Alberto Martín-Utrera @MartinUtrera

We stopped everything to write an answer (link below) to Paul Krugman's two posts of today (one informal, one with a simple model) arguing that Europe is broadly not falling behind the United States. The change measured by the Draghi report, he argues, is mostly due to growth in the technology industry, which has distorted GDP numbers without actually leading to higher standards of living. We should believe our eyes when we walk around France and walk around Mississippi. Krugman is wrong. The measures he uses understate European stagnation. This matters enormously. Divergence with the United States is the strongest evidence for reform in Europe. 1. The growth numbers Krugman compares the United States, France, and Germany at purchasing power parity in current prices. On that measure, France's and Germany's position relative to America has been roughly constant since 2000. But current price comparisons miss productivity gains in sectors where prices fall. If America produces twice as much software while the price of each unit halves, the value of American software output looks unchanged even though the volume has doubled. Most economists therefore use constant prices, which fix the base-year PPP level and apply each country's real output growth on top of it. American output growth has concentrated in tech, where prices have fallen tremendously as productivity rises. In terms of the volume of things produced, America has pulled away from Europe. 2. Is it all the tech industry? Krugman concedes this tech divergence but says it is not welfare-relevant. The American growth lead is an accounting artefact of measuring more iPhones at base-year prices, not a sign that Americans are actually richer, because Europeans buy the same iPhones at the same world prices. This is not the right way to think about the world today, as an earlier Paul Krugman would have argued. His model assumes tradable goods, interchangeable workers, marginal-cost pricing, and no profits. Each assumption fails. Most of what households buy is non-tradable: housing, healthcare, childcare, education. When American tech firms bid workers from haircutting to coding, American haircut wages rise. Germany has no growing tech sector to do the bidding, so German wages stay flat. Technology is not priced at marginal cost. Apple's margins are around 40 percent. Anthropic's inference margins are at 70 percent. The major platforms enjoy network effects, switching costs, and lock-in that hold prices well above what a competitive market would deliver. A large share of the productivity gains in technology stays as profit. A lot of the value of American technology dominance shows up in equity, not in wages. Apple, Microsoft, Nvidia, Alphabet, Meta, and Amazon together are worth $21 trillion, more than the entire combined stock market value of all European stock markets. Around 60 percent of US equity is held by American households. The median French or Spanish household holds almost no equity. The median employee at Meta, a company with almost 80,000 employees, earned $388,000 in 2025. This advantage is not going to go away. Krugman's own 1991 paper, cited in his Nobel prize, showed that comparative advantage in modern industries is produced by increasing returns to scale, specialized labor markets, supplier networks and the agglomeration of suppliers, workers, and ideas in particular places. Once an industry concentrates somewhere, the concentration is self-reinforcing. Europe is being pushed away from the next round of technology industries (AI!). 3. What about inequality? Another retort is that GDP per capita hides substantial inequality, and so even if America is rich on average, this is mostly due to the super wealthy. But despite the US's high pre-tax income inequality, it also achieves higher median incomes than Europe, in part because of such a high base, and in part because it actually redistributes more than many European countries. The cleanest comparison is median equivalised disposable household income: income after cash taxes and transfers, adjusted for household size and purchasing power. According to the OECD's 2021 numbers, the median American earns 30 percent more than the median Dutchman, about 31 percent more than the median German, and about 52 percent more than the median Frenchman. 4. What about hours worked? Krugman points out that while American GDP per person is higher, most of this is because Americans work more. For this divergence to be an hours worked story, Americans must work more relative to Europeans now than they did in 2000. The opposite has happened. Birinci, Karabarbounis, and See in a 2026 NBER paper show that about half of the American-European hours gap that existed in the 1990s has reversed by the end of the 2010s. Americans work fewer hours per person than they did in 2000, while most Europeans work more. 5. Is America not a bad place to live? Walk around Alabama and France: surely the former cannot be substantially richer than the latter? American cities often have poorer centres and richer suburbs or exurbs. European cities preserve richer and more attractive historic cores. A visit to a city as a tourist in America compared with a city in France will leave one having seen different spots on the income distribution. Americans in Europe go to the nicest and richest European cities. Rather than a walking around test, do a driving around test. Go to the periphery of any modern American city and see a level of new-built material wealth that is extremely uncommon in Europe, with thousands of enormous four- or five-bedroom homes. In the South, in places like Nashville and Austin, drive around the downtowns to see hundreds of luxury apartment buildings springing from the ground. This construction boom is replicated virtually nowhere in Europe today. The other question is generational. Housing often costs more in Europe than in the United States, despite the quality of the housing stock generally being much better. Europe has nice city cores but these are inaccessible to young Europeans. Consider the salaries available to entry-level workers. The starting pay for a London police officer is $57,000. In Washington, DC, $75,000. The entry-level Deloitte consultant job in Madrid pays around €28,000, roughly $33,000 per year. In Charlotte, the entry-level Deloitte job pays $63,000. There are many things to dislike about life in America. But relative to 25 years ago, the gap in material wealth has shifted dramatically in America's favor. siliconcontinent.com/p/european-sta…

I was honored to teach a one-day class at @EDHEC_BSchool on using AI in biz/econ research last week — from chatbots to automated research pipelines. 6 demos featuring work from @cblatts, @ben_golub, @pedrohcgs, @alejandroll10 and others. Slides + demos: github.com/velikov-mihail…

This discussion prompted me to add a "Recent" page to my "guide-of-guides". Up to 146 sources at this point. Chronological order might be the easiest way to keep track. velikov-mihail.github.io/ai-econ-wiki/

Antonio Mele @antoniomele101

5 months ago

Nice! The guides for economists are growing in number, time to put them all in a place maybe?

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Really proud of this paper! It started almost 10 years ago, and the key results stayed identical no matter which method, bells, and whistles we tried. And here's a podcast on our paper: tinyurl.com/consinret

Christian Julliard @Chris_Julliard

a year ago

🚨 "Consumption in Asset Returns" (w. @SBryzgalova & Jiantao Huang) forthcoming @JofFinance We use asset returns to uncover the elusive dynamics of consumption. Turns out, financial markets know a lot about future consumption—and it matters for both macro & asset pricing🧵👇1/n

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Honored to discuss the captivating and polarizing "AI-Powered (Finance) Scholarship" by Novy-Marx+@VelikovMihail, at @TaniaBabina's AI conference yesterday! Thought I'd share my view here 🧵

Back in pink - and this time to stay 🩷 Seven years after losing the Maglia Rosa on Stage 19 of the 2018 Giro, Simon Yates pulled the jersey back on after storming to the top of the general classification on Stage 20 of the 2025 edition. 📸 Sprint Cycling ____ 🇮🇹 #GirodItalia

Simon Yates in Maglia Rosa, one day before Rome. He returned to finish the job he started in 2018. Incredible scenes! 🩷 #GirodItalia

A review of the growing field investigating how the broad organization of financial markets affects the level and dynamics of asset prices, from Valentin Haddad and @tylersmuir nber.org/papers/w33434

💥Introducing openassetpricing!💥 a Python package for easy-breezy access to the Open Source Asset Pricing dataset. Just `pip install openassetpricing` and openap = oap.OpenAP() df = openap.dl_port('quintiles_vw', 'pandas', ['BM', 'Mom12m']) and you've got B/M and momentum.

The AI-generated podcast for our paper "A Multifactor Perspective on Volatility-Managed Portfolios" with @MartinUtrera and @RamanUppalProf is surprisingly good: notebooklm.google.com/notebook/0d189…

Victor DeMiguel @VictorDeMiguel2

2 years ago

"A Multifactor Perspective on Volatility‐Managed Portfolios" with @MartinUtrera & @RamanUppalProf: onlinelibrary.wiley.com/doi/10.1111/jo… Multifactor portfolio whose factor weights vary with market volatility and accounts for trading costs outperforms benchmark out-of-sample and net of costs.

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An academic paper has excellent empirical evidence & hypotheses that perfectly match the patterns in the data. One catch: AI wrote the hypotheses after seeing the results. Should this matter? New paper w/ Robert Novy-Marx on AI and finance research🧵 papers.ssrn.com/sol3/papers.cf…

"A Multifactor Perspective on Volatility‐Managed Portfolios" with @MartinUtrera & @RamanUppalProf: onlinelibrary.wiley.com/doi/10.1111/jo… Multifactor portfolio whose factor weights vary with market volatility and accounts for trading costs outperforms benchmark out-of-sample and net of costs.

Impressive how fast and efficient was the production process for our paper at @J_Fin_Economics. "Comparing factor models with price-impact costs" with @allen_lisicong and @MartinUtrera now in print: sciencedirect.com/science/articl…

Victor DeMiguel @VictorDeMiguel2

2 years ago

Comparing Factor Models with Price-Impact Costs, with @allen_lisicong and @MartinUtrera, accepted (pending uploads) to @J_Fin_Economics. Grateful to editor @NickRoussanov and an outstanding referee who helped us greatly improve our empirical contribution: papers.ssrn.com/sol3/papers.cf…

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Comparing Factor Models with Price-Impact Costs, with @allen_lisicong and @MartinUtrera, accepted (pending uploads) to @J_Fin_Economics. Grateful to editor @NickRoussanov and an outstanding referee who helped us greatly improve our empirical contribution: papers.ssrn.com/sol3/papers.cf…

📢 New Paper Ideas! "A Multifactor Perspective on Volatility-Managed Portfolios" Conditioning on volatility from a portfolio perspective (multifactor portfolios) outperforms the well-known single-factor volatility-managed strategies. Keep reading!👇

"Stock Return Anomalies: The p-hacking Debate" with Avanidhar Subra, Amit Goyal, Jeff Pontiff, and myself is up on @finmgmtassoc's youtube: youtube.com/watch?v=YRz9Ma…. My audio isn't great, so here's a🧵

@achenfinance @VictorDeMiguel2 @TomZ_Econ Thank you for the shout out Andrew! I very much enjoyed your discussion in SA!

Also want shout out Li, @MartinUtrera, and @VictorDeMiguel2 for showing how t-costs make the implementable efficient frontier concave (papers.ssrn.com/sol3/papers.cf…) and @TomZ_Econ et al. for direct estimation of portfolios weights with ML under t-costs (papers.ssrn.com/sol3/papers.cf…)

Discussed "Machine Learning and the Implementable Efficient Frontier" by Kelly, Jensen, Malamud, Pedersen at the AFA. My takeaways: 1) their closed-forms let you peek inside black-box ML portfolios and 2) anomalies are alive and well net of costs, you just need ML to find them

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🚨New 📜: Assaying Anomalies (w/ Robert Novy-Marx)🚨 ❓ How do we evaluate new return predictors in the cross-section of equities (aka anomalies)? 👉 We propose a protocol for understanding and testing the robustness of new anomalies 👇🧵 to follow (1/12) papers.ssrn.com/abstract=43380…