chore(release): bump version to 0.7.1

DID-focused polish release. See CHANGELOG.md [0.7.1] for the full
list of additions and fixes:

- ETWFE full parity with R etwfe (xvar multi, panel=False, cgroup,
  etwfe_emfx with four aggregations + include_leads).
- One-call method-robustness workflow (did_summary + plot + export
  bundle via did_report).
- Twelve review-round fixes across blocker (C1-C5) and high-severity
  (H1-H7) categories; regression tests locked in.

27 DID-focused pytest cases pass (tests/test_did_summary.py).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: brycewang-stanford

CHANGELOG.md

@@ -2,6 +2,98 @@
 
 All notable changes to StatsPAI will be documented in this file.
 
+## [0.7.1] - 2026-04-15
+
+DID-focused polish release. Brings the Wooldridge (2021) ETWFE
+implementation to full feature parity with the R `etwfe` package,
+adds a one-call method-robustness workflow, and closes 12 issues
+uncovered by an internal code review round. All 27 new / updated
+DID tests pass (`pytest tests/test_did_summary.py`).
+
+### Added — ETWFE full parity with R `etwfe`
+
+- **`sp.etwfe()` explicit API** aligned with R `etwfe` (McDermott 2023)
+  naming. Thin alias over `wooldridge_did()` with a full argument-
+  mapping table in the docstring.
+- **`xvar=` covariate heterogeneity** (single string or list of names).
+  Adds per-cohort × post × `(x_j − mean(x_j))` interactions; `detail`
+  gains `slope_<x>` / `slope_<x>_se` / `slope_<x>_pvalue` columns.
+  Baseline ATT is reported at the sample means of every covariate.
+- **`panel=False` repeated cross-section mode** — replaces unit FE
+  with cohort + time dummies (R `etwfe(ivar=NULL)` equivalent).
+- **`cgroup='nevertreated'`** — per-cohort regressions restricted to
+  (cohort g) ∪ (never-treated); cohort-size-weighted aggregation
+  (R `etwfe(cgroup='never')` equivalent). Default `'notyet'` preserves
+  prior ETWFE behaviour.
+- **`sp.etwfe_emfx(result, type=…)`** — R `etwfe::emfx`-equivalent
+  four aggregations: `'simple'`, `'group'`, `'event'`, `'calendar'`.
+  `include_leads=True` returns full event-time output including pre-
+  treatment leads for pre-trend inspection (`rel_time = -1` is the
+  reference category).
+
+### Added — one-call DID method-robustness workflow
+
+- **`sp.did_summary()`** — fits five modern staggered-DID estimators
+  (CS, SA, BJS, ETWFE, Stacked) to the same data and returns a tidy
+  comparison table with per-method (estimate, SE, p, 95 % CI). Mean
+  across methods + cross-method SD flag method-sensitivity of results.
+- **`include_sensitivity=True`** — attaches the Rambachan-Roth (2023)
+  breakdown `M*` to the CS row, giving a three-way robustness readout
+  in a single call.
+- **`sp.did_summary_plot()`** — forest plot of per-method estimates
+  with cross-method mean line; `sort_by='estimate'` supported.
+- **`sp.did_summary_to_markdown()` / `_to_latex()`** — publication-
+  ready exports (GFM tables / booktabs LaTeX with auto-escaped
+  ampersands).
+- **`sp.did_report(save_to=dir)`** — one-call bundle that writes
+  `did_summary.txt` / `.md` / `.tex` / `.png` / `.json` to a folder.
+
+### Fixed — 12 issues from the internal code review
+
+Blockers (C-severity):
+
+- `etwfe(xvar=…)` now raises a clear `ValueError` when the covariate
+  is all-NaN or (near-)constant. Previously returned `n_obs = 0,
+  estimate = 0` silently.
+- `etwfe(panel=False, cgroup='nevertreated')` now raises a crisp
+  `NotImplementedError` instead of silently falling back to
+  `'notyet'`.
+- `did_summary` now validates column names up front (raises
+  `KeyError` listing missing columns) and only catches narrow
+  estimator-side exceptions inside the fit loop; user typos in
+  `controls=` / `cluster=` surface as proper errors.
+- `did_summary` results round-trip cleanly through stdlib
+  serialisation (`DIDSummaryResult(CausalResult)` subclass with a
+  real `.summary()` method, replacing the prior closure-bound
+  instance attribute).
+
+High-severity:
+
+- `etwfe_emfx(type='event'/'calendar')` now computes SEs via the
+  delta method on the stored event-study vcov instead of the
+  independent-coefficient approximation. `model_info['se_method']`
+  advertises which path was used.
+- `etwfe_emfx(type='group')` headline `se` / `pvalue` / `ci` are now
+  populated (match the underlying fit's overall ATT exactly).
+- Validation for `did_summary_plot` / `_to_markdown` / `_to_latex`
+  aligned on a single sentinel `model_info['_did_summary_marker']`.
+- `_etwfe_never_only` no longer leaves a `_ft_cache` helper column
+  on the caller's DataFrame.
+- Slope indexing in `_etwfe_with_xvar` is now name-keyed
+  (`coef_index` dict); regression test verifies swapping
+  `xvar=['x1','x2']` vs `['x2','x1']` produces identical slopes per
+  name.
+- `etwfe(panel=False)` with rank-deficient designs emits a
+  `RuntimeWarning` pointing at concrete remedies (previously fell
+  through to `pinv` silently).
+
+### Tests
+
+- New test module `tests/test_did_summary.py` — 27 cases covering
+  consistency with direct estimator calls, export formats, forest
+  plot rendering, `etwfe_emfx` round-trips, xvar / panel / cgroup
+  options, the 12 review fixes, and the `include_leads` mode.
+
 ## [0.7.0] - 2026-04-14
 
 Focused release reaching feature parity with the R `did` / `HonestDiD`

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "StatsPAI"
-version = "0.7.0"
+version = "0.7.1"
 description = "The Agent-Native Causal Inference & Econometrics Toolkit for Python"
 readme = "README.md"
 license = {text = "MIT"}

src/statspai/__init__.py

@@ -22,7 +22,7 @@
 >>> sp.outreg2(result, filename="results.xlsx")
 """
 
-__version__ = "0.7.0"
+__version__ = "0.7.1"
 __author__ = "Bryce Wang"
 __email__ = "bryce@copaper.ai"
 
@@ -74,13 +74,15 @@
 from .spatial import (
     sar, sem, sdm, slx, sac, SpatialModel,
     sar_gmm, sem_gmm, sarar_gmm,
+    gwr, mgwr, gwr_bandwidth,
     W, queen_weights, rook_weights, knn_weights,
     distance_band, kernel_weights, block_weights,
     moran, moran_local, geary, getis_ord_g, getis_ord_local, join_counts,
     moran_plot, lisa_cluster_map,
     lm_tests, moran_residuals, impacts,
 )
 from . import spatial
+from . import iv
 from .plots import binscatter, set_theme, list_themes, use_chinese, interactive, get_code
 from .utils import (
     label_var, label_vars, get_label, get_labels, describe, pwcorr, winsor, read_data,