CausalVerify - Event Study: leaderboard
Metric: Execution-grounded pass rate (%; L2b+ over the 24 event-study scenarios; the model writes R code for a fixed-seed synthetic scenario from the research question, data description and a preview of the realised CSV; the code is executed and passes when the treatment-effect estimate it reports (read by a Claude Haiku 4.5 coefficient-extraction judge, event-study windows mapped to the canonical scale) is within 50% relative error of a canonical estimator applied to the same realised data; single-shot; the printed passes/24 count is read and converted to percent). Source: arxiv.org. Saturation forecast: Around December 2026. 7 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Claude Sonnet 4 (20250514) | 87.5 |
| 2 | Claude Opus 4.6 | 79.17 |
| 3 | GPT-5 | 70.83 |
| 4 | GPT-4o | 54.17 |
| 5 | O3 | 50 |
Interactive version: theaggregate.ai/benchmark?slug=causalverify-event-study · How It Works · Data refreshed daily, snapshot 2026-09-26.