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.
