Fabien Candau

Econ Pr. I work on international and urban economics issues, frequently (but not always) with environmental implications.
Also at @[email protected].

[Fabien Candau @Blogageco]

So happy to share our paper @WorldDevJournal
We show that:

🚢International trade of agricultural goods partly mitigates climate change
🚰But water scarcity in 2050 will have a strong impact on comparative advantages

HOWEVER not everywhere...check out!
https://t.co/S2fJjrfWFn

[LCP @LCP]

Près de 10 000 lettres adressées au Kremlin, révélées par une fuite, décrivent une armée russe minée par les violences internes, la corruption et les rackets. @oravanello revient sur ces témoignages transmis par les mères et les femmes des soldats

[Clément de Chaisemartin @CdeChaisemartin]

We've been using it for a few weeks to answer our users' questions, and its answers are usually very good, so we are now making it public.

Feedback welcome! #Econometrics #CausalInference #DifferenceInDifferences #DataScience

[Clément de Chaisemartin @CdeChaisemartin]

Need help with Difference-in-Differences? Meet ChatDID: a GPT specialized in modern DiD methods and the de Chaisemartin–D'Haultfoeuille estimators and software packages.

Try it here:
https://t.co/nl2fiqBP7z

[Elisa Dienesch @Elisa_Dienesch]

New working paper 🚨Using longitudinal French administrative data, the authors document that employment polarization after 1994 reflects major changes in labor-market entry rather than mass occupational downgrading or displacement of incumbent workers @cerfaust @AlessioMoro78

[Fabien Candau @Blogageco]

@JohnHCochrane quite short, but we are on X... here an interesting paper with a different explanation, but related I think https://t.co/3vsWsLcGLk

[fipaddict @fipaddict]

Mais dans l’attente, son décrochage pose une vraie question - en particulier pour les entreprises et administrations qui souhaiteraient déployer un modèle français pour des raisons de souveraineté et risquent d'avoir des résultats décevants à l'arrivée.

[Jesús Fernández-Villaverde @JesusFerna7026]

Let me explain why I believe modern economics is such a powerful tool for understanding the world. I’ll do this by discussing a great paper by Simone Cerreia-Vioglio, @UncertainLars, Fabio Maccheroni, and Massimo Marinacci, “Making Decisions Under Model Misspecification,” published in the Review of Economic Studies a few months ago.

Imagine I want to drive from UC San Diego to UCLA, but I’ve never driven that route before. I need to build a “model of the world” to guide me, which we usually call a map. Maps are simplified representations of reality. They can’t include every detail if they’re to be useful. Borges, in his short story On Exactitude in Science, makes this point beautifully. (In practice, I don’t draw the map myself—I use an app—but someone still had to make it.)

Because maps simplify, I can’t fully rely on them. Maybe last night’s storm knocked down a tree and closed a street, or there’s construction and the ramp off the highway in LA is shut down.

This uncertainty matters. Suppose I’m driving to UCLA for an important talk at 11 a.m. If the ramp is closed, I might need 15 extra minutes. When should I set my alarm to arrive on time, while still getting enough sleep to give a good talk?

The problem is that I can’t assign precise probabilities to all these contingencies. How likely is the fallen tree? Or new roadwork? Even the best traffic apps can’t capture every disruption, and some might happen after I’ve already left.

In economic terms, my “model of the world” (the map) is misspecified—and no matter how hard I try, I can’t fully fix that.

But sitting down and crying about misspecification doesn’t answer my basic question: when do I set the alarm? Too early, and I’m exhausted. Too late, and I’m late.

Simone and his co-authors offer a way to think about this. They start from the idea that we often hold several structured models of an economic phenomenon, grounded in theory. For example, a central bank might use a standard New Keynesian model and a search-and-matching model of money.

Yet, aware that each model is misspecified by design, the bank adds a protective belt of unstructured models—statistical constructs that help it gauge the consequences of misspecification.

The beauty of the paper is that it provides an axiomatic foundation for this protective belt (and even generalizes it to include a Bayesian approach). It shows that if a decision-maker’s preferences meet certain conditions —reflecting both rational and behavioral features— then those preferences can be represented by an augmented utility function that formally accounts for misspecification.

Crucially, we don’t assume that augmented utility function; we derive it. We start with general, plausible properties of preferences and prove that they imply such a representation.

That’s real progress. Instead of writing endless critiques of expected utility or rational expectations (as many have done for decades, with little to show), we now have a formal way to reason about misspecification—precise definitions, clear boundaries of validity, and awareness of what we still don’t know.

Take, for instance, a brilliant Penn graduate student on the market, Alfonso Maselli

https://t.co/rl2gu95V7t

His job-market paper pushes this frontier further. He studies cases where a decision-maker not only faces model misspecification but is also unsure which model best fits the data and can’t assign probabilities to them—what we call model ambiguity. In my example, the central bank is unsure whether the New Keynesian or the search-and-matching model fits better, and it worries that both might be incorrect.

If you read Simone et al. or Alfonso’s paper, you’ll see how misguided—and, frankly, cartoonish—many of the recent criticisms of economics on X have been.

First: the idea that economists don’t understand math or have “physics envy.” The math in these papers is subtle and advanced—utterly different from what physicists do (neither better nor worse, just distinct). An engineer transitioning into economics would find these tools unfamiliar.

Second: claims of ideological bias are unfounded. I have no idea about the political views of the authors, and I’d be surprised if anyone could infer them from the analysis—beyond vague guesses about typical academics.

Third: This has almost nothing to do with what one learns as an undergraduate, or even in first-year graduate school. If your knowledge of economics stops at an intro textbook, it’s best not to pontificate on the field’s frontiers.

Fourth: Is this science? Debating that word’s boundaries is pointless; every definition of “science” breaks down somewhere.

The Germans solved this long ago with the idea of Wissenschaft—the systematic pursuit of knowledge, whether of nature, society, or the humanities. By that measure, modern mainstream economics is clearly a Wissenschaft: a disciplined, cumulative, and highly useful effort to understand how the world works. Simone and his co-authors have demonstrated that beyond any reasonable doubt.

[Sid Gundapaneni @MacroscopeEcon]

I cannot understate how much I enjoyed Chad Jones’ talk at Hoover’s past weekly seminar. He’s an absolutely phenomenal presenter. A must-watch for anyone interested in growth, labor, or AI.

https://t.co/PthdpSDnpV

[Itai Sher @itaisher]

For no particular reason, if people are interested in ordinal vs cardinal utility and interpersonal comparisons in social welfare evaluation, here are two papers, one with a classic treatment and another with a new approach that I really like.

[Helmut🔅Reisen @HrReisen]

Chloé, Lagerfeld & Aghion:
Qui est Philippe Aghion, le conseiller de Macron devenu prix Nobel d'économie 2025 qui a grandi dans les défilés de mode ? | Vanity Fair https://t.co/8f0y5GB9yT

[Nicolas Cadène 🌍 @ncadene]

#Badinter #Panthéon
«Le fascisme ne se lève pas comme la tempête en une nuit. D’abord rampant, dissimulé, ordinaire, il progresse par les voix de la haine, avivée par les difficultés économiques. Il s’empare des cœurs avant de pervertir les esprits puis de prendre le pouvoir»☝️

[Maitre Eolas🇫🇷 @Maitre_Eolas]

Que ce soit très clair : tout ce que dit @HerveLehman ici est faux. Que ce soit un mensonge ou de l'inculture mêlée d'aveuglement idéologique, je l'ignore, et je m'en fiche un peu.

[Lulu NYT @LuluGNavarro]

I am obsessed with the soybean saga which to my mind isn’t getting enough attention. ICYMI: Because Trump’s tariff war, China has stopped buying US soybeans. Very bad for our midwestern famers. Meanwhile, Trump decides to bailout pal Argentina which turns around and sells their soybeans at a discount to … China. Our farmers doubly hurt. More reporting here. https://t.co/kxT27ZRhar

[Aymeric Pontier @aympontier]

Visualisation des courants océaniques de la Terre par la Nasa

[Fabien Candau @Blogageco]

@InseeFr top, merci!

[Fabien Candau @Blogageco]

bonjour @InseeFr je cherche des données de déflateur du pib sur disons 2000-2023, pas trouvé sur votre site, vous pourriez m'envoyer un lien vers la page, merci!

[Bia @BeatrizGietner]

We have a different post today
I've had to defend using ML in my own work, so I decided to write down my case for it - for students, colleagues, skeptics, and for anyone who believes we share the goal of solving problems with the best tools available :)
🔗https://t.co/bZyuq8MY4V

[Sylvain Catherine @sc_cath]

L'étude d'Antoine Bozio, Thomas Breda, Julien Grenet and Arthur Guillouzouic, à venir dans la Review of Economic Studies
https://t.co/az242mlsIR

[La Grande Conversation @_LaConversation]

👵👴 Passer d'un système par répartition à un système par capitalisation : quelles conséquences ?

Cela implique de faire financer deux systèmes en parallèle pendant plusieurs décennies. Le coût est colossal.

Retrouvez l'analyse d'@WeilEric ici : https://t.co/iIkTadzQwh

[Oleg Itskhoki @itskhoki]

Never have I felt so ashamed to be an American

"US joins Russia to vote against UN resolution condemning Russia war against Ukraine"
https://t.co/FpPvZ5Ihs0

18 countries voted against including Russia, Belarus, North Korea, Hungary, Israel & the United States. China abstained.