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The results on age and success in startups: older founders are good. 1) The median age in the US for launching a 1-in-1000 fastest growing company is 45 & the average age of founders is 42 aeaweb.org/articles?id=10… 2) Worldwide, older founders beat younger sciencedirect.com/science/articl…

Slow growth isn’t evidence that we got the macro wrong; it means we need to focus on the micro. My post today in Silicon Continent. siliconcontinent.com/p/focus-on-the…

Solo per essere chiari, per quanto riguarda la rinata polemica sul latino, non c’è alcuna evidenza empirica che latino e greco aumentino le capacità logiche degli studenti. docs.iza.org/dp15985.pdf

#VeilleIGPDE - 3/4 🏭 Dans cet article OECD SMEs, Regions, Cities & Tourism, Giuseppe Cappellari, carlo menon et Wessel Vermeulen présentent le cas d'une région de Finlande 🇫🇮 où un chômage de masse s'est transformé en opportunité grâce aux politiques publiques mises en place ⤵️ oecdcogito.blog/2025/01/13/lif…

New randomized, controlled trial of students using GPT-4 as a tutor in Nigeria. 6 weeks of after-school AI tutoring = 2 years of typical learning gains, outperforming 80% of other educational interventions. And it helped all students, especially girls who were initially behind

And since it isn't clear to everyone who doesn't read the blog post - the fact that this is teacher-led is likely very important. We know that independent use of AI as a tutor can harm learning in some circumstances, because it gives the illusion of learning.

This is the most important data this year (so far). Most people don't understand the implications. Some of us do.

What can regional policymakers do when #masslayoffs strike their area? Our latest blog post discusses some lessons from recent experiences 🔗 brnw.ch/21wPXvY

Very insightful decomposition of the difference in GDP per capita, FRA vs USA - since 1890! Today, FRA has more capital per worker, but lower productivity, employment rate, and working time.

Representative survey of US workers finds that GenAI use continues to grow: 30% use GenAI at work, 1/3 of those use it every day And the productivity gains appear large: workers report that when they use AI it triples their productivity (reduces a 90 minute task to 30 minutes)

🔋How to power firms in less-developed OECD ➡️ Better Policies for Better Lives regions? Join the discussion at our next #spatialproductivity webinar to find out. 🗓️26 Feb 🕞15.30-16.45 (CET) 💻 Zoom Register 🔗bit.ly/3CWS1jQ

"On average across the OECD, skills are moving in the right direction over time: growing firms employ more skilled workers than declining firms. However, in Italy declining firms employ workers with better skills than growing and static firms". oecd.org/en/publication…

This is the AI graph that big companies (and many startups) haven’t yet absorbed. Models are getting both better and cheaper at very fast rate. You either need to skate towards where the puck is going, or else make a bet on when AI will hit a wall. Don’t assume a static world.

Tomorrow!

💡Place matters - productivity grows where skills, infrastructure and innovation come together. Join us to discuss policies to bridge regional disparities and drive effective development. 🗓️5-6 June 📍Trento, Italy 🖊️Register by 22 May More info 🔗 oe.cd/5ZD

BREAKING: Pro-EU Nicusor Dan wins Romania presidential election

💡Trentino’s productivity opportunities in 3 stats: - 42.5% of the private sector work for micro-firms - 3% of SMEs are high-growth, compared to 4.1% in Northern Italy - Working-age population expected to ↓7% by 2040 Read the report (IT/EN)🔗oe.cd/630

🚀 Quali leve può attivare il #Trentino 🇮🇹 per far crescere la #produttività, nonostante le sfide demografiche e le pressioni sul mercato del lavoro? Il nostro nuovo paper #OCSE (IT/EN): oe.cd/631 carlo menon Wessel Vermeulen

Europe's industry is at the epicentre of the new "China shock" as the two compete directly across more and more product categories. The biggest rise in overlap has been with 🇮🇹&🇩🇪 - no coincidence their industry sectors have fared the worst recently.

How much code now comes from AI? In new work with Simone Daniotti, Xiangnan Feng & Frank Neffke we estimate that by end-2024 about 30% of Python functions pushed by US devs on GitHub are AI- generated. Adoption is rapid but diffusion lags globally. How did we do it?