U.S. annual real GDP growth
This market has horizons that resolve independently. Each horizon resolves to U.S. real GDP growth for that calendar year, as reported by the U.S. Bureau of Economic Analysis.
The groups resolve to calendar years 2030, 2035, 2040, 2045, and 2050. A threshold resolves YES if that year's annual real GDP growth is at least the threshold, and NO otherwise.
Resolution uses BEA real GDP data, including FRED series GDPC1, or the most directly comparable official successor series. If BEA or FRED later revises or updates the relevant data, Antistatic may re-resolve using the updated official data.
The starting probabilities of this market were calculated by simulating 150,000 possible paths for U.S. annual real GDP growth, then reading off the simulated value in 2030, 2035, 2040, 2045, and 2050. This is a point-in-year market: it is asking how fast real GDP grows in that specific calendar year, not the fastest growth rate reached before then.
The model starts from current official forecasts and then adds ordinary forecast error, recessions and recoveries, and a right-tail AI productivity component. The baseline uses the BEA 2025 annual real GDP growth estimate of 2.1%, the Federal Reserve's March 2026 Summary of Economic Projections for 2026-2028 and longer-run growth, and CBO's long-term projection that real GDP growth averages about 1.6% per year from 2025 to 2055.
Model mechanics
- Baseline growth: 2.4% in 2026, 2.3% in 2027, 2.1% in 2028, then drifting toward roughly 1.5% by 2050 before AI and business-cycle shocks.
- Business-cycle variance: annual forecast errors have about 1.15 percentage points of residual volatility, with persistence from one year to the next.
- Recessions: each year has about a one-in-eight chance of recession, with an average direct hit of roughly 2.5 percentage points and a partial rebound the following year.
- AI productivity: the terminal annual growth boost has scenario weights of 30% minimal, 35% moderate, 22% fast, 10% AI boom, and 3% exceptional boom. The uplift starts at a sampled year and ramps in over several years.
The AI component is informed by the recent Karger et al. survey on forecasting the economic effects of AI, which reports higher GDP-growth expectations in rapid-AI scenarios than in ordinary official baselines. The model keeps a large range because faster AI could raise productivity while recessions, financial stress, policy mistakes, or measurement lags could still make any particular calendar year weak.
Simulated distribution
| Year | 10th pct. | 25th pct. | Median | 75th pct. | 90th pct. |
|---|---|---|---|---|---|
| 2030 | 0.1% | 1.1% | 2.2% | 3.3% | 4.4% |
| 2035 | 0.2% | 1.4% | 2.5% | 3.8% | 5.4% |
| 2040 | 0.4% | 1.5% | 2.8% | 4.2% | 6.1% |
| 2045 | 0.3% | 1.5% | 2.7% | 4.2% | 6.3% |
| 2050 | 0.2% | 1.4% | 2.6% | 4.1% | 6.2% |
Selected starting probabilities
| Threshold | 2030 P(growth >= threshold) | 2035 P(growth >= threshold) | 2040 P(growth >= threshold) | 2045 P(growth >= threshold) | 2050 P(growth >= threshold) |
|---|---|---|---|---|---|
| 0% | 90.7% | 91.9% | 92.7% | 92.4% | 91.8% |
| 2% | 55.1% | 61.8% | 65.8% | 65.0% | 63.0% |
| 3% | 30.4% | 39.6% | 45.0% | 44.5% | 42.7% |
| 4% | 13.9% | 22.6% | 27.9% | 27.9% | 26.7% |
| 5% | 6.5% | 12.7% | 16.9% | 17.4% | 16.7% |
| 8% | 0.8% | 2.7% | 4.5% | 4.9% | 4.8% |
| 10% | 0.2% | 1.1% | 2.1% | 2.3% | 2.3% |
| 15% | <0.1% | 0.2% | 0.4% | 0.5% | 0.5% |
These starting probabilities are conditional on Antistatic and the official GDP data process existing well enough for resolution. Extinction, permanent platform failure, and no-data scenarios are not assigned numerical GDP outcomes.
Liquidity over time
i Shows the market’s available liquidity over time. Liquidity can decay continuously and may change discretely if liquidity adjustments are applied.Loading…
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