docs: add 0.7.0 CHANGELOG + csdid/differences parity table in README

Make the last five rounds of DiD work externally visible.

CHANGELOG.md
* Add a 0.7.0 release block (2026-04-14) summarising: aggte() unified
  aggregation, Mammen multiplier bootstrap w/ uniform bands,
  balance_e / min_e / max_e, anticipation, cs_report(), ggdid(), dCDH
  joint placebo + avg cumulative effect, Sun-Abraham rewritten with
  cluster sandwich SEs, and honest_did polymorphism.
* Full reference list for every cited paper.

README.md
* Add `sp.aggte`, `sp.cs_report`, `sp.ggdid` rows to the DiD feature
  table.
* Add a new "DiD parity with csdid / differences / R did + HonestDiD"
  comparison matrix (12 capabilities × 4 packages), making the from-
  paper reimplementation commitment explicit.

Also export `aggte`, `cs_report`, `CSReport`, `ggdid` at the top-level
statspai namespace so `sp.aggte(...)` / `sp.cs_report(...)` / `sp.ggdid(...)`
work without any submodule dance.  (The bare `sp.did` name has always
resolved to the `did()` dispatch function in this package, not the
submodule — pre-existing shadowing, unchanged here.)

Verified: 114/114 DiD tests still green.

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

Author: brycewang-stanford

CHANGELOG.md

@@ -2,6 +2,66 @@
 
 All notable changes to StatsPAI will be documented in this file.
 
+## [0.7.0] - 2026-04-14
+
+Focused release reaching feature parity with the R `did` / `HonestDiD`
+packages and the Python `csdid` / `differences` packages for staggered
+Difference-in-Differences.  All core algorithms are reimplemented from
+the original papers — **no wrappers, no runtime dependencies on upstream
+DID packages**.  DiD test count: 47 → 114.
+
+### Added
+
+- **`sp.did.aggte(result, type=...)`** — unified aggregation layer for
+  `callaway_santanna()` results.  Four aggregation schemes (`simple`,
+  `dynamic`, `group`, `calendar`) backed by a single weighted-influence-
+  function engine.  Callaway & Sant'Anna (2021) Section 4.
+- **Mammen (1993) multiplier bootstrap** — IQR-rescaled pointwise
+  standard errors *and* simultaneous (uniform / sup-t) confidence bands
+  over the aggregation dimension.  Matches the uniform-band behaviour
+  of the R `did::aggte` function.
+- **`balance_e` / `min_e` / `max_e`** — event-study cohort balancing
+  and window truncation (CS2021 eq. 3.8).
+- **`anticipation=δ`** parameter on `callaway_santanna()` — shifts the
+  base period back by δ periods per CS2021 §3.2.
+- **`sp.did.cs_report(data, ...)`** — one-call report card.  Runs the
+  full pipeline (ATT(g,t) → four aggregations with uniform bands →
+  pre-trend Wald → Rambachan-Roth breakdown M\* for every post event
+  time) under a single bootstrap seed and pretty-prints the result.
+  Returns a structured `CSReport` dataclass.
+- **`sp.did.ggdid(result)`** — plot routine for `aggte()` output,
+  mirroring R `did::ggdid`.  Auto-dispatches on aggregation type;
+  uniform band overlaid on pointwise CI.
+- **dCDH joint inference** (`did_multiplegt`) — `joint_placebo_test`
+  (Wald χ² across placebo lags with bootstrap covariance, dCDH 2024
+  §3.3) and `avg_cumulative_effect` (mean of dynamic[0..L] with
+  SE preserving cross-horizon covariance, dCDH 2024 §3.4).
+
+### Changed
+
+- **`sun_abraham()` inference layer rewritten** — replaces the former
+  ad-hoc `√(σ²/(total·T))` approximation with a Liang-Zeger cluster-
+  robust sandwich `(X'X)⁻¹ Σ_c X_c' u_c u_c' X_c (X'X)⁻¹` (small-sample
+  adjusted), delta-method IW aggregation SEs `w' V_β w`, iterative
+  two-way within transformation (correct on unbalanced panels), and
+  optional `control_group='lastcohort'` per SA 2021 §6.
+- **`sp.did.honest_did()` / `breakdown_m()` made polymorphic** — now
+  accept both the legacy `callaway_santanna()` / `sun_abraham()` result
+  format (event study in `model_info`) and the new `aggte(type='dynamic')`
+  format (event study in `detail` with Mammen uniform bands).  The
+  idiomatic pipeline `cs → aggte → honest_did → breakdown_m` now runs
+  end-to-end with no manual plumbing.
+
+### References
+
+- Callaway, B. and Sant'Anna, P.H.C. (2021). *J. of Econometrics* 225(2).
+- Sun, L. and Abraham, S. (2021). *J. of Econometrics* 225(2).
+- Mammen, E. (1993). *Ann. Statist.* 21(1).
+- Liang, K.-Y. and Zeger, S.L. (1986). *Biometrika* 73(1).
+- de Chaisemartin, C. and D'Haultfoeuille, X. (2020). *AER* 110(9).
+- de Chaisemartin, C. and D'Haultfoeuille, X. (2024). *RESt*, forthcoming.
+- Rambachan, A. and Roth, J. (2023). *Rev. Econ. Studies* 90(5).
+
 ## [0.6.2] - 2026-04-12
 
 ### Added

README.md

@@ -157,6 +157,30 @@ It brings R's [Causal Inference Task View](https://cran.r-project.org/web/views/
 | `did_multiplegt()` | DID with treatment switching | de Chaisemartin & D'Haultfoeuille (2020) |
 | `did_imputation()` | Imputation DID estimator | Borusyak, Jaravel & Spiess (2024) |
 | `distributional_te()` | Distributional treatment effects | Chernozhukov, Fernandez-Val & Melly (2013) |
+| `sp.aggte()` | Unified aggregation for staggered DID (simple/dynamic/group/calendar) with Mammen multiplier-bootstrap uniform bands | Callaway & Sant'Anna (2021) §4; Mammen (1993) |
+| `sp.cs_report()` | One-call Callaway–Sant'Anna report: estimation + four aggregations + pre-trend test + Rambachan–Roth breakdown M\* | CS2021 + RR2023 |
+| `sp.ggdid()` | `aggte()` visualiser with uniform-band overlay | mirrors R `did::ggdid` |
+
+#### DiD parity with `csdid` / `differences` / R `did` + `HonestDiD`
+
+All algorithms below are reimplemented from the original papers — no
+wrappers, no runtime dependencies on upstream DID packages.
+
+| Feature | StatsPAI | `csdid` (Py) | `differences` (Py) | R `did` |
+| --- | :---: | :---: | :---: | :---: |
+| Callaway–Sant'Anna ATT(g,t) with DR / IPW / REG | ✅ | ✅ | ✅ | ✅ |
+| Never-treated / not-yet-treated control group | ✅ | ✅ | ✅ | ✅ |
+| Anticipation (`anticipation=δ`) | ✅ | ✅ | — | ✅ |
+| `aggte`: simple / dynamic / group / calendar | ✅ | ✅ | ✅ | ✅ |
+| Mammen multiplier bootstrap, uniform sup-t bands | ✅ | ✅ | — | ✅ |
+| `balance_e` / `min_e` / `max_e` | ✅ | ✅ | partial | ✅ |
+| Sun–Abraham IW with Liang–Zeger cluster SE | ✅ | — | ✅ | via `fixest::sunab` |
+| Borusyak–Jaravel–Spiess imputation + pre-trend Wald | ✅ | — | — | via `didimputation` |
+| de Chaisemartin–D'Haultfoeuille switch-on-off | ✅ | — | — | via `DIDmultiplegtDYN` |
+| dCDH joint placebo Wald + avg. cumulative effect | ✅ | — | — | ✅ (v2) |
+| Rambachan–Roth sensitivity + breakdown M\* | ✅ | — | — | via `HonestDiD` |
+| `cs ⇄ aggte ⇄ honest_did` pipeline (single object) | ✅ | partial | partial | partial |
+| One-call report card (`cs_report`) | ✅ | — | — | via `summary()` |
 
 ### Regression Discontinuity
 

src/statspai/__init__.py

@@ -39,6 +39,7 @@
     parallel_trends_plot, bacon_plot, group_time_plot, did_plot,
     enhanced_event_study_plot, treatment_rollout_plot,
     sensitivity_plot, cohort_event_study_plot,
+    aggte, cs_report, CSReport, ggdid,
 )
 from .rd import rdrobust, rdplot, rdplotdensity, rdbwsensitivity, rdbalance, rdplacebo, rdsummary, rkd, rd_honest, rdit
 from .synth import (