Gonzalo Varela

@suprabonds But the remarkable growth precedes the introduction of AI, so, *not* not surprising on account of that.

@gonwei not surprising when AI slop papers mostly come from CHina

This is really an amazing chart on the geography of #science. Great paper!

@alexolegimas In case Gross Domestic Product ceases to be good proxy for market production and correlate highly with many indictors of good life, we already have a ready alternative. aeaweb.org/articles?id=10…

My colleagues wrote this piece. #3 ok #RTAs becoming more important, even a force for liberalisation, in this tough environment, and #5 on the importance of #AI trade, are 2 highlights. How is global trade responding to shocks? Five questions blogs.worldbank.org/en/development…

In this increasingly #AI powered world, this becomes an ever more important principle: _Many things *can* be done, but not everything *should* be done_

Or to coal.

This is the saddest, yet best one!

The development economics of AI: Lessons & questions Across our AI series, @deenamousa & @oliverhanney spoke with researchers & policymakers on the AI & development debate. In this episode they take stock of their main takeaways. Read, listen & watch: voxdev.org/topic/technolo…

After a meteoric rise in adoption, the use of AI at work seems to be *falling*. We see it in the survey below, which had documented the rise using the same self-report methodology. We see a similar stall/drop in adoption across other sources as well (economist.com/finance-and-ec…). This is a puzzle worth discussing. The models and harnesses are getting better; we are seeing AI show up in productivity numbers (though noisy still). Is it due to surveys being self-reports? @PeterMcCrory would then be seeing different numbers in the actual enterprise adoption. Is it due to current uses being "saturated"? Unlikely to me, given what we know from theoretical vs. actual adoption gap (below).

The Taiwan Strait carries 13% of seaborne trade by value. Yet dodging it requires only a small detour. Our model suggests, however, that more dramatic scenarios are possible economist.com/interactive/br…

🆕 The development economics of AI @deenamousa and I finished our Ideas in Development series on AI this week by recapping what we'd learned, and outlining the important questions that remained unanswered: youtube.com/watch?v=uO8n2h…

Timely paper & congrats @jcpunongbayan! Last year we used an different (but related) method. Found in #Philippines CPI goes up by 0.3-0.5% when oil price up by 10%. The pass through from supply shocks (like the 1 we face) > than from demand shocks. openknowledge.worldbank.org/server/api/cor…

Bosses who are organised and energetic can handle more people than someone who is shambolic and tends to oversleep. But bosses who invest time in coaching their teams will probably want a narrower span than those bosses who don’t economist.com/business/2025/…

🚨 “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 👇

Create enough hallucinated legal arguments, flawed engineering calculations and backdoor-ridden code, and the slop vats fill faster than our capacity to tell good work from bad, writes Tim Harford.⁠ ⁠ Read his column on telling good AI from bad: ft.trib.al/j6Io85O

Happy to have contributed to this great report on #industrial policy. #Philippines did well in reducing poverty. Next challenge: a strong middle class. It requires creating better jobs in more complex activities. The report offers lessons on upgrading. Read it!

When we talk about #AI and #jobs in #Philippines we tend to worry about displacement in IT BPO. But look at what’s happening to demand for #AI related products, in which the Philippines is well positioned! More investment in semiconductors to help upgrading is the challenge!

The World Bank (WB) approved a USD800-million Development Policy Loan (DPL) to help the Philippines strengthen its fiscal resilience, attract higher-quality private investment, and equip its workforce with the skills needed for better and more productive jobs. pna.gov.ph/articles/12710…

Excellent news. Trade agreements reduce trade costs and uncertainty. Next step is reduce export costs for #SMEs, so that they can also take advantage of these #FTAs, double down on doing business reforms, and reduce time it takes for shipments to clear customs.

AI is advancing faster than any tech before it, boosting knowledge, productivity, and new markets. But most innovation is concentrated in a few countries. How can others catch up? A new report points to the “4 Cs”: connectivity, compute, context & competency. wrld.bg/p7Xa50XFXop