Add EfficientDiD estimator (Chen, Sant'Anna & Xie 2025)

TODO.md

@@ -45,6 +45,8 @@ Deferred items from PR reviews that were not addressed before merge.
 |-------|----------|----|----------|
 | ImputationDiD dense `(A0'A0).toarray()` scales O((U+T+K)^2), OOM risk on large panels | `imputation.py` | #141 | Medium (deferred — only triggers when sparse solver fails; fixing requires sparse least-squares alternatives) |
 | Bootstrap NaN-gating gap: manual SE/CI/p-value without non-finite filtering or SE<=0 guard | `imputation_bootstrap.py`, `two_stage_bootstrap.py` | #177 | Medium — migrate to `compute_effect_bootstrap_stats` from `bootstrap_utils.py` |
+| EfficientDiD: warn when cohort share is very small (< 2 units or < 1% of sample) — inverted in Omega*/EIF | `efficient_did_weights.py` | #192 | Low |
+| EfficientDiD: API docs / tutorial page for new public estimator | `docs/` | #192 | Medium |
 
 #### Performance
 

diff_diff/__init__.py

@@ -128,6 +128,11 @@
     ContinuousDiDResults,
     DoseResponseCurve,
 )
+from diff_diff.efficient_did import (
+    EfficientDiD,
+    EfficientDiDResults,
+    EDiDBootstrapResults,
+)
 from diff_diff.trop import (
     TROP,
     TROPResults,
@@ -172,6 +177,7 @@
 DDD = TripleDifference
 Stacked = StackedDiD
 Bacon = BaconDecomposition
+EDiD = EfficientDiD
 
 __version__ = "2.6.1"
 __all__ = [
@@ -231,6 +237,11 @@
     "trop",
     "StackedDiDResults",
     "stacked_did",
+    # EfficientDiD
+    "EfficientDiD",
+    "EfficientDiDResults",
+    "EDiDBootstrapResults",
+    "EDiD",
     # Visualization
     "plot_event_study",
     "plot_group_effects",