Causal Effect (τ)
14.50
Mean post-treatment delta
Cumulative Delta
116.0
Total averted / excess events
Pre-Treatment RMSE
0.42
Fit accuracy before T₀
Parallel Trends Test
p = 0.88
Null: Equal pre-trends
Unit Trajectories & Synthetic Baseline
Observed Y₁(t)
Synthetic Y₀(t)
Controls
Fundamental Problem of Causal Inference
We cannot observe both Y₁(t) and Y₀(t) for the same unit simultaneously after intervention period T₀. The synthetic control method constructs the unobserved counterfactual Y₀(t) using a weighted combination of unexposed control cohorts.
Proof & Telemetry State
Initializing telemetry...
Intervention Setup
Intervention Time (T₀)
Period 12
Treatment Intensity
+2.5
Uncertainty Level (σ)
0.5
Control Weights (wk) Sum: 1.00
Diagnostics & Assumptions
Rubin Model: τt = Y1,t - Y0,t
Pre-period Fit: RMSE across t < T₀
SUTVA: Assumed no spillover between units.