Society & Frontier mixed · 1–3 years
A what‑if from the future

What if Congress writes most-favored-nation drug pricing into law?

A binding most-favored-nation pricing statute caps US prices to the lowest developed-market level — a structural pharma revenue cut that forces launch sequencing and EU/Japan price brinkmanship; short the high-US-mix innovators. Closest rhyme is the 2020 MFN executive order (later enjoined) that briefly hit pharma; codification removes the legal off-ramp. Crypto/MicroStrategy cascade is spurious; impact is pharma-sector earnings, not macro beta.

11%
our model probability
over 1–3 years
prediction markets — the market's odds
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Anchored to measured history 11% · 90% range 4–19% · 40 dated precedents behind it — a wider range means thinner evidence

Every number ships with its receipt — the odds, the range, the precedents, and a public grade at Reality Check. The statistical machinery that produces it is proprietary.

The butterfly cascade

How this trigger trickles across markets, left → right — the root shock, its first‑order moves, then the ripple effects. Drag any node; tap a market for its real price history.

Resolution timeline — how this probability is moving

Our model's odds (electric blue) over time vs the market's (Polymarket, amber), from the past toward the 1–3 years horizon. Each dot is a real macro event that nudged the probability — green pushed it up, red pushed it down. Tap a dot for the source. Loading the probability audit trail…

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What it would mean

If this plays out, it is a mixed shock. Congress passes a binding most-favored-nation pricing statute, converting voluntary deals into law and forcing pharma global launch delays and revenue warnings. The trigger decomposes into signed root‑shocks — Risk appetite ▼ — which propagate through our causal graph to the markets below.

Methodology. Probability and impact are anchored to history and scored against what actually happens — wins and losses, in public, at Reality Check. Market odds live from Polymarket & Kalshi. By Vikas Singh, Quantitative Strategist. Updated 2026-08-13.