Baumol's cost disease (Baumol & Bowen, 1966) explains why healthcare and other labor-intensive services keep getting relatively more expensive even with zero waste, fraud or greed involved — it is a pure productivity-growth mismatch.
Output per worker:
A_m(t) = A_m0 · e^(g_m·t) (manufacturing)
A_h(t) = A_h0 · e^(g_h·t) (healthcare)
Economy-wide wage (labor is mobile, so pay must
stay competitive with the fastest-growing sector):
W(t) = W0 · e^[(κ·g_m + (1-κ)·g_h)·t]
Unit labor cost of each sector's output:
C_i(t) = W(t) / A_i(t)
Relative price of healthcare vs manufacturing:
R(t) = [C_h(t)/C_h(0)] / [C_m(t)/C_m(0)]
= e^[(g_m - g_h)·t]
The wage-coupling term κ cancels out of R(t) algebraically — the relative-price trend depends only on the productivity-growth gap (gm − gh), not on how wages are actually set. A surgeon performs roughly one operation per hour today much as decades ago (gh ≈ 0), while a factory line produces exponentially more per worker-hour (gm ≫ 0) — yet both must pay competitive, rising wages to keep staff. The result: healthcare's relative cost compounds upward forever, with no inefficiency anywhere in the model.
- gm / gh sliders — set each sector's annual productivity growth; watch manufacturing workers convert into automation (grey) as gm rises, while the healthcare floor stays fully staffed.
- κ slider — how tightly economy-wide wages track the fast sector; changes the wage index but not the relative cost curve, exactly as the algebra predicts.
- Year slider / Play — advance simulated time; the floating chart plots Ch(t) and Cm(t) live, and the output-stack towers grow at each sector's own compounding rate.
Real-world relevance: this is the leading economic explanation for why healthcare, education and live performance costs rise faster than general inflation — the same mechanism the source article's "rising healthcare costs" section points to under "technological progress" and "administrative costs," reframed here as a productivity-growth race rather than a moral failing.