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Merge pull request #192 from igerber/efficient-diff-in-diff
Add EfficientDiD estimator (Chen, Sant'Anna & Xie 2025)
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TODO.md

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|-------|----------|----|----------|
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| 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) |
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| 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` |
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| EfficientDiD: warn when cohort share is very small (< 2 units or < 1% of sample) — inverted in Omega*/EIF | `efficient_did_weights.py` | #192 | Low |
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| EfficientDiD: API docs / tutorial page for new public estimator | `docs/` | #192 | Medium |
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#### Performance
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diff_diff/__init__.py

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ContinuousDiDResults,
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DoseResponseCurve,
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)
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from diff_diff.efficient_did import (
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EfficientDiD,
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EfficientDiDResults,
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EDiDBootstrapResults,
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)
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from diff_diff.trop import (
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TROP,
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TROPResults,
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DDD = TripleDifference
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Stacked = StackedDiD
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Bacon = BaconDecomposition
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EDiD = EfficientDiD
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__version__ = "2.6.1"
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__all__ = [
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"trop",
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"StackedDiDResults",
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"stacked_did",
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# EfficientDiD
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"EfficientDiD",
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"EfficientDiDResults",
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"EDiDBootstrapResults",
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"EDiD",
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# Visualization
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"plot_event_study",
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"plot_group_effects",

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