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The Economic Implications of Lying Silence
In February, a high school student from California who goes by the name Hannah Cairo accomplished what top mathematicians had failed to do for more than 40 years: disprove the Mizohata–Takeuchi conjecture. The breakthrough arrived in a 14-page preprint posted online, and its consequences stretch far beyond the realm of pure mathematics. Economists, policymakers, and risk managers would be wise to take note.
The Mizohata–Takeuchi conjecture had long been a comforting idea in mathematical analysis. It proposed that for certain kinds of ideal systems—linear partial differential equations with real analytic coefficients—local quietude implied global stillness. In other words, if the solution to one of these equations vanished on some open patch of space, then it had to vanish everywhere. That elegant rule served as a foundation for intuition about how waves, signals, and other smooth systems behave.
The new work destroys that foundation. Cairo constructed a counterexample: a solution that is identically zero in some open region—perfectly flat, no signal at all—but distinctly nonzero elsewhere. All the required conditions are met. The equation behaves according to the supposed rules. And yet the rule fails.
This disproof doesn’t just matter to analysts of the abstract. It should unsettle anyone who builds models or draws conclusions from partial observations—especially in macroeconomics, finance, and policy.
Much of economic reasoning depends on inference from incomplete information. When headline inflation looks calm, the assumption is that inflation expectations are stable. When payroll numbers drift sideways, the inference is that the labor market is steady. When systemic risk indicators flash green, the conclusion is that the banking system is safe. These judgments rely—often unconsciously—on the idea that well-behaved systems don’t hide active dynamics beneath locally quiet data.
The World Is Even More Complex Than We Thought
But if Mizohata–Takeuchi is false, even in the cleanest mathematical systems, then how much more cautious should we be in messier real-world settings?
Take inflation. Policymakers emphasize “core” readings, excluding food and energy, and often rely on just a few price categories to guide monetary strategy. But what if hidden pressures—margin compression, substitution effects, shrinkflation—are active outside the narrow slice being monitored? The surface looks calm, but deeper shifts are underway.
Take the labor market. A flat unemployment rate may mask falling hours worked, declining participation, or surging gig work. Until revisions arrive, the picture looks stable. Then the trapdoor opens.
Take financial regulation. Supervisors monitor a handful of big institutions and public signals. Meanwhile, risk accumulates in off-balance-sheet entities, unregulated credit channels, or new derivatives. A smooth dashboard does not mean a smooth system.
This is what the counterexample reveals: a system can appear dormant in one region while carrying real activity elsewhere, and there may be no mathematical way to detect it from the quiet region alone.
Economics has always wrestled with the limits of what can be known. The disproof of Mizohata–Takeuchi makes those limits sharper. It shows that even the most well-structured equations can admit hidden zones, blind spots, and silent storms.
That doesn’t mean we should abandon models. It means we should stop pretending they’re omniscient. Inference must be held lightly. Data gaps must be acknowledged. Local quiet must not be mistaken for global calm.
The math used to tell us that silence was a kind of proof. Now it tells us something else: silence can lie.
For those of us that thought that mathematical models of economy or weather or lots of other complex systems would not work well all the time, this is one of the reasons that they do not work. The idea of homogeneity over a field because they equations do not specifically denote any soft spots, meaning that the field being examined may not necessarily be homogeneous but, rather, hetrogeneous will make it very difficult for especially, economists to derive conclusions from something less than a complete sample of all the parts of the field. There are going to be a lot of measures that are now obsolete, but they were never good measures or metrics in the first place, were they.
Eh, sounds like pseudoscientific conjecture to me.
Economists have long known that their models have many types of instabilities, irrespective of this theorem.
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Economists have long known that their models have many types of instabilities, irrespective of this theorem.
Then why do they insist on making policy recommendations and screwing up the economy rather than let it control itself through the myriad decisions made by all consumers and producers? Their models are bogus and their conclusions seem to only fit the requirements of their paymasters, the clowns in the state.
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I'll just say that the regular population tends to be more supportive of bad ideas like rent control than economists are. Just sayin'. The problems with economic policymaking run deeper than the use of economic models.
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I will have to agree with you! But, why is it that the general population falls for the kind of isht like rent controls and free bus rides and any other free stuff? What are the public schools and universities pumping into their heads? I guess when you start framing everything into oppressor/oppressed ideology, taking from someone else or even if it is yourself is a good idea. At least the intermediary gets to stick some to his fingers!
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I wasn't familiar with this conjecture. From the description provided, I'm a little surprised that it was assumed to be true.
None of the examples struck me as particularly controversial. I think everyone knows that macro indicators are imperfect proxies at best and should be taken as suggestive rather than conclusive.
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Yes, however, the whole of the theories based on aggregates depend on the whole field being homogeneous. Heterogeneity blows those theories and the metrics and mesurements, as well as the resultant policy prescriptions, out of the water. It makes them much more less than even useless, they distract from reality and cause even more problems in the economy.
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Most economists understand that too. It's worth keeping in mind though, that just because a conclusion isn't mathematically certain doesn't mean mean it's wrong either.
The reason mathematicians couldn't think up an example that disproved the conjecture is because the conjecture holds under an enormous range of conditions. Mathematicians are insanely clever and will have thrown a lot at this problem. There's no reason to assume a particular case is in the class that doesn't conform to the conjecture.
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Most economists understand that too. It's worth keeping in mind though, that just because a conclusion isn't mathematically certain doesn't mean mean it's wrong either.
Then the question is: Why do they keep on using metrics, measurements and theories that discount this reasoning and, thus, making policy recommendations that are not working? Why would they do that, other than to support their paymasters, the clowns of the state? This is my problem with mathematical, empirical economics.
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It’s a very good question and I don’t know the answer. I always found it hard to square.
My sense is that they just don’t know how else to approach these questions that have so much interest, so they do something they know is wrong and hope they find something that’s at least useful.
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It’s a very good question and I don’t know the answer. I always found it hard to square.
Try this one on for size: they keep using them because those are the answers the paymaster/clowns are looking for! Like everyone else, the people making the economic analyses and prognostications wants to make a healthy, comfortable living! The best way to do that is to please your masters, isn’t it?