including work by @davidautor, @ProfNeilT, & my own work w/ @EduardTalamas at @JPolEcon (building on @lugaricano). Missed it? Full talk below 👇

People looking for research ideas: think this through/nice place to do some empirical work! Ide and @EduardTalamas ((JPE 2025) did some of the necessary theory work, though with the same communication cost between agent and supervisor as between humans (seems may be lower!).

🆕Hot off the press! The January 2026 issue featuring Editor’s Choice ‘When Information is Not Enough: Evidence from a Centralised School Choice System’ by Kehinde F Ajayi, @willafriedman, @ProfALucas @RoyalEconSoc @OxfordJournals #econtwitter 👉bit.ly/4ql3cGD

Trending in #Economics: ooir.org/index.php?fiel… 1) Grandparental Care (@HECJournalTweet) 2) Marginal Returns to Public Universities (@QJEHarvard) 3) AI & Knowledge Economy (@JPolEcon) 4) Internet, Inequality & Regime Stability (@sjpeatses) 5) Who’s Afraid of Minimum Wage?

New CEPR Discussion Paper - DP20940 Automation, AI, and the Intergenerational Transmission of Knowledge Enrique Ide @iesebschool ow.ly/PbJn50XKMuS #CEPR_LE #CEPR_MG #CEPR_OE #EconTwitter

Dear All, just out: I did a long podcast conversation on the economics of AI with @EpochAIResearch. We discussed its impact on labour markets, recent evidence of complementarities and substitution, training and careers, macro/growth/interest rates, on AI regulation and Europe and much more. I hope you enjoy it. I cited recent research (list next) among others by (list below): @erikbryn @Danielle__Li @LindseyRRaymond @spjaffe @BharatKChandar @RuyuChen @LichtingerGuy @ide_enrique @EduardTalamas @a_auclert @HannesMalmberg1 @ludwigstraub @Ph_Aghion @DAcemogluMIT @baselinescene.

Program: nber.org/conferences/or… Livestream: youtube.com/watch?v=K3sD2Q…

Live today from Cambridge, MA! Org. Econ. @nberpubs Working Group (program and livestream below). Organized by @raffasadun and @andreapratnyc Papers by @joshgans, @I_Am_NickBloom, and @erikbryn (among many others) I’ll also be talking about my latest paper: Automation, AI, and the Intergenerational Transmission of Knowledge