Diogo Lima @DFSL13

@puppyeh1 Now check Tempura... 😉

@SakiBigio Aren't we doing it already with, say, Amazon prime?

Frequency domain methods in action via @Shazam

Noah Williams @Bellmanequation

8 months ago

My "Uncertain Network Dynamics" paper uses frequency domain methods, which are uncommon in economics now. So Claude & I came up with a visualization tool. The transfer function G(jω) is the Laplace transform of the impulse response g(t). At ω=0, G(0) is the area under g(t). [1/3]

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R.I.P. Christopher Sims (21 Oct. 1942 - 14 March 2026) - a giant in macroeconomics and one of the finest human beings I have ever met -

‘Til the day I die, I will never understand how this wasn’t the end of it, right from the very beginning.

Hang it in the Louvre.

Alex Jeffrey Pretti. White male born in Illinois. University of Minnesota graduate, medical professional employed at the US Dept. of Veterans Affairs, avid outdoorsman & dog dad, legal gun owner with no criminal record. Murdered by his government 01/24/2026

Video message from Federal Reserve Chair Jerome H. Powell: federalreserve.gov/newsevents/spe…

MMT be like

Zelensky made a surprise visit to the frontline city of Kupyansk, which Russia claimed its forces had captured – but now Ukraine's soldiers "are achieving results" and pushing them back, the president said. Zelensky underscored the importance of the shooting war as well as narrative warfare: "Today it is extremely important to achieve results at the front so that Ukraine can achieve results in diplomacy. This is exactly how it works: all our strong positions inside the country become strong positions in discussions about ending the war."

Bessent's Key Square hedge fund at its peak: 10–20 research analysts for $5B. Fed: 411 PhD research analysts for $9T. That's 44–88× more per dollar on Bessent's side. His fund fell from $5B to $0.5B. Perhaps Bessent's most pressing economic problem isn't Fed economists.

Chief Nerd @TheChiefNerd

11 months ago

BESSENT: “The Fed is turning into universal basic income for PhD economists. I don't know what they do. They're never right … If air traffic controllers did this, no one would get in an airplane.” 🤣

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I joined Cambridge Economics in 2011 as an assistant professor. For historical reasons, Cambridge is still a bastion of heterodox economics - not so much in the department, but definitely in the colleges. (The college structure deserves its own thread.) 1/10

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 economics.sas.upenn.edu/people/alfonso… 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.

Friends and students occasionally ask me about the genesis of my 2005 QJE paper with Marc Melitz on “International Trade and Macroeconomic Dynamics with Heterogeneous Firms.” Here is the story, for anyone who may be interested. 1/n

So glad this is out. Our tribute to Bob Lucas at the JPE.

JPE @JPolEcon

a year ago

The November issue of JPE is now available at journals.uchicago.edu/toc/jpe/2025/1…. This issue features an In Memoriam to Robert E. Lucas Jr.--a tribute to his lasting impact on economics and as JPE editor. Contributors include T. Sargent, F. Alvarez, B. Jovanovic, and N. Stokey. #econtwitter

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Last Thursday, I had an interesting dinner with two prominent economists. Soon, the conversation turned to Joel Mokyr’s work and its relationship with @danwwang’s recent book, Breakneck: China’s Quest to Engineer the Future. Mokyr has long argued that Europe’s Republic of Letters encouraged broad scientific and technological innovation by providing a setting where new ideas could be evaluated and disseminated. For him, Europe occupied the ideal midpoint between political fragmentation and cultural unity: enough polycentrism to prevent the suppression of ideas by heavy-handed rulers, but enough common ground to sustain serious dialogue and a deep pool of potential patrons and protectors. But what if, as Wang cautiously suggests, the institutions of an open society are no longer necessary for scientific and technological innovation? (To be fair, Wang does not assert this as fact—he only hints at it). Elaborating on Wang, one could construct the following argument: 1️⃣ Yes, the Republic of Letters was essential for the flourishing of the scientific method that had emerged in the late Middle Ages and the Renaissance. 2️⃣ Yes, the institutions of an open society were necessary in the 19th and 20th centuries to create today’s framework of universities, academic societies, and scientific journals. 3️⃣ But no, once the scientific method and its institutional architecture are established, an open society might no longer be needed. 4️⃣ Indeed, China possesses institutions such as Peking University and Tsinghua University, and it performs impressively in mathematics, engineering, and computer science—fields central to scientific and technological progress. 5️⃣ Lack of political freedom likely still harms the social sciences (including economics) and the humanities, but those fields may be of secondary importance for technological innovation. 6️⃣ By limiting the rise of anti-scientific movements—such as the “decolonize science” trend on many Western campuses—or by avoiding resource allocation to “useless” humanities, China might even gain a comparative advantage. 7️⃣ The historical episodes of anti-science in totalitarian regimes (e.g., Deutsche Physik in Nazi Germany or Lysenkoism in the USSR) are not inevitable in a modern, technocratic Confucian state such as China’s, which prizes pragmatism. 8️⃣ In fact, pragmatism might help China avoid some of the West’s current problems: the creeping politicization of the natural sciences, rising bureaucratization, and resource allocation driven more by lobbying than by scientific merit. In short, have science and technology grown so powerful and self-sustaining that they no longer depend on their historical institutional scaffolding? Let me stress that I am not endorsing points 3), 5), 6), 7), or 8). Points 1), 2), and 4) are hard to deny. My regular readers know that I would never call philosophy or history “useless.” Moreover, I believe deeply that the institutions of an open society have intrinsic value—an argument far stronger in their favor than any instrumental one. Still, as a researcher, I must separate what I want to be true (that open societies are better for innovation) from what the evidence actually shows. So, what kind of empirical evidence could one gather to disprove claims 3), 5), 6), 7), and 8)? Finally, it’s worth recalling that similar anxieties haunted the West in the 1950s and 1960s, back then focused on the Soviet Union. Would it surpass the West in economic growth and scientific innovation? It did not. Hence, my prior distribution still places a higher probability on China not overtaking the West than on the opposite outcome. Yet China is not the Soviet Union, and overfacile historical analogies are always dangerous.

The European continent is still very innovative. Time to translate into leading companies.

Holger Zschaepitz @Schuldensuehner

a year ago

Good Morning from #Germany, which is no longer among world’s 10 most innovative countries. Acc to World Intellectual Property Organization (WIPO), which measures innovation strength of 139 nations, Germany has fallen to 11th place, overtaken by China. WIPO uses 78 indicators to

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What gets me upset about these complaints … every day a different one but all the same, is the subtle sense of wanting to impose their view on economists while claiming that’s what economists do to them. If this economics is bad do the good one - if economists are protective of their discipline, call it socio-physics, call it socio-economics or econo-sociology, or whatever … just go ahead. Do stuff instead of complaining the other guys are bad. Medieval theology is dead because of science, illuminism, not because of crying…. neoclassical economics could be killed by socio-economics. I do not know what Chang does - if he does anything research-wise besides complaining - and I do not like at all the economics (or whatever you call it) that @MazzucatoM does, but she does it with great success … that’s how it works. Chang should do a PhD program (or a sub-program into a program) - and push it to students … not FT journalist who have their own agendas … behavioral economists attacked economics and did it wirh great success - rational expectations macroeconomists did the same before …. they both had ideas, tools, … they pushed and won. Stop asking for neoclassical economics to open up to alternative stuff - do the alternative stuff closing up to neoclassical economics … and see if you can make it. Convince people your research is good by doing research. It takes a model to beat a model Show it.

Carlota Perez @CarlotaPrzPerez

a year ago

Ha-Joon Chang wrote in the @FT about the need to rejuvenate economics teaching (as @MazzucatoM and many others have been claiming). Not only does its teaching need to be open to variety, but the economics science itself needs to become interdisciplinary.

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