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Merged
igerber merged 1 commit into from
Feb 10, 2026
Merged

Sync ROADMAP and TODO with v2.3.0 release #143

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15 changes: 3 additions & 12 deletions ROADMAP.md
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Expand Up @@ -8,7 +8,7 @@ For past changes and release history, see [CHANGELOG.md](CHANGELOG.md).

## Current Status

diff-diff v2.1.1 is a **production-ready** DiD library with feature parity with R's `did` + `HonestDiD` + `synthdid` ecosystem for core DiD analysis:
diff-diff v2.3.0 is a **production-ready** DiD library with feature parity with R's `did` + `HonestDiD` + `synthdid` ecosystem for core DiD analysis:

- **Core estimators**: Basic DiD, TWFE, MultiPeriod, Callaway-Sant'Anna, Sun-Abraham, Borusyak-Jaravel-Spiess Imputation, Synthetic DiD, Triple Difference (DDD), TROP
- **Valid inference**: Robust SEs, cluster SEs, wild bootstrap, multiplier bootstrap, placebo-based variance
Expand All @@ -20,14 +20,10 @@ diff-diff v2.1.1 is a **production-ready** DiD library with feature parity with

---

## Near-Term Enhancements (v2.2)
## Near-Term Enhancements (v2.4)

High-value additions building on our existing foundation.

### ~~Borusyak-Jaravel-Spiess Imputation Estimator~~ ✅ Implemented (v2.2)

Implemented as `ImputationDiD` — see `diff_diff/imputation.py`. Includes conservative variance (Theorem 3), event study and group aggregation, pre-trend test (Equation 9), multiplier bootstrap, and Proposition 5 handling for no never-treated units.

### Gardner's Two-Stage DiD (did2s)

Two-stage approach gaining traction in applied work. First residualizes outcomes, then estimates effects.
Expand Down Expand Up @@ -81,7 +77,7 @@ Extend the existing `TripleDifference` estimator to handle staggered adoption se

---

## Medium-Term Enhancements (v2.3+)
## Medium-Term Enhancements (v2.5+)

Extending diff-diff to handle more complex settings.

Expand Down Expand Up @@ -206,11 +202,6 @@ For high-dimensional settings with many potential confounders.

Ongoing maintenance and developer experience.

### Code Quality

- Consider splitting `staggered.py` (1800+ lines)
- Consider splitting `prep.py` (now 2000+ lines with DGP functions)

### Documentation

- Video tutorials and worked examples
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29 changes: 0 additions & 29 deletions TODO.md
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Expand Up @@ -15,23 +15,6 @@ Current limitations that may affect users:
| MultiPeriodDiD wild bootstrap not supported | `estimators.py:1068-1074` | Low | Edge case |
| `predict()` raises NotImplementedError | `estimators.py:532-554` | Low | Rarely needed |

### ~~NaN Standard Errors for Rank-Deficient Matrices~~ (RESOLVED)

**Status**: Resolved in v2.2.0 with R-style rank deficiency handling.

**Solution**: The OLS solver now detects rank-deficient design matrices using pivoted QR decomposition and handles them following R's `lm()` approach:
- Warns users about dropped columns
- Sets NaN for coefficients of linearly dependent columns
- Computes valid SEs for identified (non-dropped) coefficients only
- Expands vcov matrix with NaN for dropped rows/columns

This is controlled by the `rank_deficient_action` parameter in `solve_ols()`:
- `"warn"` (default): Emit warning, set NA for dropped coefficients
- `"error"`: Raise ValueError
- `"silent"`: No warning, but still set NA for dropped coefficients

---

## Code Quality

### Large Module Files
Expand Down Expand Up @@ -106,16 +89,6 @@ Pyright reports 282 type errors. Most are false positives from numpy/pandas type

**Note:** Most errors are false positives from imprecise type stubs. Mypy config in pyproject.toml already handles these via `disable_error_code`.

### ~~Rust Code Quality~~ (RESOLVED)

**Status**: Resolved in v2.1.5. All Clippy warnings addressed:

- [x] `rust/src/linalg.rs` - Added `#[allow(clippy::type_complexity)]` for complex return type, prefixed unused `n` with `_`
- [x] `rust/src/trop.rs` - Added `#[allow(clippy::too_many_arguments)]` to internal functions
- [x] `rust/src/weights.rs` - Replaced needless range loop with iterator

---

## Deprecated Code

Deprecated parameters still present for backward compatibility:
Expand Down Expand Up @@ -149,8 +122,6 @@ Enhancements for `honest_did.py`:
## CallawaySantAnna Bootstrap Improvements

- [ ] Consider aligning p-value computation with R `did` package (symmetric percentile method)
- [x] ~~Investigate RuntimeWarnings in influence function aggregation~~
- ✅ Added `np.errstate` context manager in `staggered_aggregation.py` to suppress warnings during weight influence function computation

---

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