Add Output Area crosswalk and geographic assignment (Phase 1)

changelog.d/oa-calibration-pipeline.added.md

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+Add Output Area crosswalk and geographic assignment for OA-level calibration pipeline.

docs/oa_calibration_pipeline.md

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+# Output Area Calibration Pipeline
+
+This document describes the plan to port the US-side clone-and-prune calibration methodology to the UK data, going down to Output Area (OA) level — the UK equivalent of the US Census Block.
+
+## Background
+
+The US pipeline (policyengine-us-data) uses an L0-regularized clone-and-prune approach:
+1. Clone each CPS household N times
+2. Assign each clone a different Census Block (population-weighted)
+3. Build a sparse calibration matrix (targets x records)
+4. Run L0-regularized optimization to drop most clones, keeping only the best-fitting records per area
+5. Publish per-area H5 files from the sparse weight vector
+
+The UK pipeline currently uses standard PyTorch Adam gradient descent on a dense weight matrix (n_areas x n_households) at constituency (650) and local authority (360) level. We want to bring the US approach to the UK at Output Area (~180K OAs) granularity.
+
+## Implementation Phases
+
+### Phase 1: Output Area Crosswalk & Geographic Assignment
+**Status: In Progress**
+
+Build the OA crosswalk and population-weighted assignment function.
+
+**Deliverables:**
+- `policyengine_uk_data/calibration/oa_crosswalk.py` — downloads/builds the OA → LSOA → MSOA → LA → constituency → region → country crosswalk
+- `policyengine_uk_data/storage/oa_crosswalk.csv.gz` — compressed crosswalk file
+- `policyengine_uk_data/calibration/oa_assignment.py` — assigns cloned records to OAs (population-weighted, country-constrained)
+- Tests validating crosswalk completeness and assignment correctness
+
+**Data sources:**
+- ONS Open Geography Portal: OA → LSOA → MSOA → LA lookup
+- ONS mid-year population estimates at OA level
+- ONS OA → constituency lookup (2024 boundaries)
+
+**US reference:** PR #484 (census-block-assignment)
+
+---
+
+### Phase 2: Clone-and-Assign
+**Status: Not Started**
+
+Clone each FRS household N times and assign each clone a different OA.
+
+**Deliverables:**
+- `policyengine_uk_data/calibration/clone_and_assign.py`
+- Modify `datasets/create_datasets.py` to insert clone step after imputations, before calibration
+
+**Key design:**
+- N=10 clones initially (tune later)
+- Constituency collision avoidance: each clone gets a different constituency where possible
+- Country constraint preserved: English households → English OAs only
+
+**US reference:** PR #457 (district-h5) + PR #531 (census-block-calibration)
+
+---
+
+### Phase 3: L0 Calibration Engine
+**Status: Not Started**
+
+Port L0-regularized optimization from US side.
+
+**Deliverables:**
+- `policyengine_uk_data/utils/calibrate_l0.py`
+- Add `l0-python` dependency to `pyproject.toml`
+
+**Key design:**
+- HardConcrete gates for continuous L0 relaxation
+- Relative squared error loss
+- L0 + L2 regularization with presets (local vs national)
+- Keep existing `calibrate.py` as fallback during validation
+
+**US reference:** PR #364 (bogorek-l0) + PR #365
+
+---
+
+### Phase 4: Sparse Matrix Builder
+**Status: Not Started**
+
+Build sparse calibration matrix from cloned dataset.
+
+**Deliverables:**
+- `policyengine_uk_data/calibration/matrix_builder.py`
+- Wire existing `targets/sources/` definitions into sparse matrix rows
+
+**US reference:** PR #456 + PR #489
+
+---
+
+### Phase 5: SQLite Target Database
+**Status: Not Started**
+
+Hierarchical target storage: UK → country → region → LA → constituency → MSOA → LSOA → OA.
+
+**Deliverables:**
+- `policyengine_uk_data/db/` directory with ETL scripts
+- Migrate existing CSV/Excel targets into SQLite
+
+**US reference:** PR #398 (treasury) + PR #488 (db-work)
+
+---
+
+### Phase 6: Local Area Publishing
+**Status: Not Started**
+
+Generate per-area H5 files from sparse weights. Modal integration for scale.
+
+**Deliverables:**
+- `policyengine_uk_data/calibration/publish_local_h5s.py`
+
+**US reference:** PR #465 (modal)