Geoffrey Fouvry
22.4K posts
@GraphCall
Connect the Financial dots. Analysis organized & presented in proprietary big-data & augmented web. Patent US 11,327,775 B2 ex hedgie 👇 get a free account
Bombshell: Leaked audio recordings prove Argentina's libertarian President Javier Milei is conspiring with the drug lord Juan Orlando Hernández -- the drug-trafficking former dictator of Honduras, whom Trump freed from prison. In a recording between Milei and the drug lord, Hernández proposed creating a right-wing fake news operation, with the support of the US government, in order to spread propaganda online to "eliminate the left" in Latin America, targeting Mexico, Brazil, Colombia, Venezuela, and the left-wing opposition in Honduras. The self-declared "anarcho-capitalist" Milei offered to contribute $350,000 USD of Argentine government money to help fund this disinformation operation, while millions of Argentines are suffering in poverty, and they have to eat donkey meat, because they can't afford local beef. Link: jornada.com.mx/noticia/2026/0…
🚨عاجـــــــــــــــل صاروخان إيرانيان أصابا فرقاطة للبحرية الأميركية خلال عبورها مضيق هرمز
It's certainly true that cross-country growth regressions suffer from all kinds of identification problems, but I think we've still learned far more about what generates material improvements in living standards from macro-dev than micro-dev. Empirical macro-dev research isn't bad just because it lacks clean causal identification. That's an impossible bar to meet for macro in general (at least if we want to explain a significant fraction of the economically meaningful variation). There are lots of very bad empirical macro-dev papers, of course, but there are also some good ones. Take Dani Rodrik's 2008 paper on undervaluation and growth (brookings.edu/wp-content/upl…). The main observation is that real exchange rate depreciation (relative to where a country's exchange rate "ought" to be based on its initial level of development) triggers persistent growth in developing countries, but not developed ones. Rodrik's hypothesis is that market imperfections (e.g. financial frictions) that are pervasive in developing countries disproportionately affect the tradable sector (manufacturing relies more on external financing than services in the Rajan-Zingales sense), and depreciation alleviates the effects of these frictions by raising the relative price of tradables. This is important because it tells policymakers that even when fixing the underlying institutional causes of poverty is hard, there may be some second-best options that involve distorting relative prices away from the laissez-faire equilibrium. The paper shows convincing evidence that this is indeed the operative channel: undervaluation reallocates resources from services to industry, and the association between growth and undervaluation is largely explained by this reallocation in a two-stage regression. (IVs can be used to learn something about economics, not just to get identification!) Rodrik is also not just cherry-picking Asian tigers: appreciation hurts growth in lots of African countries in his sample through the same channel. This, in and of itself, provides an important (if underappreciated) cautionary tale about the unintended consequences of foreign aid. Rodrik's identification isn't clean (as Mike Woodford explains in a follow-on comment) and the paper wasn't published in a prestigious outlet (it's in the BPEA), but I think it teaches us more about development than the vast majority of micro-dev papers published in QJE & AER. Moreover, macro-dev isn't just empirics, it's also theory and quantitative modeling. Take the 2019 Econometrica by Itskhoki and Moll (onlinelibrary.wiley.com/doi/abs/10.398…).* I love this paper because it illustrates how market imperfections create a role for government to accelerate growth, but also highlights the tradeoffs and distributional tensions inherent in doing so: "The optimal policy intervention involves pro-business policies like suppressed wages in early stages of the transition, resulting in higher entrepreneurial profits and faster wealth accumulation." Finally, even focusing specifically on the empirical part of macro-dev, it isn't just growth regressions. Like many other subfields of macro, it's also increasingly come to emphasize rigorous microdata work, despite the challenges in collecting this data in developing countries. My colleague, Diego Restuccia, exemplifies this trend with his work on African farm-level data. Overall, I think this research program has been far more successful than many people think. Conversely, the elevation of clean identification as the primary goal of research in development economics has been far less successful in yielding useful insights than many people think. As John Cochrane argues (grumpy-economist.com/p/causation-do…), the primary goal of economic research should always be to explain economically-meaningful variation, even if doing so is inherently messy. * This is the paper I tried (and largely failed) to write in grad school when I was thinking about Rodrik's empirical work. My attempt is preserved for posterity here: joesteinberg.com/pdf/rerpaper. It's amazing to look back and see how far I've come as a researcher in 15 years!
This 100MW data center in UAE is the largest solar powered datacenter in the world. There are currently 1,300 data centers in the world that are bigger than this one, but this one is the largest solar powered one. That’s 10 square kilometres of solar panels you can see. The datacenter itself is 0.02 square kilometres, so a solar powered datacenter is ~500x larger than a data center using any other form of power. A five hundred times larger site. UAE has some of the highest solar irradiance anywhere on Earth, it is an inhospitable desert. Averaging 9.7 hours of sunlight per day with average irradiance above 2,200 kWh/m^2. If you build this somewhere else, you need more solar panels because your irradiance will almost certainly be lower. Even if the world had an infinite supply of free solar panels, solar power will not be free. Anyone who has ever done major capital projects, who looks at where data centers need to be in the next 5 years and the next 10 years… we know it aint solar. Sorry. You struggle to even build a train track that’s 100 miles long and 10ft wide anywhere in the West, there is zero chance of build 100 square mile solar farms for GW compute. This is why people are talking about space compute. Deploying into space is one strategy to solve the constraints. But there are faster and more scalable strategies, that get you to mass deployment of multi GW data centers. There are strategies that also allow you to power the 10 billion robots and their newtonian actuators, that immediately follow the inference demand cycle. Step back and look at the full cycle of this industrial revolution… There will be billions of chips, but there will be trillions of actuators. This biggest part of this revolution is the embodiment cycle, and it’s big by a factor of 20 or 50x over the stuff that comes before it. There is no analogy in human history for the scale of this economy, of the demand it will place on energy and commodities. The humans own the Earth, and if you exist inside their legal system, they won’t let you turn the surface of their planet into glass. But they do want your chips and your actuators to serve their needs and desires. There is a way to do all of this, and so it will happen.
Iran eyeing mine-carrying dolphins to attack US warships in Strait of Hormuz trib.al/ohNTNFO
