From 12560c0cc5d9f39ae35a7ec381a77075b2d9c82e Mon Sep 17 00:00:00 2001 From: Max Ghenis Date: Sun, 2 Aug 2026 21:03:27 -0400 Subject: [PATCH 1/4] Schema: baselines registry (#13), descriptive register gate (#9), UK vocab MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - baselines table + baseline_key on external_scores/pe_results/pe_exhibits; ReformRef.baseline_key() derives from the baseline descriptor (claim-id hashing unchanged — additive projection). Registry curated in scorecard_db/baselines.py; runners fail loudly on unregistered worlds. - comparisons view exposes claim/PE baseline labels and pe_status_effective: comparable across different baselines can never render as plain agreement. - DiagnosisClass.methodological_difference (descriptive semantics); pe_gap/external_issue now REQUIRE a citable action_link — the CPSP erratum diagnosis cites its vendored NOTES anchor. - Metric/UnitConcept UK extensions (COLLATION UK worklist item 1): gbp family, exchequer_impact, unclaimed_expenditure, revenue/expenditure levels+changes, policy_parameter_level, taxpayer/percentile/average-tax families, income-distribution family (median/mean/share/gini/S80S20), poverty_threshold, persistent_poverty_rate, IFS/RF reform-distribution family; STANDARD_CONDITIONS UK keys (fy, basis, equivalisation, …). - poverty_count + persistent_poverty_rate join the permanent-holdout set. - platform/urban/solo ingests record the baseline actually executed. Co-Authored-By: Claude Fable 5 --- scorecard_db/__init__.py | 4 + scorecard_db/baselines.py | 157 +++++++++++++++++++++++++ scorecard_db/db.py | 191 ++++++++++++++++++++++++++----- scorecard_db/ingest_cpsp.py | 3 + scorecard_db/ingest_harvest.py | 2 + scorecard_db/ingest_platform.py | 7 ++ scorecard_db/ingest_solo.py | 2 + scorecard_db/ingest_urban.py | 1 + scorecard_db/models.py | 165 ++++++++++++++++++++++++++- scorecard_db/relationships.py | 5 + tests/test_scorecard_db.py | 196 ++++++++++++++++++++++++++++++++ 11 files changed, 706 insertions(+), 27 deletions(-) create mode 100644 scorecard_db/baselines.py diff --git a/scorecard_db/__init__.py b/scorecard_db/__init__.py index ab2a47f..11d9483 100644 --- a/scorecard_db/__init__.py +++ b/scorecard_db/__init__.py @@ -1,6 +1,7 @@ from .db import ScorecardDB from .models import ( BASELINE, + CURRENT_LAW_DESCRIPTOR, STANDARD_CONDITIONS, CalibrationRelationship, ComparisonStatus, @@ -11,10 +12,12 @@ ReformRef, TimeBasis, UnitConcept, + baseline_key, ) __all__ = [ "BASELINE", + "CURRENT_LAW_DESCRIPTOR", "STANDARD_CONDITIONS", "CalibrationRelationship", "ComparisonStatus", @@ -26,4 +29,5 @@ "ScorecardDB", "TimeBasis", "UnitConcept", + "baseline_key", ] diff --git a/scorecard_db/baselines.py b/scorecard_db/baselines.py new file mode 100644 index 0000000..e60cb71 --- /dev/null +++ b/scorecard_db/baselines.py @@ -0,0 +1,157 @@ +"""Baseline registry (issue #13): every baseline world, deliberately named. + +A score's meaning is its (reform, baseline) pair. ReformRef keeps carrying +the baseline descriptor for claim-id hashing (unchanged); this module is +the queryable projection — one registry row per distinct descriptor, with +the source's own words defining the world. `register_baselines` seeds the +table and fails loudly if any baseline_key referenced by the data is not +described here: extending the registry is a deliberate act. + +Convention (mirrors JCT/HMT practice): a costing scored against the law in +force at its own publication is the null baseline `current_law` — the +announcement vintage is a condition (fiscal_event, data_vintage), not a +distinct baseline world. Only genuinely non-current-law worlds (TCJA +extension, JCT current policy, TPC current-law + Senate Title VII, CPSP +counterfactual CTC regimes, PE's pre-AB2025 reinstated two-child limit) +get their own entries. +""" + +from __future__ import annotations + +from .db import ScorecardDB +from .models import CURRENT_LAW_DESCRIPTOR, baseline_key + +# descriptor, label, description, framework, provenance +BASELINES: list[tuple[dict, str, str, str, str]] = [ + ( + CURRENT_LAW_DESCRIPTOR, + "current_law", + "Law in force at the source's scoring date (the null baseline; " + "announcement vintage rides in conditions, not here).", + "baseline", + "Default for every claim without an explicit baseline descriptor.", + ), + ( + {"policy": "current_policy"}, + "current_policy", + "JCT current-policy baseline: expiring provisions assumed " + "continued rather than sunsetting under present law.", + "policy_ref", + "JCX-29-25 (manager's amendment scored vs current policy; twin of " + "JCX-30/31 present-law scoring) — sources/harvest-2026-08-02/jct.", + ), + ( + {"policy": "tcja_extension"}, + "tcja_extension", + "TCJA individual provisions extended past their scheduled 2025 " + "sunset.", + "policy_ref", + "PWBM tables scored against a TCJA-extension baseline " + "(sources/harvest-2026-08-02/pwbm NOTES: conditions." + "baseline_policy=tcja_extension rows).", + ), + ( + {"policy": "current_law_pre_2025_tariffs"}, + "current_law_pre_2025_tariffs", + "Current law excluding the 2025 tariff actions (Tax Foundation " + "Tariff Tracker scoring convention).", + "policy_ref", + "Tax Foundation Tariff Tracker, July-2026 vintage " + "(sources/harvest-2026-08-02/tax_foundation).", + ), + ( + {"policy": "current_law_plus_senate_obbba_title_vii"}, + "current_law_plus_senate_obbba_title_vii", + "Current law plus the Senate OBBBA Title VII draft — the baseline " + "under TPC's CTC options set.", + "policy_ref", + "TPC T25-0209/0213/0215 baseline_hint (sources/harvest-2026-08-02/" + "tpc); draft≈enacted for these provisions per the campaign " + "conventions note.", + ), + ( + {"policy": "no_ctc"}, + "no_ctc", + "Counterfactual world with the Child Tax Credit removed (CPSP " + "poverty counterfactual tables, 100% take-up, no behavior).", + "policy_ref", + "CPSP CTC counterfactual tables 2023/2024 " + "(sources/harvest-2026-08-02/cpsp).", + ), + ( + {"policy": "tcja_ctc"}, + "tcja_ctc", + "TCJA-parameter CTC world (CPSP counterfactual scenario).", + "policy_ref", + "CPSP CTC counterfactual tables (sources/harvest-2026-08-02/cpsp).", + ), + ( + {"policy": "tcja_ctc", "take_up": "full"}, + "tcja_ctc_full_takeup", + "TCJA-parameter CTC world at explicit 100% take-up.", + "policy_ref", + "CPSP CTC counterfactual tables (sources/harvest-2026-08-02/cpsp).", + ), + ( + {"policy": "bl_ctc_option", "option": "1. TCJA CTC"}, + "bl_ctc_option_1_tcja_ctc", + "Budget Lab CTC options workbook baseline: option 1 (TCJA CTC) " + "under the current-law sunset path.", + "policy_ref", + "Budget Lab 16-scenario CTC options workbook " + "(sources/harvest-2026-08-02/budget_lab).", + ), + ( + {"policy": "bl_ctc_option_permanent", "option": "1. TCJA Extension"}, + "bl_ctc_option_permanent_1_tcja_extension", + "Budget Lab CTC options workbook baseline: option 1 under the " + "TCJA-permanence path.", + "policy_ref", + "Budget Lab 16-scenario CTC options workbook " + "(sources/harvest-2026-08-02/budget_lab).", + ), + ( + {"policy": "pre_ab2025"}, + "pre_ab2025", + "UK current law with the Autumn Budget 2025 two-child-limit " + "abolition reversed (limit reinstated at 2 children; born-pre-2017 " + "exemptions active) — the reinstated counterfactual PE executes as " + "baseline so 'removal' is measured explicitly, not implied by " + "sign.", + "policyengine_uk", + "Campaign run results/uk/two_child_reinstate_2026.json " + "(gov.dwp.universal_credit.elements.child.limit.child_count: " + "inf -> 2); issue #13 grounding artifact.", + ), +] + + +def register_baselines(db: ScorecardDB) -> int: + """Seed the registry, then fail loudly on any baseline_key the data + references that is not curated above.""" + for descriptor, label, description, framework, provenance in BASELINES: + db.register_baseline( + baseline_key(descriptor), + label, + description=description, + framework=framework, + spec_json=None, + provenance=provenance, + ) + missing = db.unregistered_baselines() + if missing: + described = [] + for key in missing: + sample = db.conn.execute( + "SELECT reform_json FROM external_scores" + " WHERE baseline_key = ? LIMIT 1", + (key,), + ).fetchone() + described.append( + f"{key} (e.g. {sample['reform_json']})" if sample else key + ) + raise ValueError( + "baseline_keys in data but not in the registry (add them to " + f"scorecard_db/baselines.py deliberately): {described}" + ) + return len(BASELINES) diff --git a/scorecard_db/db.py b/scorecard_db/db.py index 071797c..a6f620d 100644 --- a/scorecard_db/db.py +++ b/scorecard_db/db.py @@ -1,10 +1,16 @@ """SQLite storage for the Scorecard database. -One file (`scorecard.db`), four tables: +One file (`scorecard.db`), five tables: - external_scores — the claims (populace-targets shape; see models.py) - pe_results — PolicyEngine computations, full history per claim -- diagnoses — adjudications of material divergences +- baselines — registry of baseline worlds (issue #13): every claim and + every PE run carries a baseline_key FK; the comparisons + view exposes both sides and refuses to render plain + agreement across different baselines +- diagnoses — adjudications of material divergences (descriptive + register, issue #9: pe_gap / external_issue require a + citable known issue in action_link) - lanes — live mission-control status per (source × area) lane `comparisons` is a VIEW joining each claim to its latest PE result. Common @@ -19,7 +25,12 @@ from pathlib import Path from typing import Iterable, Optional -from .models import ExternalScore, PEResult +from .models import ( + GATED_DIAGNOSIS_CLASSES, + DiagnosisClass, + ExternalScore, + PEResult, +) DDL = """ CREATE TABLE IF NOT EXISTS external_scores ( @@ -46,7 +57,8 @@ ('consumed_as_target','seed_source','held_out') ), period_start INTEGER, - period_end INTEGER + period_end INTEGER, + baseline_key TEXT ); CREATE INDEX IF NOT EXISTS idx_scores_source ON external_scores(source); CREATE INDEX IF NOT EXISTS idx_scores_geo ON external_scores(geography); @@ -65,14 +77,25 @@ pe_construction TEXT NOT NULL DEFAULT '', run_id TEXT NOT NULL DEFAULT '', computed_at TEXT NOT NULL DEFAULT '', - annotations TEXT NOT NULL DEFAULT '[]' + annotations TEXT NOT NULL DEFAULT '[]', + baseline_key TEXT ); CREATE INDEX IF NOT EXISTS idx_results_claim ON pe_results(claim_id); +CREATE TABLE IF NOT EXISTS baselines ( + baseline_key TEXT PRIMARY KEY, + label TEXT NOT NULL UNIQUE, + description TEXT NOT NULL DEFAULT '', + framework TEXT NOT NULL DEFAULT '', + spec_json TEXT, + provenance TEXT NOT NULL DEFAULT '' +); + CREATE TABLE IF NOT EXISTS diagnoses ( claim_id TEXT PRIMARY KEY REFERENCES external_scores(claim_id), diagnosis_class TEXT NOT NULL CHECK (diagnosis_class IN ( - 'pe_gap','external_issue','concept_mismatch','vintage','undiagnosed' + 'pe_gap','external_issue','concept_mismatch', + 'methodological_difference','vintage','undiagnosed' )), rationale TEXT NOT NULL DEFAULT '', action_link TEXT NOT NULL DEFAULT '' @@ -97,7 +120,8 @@ data_bundle TEXT NOT NULL, run_id TEXT NOT NULL DEFAULT '', computed_at TEXT NOT NULL DEFAULT '', - note TEXT NOT NULL DEFAULT '' + note TEXT NOT NULL DEFAULT '', + baseline_key TEXT ); CREATE INDEX IF NOT EXISTS idx_exhibits_kind ON pe_exhibits(exhibit); @@ -111,7 +135,16 @@ updated_at TEXT NOT NULL DEFAULT '' ); -CREATE VIEW IF NOT EXISTS comparisons AS +""" + +# Everything below is (re)created after _migrate so it may reference +# columns added by migration (baseline_key on pre-#13 files); DROP+CREATE +# keeps the view definition current on old files. +VIEW_DDL = """ +CREATE INDEX IF NOT EXISTS idx_scores_baseline + ON external_scores(baseline_key); +DROP VIEW IF EXISTS comparisons; +CREATE VIEW comparisons AS SELECT s.*, r.computed_value AS pe_value, @@ -120,6 +153,21 @@ r.data_bundle, r.pe_construction, r.computed_at, + r.baseline_key AS pe_baseline_key, + bc.label AS claim_baseline_label, + bp.label AS pe_baseline_label, + -- Issue #13 guard: a result computed against a different baseline + -- world than the claim's can never render as plain agreement — it is + -- at best a documented construction. (A registry-equivalence table + -- can relax specific pairs later; none exist yet.) + CASE + WHEN r.status = 'comparable' + AND r.baseline_key IS NOT NULL + AND s.baseline_key IS NOT NULL + AND r.baseline_key != s.baseline_key + THEN 'constructed' + ELSE r.status + END AS pe_status_effective, r.computed_value - s.value AS delta, CASE WHEN s.value != 0 THEN r.computed_value / s.value END AS ratio, d.diagnosis_class, @@ -131,7 +179,9 @@ WHERE claim_id = s.claim_id ORDER BY computed_at DESC, id DESC LIMIT 1 ) -LEFT JOIN diagnoses d ON d.claim_id = s.claim_id; +LEFT JOIN diagnoses d ON d.claim_id = s.claim_id +LEFT JOIN baselines bc ON bc.baseline_key = s.baseline_key +LEFT JOIN baselines bp ON bp.baseline_key = r.baseline_key; """ @@ -142,27 +192,65 @@ def __init__(self, path: str | Path): self.conn.row_factory = sqlite3.Row self.conn.executescript(DDL) self._migrate() + self.conn.executescript(VIEW_DDL) def _migrate(self): """Bring a pre-existing file up to the current schema. CREATE TABLE IF NOT EXISTS leaves old files untouched, so columns - added later (period_start/period_end, 2026-08-02) are ALTERed in. - The comparisons view stores its SELECT as text and expands s.* at - query time, so it needs no rebuild. + added later (period_start/period_end 2026-08-02, baseline_key + 2026-08-02 #13) are ALTERed in, and the diagnoses CHECK is + rebuilt when it predates methodological_difference (issue #9). + The comparisons view is dropped and recreated after migration so + its definition always matches the code. """ - cols = { - r["name"] - for r in self.conn.execute( - "PRAGMA table_info(external_scores)" - ) - } + def cols(table): + return { + r["name"] + for r in self.conn.execute(f"PRAGMA table_info({table})") + } + with self.conn: - for col in ("period_start", "period_end"): - if col not in cols: + score_cols = cols("external_scores") + for col, typ in ( + ("period_start", "INTEGER"), + ("period_end", "INTEGER"), + ("baseline_key", "TEXT"), + ): + if col not in score_cols: + self.conn.execute( + f"ALTER TABLE external_scores ADD COLUMN {col} {typ}" + ) + for table in ("pe_results", "pe_exhibits"): + if "baseline_key" not in cols(table): self.conn.execute( - f"ALTER TABLE external_scores ADD COLUMN {col} INTEGER" + f"ALTER TABLE {table} ADD COLUMN baseline_key TEXT" ) + diag_sql = self.conn.execute( + "SELECT sql FROM sqlite_master" + " WHERE type='table' AND name='diagnoses'" + ).fetchone() + if diag_sql and "methodological_difference" not in diag_sql["sql"]: + self.conn.executescript( + """ + ALTER TABLE diagnoses RENAME TO diagnoses_old; + CREATE TABLE diagnoses ( + claim_id TEXT PRIMARY KEY + REFERENCES external_scores(claim_id), + diagnosis_class TEXT NOT NULL CHECK ( + diagnosis_class IN ( + 'pe_gap','external_issue','concept_mismatch', + 'methodological_difference','vintage', + 'undiagnosed' + ) + ), + rationale TEXT NOT NULL DEFAULT '', + action_link TEXT NOT NULL DEFAULT '' + ); + INSERT INTO diagnoses SELECT * FROM diagnoses_old; + DROP TABLE diagnoses_old; + """ + ) def close(self): self.conn.close() @@ -194,6 +282,7 @@ def upsert_scores(self, scores: Iterable[ExternalScore]) -> int: s.calibration_relationship.value, s.period_start, s.period_end, + s.reform.baseline_key(), ) ) with self.conn: @@ -203,8 +292,9 @@ def upsert_scores(self, scores: Iterable[ExternalScore]) -> int: " source_column, publication, reform_key, reform_json," " metric, unit_concept, period, time_basis, conditions," " geography, program, value, value_kind, status," - " calibration_relationship, period_start, period_end)" - " VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)", + " calibration_relationship, period_start, period_end," + " baseline_key)" + " VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)", rows, ) return len(rows) @@ -221,6 +311,7 @@ def add_results(self, results: Iterable[PEResult]) -> int: r.run_id, r.computed_at, json.dumps(r.annotations), + r.baseline_key, ) for r in results ] @@ -228,7 +319,8 @@ def add_results(self, results: Iterable[PEResult]) -> int: self.conn.executemany( "INSERT INTO pe_results (claim_id, computed_value, status," " engine_version, data_bundle, pe_construction, run_id," - " computed_at, annotations) VALUES (?,?,?,?,?,?,?,?,?)", + " computed_at, annotations, baseline_key)" + " VALUES (?,?,?,?,?,?,?,?,?,?)", rows, ) return len(rows) @@ -245,6 +337,7 @@ def add_exhibits(self, rows: Iterable[dict]) -> int: r.get("baseline_value"), r.get("delta"), r["engine_version"], r["data_bundle"], r.get("run_id", ""), r.get("computed_at", ""), r.get("note", ""), + r.get("baseline_key"), ) for r in rows ] @@ -253,8 +346,9 @@ def add_exhibits(self, rows: Iterable[dict]) -> int: "INSERT INTO pe_exhibits (exhibit, reform_key, reform_json," " metric, unit_concept, period, time_basis, conditions," " geography, program, value, baseline_value, delta," - " engine_version, data_bundle, run_id, computed_at, note)" - " VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)", + " engine_version, data_bundle, run_id, computed_at, note," + " baseline_key)" + " VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)", prepared, ) return len(prepared) @@ -274,6 +368,42 @@ def set_lane(self, lane: str, stage: str, detail: str = "", at: str = ""): (lane, stage, detail, at), ) + def register_baseline( + self, + baseline_key: str, + label: str, + description: str = "", + framework: str = "", + spec_json: Optional[str] = None, + provenance: str = "", + ): + with self.conn: + self.conn.execute( + "INSERT INTO baselines VALUES (?,?,?,?,?,?)" + " ON CONFLICT(baseline_key) DO UPDATE SET" + " label=excluded.label, description=excluded.description," + " framework=excluded.framework, spec_json=excluded.spec_json," + " provenance=excluded.provenance", + (baseline_key, label, description, framework, spec_json, + provenance), + ) + + def unregistered_baselines(self) -> list[str]: + """baseline_keys referenced by claims or results but missing from + the registry — runners fail loudly on these so every baseline + world is deliberately described (issue #13).""" + return [ + r["baseline_key"] + for r in self.conn.execute( + "SELECT DISTINCT baseline_key FROM (" + " SELECT baseline_key FROM external_scores" + " UNION SELECT baseline_key FROM pe_results" + " UNION SELECT baseline_key FROM pe_exhibits)" + " WHERE baseline_key IS NOT NULL AND baseline_key NOT IN" + " (SELECT baseline_key FROM baselines)" + ) + ] + def diagnose( self, claim_id: str, @@ -281,6 +411,15 @@ def diagnose( rationale: str = "", action_link: str = "", ): + # Descriptive register (issue #9): normative classes are gated on + # a citable known issue; divergence alone never qualifies. + if DiagnosisClass(diagnosis_class) in GATED_DIAGNOSIS_CLASSES and ( + not action_link + ): + raise ValueError( + f"{diagnosis_class} requires a citable known issue in " + "action_link (descriptive register, issue #9)" + ) with self.conn: self.conn.execute( "INSERT INTO diagnoses VALUES (?,?,?,?) ON CONFLICT(claim_id)" diff --git a/scorecard_db/ingest_cpsp.py b/scorecard_db/ingest_cpsp.py index 8bd7b4d..fe5f16e 100644 --- a/scorecard_db/ingest_cpsp.py +++ b/scorecard_db/ingest_cpsp.py @@ -251,6 +251,9 @@ def ingest(db_path: Path) -> dict: erratum_claim(scores).claim_id(), "external_issue", ERRATUM_RATIONALE, + # Gated class (issue #9): the citable known issue is the source's + # own internal contradiction, documented in the vendored notes. + action_link="sources/harvest-2026-08-02/cpsp/NOTES.md#erratum", ) db.set_lane( "cpsp-poverty", diff --git a/scorecard_db/ingest_harvest.py b/scorecard_db/ingest_harvest.py index 1c18eb1..292647a 100644 --- a/scorecard_db/ingest_harvest.py +++ b/scorecard_db/ingest_harvest.py @@ -21,6 +21,7 @@ ingest_tax_foundation, ingest_tpc, ) +from .baselines import register_baselines from .db import ScorecardDB from .harvest import REPO @@ -101,6 +102,7 @@ def ingest(db_path: Path) -> dict: for name, adapter in ADAPTERS.items(): stats[name] = adapter.ingest(db_path) db = ScorecardDB(db_path) + stats["baselines_registered"] = register_baselines(db) stats["lanes_synced"] = sync_lane_feed( db, REPO / "data" / "lanes.json", "2026-08-02" ) diff --git a/scorecard_db/ingest_platform.py b/scorecard_db/ingest_platform.py index 1f386e3..48bac28 100644 --- a/scorecard_db/ingest_platform.py +++ b/scorecard_db/ingest_platform.py @@ -28,14 +28,20 @@ from .ingest_urban import FULLPART_REFORM, POP_UNIT, UNITS_UNIT from .models import ( BASELINE, + CURRENT_LAW_DESCRIPTOR, ComparisonStatus, ExternalScore, Metric, PEResult, TimeBasis, UnitConcept, + baseline_key, ) +# Platform-grid runs execute on the certified current-law world (fullpart +# rows force take-up flags on that same world) — record it per issue #13. +_CURRENT_LAW_KEY = baseline_key(CURRENT_LAW_DESCRIPTOR) + REPO = Path(__file__).resolve().parent.parent # platform metric vocabulary -> (tidy program override, Metric) @@ -157,6 +163,7 @@ def ingest(db_path: Path, comparison_json: Path | None = None, run_id="platform-grid-2024", computed_at=f"{comp.get('built', '')}T12:00:00", annotations=row.get("annotations", []), + baseline_key=_CURRENT_LAW_KEY, ) ) if unmatched: diff --git a/scorecard_db/ingest_solo.py b/scorecard_db/ingest_solo.py index 9082d34..8735191 100644 --- a/scorecard_db/ingest_solo.py +++ b/scorecard_db/ingest_solo.py @@ -24,6 +24,7 @@ from .db import ScorecardDB from .ingest_urban import solo_reform +from .models import BASELINE COMPARISON_DIR = Path.home() / "populace-sotsn-takeup" / "comparison" REPO = Path(__file__).resolve().parent.parent @@ -112,6 +113,7 @@ def ingest(db_path: Path, comparison_dir: Path = COMPARISON_DIR) -> dict: "run_id": "solo-takeup-2024", "computed_at": "2026-08-01T20:20:00", "note": NOTE, + "baseline_key": BASELINE.baseline_key(), } ) if len(seen) != 52: diff --git a/scorecard_db/ingest_urban.py b/scorecard_db/ingest_urban.py index 152c225..26cd3fb 100644 --- a/scorecard_db/ingest_urban.py +++ b/scorecard_db/ingest_urban.py @@ -195,6 +195,7 @@ def pe_results_from_comparison( pe_construction=r.get("concept_note", ""), run_id=meta.get("run_id", ""), computed_at=meta.get("computed_at", ""), + baseline_key=BASELINE.baseline_key(), ) ) return results diff --git a/scorecard_db/models.py b/scorecard_db/models.py index 00ee4bc..4161c8f 100644 --- a/scorecard_db/models.py +++ b/scorecard_db/models.py @@ -70,6 +70,57 @@ class Metric(str, Enum): MAXIMUM_MONTHLY_BENEFIT = "maximum_monthly_benefit" AVERAGE_WEEKLY_BENEFIT = "average_weekly_benefit" FIRST_PAYMENT_COUNT = "first_payment_count" + # 2026-08-02 UK-harvest extensions (COLLATION UK worklist item 1). + # exchequer_impact is deliberately NOT revenue_change: HMT/OBR scorecard + # lines mix Tax and Spend heads (classification is by largest impact), + # so the metric asserts only "net impact on the public finances"; + # conditions carry head / tax_head / spending_head verbatim. + EXCHEQUER_IMPACT = "exchequer_impact" + # DWP income-related-benefit take-up: the £ entitled but unclaimed + # (with bounds in conditions["bound"]). + UNCLAIMED_EXPENDITURE = "unclaimed_expenditure" + # Level (not change) families shared by OBR EFO receipts tables and + # UKMOD's validation block (their "tax_revenue" simulated receipts). + REVENUE_LEVEL = "revenue_level" + EXPENDITURE_LEVEL = "expenditure_level" + EXPENDITURE_CHANGE = "expenditure_change" + # Statutory/administrative parameter values by year (OBR EFO 3.19 + # threshold walks, RF April-2026 uprating set) — pure parameter checks. + POLICY_PARAMETER_LEVEL = "policy_parameter_level" + BENEFIT_UPRATING = "benefit_uprating" # annual uprating rate applied + TAXPAYER_COUNT = "taxpayer_count" + TAXPAYER_COUNT_CHANGE = "taxpayer_count_change" + # HMRC SPI percentile points: income level at percentile p + # (conditions: percentile, income_concept). + INCOME_PERCENTILE_POINT = "income_percentile_point" + AVERAGE_TAX_RATE = "average_tax_rate" + AVERAGE_TAX_AMOUNT = "average_tax_amount" + # Distribution levels (UKMOD 4.7, HMT annex 2.C). Median-vs-mean is + # baked into the metric (level statistics, unlike the avg_* change + # family); the income concept rides conditions["income_concept"]. + MEDIAN_INCOME = "median_income" + MEAN_INCOME = "mean_income" + INCOME_SHARE = "income_share" + GINI_COEFFICIENT = "gini_coefficient" + GINI_COEFFICIENT_CHANGE = "gini_coefficient_change" + S80_S20_RATIO = "s80_s20_ratio" + S80_S20_RATIO_CHANGE = "s80_s20_ratio_change" + POVERTY_THRESHOLD = "poverty_threshold" + # JRF headline series PE cannot produce without longitudinal data; + # staged as claims, results stay not_computed until that capability + # exists (descriptive register: capability statement, not a defect). + PERSISTENT_POVERTY_RATE = "persistent_poverty_rate" + # Reform-distribution family (IFS options tables, RF decile blocks). + AVG_CHANGE_HOUSEHOLD_NET_INCOME = "avg_change_household_net_income" + SHARE_GAINING = "share_gaining" + SHARE_LOSING = "share_losing" + SHARE_OF_SPENDING_TO_GROUP = "share_of_spending_to_group" + COST_PER_CHILD_LIFTED_OUT_OF_POVERTY = ( + "cost_per_child_lifted_out_of_poverty" + ) + FAMILIES_AFFECTED_COUNT = "families_affected_count" + # RF Living Standards Outlook household income growth projections. + REAL_INCOME_GROWTH = "real_income_growth" class UnitConcept(str, Enum): @@ -94,6 +145,27 @@ class UnitConcept(str, Enum): # pct_change_after_tax_income / share_with_tax_cut row to PERCENT; # SHARE stays the fraction convention for rates (poverty, take-up). PERCENT = "percent" + # 2026-08-02 UK-harvest extensions: GBP aggregates and the per-period / + # per-unit statistics the UK sources publish (MIS weekly budgets, RF + # weekly benefit rates, IFS per-year averages). The per-unit split is + # load-bearing for the same reason as USD_PER_TAX_UNIT: averages must + # never sum like aggregates, and the denominator population differs. + GBP = "gbp" + GBP_PER_WEEK = "gbp_per_week" + GBP_PER_MONTH = "gbp_per_month" + GBP_PER_YEAR = "gbp_per_year" + GBP_PER_HOUSEHOLD = "gbp_per_household" + GBP_PER_FAMILY = "gbp_per_family" + GBP_PER_PERSON = "gbp_per_person" + # Rate-change claims published in percentage points (IFS poverty-rate + # changes). Distinct from PERCENT (a level on the 0–100 scale) so a + # query cannot mistake a change for a level. + PERCENTAGE_POINTS = "percentage_points" + # Inequality statistics: S80/S20 quintile-share ratios, Gini on the + # 0–1 scale, and Gini differences in index points × 100 (UKMOD 4.7). + RATIO = "ratio" + INDEX_0_1 = "index_0_1" + INDEX_POINTS_0_100 = "index_points_0_100" # Standardized conditions vocabulary (COLLATION worklist item 4). @@ -112,6 +184,29 @@ class UnitConcept(str, Enum): # window_kind "total" | "annual_average" on period-range claims # month "YYYY-MM" for monthly series # data_vintage dataset base when it is not the obvious current one +# +# UK additions (2026-08-02 UK harvest; COLLATION UK worklist items 2-3): +# fy normalized fiscal-year label "2026-27" (Apr–Mar). The +# integer period is ALWAYS the FY start year (pe-uk-data +# convention) — adapters re-derive it from this label, so +# end-year staging conventions cannot leak in. +# basis source's own designation: "outturn" | "forecast" | +# "projected" | "provisional" | "unstated". Admin outturn +# rows never reach external_scores (ledger routing rule). +# income_concept UK distribution rows: "BHC" | "AHC" (load-bearing on +# every HBAI-family statistic), alongside the US values. +# equivalisation e.g. "modified_oecd" — load-bearing with income_concept. +# poverty_measure "relative" | "absolute" (+ poverty_line, e.g. +# "60pct_median"; poverty_line_anchor for absolute lines) +# fiscal_event "autumn_budget_2024" | "budget_2025" | … — the event a +# costing/measure belongs to +# measure verbatim measure title on scored fiscal-event lines +# (mirrors the policy_ref slug, which hashes this title) +# series UKMOD validation-block column: "ukmod" | +# "official_estimate" | "input_data" | "hbai" +# edition publication edition when two editions of the same +# statistic are staged (HBAI FYE2025 vs admin-linked) +# bound "lower" | "central" | "upper" on estimate ranges STANDARD_CONDITIONS = frozenset( { "geography", @@ -127,6 +222,16 @@ class UnitConcept(str, Enum): "window_kind", "month", "data_vintage", + "fy", + "basis", + "equivalisation", + "poverty_measure", + "poverty_line", + "fiscal_event", + "measure", + "series", + "edition", + "bound", } ) @@ -153,17 +258,49 @@ class ComparisonStatus(str, Enum): class DiagnosisClass(str, Enum): + """Adjudication classes under the descriptive register (issue #9, + Max 2026-08-02): the Scorecard is descriptive by default. PE_GAP and + EXTERNAL_ISSUE are normative and therefore GATED — they require a + citable known issue in action_link (a GitHub issue, published erratum, + internal contradiction, or tracked correction); divergence alone never + qualifies. METHODOLOGICAL_DIFFERENCE is strictly descriptive: the + models differ because of documented choices on both sides, stated, + sourced, and left there — no convergence or defended-departure + framing in either direction.""" + PE_GAP = "pe_gap" EXTERNAL_ISSUE = "external_issue" CONCEPT_MISMATCH = "concept_mismatch" + METHODOLOGICAL_DIFFERENCE = "methodological_difference" VINTAGE = "vintage" UNDIAGNOSED = "undiagnosed" +# Diagnosis classes that may only be assigned with a citable known issue. +GATED_DIAGNOSIS_CLASSES = frozenset( + {DiagnosisClass.PE_GAP, DiagnosisClass.EXTERNAL_ISSUE} +) + + def _canonical(obj: Any) -> str: return json.dumps(obj, sort_keys=True, separators=(",", ":")) +# The null baseline descriptor: current law at the source's scoring date. +CURRENT_LAW_DESCRIPTOR = {"policy": "current_law"} + + +def baseline_key(descriptor: dict) -> str: + """Stable key over a baseline descriptor dict (issue #13). The same + descriptor shape ReformRef.baseline carries; {"policy": "current_law"} + keys the null baseline.""" + if not (isinstance(descriptor, dict) and descriptor.get("policy")): + raise ValueError( + f"baseline descriptor needs a 'policy' slug: {descriptor!r}" + ) + return hashlib.sha256(_canonical(descriptor).encode()).hexdigest()[:16] + + @dataclass(frozen=True) class ReformRef: """The policy world a claim scores. @@ -243,6 +380,24 @@ def key(self) -> str: ).encode() ).hexdigest()[:16] + def baseline_descriptor(self) -> dict: + """The baseline world this reform is scored against, as a + descriptor dict. Absent baseline means current law — the JCT / + HMT-costing convention: scored against the law in force at + publication (the announcement vintage rides in conditions such as + fiscal_event / data_vintage, not in the baseline world).""" + return ( + self.baseline + if self.baseline is not None + else CURRENT_LAW_DESCRIPTOR + ) + + def baseline_key(self) -> str: + """First-class baseline identity (issue #13): a stable hash of the + baseline descriptor, FK into the baselines registry. Additive + projection only — claim_id/key() hashing is unchanged.""" + return baseline_key(self.baseline_descriptor()) + def to_json(self) -> str: return _canonical( { @@ -340,7 +495,14 @@ def claim_id(self) -> str: @dataclass class PEResult: - """PolicyEngine's computation for a claim (history preserved per run).""" + """PolicyEngine's computation for a claim (history preserved per run). + + baseline_key records the baseline world the run ACTUALLY executed + (issue #13 point 5) — e.g. the two-child-limit runs execute a + pre_ab2025 reinstated counterfactual as their baseline, not current + law. None on legacy rows only; new ingests must pass it, and the + comparisons view refuses to render plain agreement when it differs + from the claim's baseline.""" claim_id: str computed_value: Optional[float] @@ -351,6 +513,7 @@ class PEResult: run_id: str = "" computed_at: str = "" # ISO timestamp, caller-supplied annotations: list = field(default_factory=list) + baseline_key: Optional[str] = None # baseline actually executed def __post_init__(self): self.status = ComparisonStatus(self.status) diff --git a/scorecard_db/relationships.py b/scorecard_db/relationships.py index 5207975..0d66092 100644 --- a/scorecard_db/relationships.py +++ b/scorecard_db/relationships.py @@ -104,6 +104,11 @@ Metric.POVERTY_RATE, Metric.POVERTY_RATE_CHANGE, Metric.POVERTY_COUNT_CHANGE, + # 2026-08-02 UK ingest: poverty headcounts (HBAI counts, JRF + # series) and persistent poverty are the same modeled-outcome + # family — the doctrine is metric-shaped, not country-shaped. + Metric.POVERTY_COUNT, + Metric.PERSISTENT_POVERTY_RATE, } ) PERMANENT_HOLDOUT_BASIS = ( diff --git a/tests/test_scorecard_db.py b/tests/test_scorecard_db.py index 269808b..59fa1a7 100644 --- a/tests/test_scorecard_db.py +++ b/tests/test_scorecard_db.py @@ -516,3 +516,199 @@ def test_admin_metrics_unaffected(self): assert not never_calibrate(Metric.PARTICIPATION_RATE) assert not never_calibrate(Metric.ELIGIBLE_COUNT) + + +class TestBaselineRegistry: + """Baseline as a first-class attribute of every score (issue #13).""" + + def test_null_baseline_keys_current_law(self): + from scorecard_db import CURRENT_LAW_DESCRIPTOR, baseline_key + + assert BASELINE.baseline_key() == baseline_key(CURRENT_LAW_DESCRIPTOR) + pe = ReformRef("policyengine_us", reform={"p": {"2025": 1}}) + assert pe.baseline_key() == BASELINE.baseline_key() + + def test_non_current_law_baseline_distinct(self): + r = ReformRef( + framework="policy_ref", + reform={"policy": "obbba"}, + baseline={"policy": "tcja_extension"}, + ) + assert r.baseline_key() != BASELINE.baseline_key() + + def test_descriptor_requires_policy_slug(self): + from scorecard_db import baseline_key + + with pytest.raises(ValueError): + baseline_key({"label": "nope"}) + + def test_claim_id_unchanged_by_baseline_key_projection(self): + # Additive projection only: the #13 columns must not move ids. + assert score().claim_id() == "157243b61838075381ed" + + def test_scores_carry_baseline_key(self, tmp_path): + db = ScorecardDB(tmp_path / "t.db") + db.upsert_scores([score()]) + row = db.conn.execute("SELECT baseline_key FROM external_scores").fetchone() + assert row["baseline_key"] == BASELINE.baseline_key() + db.close() + + def test_registry_seeding_and_unregistered_detection(self, tmp_path): + from scorecard_db.baselines import register_baselines + + db = ScorecardDB(tmp_path / "t.db") + db.upsert_scores([score()]) + register_baselines(db) + assert db.unregistered_baselines() == [] + row = db.comparisons()[0] + assert row["claim_baseline_label"] == "current_law" + + alien = score( + conditions={"geography": "US", "program": "wic"}, + reform=ReformRef( + framework="policy_ref", + reform={"policy": "x"}, + baseline={"policy": "never_registered_world"}, + ), + ) + db.upsert_scores([alien]) + with pytest.raises(ValueError, match="never_registered"): + register_baselines(db) + db.close() + + def test_view_guard_downgrades_cross_baseline_agreement(self, tmp_path): + """comparable vs a different executed baseline can never render as + plain agreement — pe_status_effective says constructed.""" + from scorecard_db import baseline_key + + db = ScorecardDB(tmp_path / "t.db") + s = score() + db.upsert_scores([s]) + db.add_results( + [ + PEResult( + claim_id=s.claim_id(), + computed_value=999.0, + status=ComparisonStatus.COMPARABLE, + engine_version="x", + data_bundle="y", + baseline_key=baseline_key({"policy": "pre_ab2025"}), + ) + ] + ) + row = db.comparisons()[0] + assert row["pe_status"] == "comparable" + assert row["pe_status_effective"] == "constructed" + db.close() + + def test_view_guard_passes_same_baseline(self, tmp_path): + db = ScorecardDB(tmp_path / "t.db") + s = score() + db.upsert_scores([s]) + db.add_results( + [ + PEResult( + claim_id=s.claim_id(), + computed_value=999.0, + status=ComparisonStatus.COMPARABLE, + engine_version="x", + data_bundle="y", + baseline_key=BASELINE.baseline_key(), + ) + ] + ) + row = db.comparisons()[0] + assert row["pe_status_effective"] == "comparable" + db.close() + + def test_legacy_results_without_baseline_pass_through(self, tmp_path): + db = ScorecardDB(tmp_path / "t.db") + s = score() + db.upsert_scores([s]) + db.add_results( + [ + PEResult( + claim_id=s.claim_id(), + computed_value=999.0, + status=ComparisonStatus.COMPARABLE, + engine_version="x", + data_bundle="y", + ) + ] + ) + assert db.comparisons()[0]["pe_status_effective"] == "comparable" + db.close() + + +class TestDescriptiveRegister: + """Issue #9 latest ruling: normative classes gated on citable issues.""" + + def test_gated_classes_require_action_link(self, tmp_path): + db = ScorecardDB(tmp_path / "t.db") + s = score() + db.upsert_scores([s]) + for cls in ("pe_gap", "external_issue"): + with pytest.raises(ValueError, match="citable"): + db.diagnose(s.claim_id(), cls, "divergence looks big") + db.diagnose( + s.claim_id(), "pe_gap", "EHS at engine-default take-up", + action_link="https://github.com/PolicyEngine/populace/issues/593", + ) + db.close() + + def test_methodological_difference_is_descriptive(self, tmp_path): + db = ScorecardDB(tmp_path / "t.db") + s = score() + db.upsert_scores([s]) + db.diagnose( + s.claim_id(), + "methodological_difference", + "Populace calculates benefits and recalibrates where ASEC " + "carries reported attributes.", + ) + assert ( + db.comparisons()[0]["diagnosis_class"] + == "methodological_difference" + ) + db.close() + + def test_old_diagnoses_table_migrates_to_new_check(self, tmp_path): + import sqlite3 as s3 + + path = tmp_path / "old.db" + conn = s3.connect(path) + conn.executescript( + """ + CREATE TABLE external_scores ( + claim_id TEXT PRIMARY KEY, source TEXT NOT NULL, + source_model TEXT, ledger_fact TEXT, source_column TEXT, + publication TEXT NOT NULL DEFAULT '{}', + reform_key TEXT NOT NULL, reform_json TEXT NOT NULL, + metric TEXT NOT NULL, unit_concept TEXT NOT NULL, + period INTEGER NOT NULL, time_basis TEXT NOT NULL, + conditions TEXT NOT NULL DEFAULT '{}', + geography TEXT, program TEXT, value REAL, + value_kind TEXT NOT NULL, status TEXT NOT NULL, + calibration_relationship TEXT NOT NULL + ); + CREATE TABLE diagnoses ( + claim_id TEXT PRIMARY KEY, + diagnosis_class TEXT NOT NULL CHECK (diagnosis_class IN ( + 'pe_gap','external_issue','concept_mismatch','vintage', + 'undiagnosed' + )), + rationale TEXT NOT NULL DEFAULT '', + action_link TEXT NOT NULL DEFAULT '' + ); + INSERT INTO diagnoses VALUES ('c1', 'vintage', 'r', ''); + """ + ) + conn.close() + db = ScorecardDB(path) + db.upsert_scores([score()]) + db.diagnose(score().claim_id(), "methodological_difference", "ok") + kept = db.conn.execute( + "SELECT diagnosis_class FROM diagnoses WHERE claim_id='c1'" + ).fetchone() + assert kept["diagnosis_class"] == "vintage" + db.close() From 1c5f76f2c8778cb2683cfc85e831362fb4f23626 Mon Sep 17 00:00:00 2001 From: Max Ghenis Date: Sun, 2 Aug 2026 21:45:02 -0400 Subject: [PATCH 2/4] Ingest the 2026-08-02 seven-source UK harvest (31,762 claims + Ledger routing) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Seven adapters over vendored gzipped staging (sources/harvest-uk-2026-08-02; raw downloads stay outside, pinned by manifests): obr 25,425 · dwp 1,952 · hmt 1,368 · hmrc 987 · ukmod 1,392 · jrf 300 · ifs 268 · resolution_foundation 70 Full accounting against the 33,943 staged rows: 31,762 ingested + 2,090 admin outturns routed to Ledger staging (data/ledger/uk_admin_outturns .jsonl — OBR EFO outturn columns 133, DWP BECL outturns 102, HMRC outturn/provisional statistics 1,855; deterministic pre-agreed fact ids) + 89 deliberate drops tallied in lane notes (88 JRF MIS budget cells, 1 RF price-index row) + 2 JRF rounded/unrounded twins merged with rounding-consistency assertions. Load-bearing decisions: - period = FY START year everywhere, re-derived from verbatim fy labels (fixes DWP FYE end-year keying and the 1999/00→1900 staging defect); - OBR measures database: policy_ref world per measure title × 84 fiscal events; workbook-order reconstruction of component runs, 4.9 welfare-cap sections, 4.11 parent lines, and the Mar-2026/Nov-2025 EFO vintage split — all condition axes the staging had dropped; - consumed_as_target only on lines populace-UK literally consumes, read from policyengine-uk-data this session (obr.py receipts/CT/NICs/4.9 welfare; BECL expenditure for the five exact-line benefits; SPI-family projections seed_source via the shared SPI 2023-24 base; DWP UC admin and PC take-up per the staged verified notes; HB take-up held out as the live comparator for policyengine-uk#1813); - IFS Green-Budget options ride the registered non-current-law baseline world ifs_2cl_fp_removal_rolled_out (#13); - HMRC ready-reckoner lines are policy worlds slugged identically to the campaign runs' join keys. Tests: 42 new (tests/test_uk_ingest.py). Co-Authored-By: Claude Fable 5 --- data/lanes.json | 70 +- data/ledger/uk_admin_outturns.jsonl | 2090 +++++++++++++++++ scorecard_db/baselines.py | 11 + scorecard_db/ingest_harvest.py | 9 +- scorecard_db/ingest_uk.py | 118 + scorecard_db/ingest_uk_dwp.py | 305 +++ scorecard_db/ingest_uk_hmrc.py | 241 ++ scorecard_db/ingest_uk_hmt.py | 184 ++ scorecard_db/ingest_uk_ifs.py | 253 ++ scorecard_db/ingest_uk_obr.py | 445 ++++ scorecard_db/ingest_uk_rf.py | 252 ++ scorecard_db/ingest_uk_ukmod_jrf.py | 333 +++ scorecard_db/uk.py | 247 ++ sources/harvest-uk-2026-08-02/COLLATION.md | 76 + sources/harvest-uk-2026-08-02/uk_dwp/NOTES.md | 177 ++ .../uk_dwp/claims_staged.jsonl.gz | Bin 0 -> 63493 bytes .../uk_dwp/manifest.jsonl | 15 + .../harvest-uk-2026-08-02/uk_hmrc/NOTES.md | 124 + .../uk_hmrc/claims_staged.jsonl.gz | Bin 0 -> 61920 bytes .../uk_hmrc/manifest.jsonl | 11 + sources/harvest-uk-2026-08-02/uk_hmt/NOTES.md | 1601 +++++++++++++ .../uk_hmt/claims_staged.jsonl.gz | Bin 0 -> 46960 bytes .../uk_hmt/manifest.jsonl | 16 + sources/harvest-uk-2026-08-02/uk_ifs/NOTES.md | 145 ++ .../uk_ifs/claims_staged.jsonl.gz | Bin 0 -> 13706 bytes .../uk_ifs/manifest.jsonl | 16 + sources/harvest-uk-2026-08-02/uk_obr/NOTES.md | 131 ++ .../uk_obr/claims_staged.jsonl.gz | Bin 0 -> 609965 bytes .../uk_obr/manifest.jsonl | 16 + .../uk_resolution_foundation/NOTES.md | 178 ++ .../claims_staged.jsonl.gz | Bin 0 -> 5855 bytes .../uk_resolution_foundation/manifest.jsonl | 15 + .../uk_ukmod_jrf/NOTES.md | 139 ++ .../uk_ukmod_jrf/claims_staged.jsonl.gz | Bin 0 -> 46853 bytes .../uk_ukmod_jrf/manifest.jsonl | 5 + tests/test_uk_ingest.py | 542 +++++ 36 files changed, 7748 insertions(+), 17 deletions(-) create mode 100644 data/ledger/uk_admin_outturns.jsonl create mode 100644 scorecard_db/ingest_uk.py create mode 100644 scorecard_db/ingest_uk_dwp.py create mode 100644 scorecard_db/ingest_uk_hmrc.py create mode 100644 scorecard_db/ingest_uk_hmt.py create mode 100644 scorecard_db/ingest_uk_ifs.py create mode 100644 scorecard_db/ingest_uk_obr.py create mode 100644 scorecard_db/ingest_uk_rf.py create mode 100644 scorecard_db/ingest_uk_ukmod_jrf.py create mode 100644 scorecard_db/uk.py create mode 100644 sources/harvest-uk-2026-08-02/COLLATION.md create mode 100644 sources/harvest-uk-2026-08-02/uk_dwp/NOTES.md create mode 100644 sources/harvest-uk-2026-08-02/uk_dwp/claims_staged.jsonl.gz create mode 100644 sources/harvest-uk-2026-08-02/uk_dwp/manifest.jsonl create mode 100644 sources/harvest-uk-2026-08-02/uk_hmrc/NOTES.md create mode 100644 sources/harvest-uk-2026-08-02/uk_hmrc/claims_staged.jsonl.gz create mode 100644 sources/harvest-uk-2026-08-02/uk_hmrc/manifest.jsonl create mode 100644 sources/harvest-uk-2026-08-02/uk_hmt/NOTES.md create mode 100644 sources/harvest-uk-2026-08-02/uk_hmt/claims_staged.jsonl.gz create mode 100644 sources/harvest-uk-2026-08-02/uk_hmt/manifest.jsonl create mode 100644 sources/harvest-uk-2026-08-02/uk_ifs/NOTES.md create mode 100644 sources/harvest-uk-2026-08-02/uk_ifs/claims_staged.jsonl.gz create mode 100644 sources/harvest-uk-2026-08-02/uk_ifs/manifest.jsonl create mode 100644 sources/harvest-uk-2026-08-02/uk_obr/NOTES.md create mode 100644 sources/harvest-uk-2026-08-02/uk_obr/claims_staged.jsonl.gz create mode 100644 sources/harvest-uk-2026-08-02/uk_obr/manifest.jsonl create mode 100644 sources/harvest-uk-2026-08-02/uk_resolution_foundation/NOTES.md create mode 100644 sources/harvest-uk-2026-08-02/uk_resolution_foundation/claims_staged.jsonl.gz create mode 100644 sources/harvest-uk-2026-08-02/uk_resolution_foundation/manifest.jsonl create mode 100644 sources/harvest-uk-2026-08-02/uk_ukmod_jrf/NOTES.md create mode 100644 sources/harvest-uk-2026-08-02/uk_ukmod_jrf/claims_staged.jsonl.gz create mode 100644 sources/harvest-uk-2026-08-02/uk_ukmod_jrf/manifest.jsonl create mode 100644 tests/test_uk_ingest.py diff --git a/data/lanes.json b/data/lanes.json index 7f30f16..a938a9c 100644 --- a/data/lanes.json +++ b/data/lanes.json @@ -140,50 +140,50 @@ "source": "DWP", "area": "UK income-related benefits take-up", "mode": 1, - "stage": "registered", + "stage": "ingested", "running": false, - "updated": "2026-08-01", - "note": "Canonical UK take-up publication (#3)" + "updated": "2026-08-02", + "note": "805 take-up claims with bounds (609 PC rows seed_source \u2014 pe-uk takeup.yaml cites this series; HB rows held_out vs PE takeup=1, policyengine-uk#1813); 102 BECL forecast rows (30 expenditure lines consumed_as_target via OBR 4.9); 102 BECL outturn rows routed to Ledger staging" }, { "id": "hbai-poverty", "source": "DWP HBAI", "area": "UK poverty rates", "mode": 1, - "stage": "registered", + "stage": "ingested", "running": false, - "updated": "2026-08-01", - "note": "#3" + "updated": "2026-08-02", + "note": "1040 HBAI claims (FYE 1995-2025, relative+absolute \u00d7 BHC+AHC, rates+counts; FYE-2025 + admin-linked FYE-2024 edition pair staged \u2014 the ~2pp methodology-gap diagnosis seed); permanent poverty holdout" }, { "id": "hmrc-personal-tax", "source": "HMRC", "area": "UK personal tax statistics", "mode": 1, - "stage": "registered", + "stage": "ingested", "running": false, - "updated": "2026-08-01", - "note": "#3" + "updated": "2026-08-02", + "note": "225 ready-reckoner claims (policy worlds per line, FY2026-27+, behavioural per HMRC notes \u2014 the campaign reckoner join surface) + 762 SPI-based projections (726 seed_source via the shared SPI 2023-24 base, 36 whole-population liability totals consumed-class); 1855 outturn/provisional admin rows routed to Ledger staging" }, { "id": "obr-welfare", "source": "OBR", "area": "welfare trends / EFO baselines", "mode": 1, - "stage": "registered", + "stage": "ingested", "running": false, - "updated": "2026-08-01", - "note": "#3" + "updated": "2026-08-02", + "note": "1121 EFO Mar-2026 claims (receipts 3.4/3.8, welfare 4.9/4.11, threshold analysis 3.17-3.19); 150 consumed_as_target (exact pe-uk-data target lines, targets/sources/obr.py); 133 outturn rows routed to Ledger staging" }, { "id": "ukmod-stats", "source": "UKMOD", "area": "published statistics", "mode": 1, - "stage": "registered", + "stage": "ingested", "running": false, - "updated": "2026-08-01", - "note": "#3" + "updated": "2026-08-02", + "note": "1392 UKMOD claims \u2014 Country Report 2023-2030 validation block (simulated/official/input-data/HBAI series side by side; take-up priors frozen since 2021 per their own \u00a74.3 warning) + CeMPA 3/26 AB2025 package assessment (209 reform-keyed rows); 300 JRF claims (unrounded AHC headline series, persistent poverty, MIS-adjacent thresholds); 88 MIS weekly-budget cells deliberately dropped (focus-group budget standards, not model-checkable \u2014 recoverable in vendored staging)" }, { "id": "jct-reform-scores", @@ -294,6 +294,46 @@ "running": false, "updated": "2026-08-02", "note": "1033 claims: monthly SPM 2024-01\u21922025-12 (final series \u2014 project ended Dec 2025), CTC counterfactuals 2023/2024 at 100% take-up, state refundable-CTC designs, SNAP TFP-revocation state tables (TRIM3 2015-19 base); annual-SPM\u2248Census reviewed \u2192 held_out (no poverty targets in pe-us calibration); 16.6-vs-11.4 erratum diagnosed external_issue" + }, + { + "id": "obr-measures", + "source": "OBR", + "area": "policy measures database (1970\u2192)", + "mode": 2, + "stage": "ingested", + "running": false, + "updated": "2026-08-02", + "note": "24304 policy-measures-database claims (84 fiscal events since 1970, reform-keyed per measure title, positive_gain_to_exchequer verbatim)" + }, + { + "id": "hmt-costings", + "source": "HM Treasury", + "area": "fiscal-event scorecards + DA", + "mode": 2, + "stage": "ingested", + "running": false, + "updated": "2026-08-02", + "note": "1218 OBR-certified scorecard costings (AB2024 5.1 / B2025 4.1 / SS2025 3.1; exchequer_impact \u2014 Tax/Spend heads mix by design; 31 suppressed cells verbatim) + 150 IGOTM decile medians (annex 2.C); B2025 two-child measure title embeds the government's 450k-children poverty claim \u2014 pentagon leg" + }, + { + "id": "ifs-taxben", + "source": "IFS TAXBEN", + "area": "poverty + benefit options", + "mode": 2, + "stage": "ingested", + "running": false, + "updated": "2026-08-02", + "note": "268 TAXBEN claims: absolute-AHC child-poverty series, Green-Budget-2025 options block (164 reform-keyed rows incl. the \u2212540k steady-state two-child-limit leg of the pentagon), threshold-freeze revenue rows; options baseline = registered ifs_2cl_fp_removal_rolled_out world; TAXBEN is entitlements-basis (full take-up) \u2014 registry axis on every poverty comparison" + }, + { + "id": "rf-outlook", + "source": "Resolution Foundation", + "area": "living standards outlook + Budget analysis", + "mode": 2, + "stage": "ingested", + "running": false, + "updated": "2026-08-02", + "note": "70 Resolution Foundation claims (IPPR Tax Benefit Model on FRS/HBAI 2023-24): LSO 2026 poverty projections incl. the \u2212420k two-child pentagon leg, Budget-2025 decile block, April-2026 uprating set (11 parameter-check rows \u2014 campaign uprating_check joins here); 26 reform-keyed rows; 1 price-index-only row dropped (out of tax/benefit scope, tallied)" } ] } diff --git a/data/ledger/uk_admin_outturns.jsonl b/data/ledger/uk_admin_outturns.jsonl new file mode 100644 index 0000000..e7d533c --- /dev/null +++ b/data/ledger/uk_admin_outturns.jsonl @@ -0,0 +1,2090 @@ +{"fact_id": "uk:uk_dwp:00ed545f86d6db8aae16", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "state_pension", "fy": "2021/22", "geography": "gb"}, "conversion": "sheet value in GBP million (nominal terms) x 1e6 -> GBP", "metric": "benefit_cost", "period": 2022, "proposed_unit": "gbp", "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r4c77", "date": "2026-04-14", "sheet": "State Pension", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "State Pension | Total | 2021/22 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "value": 104691670423.69, "value_kind": "gbp", "value_raw": "104691.67042369001"}} +{"fact_id": "uk:uk_dwp:042b51efbd9105afae61", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "personal_tax_credits", "fy": "2024/25", "geography": "gb"}, "conversion": "sheet value in GBP million (nominal terms) x 1e6 -> GBP", "metric": "benefit_cost", "period": 2025, "proposed_unit": "gbp", "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r5c80", "date": "2026-04-14", "sheet": "Non-DWP Welfare", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Non-DWP Welfare | Personal tax credits | 2024/25 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "value": 1763602550.74, "value_kind": "gbp", "value_raw": "1763.602550738144"}} +{"fact_id": "uk:uk_dwp:0e54e44c94be47023652", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "pension_credit", "fy": "2023/24", "geography": "gb"}, "conversion": "sheet value in thousands x 1000 -> count", "metric": "caseload", "period": 2024, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r20c79", "date": "2026-04-14", "sheet": "Pension Credit", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Pension Credit | Pension Credit | 2023/24 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "families", "unit_note": "PC caseload = claims (benefit units); staged as families", "value": 1370000.0, "value_kind": "count", "value_raw": "1370"}} +{"fact_id": "uk:uk_dwp:0e5b7bdfed0aff5d832a", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "universal_credit", "fy": "2023/24", "geography": "gb"}, "conversion": "sheet value in thousands x 1000 -> count", "metric": "caseload", "period": 2024, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r53c79", "date": "2026-04-14", "sheet": "Universal Credit and equivalent", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Universal Credit and equivalent | Universal Credit | 2023/24 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "households", "unit_note": "UC caseload = households (benefit units) per BECL notes", "value": 4706000.0, "value_kind": "count", "value_raw": "4706"}} +{"fact_id": "uk:uk_dwp:1171835d566b8100348b", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "attendance_allowance", "component": "total", "fy": "2021/22", "geography": "england_wales"}, "conversion": "sheet value in thousands x 1000 -> count", "geography_note": "England and Wales only from FY 2020/21 (Scottish devolution of disability benefits 1 April 2020; BECL Notes tab)", "metric": "caseload", "period": 2022, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r73c77", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | Attendance Allowance | 2021/22 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "persons", "value": 1373000.0, "value_kind": "count", "value_raw": "1373"}} +{"fact_id": "uk:uk_dwp:126fb5bbc9c1a9308e17", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "pip", "component": "total", "fy": "2019/20", "geography": "gb"}, "conversion": "sheet value in thousands x 1000 -> count", "metric": "caseload", "period": 2020, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r64c75", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | Personal Independence Payment | 2019/20 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "persons", "value": 2213000.0, "value_kind": "count", "value_raw": "2213"}} +{"fact_id": "uk:uk_dwp:14b39e9534aea7fd0653", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "universal_credit", "fy": "2019/20", "geography": "gb"}, "conversion": "sheet value in GBP million (nominal terms) x 1e6 -> GBP", "metric": "benefit_cost", "period": 2020, "proposed_unit": "gbp", "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r15c75", "date": "2026-04-14", "sheet": "Universal Credit and equivalent", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Universal Credit and equivalent | Universal Credit | 2019/20 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "value": 18376926201.87, "value_kind": "gbp", "value_raw": "18376.92620187"}} +{"fact_id": "uk:uk_dwp:1c4e6fb644252bdf6d4c", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "dla", "component": "total", "fy": "2019/20", "geography": "gb"}, "conversion": "sheet value in thousands x 1000 -> count", "metric": "caseload", "period": 2020, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r54c75", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | Disability Living Allowance | 2019/20 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "persons", "value": 1554000.0, "value_kind": "count", "value_raw": "1554"}} +{"fact_id": "uk:uk_dwp:213945325e1b079b7f15", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "uc_and_equivalents", "fy": "2022/23", "geography": "gb"}, "conversion": "sheet value in GBP million (nominal terms) x 1e6 -> GBP", "metric": "benefit_cost", "period": 2023, "proposed_unit": "gbp", "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r4c78", "date": "2026-04-14", "sheet": "Universal Credit and equivalent", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Universal Credit and equivalent | Total UC and equivalents | 2022/23 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "value": 73403838363.16, "value_kind": "gbp", "value_raw": "73403.83836315526"}} +{"fact_id": "uk:uk_dwp:222cd8fd18422df49095", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "pip", "fy": "2023/24", "geography": "england_wales"}, "conversion": "sheet value in GBP million (nominal terms) x 1e6 -> GBP", "geography_note": "England and Wales only from FY 2020/21 (Scottish devolution of disability benefits 1 April 2020; BECL Notes tab)", "metric": "benefit_cost", "period": 2024, "proposed_unit": "gbp", "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r11c79", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | Personal Independence Payment | 2023/24 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "value": 21668789777.11, "value_kind": "gbp", "value_raw": "21668.789777107457"}} +{"fact_id": "uk:uk_dwp:3852c25b0bb516a0f347", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "pip", "component": "in_payment", "fy": "2021/22", "geography": "england_wales"}, "conversion": "sheet value in thousands x 1000 -> count", "geography_note": "England and Wales only from FY 2020/21 (Scottish devolution of disability benefits 1 April 2020; BECL Notes tab)", "metric": "caseload", "period": 2022, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r65c77", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | of which in payment | 2021/22 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "persons", "value": 2530000.0, "value_kind": "count", "value_raw": "2530"}} +{"fact_id": "uk:uk_dwp:3868a2aedf502314166c", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "pension_credit", "fy": "2020/21", "geography": "gb"}, "conversion": "sheet value in GBP million (nominal terms) x 1e6 -> GBP", "metric": "benefit_cost", "period": 2021, "proposed_unit": "gbp", "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r5c76", "date": "2026-04-14", "sheet": "Pension Credit", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Pension Credit | Total Pension Credit | 2020/21 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "value": 5070936824.2, "value_kind": "gbp", "value_raw": "5070.9368242"}} +{"fact_id": "uk:uk_dwp:3eba22803ff7dc736d7e", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "personal_tax_credits", "fy": "2021/22", "geography": "gb"}, "conversion": "sheet value in GBP million (nominal terms) x 1e6 -> GBP", "metric": "benefit_cost", "period": 2022, "proposed_unit": "gbp", "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r5c77", "date": "2026-04-14", "sheet": "Non-DWP Welfare", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Non-DWP Welfare | Personal tax credits | 2021/22 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "value": 10315715819.23, "value_kind": "gbp", "value_raw": "10315.715819234068"}} +{"fact_id": "uk:uk_dwp:5089b9adde2e3041d9e8", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "universal_credit", "fy": "2022/23", "geography": "gb"}, "conversion": "sheet value in thousands x 1000 -> count", "metric": "caseload", "period": 2023, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r53c78", "date": "2026-04-14", "sheet": "Universal Credit and equivalent", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Universal Credit and equivalent | Universal Credit | 2022/23 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "households", "unit_note": "UC caseload = households (benefit units) per BECL notes", "value": 4229000.0, "value_kind": "count", "value_raw": "4229"}} +{"fact_id": "uk:uk_dwp:5766affac034a4d4456e", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "pension_credit", "fy": "2020/21", "geography": "gb"}, "conversion": "sheet value in thousands x 1000 -> count", "metric": "caseload", "period": 2021, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r20c76", "date": "2026-04-14", "sheet": "Pension Credit", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Pension Credit | Pension Credit | 2020/21 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "families", "unit_note": "PC caseload = claims (benefit units); staged as families", "value": 1480000.0, "value_kind": "count", "value_raw": "1480"}} +{"fact_id": "uk:uk_dwp:70bd871dbf25df935406", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "dla", "component": "total", "fy": "2020/21", "geography": "england_wales"}, "conversion": "sheet value in thousands x 1000 -> count", "geography_note": "England and Wales only from FY 2020/21 (Scottish devolution of disability benefits 1 April 2020; BECL Notes tab)", "metric": "caseload", "period": 2021, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r54c76", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | Disability Living Allowance | 2020/21 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "persons", "value": 1232000.0, "value_kind": "count", "value_raw": "1232"}} +{"fact_id": "uk:uk_dwp:88f0d0af80bff3dcde47", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "attendance_allowance", "fy": "2024/25", "geography": "england_wales"}, "conversion": "sheet value in GBP million (nominal terms) x 1e6 -> GBP", "geography_note": "England and Wales only from FY 2020/21 (Scottish devolution of disability benefits 1 April 2020; BECL Notes tab)", "metric": "benefit_cost", "period": 2025, "proposed_unit": "gbp", "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r16c80", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | Attendance Allowance | 2024/25 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "value": 7766559260.42, "value_kind": "gbp", "value_raw": "7766.559260419999"}} +{"fact_id": "uk:uk_dwp:905441aab716ef2e8f3a", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "attendance_allowance", "fy": "2023/24", "geography": "england_wales"}, "conversion": "sheet value in GBP million (nominal terms) x 1e6 -> GBP", "geography_note": "England and Wales only from FY 2020/21 (Scottish devolution of disability benefits 1 April 2020; BECL Notes tab)", "metric": "benefit_cost", "period": 2024, "proposed_unit": "gbp", "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r16c79", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | Attendance Allowance | 2023/24 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "value": 6695944034.01, "value_kind": "gbp", "value_raw": "6695.944034009999"}} +{"fact_id": "uk:uk_dwp:90cc7558f40410c8af41", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "attendance_allowance", "component": "total", "fy": "2023/24", "geography": "england_wales"}, "conversion": "sheet value in thousands x 1000 -> count", "geography_note": "England and Wales only from FY 2020/21 (Scottish devolution of disability benefits 1 April 2020; BECL Notes tab)", "metric": "caseload", "period": 2024, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r73c79", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | Attendance Allowance | 2023/24 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "persons", "value": 1518000.0, "value_kind": "count", "value_raw": "1518"}} +{"fact_id": "uk:uk_dwp:9b4aeb78976f4fc77426", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "dla", "component": "in_payment", "fy": "2023/24", "geography": "england_wales"}, "conversion": "sheet value in thousands x 1000 -> count", "geography_note": "England and Wales only from FY 2020/21 (Scottish devolution of disability benefits 1 April 2020; BECL Notes tab)", "metric": "caseload", "period": 2024, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r55c79", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | of which in payment | 2023/24 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "persons", "value": 1232000.0, "value_kind": "count", "value_raw": "1232"}} +{"fact_id": "uk:uk_dwp:9ca2e5d8ace400ddf2c6", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "dla", "component": "in_payment", "fy": "2019/20", "geography": "gb"}, "conversion": "sheet value in thousands x 1000 -> count", "metric": "caseload", "period": 2020, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r55c75", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | of which in payment | 2019/20 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "persons", "value": 1539000.0, "value_kind": "count", "value_raw": "1539"}} +{"fact_id": "uk:uk_dwp:9d5b7f1566df3f0555bc", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "personal_tax_credits", "fy": "2020/21", "geography": "gb"}, "conversion": "sheet value in GBP million (nominal terms) x 1e6 -> GBP", "metric": "benefit_cost", "period": 2021, "proposed_unit": "gbp", "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r5c76", "date": "2026-04-14", "sheet": "Non-DWP Welfare", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Non-DWP Welfare | Personal tax credits | 2020/21 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "value": 14608860761.0, "value_kind": "gbp", "value_raw": "14608.860760997823"}} +{"fact_id": "uk:uk_dwp:9f4a9068f324249950d9", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "pension_credit", "fy": "2023/24", "geography": "gb"}, "conversion": "sheet value in GBP million (nominal terms) x 1e6 -> GBP", "metric": "benefit_cost", "period": 2024, "proposed_unit": "gbp", "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r5c79", "date": "2026-04-14", "sheet": "Pension Credit", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Pension Credit | Total Pension Credit | 2023/24 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "value": 5467137915.01, "value_kind": "gbp", "value_raw": "5467.137915009998"}} +{"fact_id": "uk:uk_dwp:abecb98f384c4e55c288", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "pip", "component": "in_payment", "fy": "2023/24", "geography": "england_wales"}, "conversion": "sheet value in thousands x 1000 -> count", "geography_note": "England and Wales only from FY 2020/21 (Scottish devolution of disability benefits 1 April 2020; BECL Notes tab)", "metric": "caseload", "period": 2024, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r65c79", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | of which in payment | 2023/24 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "persons", "value": 3163000.0, "value_kind": "count", "value_raw": "3163"}} +{"fact_id": "uk:uk_dwp:c149a9c32f23138586e5", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "attendance_allowance", "component": "total", "fy": "2024/25", "geography": "england_wales"}, "conversion": "sheet value in thousands x 1000 -> count", "geography_note": "England and Wales only from FY 2020/21 (Scottish devolution of disability benefits 1 April 2020; BECL Notes tab)", "metric": "caseload", "period": 2025, "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r73c80", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | Attendance Allowance | 2024/25 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "time_note": "FY-average caseload (BECL Notes: 'Caseload figures represent an average over the full financial year')", "unit_concept": "persons", "value": 1645000.0, "value_kind": "count", "value_raw": "1645"}} +{"fact_id": "uk:uk_dwp:c5214fa8f63081b9e06e", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "dla", "fy": "2024/25", "geography": "england_wales"}, "conversion": "sheet value in GBP million (nominal terms) x 1e6 -> GBP", "geography_note": "England and Wales only from FY 2020/21 (Scottish devolution of disability benefits 1 April 2020; BECL Notes tab)", "metric": "benefit_cost", "period": 2025, "proposed_unit": "gbp", "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r6c80", "date": "2026-04-14", "sheet": "Disability benefits", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Disability benefits | Disability Living Allowance | 2024/25 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "value": 7722593090.56, "value_kind": "gbp", "value_raw": "7722.59309056"}} +{"fact_id": "uk:uk_dwp:d63e12e0abbf3023a4a8", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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NOTE ALSO: pe-uk-data maps FY to its STARTING calendar year (FY 2025-26 -> 2025); this staging uses FY ENDING year (-> 2026); conditions.fy is the unambiguous label", "calibration_relationship": "held_out", "conditions": {"basis": "outturn", "benefit": "personal_tax_credits", "fy": "2023/24", "geography": "gb"}, "conversion": "sheet value in GBP million (nominal terms) x 1e6 -> GBP", "metric": "benefit_cost", "period": 2024, "proposed_unit": "gbp", "publication": {"artifact": "downloads/outturn-and-forecast-tables-spring-forecast-2026.xlsx", "cell": "r5c79", "date": "2026-04-14", "sheet": "Non-DWP Welfare", "title": "Benefit expenditure and caseload tables 2026: Outturn and forecast tables, Spring Forecast 2026", "url": "https://www.gov.uk/government/publications/benefit-expenditure-and-caseload-tables-2026", "vintage": "Spring Forecast 2026 (OBR Spring 2026 forecast-consistent)", "workbook": "outturn-and-forecast-tables-spring-forecast-2026.xlsx"}, "reform": {"framework": "baseline"}, "source": "uk_dwp", "source_column": "Non-DWP Welfare | Personal tax credits | 2023/24 outturn", "source_model": "dwp_becl", "status": "ok", "time_basis": "fiscal_year", "value": 7033724189.66, "value_kind": "gbp", "value_raw": "7033.724189656961"}} +{"fact_id": "uk:uk_dwp:e386753bada140d89a00", "routed_because": "DWP BECL outturn \u2014 admin expenditure/caseload fact (ledger routing rule, Max 2026-08-02)", "source": "uk_dwp", "staged": {"calibration_note": "VERIFIED 2026-08-02: policyengine-uk-data/targets/sources/obr.py consumes benefit expenditure AND caseload forecasts from OBR March 2026 EFO supplementary tables; BECL Spring Forecast 2026 is OBR-Spring-2026-consistent, so rows for benefits in obr.py's parse are effectively consumed_as_target \u2014 reclass at ingest after matching benefit lists. dwp.py separately consumes PIP claimant counts (England & Wales) and UC claimant counts from DWP admin statistics. 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"https://www.gov.uk/government/statistics/child-and-working-tax-credits-statistics-finalised-annual-awards-2022-to-2023", "row_index": 10, "sha256": "c746a7ad7d8c206ffe0ed1ac0060d2f60d4529de6dd57a72a15a8ffa78e911bf", "sheet": "Table_1_2", "title": "Child and Working Tax Credits statistics: Finalised Annual Awards - 2022 to 2023", "url": "https://assets.publishing.service.gov.uk/media/669a503a0808eaf43b50d2e4/Finalised_Awards_2023_Main.ods", "vintage": "Finalised annual awards 2022-23 (final edition; tax credits ended 5 April 2025)", "workbook": "Finalised_Awards_2023_Main.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "2019-20", "source_model": "hmrc_tax_credits_admin", "status": "ok", "time_basis": "annual", "unit_concept": "families", "unit_note": "sheet value thousands x 1e3 -> count", "value": 212000.0, "value_kind": "count", "value_raw": "212"}} +{"fact_id": "uk:uk_hmrc:02f40f413228ffa23cd6", "routed_because": "HMRC hmrc_spi outturn statistics 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"routed_because": "HMRC hmrc_admin_data outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"area_code": "N92000002", "as_of": "August 2025", "basis": "outturn", "count_of": "families_in_receipt_of_payments", "geography": "Northern Ireland", "program": "child_benefit"}, "metric": "caseload", "period": 2025, "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 27, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_1", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", 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{"calibration_relationship": "held_out", "conditions": {"area_code": "S92000003", "as_of": "August 2022", "basis": "outturn", "count_of": "children_for_whom_payment_received", "geography": "Scotland", "program": "child_benefit"}, "metric": "participant_count", "period": 2022, "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 49, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_1", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": "Child_Benefit_August_2025_Main_Tables.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "Scotland 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"conditions": {"basis": "outturn", "fy": "2016-17", "geography": "UK", "income_concept": "total income after tax", "percentile": "5", "population": "UK Income Tax payers (SPI; individuals with total income above the personal allowance threshold)"}, "period": 2016, "proposed_metric": "income_percentile_point", "proposed_unit": "gbp", "publication": {"date": "2026-04-29", "local_path": "downloads/Collated_Tables_3_1_to_3_11_2324.ods", "publication_url": "https://www.gov.uk/government/statistics/personal-incomes-statistics-for-the-tax-year-2023-to-2024", "row_index": 29, "sha256": "ad063b06b2bdeef8600dbbb09d48153337a4966f8c7eea50df7a2e0304ebd73e", "sheet": "Table_3_1_after_tax", "title": "Personal Incomes Statistics for the tax year 2023 to 2024", "url": "https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": 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{"basis": "outturn", "fy": "2023-24", "geography": "UK", "income_concept": "total income before tax", "percentile": "42", "population": "UK Income Tax payers (SPI; individuals with total income above the personal allowance threshold)"}, "period": 2023, "proposed_metric": "income_percentile_point", "proposed_unit": "gbp", "publication": {"date": "2026-04-29", "local_path": "downloads/Collated_Tables_3_1_to_3_11_2324.ods", "publication_url": "https://www.gov.uk/government/statistics/personal-incomes-statistics-for-the-tax-year-2023-to-2024", "row_index": 46, "sha256": "ad063b06b2bdeef8600dbbb09d48153337a4966f8c7eea50df7a2e0304ebd73e", "sheet": "Table_3_1a_before_tax", "title": "Personal Incomes Statistics for the tax year 2023 to 2024", "url": "https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": "baseline"}, 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"url": "https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "99th percentile", "source_model": "hmrc_spi", "status": "ok", "time_basis": "fiscal_year", "value": 175000.0, "value_kind": "gbp", "value_raw": "175,000"}} +{"fact_id": "uk:uk_hmrc:1f15cb93dbebc2351d85", "routed_because": "HMRC hmrc_tax_credits_admin outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"annual_entitlement_band": "\u00a32,000 to \u00a33,999", "basis": "outturn", "count_basis": "average_number_of_families", "family_group": "In-work single families with three children", "fy": "2022-23", "geography": "UK", "program": "tax_credits"}, "metric": "caseload", "period": 2022, 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"publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 48, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_1", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": "Child_Benefit_August_2025_Main_Tables.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "West Midlands E12000005", "source_model": "hmrc_admin_data", "status": "ok", "time_basis": "point_in_time", "unit_concept": "persons", "value": 1216975.0, "value_kind": "count", "value_raw": "1,216,975"}} +{"fact_id": "uk:uk_hmrc:20bd7e19dceb0ce17a6d", "routed_because": "HMRC hmrc_tax_credits_admin outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"annual_entitlement_band": "Total", "basis": "outturn", "count_basis": "average_number_of_families", "family_group": "In-work couple families with three children", "fy": "2022-23", "geography": "UK", "program": "tax_credits"}, "metric": "caseload", "period": 2022, "publication": {"date": "2024-07-24", "local_path": "downloads/Finalised_Awards_2023_Main.ods", "publication_url": "https://www.gov.uk/government/statistics/child-and-working-tax-credits-statistics-finalised-annual-awards-2022-to-2023", "row_index": 22, "sha256": "c746a7ad7d8c206ffe0ed1ac0060d2f60d4529de6dd57a72a15a8ffa78e911bf", "sheet": "Table_2_3", "title": "Child and Working Tax Credits statistics: Finalised Annual Awards - 2022 to 2023", "url": "https://assets.publishing.service.gov.uk/media/669a503a0808eaf43b50d2e4/Finalised_Awards_2023_Main.ods", "vintage": "Finalised annual awards 2022-23 (final edition; tax credits ended 5 April 2025)", 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"uk:uk_hmrc:2126bd43947ed172f543", "routed_because": "HMRC hmrc_tax_credits_admin outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"annual_entitlement_band": "\u00a34,000 to \u00a35,999", "basis": "outturn", "count_basis": "average_number_of_families", "family_group": "In-work single families with no children (receiving WTC only)", "fy": "2022-23", "geography": "UK", "program": "tax_credits"}, "metric": "caseload", "period": 2022, "publication": {"date": "2024-07-24", "local_path": "downloads/Finalised_Awards_2023_Main.ods", "publication_url": "https://www.gov.uk/government/statistics/child-and-working-tax-credits-statistics-finalised-annual-awards-2022-to-2023", "row_index": 11, "sha256": "c746a7ad7d8c206ffe0ed1ac0060d2f60d4529de6dd57a72a15a8ffa78e911bf", "sheet": "Table_2_3", "title": "Child and Working Tax Credits statistics: Finalised Annual Awards - 2022 to 2023", 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"staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2023-24", "geography": "UK", "income_range_lower": "\u00a330,000", "tax": "income_tax"}, "period": 2023, "proposed_metric": "average_tax_amount", "proposed_unit": "gbp", "publication": {"date": "2026-07-15", "local_path": "downloads/Collated_Income_Tax_liabilities_statistics_tables_-_2.1_to_2.6.ods", "publication_url": "https://www.gov.uk/government/statistics/income-tax-liabilities-statistics-tax-year-2023-to-2024-to-tax-year-2026-to-2027", "row_index": 6, "sha256": "40e1c7bb75d484132e8329fcac75f16e1a96305302fc422ee446a688d52bdbc2", "sheet": "2_5_IT_Liabilities_2023-24", "title": "Income Tax liabilities statistics: tax year 2023 to 2024 to tax year 2026 to 2027", "url": "https://assets.publishing.service.gov.uk/media/6a5a49b47eb057103bd946a4/Collated_Income_Tax_liabilities_statistics_tables_-_2.1_to_2.6.ods", "vintage": "July 2026 edition (SPI 2023-24 outturn; projections on OBR March 2026 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{"calibration_relationship": "held_out", "conditions": {"as_of": "August 2025", "basis": "outturn", "count_of": "families_in_receipt_of_payments", "geography": "Foreign and not known", "program": "child_benefit"}, "metric": "caseload", "period": 2025, "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 27, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_1", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": "Child_Benefit_August_2025_Main_Tables.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "Foreign and not known", "source_model": "hmrc_admin_data", "status": "ok", "time_basis": "point_in_time", "unit_concept": "families", "value": 8945.0, "value_kind": "count", "value_raw": "8,945"}} +{"fact_id": "uk:uk_hmrc:31c07dea8d0f988e210f", "routed_because": "HMRC hmrc_tax_credits_admin outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "family_group": "Annual entitlement for all families", "fy": "2018-19", "geography": "UK", "measure": "finalised annual entitlement", "program": "tax_credits"}, "metric": "benefit_cost", "period": 2018, "proposed_unit": "gbp", "publication": {"date": "2024-07-24", "local_path": "downloads/Finalised_Awards_2023_Main.ods", "publication_url": "https://www.gov.uk/government/statistics/child-and-working-tax-credits-statistics-finalised-annual-awards-2022-to-2023", "row_index": 48, "sha256": 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{"annual_entitlement_band": "Total", "basis": "outturn", "count_basis": "average_number_of_families", "family_group": "All in-work families with three children", "fy": "2022-23", "geography": "UK", "program": "tax_credits"}, "metric": "caseload", "period": 2022, "publication": {"date": "2024-07-24", "local_path": "downloads/Finalised_Awards_2023_Main.ods", "publication_url": "https://www.gov.uk/government/statistics/child-and-working-tax-credits-statistics-finalised-annual-awards-2022-to-2023", "row_index": 30, "sha256": "c746a7ad7d8c206ffe0ed1ac0060d2f60d4529de6dd57a72a15a8ffa78e911bf", "sheet": "Table_2_3", "title": "Child and Working Tax Credits statistics: Finalised Annual Awards - 2022 to 2023", "url": "https://assets.publishing.service.gov.uk/media/669a503a0808eaf43b50d2e4/Finalised_Awards_2023_Main.ods", "vintage": "Finalised annual awards 2022-23 (final edition; tax credits ended 5 April 2025)", "workbook": "Finalised_Awards_2023_Main.ods"}, "reform": {"framework": "baseline"}, 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"HMRC hmrc_admin_data outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"area_code": "W92000004", "as_of": "August 2025", "basis": "outturn", "count_of": "families_in_receipt_of_payments", "geography": "Wales", "program": "child_benefit"}, "metric": "caseload", "period": 2025, "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 27, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_1", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": 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"uk:uk_hmrc:3a2c14fdd62a4432497f", "routed_because": "HMRC hmrc_self_assessment outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2020-21", "geography": "UK", "tax": "high_income_child_benefit_charge"}, "period": 2020, "proposed_metric": "taxpayer_count", "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 11, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_16", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": 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"metric": "caseload", "period": 2022, "publication": {"date": "2024-07-24", "local_path": "downloads/Finalised_Awards_2023_Main.ods", "publication_url": "https://www.gov.uk/government/statistics/child-and-working-tax-credits-statistics-finalised-annual-awards-2022-to-2023", "row_index": 29, "sha256": "c746a7ad7d8c206ffe0ed1ac0060d2f60d4529de6dd57a72a15a8ffa78e911bf", "sheet": "Table_2_3", "title": "Child and Working Tax Credits statistics: Finalised Annual Awards - 2022 to 2023", "url": "https://assets.publishing.service.gov.uk/media/669a503a0808eaf43b50d2e4/Finalised_Awards_2023_Main.ods", "vintage": "Finalised annual awards 2022-23 (final edition; tax credits ended 5 April 2025)", "workbook": "Finalised_Awards_2023_Main.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "\u00a32,000 to \u00a33,999", "source_model": "hmrc_tax_credits_admin", "status": "ok", "time_basis": "annual", "unit_concept": "families", "unit_note": "sheet value thousands x 1e3 -> 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"period": 2020, "proposed_metric": "income_percentile_point", "proposed_unit": "gbp", "publication": {"date": "2026-04-29", "local_path": "downloads/Collated_Tables_3_1_to_3_11_2324.ods", "publication_url": "https://www.gov.uk/government/statistics/personal-incomes-statistics-for-the-tax-year-2023-to-2024", "row_index": 33, "sha256": "ad063b06b2bdeef8600dbbb09d48153337a4966f8c7eea50df7a2e0304ebd73e", "sheet": "Table_3_1_before_tax", "title": "Personal Incomes Statistics for the tax year 2023 to 2024", "url": "https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "50th percentile", "source_model": "hmrc_spi", "status": "ok", "time_basis": "fiscal_year", "value": 26300.0, "value_kind": "gbp", "value_raw": "26,300"}} +{"fact_id": "uk:uk_hmrc:456d9cded471db64de9b", "routed_because": "HMRC hmrc_self_assessment outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2022-23", "geography": "UK", "tax": "high_income_child_benefit_charge"}, "period": 2022, "proposed_metric": "taxpayer_count", "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 13, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_16", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": 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"staged": {"calibration_relationship": "held_out", "conditions": {"area_code": "K04000001", "as_of": "August 2022", "basis": "outturn", "count_of": "families_in_receipt_of_payments", "geography": "England and Wales", "program": "child_benefit"}, "metric": "caseload", "period": 2022, "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 24, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_1", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": "Child_Benefit_August_2025_Main_Tables.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": 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{"basis": "outturn", "fy": "2023-24", "geography": "UK", "income_concept": "total income before tax", "percentile": "62", "population": "UK Income Tax payers (SPI; individuals with total income above the personal allowance threshold)"}, "period": 2023, "proposed_metric": "income_percentile_point", "proposed_unit": "gbp", "publication": {"date": "2026-04-29", "local_path": "downloads/Collated_Tables_3_1_to_3_11_2324.ods", "publication_url": "https://www.gov.uk/government/statistics/personal-incomes-statistics-for-the-tax-year-2023-to-2024", "row_index": 66, "sha256": "ad063b06b2bdeef8600dbbb09d48153337a4966f8c7eea50df7a2e0304ebd73e", "sheet": "Table_3_1a_before_tax", "title": "Personal Incomes Statistics for the tax year 2023 to 2024", "url": "https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": "baseline"}, 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"conditions": {"annual_entitlement_band": "\u00a32,000 to \u00a33,999", "basis": "outturn", "count_basis": "average_number_of_families", "family_group": "All in-work families receiving WTC and CTC", "fy": "2022-23", "geography": "UK", "program": "tax_credits"}, "metric": "caseload", "period": 2022, "publication": {"date": "2024-07-24", "local_path": "downloads/Finalised_Awards_2023_Main.ods", "publication_url": "https://www.gov.uk/government/statistics/child-and-working-tax-credits-statistics-finalised-annual-awards-2022-to-2023", "row_index": 4, "sha256": "c746a7ad7d8c206ffe0ed1ac0060d2f60d4529de6dd57a72a15a8ffa78e911bf", "sheet": "Table_2_3", "title": "Child and Working Tax Credits statistics: Finalised Annual Awards - 2022 to 2023", "url": "https://assets.publishing.service.gov.uk/media/669a503a0808eaf43b50d2e4/Finalised_Awards_2023_Main.ods", "vintage": "Finalised annual awards 2022-23 (final edition; tax credits ended 5 April 2025)", "workbook": "Finalised_Awards_2023_Main.ods"}, 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"conditions": {"basis": "outturn", "fy": "2021-22", "geography": "UK", "measure": "finalised annual entitlement", "program": "tax_credits"}, "metric": "benefit_cost", "period": 2021, "proposed_unit": "gbp", "publication": {"date": "2024-07-24", "local_path": "downloads/Finalised_Awards_2023_Main.ods", "publication_url": "https://www.gov.uk/government/statistics/child-and-working-tax-credits-statistics-finalised-annual-awards-2022-to-2023", "row_index": 76, "sha256": "c746a7ad7d8c206ffe0ed1ac0060d2f60d4529de6dd57a72a15a8ffa78e911bf", "sheet": "Table_1_1", "title": "Child and Working Tax Credits statistics: Finalised Annual Awards - 2022 to 2023", "url": "https://assets.publishing.service.gov.uk/media/669a503a0808eaf43b50d2e4/Finalised_Awards_2023_Main.ods", "vintage": "Finalised annual awards 2022-23 (final edition; tax credits ended 5 April 2025)", "workbook": "Finalised_Awards_2023_Main.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "Total in receipt 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"uk:uk_hmrc:64544e2a8d37bc6e057d", "routed_because": "HMRC hmrc_spi outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2023-24", "geography": "UK", "income_concept": "total income after tax", "percentile": "48", "population": "UK Income Tax payers (SPI; individuals with total income above the personal allowance threshold)"}, "period": 2023, "proposed_metric": "income_percentile_point", "proposed_unit": "gbp", "publication": {"date": "2026-04-29", "local_path": "downloads/Collated_Tables_3_1_to_3_11_2324.ods", "publication_url": "https://www.gov.uk/government/statistics/personal-incomes-statistics-for-the-tax-year-2023-to-2024", "row_index": 52, "sha256": "ad063b06b2bdeef8600dbbb09d48153337a4966f8c7eea50df7a2e0304ebd73e", "sheet": "Table_3_1a_after_tax", "title": "Personal Incomes Statistics for the tax year 2023 to 2024", "url": 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{"calibration_relationship": "held_out", "conditions": {"area_code": "E12000009", "as_of": "August 2013", "basis": "outturn", "count_of": "children_for_whom_payment_received", "geography": "South West", "program": "child_benefit"}, "metric": "participant_count", "period": 2013, "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 40, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_1", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": "Child_Benefit_August_2025_Main_Tables.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "South West 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"proposed_unit": "gbp", "publication": {"date": "2026-04-29", "local_path": "downloads/Collated_Tables_3_1_to_3_11_2324.ods", "publication_url": "https://www.gov.uk/government/statistics/personal-incomes-statistics-for-the-tax-year-2023-to-2024", "row_index": 6, "sha256": "ad063b06b2bdeef8600dbbb09d48153337a4966f8c7eea50df7a2e0304ebd73e", "sheet": "Table_3_1a_after_tax", "title": "Personal Incomes Statistics for the tax year 2023 to 2024", "url": "https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "2023 to 2024", "source_model": "hmrc_spi", "status": "ok", "time_basis": "fiscal_year", "value": 13100.0, "value_kind": "gbp", "value_raw": "13,100"}} +{"fact_id": "uk:uk_hmrc:6bbfc8464ead09b6693c", "routed_because": "HMRC hmrc_spi outturn statistics \u2014 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"vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "99th percentile", "source_model": "hmrc_spi", "status": "ok", "time_basis": "fiscal_year", "value": 119000.0, "value_kind": "gbp", "value_raw": "119,000"}} +{"fact_id": "uk:uk_hmrc:6c42fe7a2854f90ff84b", "routed_because": "HMRC hmrc_admin_data outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"area_code": "E12000008", "as_of": "August 2016", "basis": "outturn", "count_of": "children_for_whom_payment_received", "geography": "South East", "program": "child_benefit"}, "metric": "participant_count", "period": 2016, "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": 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{"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2021-22", "geography": "UK", "tax": "high_income_child_benefit_charge"}, "period": 2021, "proposed_metric": "taxpayer_count", "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 12, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_16", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": "Child_Benefit_August_2025_Main_Tables.ods"}, "reform": {"framework": "baseline"}, "row_note": null, "source": "uk_hmrc", "source_column": "Individuals with HICBC liability", "source_model": 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"gbp", "value_raw": "53,100"}} +{"fact_id": "uk:uk_hmrc:6d0147ecfb28ac9523e9", "routed_because": "HMRC hmrc_spi outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2015-16", "geography": "UK", "income_concept": "total income before tax", "percentile": "95", "population": "UK Income Tax payers (SPI; individuals with total income above the personal allowance threshold)"}, "period": 2015, "proposed_metric": "income_percentile_point", "proposed_unit": "gbp", "publication": {"date": "2026-04-29", "local_path": "downloads/Collated_Tables_3_1_to_3_11_2324.ods", "publication_url": "https://www.gov.uk/government/statistics/personal-incomes-statistics-for-the-tax-year-2023-to-2024", "row_index": 28, "sha256": "ad063b06b2bdeef8600dbbb09d48153337a4966f8c7eea50df7a2e0304ebd73e", "sheet": "Table_3_1_before_tax", "title": "Personal Incomes Statistics for the tax 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"local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 46, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_1", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": "Child_Benefit_August_2025_Main_Tables.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "England and Wales K04000001", "source_model": "hmrc_admin_data", "status": "ok", "time_basis": "point_in_time", "unit_concept": "persons", "value": 11294260.0, "value_kind": "count", "value_raw": "11,294,260"}} +{"fact_id": "uk:uk_hmrc:6d2356127f1ca010fb7b", "routed_because": "HMRC hmrc_self_assessment provisional statistics 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"https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "2023 to 2024", "source_model": "hmrc_spi", "status": "ok", "time_basis": "fiscal_year", "value": 17600.0, "value_kind": "gbp", "value_raw": "17,600"}} +{"fact_id": "uk:uk_hmrc:798163aa4ec26b74bbfa", "routed_because": "HMRC hmrc_admin_data outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"area_code": "N92000002", "as_of": "August 2024", "basis": "outturn", "count_of": "children_for_whom_payment_received", "geography": "Northern Ireland", "program": "child_benefit"}, "metric": "participant_count", "period": 2024, "publication": {"date": "2026-04-23", "local_path": 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"https://assets.publishing.service.gov.uk/media/669a503a0808eaf43b50d2e4/Finalised_Awards_2023_Main.ods", "vintage": "Finalised annual awards 2022-23 (final edition; tax credits ended 5 April 2025)", "workbook": "Finalised_Awards_2023_Main.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "\u00a316,000 or over", "source_model": "hmrc_tax_credits_admin", "status": "ok", "time_basis": "annual", "unit_concept": "families", "unit_note": "sheet value thousands x 1e3 -> families", "value": 34000.0, "value_kind": "count", "value_raw": "34"}} +{"fact_id": "uk:uk_hmrc:a66ef03e3054831a5433", "routed_because": "HMRC hmrc_spi outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2016-17", "geography": "UK", "income_concept": "total income after tax", "percentile": "95", "population": "UK Income Tax payers (SPI; individuals with 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"url": "https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "2023 to 2024", "source_model": "hmrc_spi", "status": "ok", "time_basis": "fiscal_year", "value": 19300.0, "value_kind": "gbp", "value_raw": "19,300"}} +{"fact_id": "uk:uk_hmrc:a6bd053de8dfda9ff668", "routed_because": "HMRC hmrc_admin_data outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"area_code": "N92000002", "as_of": "August 2020", "basis": "outturn", "count_of": "children_for_whom_payment_received", "geography": "Northern Ireland", "program": "child_benefit"}, "metric": "participant_count", "period": 2020, "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 47, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_1", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": "Child_Benefit_August_2025_Main_Tables.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "Northern Ireland N92000002", "source_model": "hmrc_admin_data", "status": "ok", "time_basis": "point_in_time", "unit_concept": "persons", "value": 422145.0, "value_kind": "count", "value_raw": "422,145"}} +{"fact_id": "uk:uk_hmrc:a6dbb9b37521df291bc9", "routed_because": "HMRC hmrc_tax_credits_admin outturn statistics \u2014 admin fact 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"publication": {"date": "2026-04-29", "local_path": "downloads/Collated_Tables_3_1_to_3_11_2324.ods", "publication_url": "https://www.gov.uk/government/statistics/personal-incomes-statistics-for-the-tax-year-2023-to-2024", "row_index": 92, "sha256": "ad063b06b2bdeef8600dbbb09d48153337a4966f8c7eea50df7a2e0304ebd73e", "sheet": "Table_3_1a_before_tax", "title": "Personal Incomes Statistics for the tax year 2023 to 2024", "url": "https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "2023 to 2024", "source_model": "hmrc_spi", "status": "ok", "time_basis": "fiscal_year", "value": 61800.0, "value_kind": "gbp", "value_raw": "61,800"}} +{"fact_id": "uk:uk_hmrc:a708d71f2f9be030847f", "routed_because": "HMRC hmrc_admin_data outturn statistics \u2014 admin fact (ledger 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"proposed_metric": "income_percentile_point", "proposed_unit": "gbp", "publication": {"date": "2026-04-29", "local_path": "downloads/Collated_Tables_3_1_to_3_11_2324.ods", "publication_url": "https://www.gov.uk/government/statistics/personal-incomes-statistics-for-the-tax-year-2023-to-2024", "row_index": 47, "sha256": "ad063b06b2bdeef8600dbbb09d48153337a4966f8c7eea50df7a2e0304ebd73e", "sheet": "Table_3_1a_after_tax", "title": "Personal Incomes Statistics for the tax year 2023 to 2024", "url": "https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "2023 to 2024", "source_model": "hmrc_spi", "status": "ok", "time_basis": "fiscal_year", "value": 24300.0, "value_kind": "gbp", "value_raw": "24,300"}} +{"fact_id": "uk:uk_hmrc:a79012ef9b1557a5c576", "routed_because": "HMRC hmrc_spi outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2017-18", "geography": "UK", "income_concept": "total income before tax", "percentile": "25", "population": "UK Income Tax payers (SPI; individuals with total income above the personal allowance threshold)"}, "period": 2017, "proposed_metric": "income_percentile_point", "proposed_unit": "gbp", "publication": {"date": "2026-04-29", "local_path": "downloads/Collated_Tables_3_1_to_3_11_2324.ods", "publication_url": "https://www.gov.uk/government/statistics/personal-incomes-statistics-for-the-tax-year-2023-to-2024", "row_index": 30, "sha256": "ad063b06b2bdeef8600dbbb09d48153337a4966f8c7eea50df7a2e0304ebd73e", "sheet": "Table_3_1_before_tax", "title": "Personal Incomes Statistics for the tax year 2023 to 2024", "url": "https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "25th percentile", "source_model": "hmrc_spi", "status": "ok", "time_basis": "fiscal_year", "value": 17400.0, "value_kind": "gbp", "value_raw": "17,400"}} +{"fact_id": "uk:uk_hmrc:a7a0d1c7726cd864f5a9", "routed_because": "HMRC hmrc_admin_data outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"area_code": "S92000003", "as_of": "August 2023", "basis": "outturn", "count_of": "children_for_whom_payment_received", "geography": "Scotland", "program": "child_benefit"}, "metric": "participant_count", "period": 2023, "publication": {"date": "2026-04-23", "local_path": 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"sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_1", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": "Child_Benefit_August_2025_Main_Tables.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "Foreign and not known", "source_model": "hmrc_admin_data", "status": "ok", "time_basis": "point_in_time", "unit_concept": "persons", "value": 32950.0, "value_kind": "count", "value_raw": "32,950"}} +{"fact_id": "uk:uk_hmrc:b2de0095e391cc87854a", "routed_because": "HMRC hmrc_spi outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2023-24", "geography": "UK", "income_concept": "total 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"uk_hmrc", "source_column": "2020-21", "source_model": "hmrc_tax_credits_admin", "status": "ok", "time_basis": "fiscal_year", "unit_note": "sheet value GBP millions x 1e6 -> GBP", "value": 655000000.0, "value_kind": "gbp", "value_raw": "655"}} +{"fact_id": "uk:uk_hmrc:b344a5989532a7c024fd", "routed_because": "HMRC hmrc_spi outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"band": "Higher rate", "basis": "outturn", "fy": "2023-24", "geography": "UK", "income_range_lower": "\u00a3200,000", "tax": "income_tax"}, "period": 2023, "proposed_metric": "tax_liability", "proposed_unit": "gbp", "publication": {"date": "2026-07-15", "local_path": "downloads/Collated_Income_Tax_liabilities_statistics_tables_-_2.1_to_2.6.ods", "publication_url": "https://www.gov.uk/government/statistics/income-tax-liabilities-statistics-tax-year-2023-to-2024-to-tax-year-2026-to-2027", "row_index": 10, "sha256": "40e1c7bb75d484132e8329fcac75f16e1a96305302fc422ee446a688d52bdbc2", "sheet": "2_5_IT_Liabilities_2023-24", "title": "Income Tax liabilities statistics: tax year 2023 to 2024 to tax year 2026 to 2027", "url": "https://assets.publishing.service.gov.uk/media/6a5a49b47eb057103bd946a4/Collated_Income_Tax_liabilities_statistics_tables_-_2.1_to_2.6.ods", "vintage": "July 2026 edition (SPI 2023-24 outturn; projections on OBR March 2026 EFO)", "workbook": "Collated_Income_Tax_liabilities_statistics_tables_-_2.1_to_2.6.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "Income Tax liability for higher rate Income Tax payers", "source_model": "hmrc_spi", "status": "ok", "time_basis": "fiscal_year", "unit_note": "sheet value GBP millions x 1e6 -> GBP", "value": 32000000.0, "value_kind": "gbp", "value_raw": "32"}} +{"fact_id": "uk:uk_hmrc:b34c6c2e79bab4f51f40", "routed_because": "HMRC hmrc_admin_data outturn statistics \u2014 admin fact (ledger routing rule, 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"conditions": {"basis": "outturn", "fy": "2023-24", "geography": "UK", "income_concept": "total income after tax", "percentile": "44", "population": "UK Income Tax payers (SPI; individuals with total income above the personal allowance threshold)"}, "period": 2023, "proposed_metric": "income_percentile_point", "proposed_unit": "gbp", "publication": {"date": "2026-04-29", "local_path": "downloads/Collated_Tables_3_1_to_3_11_2324.ods", "publication_url": "https://www.gov.uk/government/statistics/personal-incomes-statistics-for-the-tax-year-2023-to-2024", "row_index": 48, "sha256": "ad063b06b2bdeef8600dbbb09d48153337a4966f8c7eea50df7a2e0304ebd73e", "sheet": "Table_3_1a_after_tax", "title": "Personal Incomes Statistics for the tax year 2023 to 2024", "url": "https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": 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"source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"age_group": "Age under 65", "basis": "outturn", "fy": "2023-24", "geography": "UK", "tax": "income_tax"}, "period": 2023, "proposed_metric": "taxpayer_count", "publication": {"date": "2026-07-15", "local_path": "downloads/Collated_Income_Tax_liabilities_statistics_tables_-_2.1_to_2.6.ods", "publication_url": "https://www.gov.uk/government/statistics/income-tax-liabilities-statistics-tax-year-2023-to-2024-to-tax-year-2026-to-2027", "row_index": 36, "sha256": "40e1c7bb75d484132e8329fcac75f16e1a96305302fc422ee446a688d52bdbc2", "sheet": "2_1_IT_payers_by_demographic", "title": "Income Tax liabilities statistics: tax year 2023 to 2024 to tax year 2026 to 2027", "url": "https://assets.publishing.service.gov.uk/media/6a5a49b47eb057103bd946a4/Collated_Income_Tax_liabilities_statistics_tables_-_2.1_to_2.6.ods", "vintage": "July 2026 edition (SPI 2023-24 outturn; projections on OBR March 2026 EFO)", 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"https://www.gov.uk/government/statistics/child-and-working-tax-credits-statistics-finalised-annual-awards-2022-to-2023", "row_index": 19, "sha256": "c746a7ad7d8c206ffe0ed1ac0060d2f60d4529de6dd57a72a15a8ffa78e911bf", "sheet": "Table_1_2", "title": "Child and Working Tax Credits statistics: Finalised Annual Awards - 2022 to 2023", "url": "https://assets.publishing.service.gov.uk/media/669a503a0808eaf43b50d2e4/Finalised_Awards_2023_Main.ods", "vintage": "Finalised annual awards 2022-23 (final edition; tax credits ended 5 April 2025)", "workbook": "Finalised_Awards_2023_Main.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "2021-22", "source_model": "hmrc_tax_credits_admin", "status": "ok", "time_basis": "annual", "unit_concept": "families", "unit_note": "sheet value thousands x 1e3 -> count", "value": 452000.0, "value_kind": "count", "value_raw": "452"}} +{"fact_id": "uk:uk_hmrc:c6174bdd990b5386c92e", "routed_because": "HMRC hmrc_tax_credits_admin outturn 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"routed_because": "HMRC hmrc_spi outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"band": "all", "basis": "outturn", "fy": "2010-11", "geography": "UK", "tax": "income_tax"}, "period": 2010, "proposed_metric": "taxpayer_count", "publication": {"date": "2026-07-15", "local_path": "downloads/Collated_Income_Tax_liabilities_statistics_tables_-_2.1_to_2.6.ods", "publication_url": "https://www.gov.uk/government/statistics/income-tax-liabilities-statistics-tax-year-2023-to-2024-to-tax-year-2026-to-2027", "row_index": 23, "sha256": "40e1c7bb75d484132e8329fcac75f16e1a96305302fc422ee446a688d52bdbc2", "sheet": "2_1_IT_payers_by_demographic", "title": "Income Tax liabilities statistics: tax year 2023 to 2024 to tax year 2026 to 2027", "url": "https://assets.publishing.service.gov.uk/media/6a5a49b47eb057103bd946a4/Collated_Income_Tax_liabilities_statistics_tables_-_2.1_to_2.6.ods", 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"status": "ok", "time_basis": "fiscal_year", "value": 41600.0, "value_kind": "gbp", "value_raw": "41,600"}} +{"fact_id": "uk:uk_hmrc:dc51e855a0a29488550b", "routed_because": "HMRC hmrc_tax_credits_admin outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"annual_entitlement_band": "\u00a314,000 to \u00a315,999", "basis": "outturn", "count_basis": "average_number_of_families", "family_group": "In-work couple families with four or more children", "fy": "2022-23", "geography": "UK", "program": "tax_credits"}, "metric": "caseload", "period": 2022, "publication": {"date": "2024-07-24", "local_path": "downloads/Finalised_Awards_2023_Main.ods", "publication_url": "https://www.gov.uk/government/statistics/child-and-working-tax-credits-statistics-finalised-annual-awards-2022-to-2023", "row_index": 23, "sha256": "c746a7ad7d8c206ffe0ed1ac0060d2f60d4529de6dd57a72a15a8ffa78e911bf", "sheet": "Table_2_3", "title": "Child and Working Tax Credits statistics: Finalised Annual Awards - 2022 to 2023", "url": "https://assets.publishing.service.gov.uk/media/669a503a0808eaf43b50d2e4/Finalised_Awards_2023_Main.ods", "vintage": "Finalised annual awards 2022-23 (final edition; tax credits ended 5 April 2025)", "workbook": "Finalised_Awards_2023_Main.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "\u00a314,000 to \u00a315,999", "source_model": "hmrc_tax_credits_admin", "status": "ok", "time_basis": "annual", "unit_concept": "families", "unit_note": "sheet value thousands x 1e3 -> families", "value": 9000.0, "value_kind": "count", "value_raw": "9"}} +{"fact_id": "uk:uk_hmrc:dc6b72b1fae0ba3d4ac2", "routed_because": "HMRC hmrc_admin_data outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"area_code": "E12000002", "as_of": "August 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{"calibration_relationship": "held_out", "conditions": {"annual_entitlement_band": "\u00a36,000 to \u00a37,999", "basis": "outturn", "count_basis": "average_number_of_families", "family_group": "All in-work families receiving CTC only", "fy": "2022-23", "geography": "UK", "program": "tax_credits"}, "metric": "caseload", "period": 2022, "publication": {"date": "2024-07-24", "local_path": "downloads/Finalised_Awards_2023_Main.ods", "publication_url": "https://www.gov.uk/government/statistics/child-and-working-tax-credits-statistics-finalised-annual-awards-2022-to-2023", "row_index": 5, "sha256": "c746a7ad7d8c206ffe0ed1ac0060d2f60d4529de6dd57a72a15a8ffa78e911bf", "sheet": "Table_2_3", "title": "Child and Working Tax Credits statistics: Finalised Annual Awards - 2022 to 2023", "url": "https://assets.publishing.service.gov.uk/media/669a503a0808eaf43b50d2e4/Finalised_Awards_2023_Main.ods", "vintage": "Finalised annual awards 2022-23 (final edition; tax credits ended 5 April 2025)", "workbook": "Finalised_Awards_2023_Main.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "\u00a36,000 to \u00a37,999", "source_model": "hmrc_tax_credits_admin", "status": "ok", "time_basis": "annual", "unit_concept": "families", "unit_note": "sheet value thousands x 1e3 -> families", "value": 31000.0, "value_kind": "count", "value_raw": "31"}} +{"fact_id": "uk:uk_hmrc:dd244b41a8705154802a", "routed_because": "HMRC hmrc_admin_data outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"area_code": "E12000008", "as_of": "August 2017", "basis": "outturn", "count_of": "children_for_whom_payment_received", "geography": "South East", "program": "child_benefit"}, "metric": "participant_count", "period": 2017, "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": 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{"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2019-20", "geography": "UK", "measure": "finalised annual entitlement", "program": "tax_credits"}, "metric": "benefit_cost", "period": 2019, "proposed_unit": "gbp", "publication": {"date": "2024-07-24", "local_path": "downloads/Finalised_Awards_2023_Main.ods", "publication_url": "https://www.gov.uk/government/statistics/child-and-working-tax-credits-statistics-finalised-annual-awards-2022-to-2023", "row_index": 68, "sha256": "c746a7ad7d8c206ffe0ed1ac0060d2f60d4529de6dd57a72a15a8ffa78e911bf", "sheet": "Table_1_1", "title": "Child and Working Tax Credits statistics: Finalised Annual Awards - 2022 to 2023", "url": "https://assets.publishing.service.gov.uk/media/669a503a0808eaf43b50d2e4/Finalised_Awards_2023_Main.ods", "vintage": "Finalised annual awards 2022-23 (final edition; tax credits ended 5 April 2025)", "workbook": "Finalised_Awards_2023_Main.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "Total in receipt (out-of-work and in-work families)", "source_model": "hmrc_tax_credits_admin", "status": "ok", "time_basis": "fiscal_year", "unit_note": "sheet value GBP millions x 1e6 -> GBP", "value": 17700000000.0, "value_kind": "gbp", "value_raw": "17700"}} +{"fact_id": "uk:uk_hmrc:dd4da00bb0c88dacf0a6", "routed_because": "HMRC hmrc_admin_data outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"area_code": "K02000001", "as_of": "August 2024", "basis": "outturn", "count_of": "families_in_receipt_of_payments", "geography": "United Kingdom", "program": "child_benefit"}, "metric": "caseload", "period": 2024, "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 26, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_1", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": "Child_Benefit_August_2025_Main_Tables.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "United Kingdom K02000001 [note 1]", "source_model": "hmrc_admin_data", "status": "ok", "time_basis": "point_in_time", "unit_concept": "families", "value": 6907240.0, "value_kind": "count", "value_raw": "6,907,240"}} +{"fact_id": "uk:uk_hmrc:dd62b870d171b900916a", "routed_because": "HMRC hmrc_spi outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2023-24", "geography": "UK", "income_concept": "total income after tax", "percentile": "31", "population": "UK Income Tax payers (SPI; individuals with total income above the personal allowance threshold)"}, "period": 2023, "proposed_metric": "income_percentile_point", "proposed_unit": "gbp", "publication": {"date": "2026-04-29", "local_path": "downloads/Collated_Tables_3_1_to_3_11_2324.ods", "publication_url": "https://www.gov.uk/government/statistics/personal-incomes-statistics-for-the-tax-year-2023-to-2024", "row_index": 35, "sha256": "ad063b06b2bdeef8600dbbb09d48153337a4966f8c7eea50df7a2e0304ebd73e", "sheet": "Table_3_1a_after_tax", "title": "Personal Incomes Statistics for the tax year 2023 to 2024", "url": "https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "vintage": "March 2026 release, SPI 2023-24", "workbook": "Collated_Tables_3_1_to_3_11_2324.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "2023 to 2024", "source_model": "hmrc_spi", "status": "ok", "time_basis": "fiscal_year", "value": 20900.0, "value_kind": "gbp", "value_raw": "20,900"}} +{"fact_id": "uk:uk_hmrc:dd6f2af52c0b3058abc0", "routed_because": "HMRC hmrc_admin_data outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"area_code": "E12000003", "as_of": "August 2015", "basis": "outturn", "count_of": "children_for_whom_payment_received", "geography": "Yorkshire and the Humber", "program": "child_benefit"}, "metric": "participant_count", "period": 2015, "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 42, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_1", "title": "Child Benefit Statistics: 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"proposed_unit": "gbp", "publication": {"date": "2026-07-15", "local_path": "downloads/Collated_Income_Tax_liabilities_statistics_tables_-_2.1_to_2.6.ods", "publication_url": "https://www.gov.uk/government/statistics/income-tax-liabilities-statistics-tax-year-2023-to-2024-to-tax-year-2026-to-2027", "row_index": 4, "sha256": "40e1c7bb75d484132e8329fcac75f16e1a96305302fc422ee446a688d52bdbc2", "sheet": "2_5_IT_Liabilities_2023-24", "title": "Income Tax liabilities statistics: tax year 2023 to 2024 to tax year 2026 to 2027", "url": "https://assets.publishing.service.gov.uk/media/6a5a49b47eb057103bd946a4/Collated_Income_Tax_liabilities_statistics_tables_-_2.1_to_2.6.ods", "vintage": "July 2026 edition (SPI 2023-24 outturn; projections on OBR March 2026 EFO)", "workbook": "Collated_Income_Tax_liabilities_statistics_tables_-_2.1_to_2.6.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "Income Tax liability for savers rate Income Tax payers", "source_model": 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"title": "Child and Working Tax Credits statistics: Finalised Annual Awards - 2022 to 2023", "url": "https://assets.publishing.service.gov.uk/media/669a503a0808eaf43b50d2e4/Finalised_Awards_2023_Main.ods", "vintage": "Finalised annual awards 2022-23 (final edition; tax credits ended 5 April 2025)", "workbook": "Finalised_Awards_2023_Main.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "2018-19", "source_model": "hmrc_tax_credits_admin", "status": "ok", "time_basis": "annual", "unit_concept": "families", "unit_note": "sheet value thousands x 1e3 -> count", "value": 686000.0, "value_kind": "count", "value_raw": "686"}} +{"fact_id": "uk:uk_hmrc:ddfaa4379bee7a0766e2", "routed_because": "HMRC hmrc_spi outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2023-24", "geography": "UK", "income_range_lower": "\u00a330,000", 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"unit_concept": "families", "unit_note": "sheet value thousands x 1e3 -> count", "value": 104000.0, "value_kind": "count", "value_raw": "104"}} +{"fact_id": "uk:uk_hmrc:f04c757d49a50e9bdc4a", "routed_because": "HMRC hmrc_tax_credits_admin outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"annual_entitlement_band": "\u00a38,000 to \u00a39,999", "basis": "outturn", "count_basis": "average_number_of_families", "family_group": "Total single families", "fy": "2022-23", "geography": "UK", "program": "tax_credits"}, "metric": "caseload", "period": 2022, "publication": {"date": "2024-07-24", "local_path": "downloads/Finalised_Awards_2023_Main.ods", "publication_url": "https://www.gov.uk/government/statistics/child-and-working-tax-credits-statistics-finalised-annual-awards-2022-to-2023", "row_index": 17, "sha256": "c746a7ad7d8c206ffe0ed1ac0060d2f60d4529de6dd57a72a15a8ffa78e911bf", "sheet": "Table_2_3", "title": "Child and Working Tax Credits statistics: Finalised Annual Awards - 2022 to 2023", "url": "https://assets.publishing.service.gov.uk/media/669a503a0808eaf43b50d2e4/Finalised_Awards_2023_Main.ods", "vintage": "Finalised annual awards 2022-23 (final edition; tax credits ended 5 April 2025)", "workbook": "Finalised_Awards_2023_Main.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "\u00a38,000 to \u00a39,999", "source_model": "hmrc_tax_credits_admin", "status": "ok", "time_basis": "annual", "unit_concept": "families", "unit_note": "sheet value thousands x 1e3 -> families", "value": 89000.0, "value_kind": "count", "value_raw": "89"}} +{"fact_id": "uk:uk_hmrc:f07d9de80025b2ef4e45", "routed_because": "HMRC hmrc_cgt_admin outturn statistics \u2014 admin fact (ledger routing rule, Max 2026-08-02)", "source": "uk_hmrc", "staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2008-09", "geography": "UK", "population": "individuals", "tax": "capital_gains_tax"}, "period": 2008, "proposed_metric": "taxpayer_count", "publication": {"date": "2025-07-24", "local_path": "downloads/Table_1_2025_Taxpayer_numbers_gains_and_tax_liabilities.ods", "publication_url": "https://www.gov.uk/government/statistics/capital-gains-tax-statistics", "row_index": 29, "sha256": "95c1bb1548483cb0ed0090e820a1fba129d725ade418cf64e5f85793655e92a1", "sheet": "Table_1", "title": "Capital Gains Tax statistics", "url": "https://assets.publishing.service.gov.uk/media/6878ac497ea209168636386e/Table_1_2025_Taxpayer_numbers_gains_and_tax_liabilities.ods", "vintage": "August 2025 edition (2023-24 first outturn; 2021-22 onwards provisional)", "workbook": "Table_1_2025_Taxpayer_numbers_gains_and_tax_liabilities.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "Number of individuals", "source_model": "hmrc_cgt_admin", "status": "ok", "time_basis": "fiscal_year", 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"UK", "population": "eligible children for whom Child Benefit is claimed, including opted out", "program": "child_benefit"}, "metric": "participation_rate", "period": 2025, "publication": {"date": "2026-04-23", "local_path": "downloads/Child_Benefit_August_2025_Main_Tables.ods", "publication_url": "https://www.gov.uk/government/statistics/child-benefit-statistics-annual-release-august-2025", "row_index": 12, "sha256": "c2064c6cc03af2ea60f21129e5531d957556bb67423e89bdd8b1d074ac5819c1", "sheet": "Table_15", "title": "Child Benefit Statistics: annual release, August 2025", "url": "https://assets.publishing.service.gov.uk/media/69e5f48c3e3b4e9340cc92b5/Child_Benefit_August_2025_Main_Tables.ods", "vintage": "Annual release, data at August 2025", "workbook": "Child_Benefit_August_2025_Main_Tables.ods"}, "reform": {"framework": "baseline"}, "source": "uk_hmrc", "source_column": "May 2025", "source_model": "hmrc_admin_data", "status": "ok", "time_basis": "point_in_time", "unit_concept": 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2024, "proposed_unit": "gbp", "publication": {"publication_url": "https://obr.uk/efo/economic-and-fiscal-outlook-november-2025/", "publisher": "Office for Budget Responsibility", "title": "Economic and fiscal outlook November 2025 - detailed forecast tables: expenditure", "url": "https://obr.uk/docs/dlm_uploads/Expenditure_Detailed_forecast_tables_November_2025.xlsx", "vintage": "November 2025 EFO", "wayback": "https://web.archive.org/web/20260316163307id_/https://obr.uk/docs/dlm_uploads/Expenditure_Detailed_forecast_tables_November_2025.xlsx", "workbook": "Expenditure_Detailed_forecast_tables_November_2025.xlsx"}, "reform_hint": null, "source": "obr", "source_column": "2024-25", "source_model": "obr_efo_forecast", "source_table": "4.11: 4.11 Health- and disability-related welfare spending", "status": "ok", "time_basis": "fiscal_year", "value": 4517038325.149783, "value_raw": 4.517038325149783}} +{"fact_id": "uk:uk_obr:f8a11c0d9a0c21adbe10", "routed_because": "OBR EFO outturn column \u2014 admin receipts/expenditure fact (ledger routing rule, Max 2026-08-02)", "source": "uk_obr", "staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2024-25", "geography": "UK", "line_item": "Temporary Repatriation Facility (TRF)"}, "normalization": "GBP billion x 1e9 -> GBP", "period": 2024, "proposed_metric": "revenue_level", "proposed_unit": "gbp", "publication": {"publication_url": "https://obr.uk/efo/economic-and-fiscal-outlook-march-2026/", "publisher": "Office for Budget Responsibility", "title": "Economic and fiscal outlook March 2026 - detailed forecast tables: receipts", "url": "https://obr.uk/docs/d055fbf02d5b3g6jq8l2/efo-march-2026-detailed-forecast-tables-receipts.xlsx", "vintage": "March 2026 EFO", "wayback": "https://web.archive.org/web/20260316163140id_/https://obr.uk/docs/d055fbf02d5b3g6jq8l2/efo-march-2026-detailed-forecast-tables-receipts.xlsx", "workbook": "efo-march-2026-detailed-forecast-tables-receipts.xlsx"}, "reform_hint": null, "source": "obr", "source_column": "2024-25", "source_model": "obr_efo_forecast", "source_table": "3.4: 3.4 Income tax and NICs forecast: detailed breakdown", "status": "ok", "time_basis": "fiscal_year", "value": 0.0, "value_raw": 0.0}} +{"fact_id": "uk:uk_obr:fdcb2a85958105033548", "routed_because": "OBR EFO outturn column \u2014 admin receipts/expenditure fact (ledger routing rule, Max 2026-08-02)", "source": "uk_obr", "staged": {"calibration_relationship": "held_out", "conditions": {"basis": "outturn", "fy": "2024-25", "geography": "UK", "line_item": "Apprenticeship Levy"}, "normalization": "GBP billion x 1e9 -> GBP", "period": 2024, "proposed_metric": "revenue_level", "proposed_unit": "gbp", "publication": {"publication_url": "https://obr.uk/efo/economic-and-fiscal-outlook-march-2026/", "publisher": "Office for Budget Responsibility", "title": "Economic and fiscal outlook March 2026 - detailed forecast tables: receipts", "url": "https://obr.uk/docs/d055fbf02d5b3g6jq8l2/efo-march-2026-detailed-forecast-tables-receipts.xlsx", "vintage": "March 2026 EFO", "wayback": "https://web.archive.org/web/20260316163140id_/https://obr.uk/docs/d055fbf02d5b3g6jq8l2/efo-march-2026-detailed-forecast-tables-receipts.xlsx", "workbook": "efo-march-2026-detailed-forecast-tables-receipts.xlsx"}, "reform_hint": null, "source": "obr", "source_column": "2024-25", "source_model": "obr_efo_forecast", "source_table": "3.8: 3.8 Current receipts (on a cash basis)", "status": "ok", "time_basis": "fiscal_year", "value": 4099999999.9999995, "value_raw": 4.1}} diff --git a/scorecard_db/baselines.py b/scorecard_db/baselines.py index e60cb71..09dd25a 100644 --- a/scorecard_db/baselines.py +++ b/scorecard_db/baselines.py @@ -110,6 +110,17 @@ "Budget Lab 16-scenario CTC options workbook " "(sources/harvest-2026-08-02/budget_lab).", ), + ( + {"policy": "ifs_2cl_fp_removal_rolled_out"}, + "ifs_2cl_fp_removal_rolled_out", + "IFS Green-Budget-2025 options baseline: the current UK " + "tax-benefit system with the two-child limit and family-premium " + "removal fully rolled out (steady state).", + "policy_ref", + "IFS staged conditions verbatim: 'current tax-benefit system " + "with two-child limit and family premium removal fully rolled " + "out' (sources/harvest-uk-2026-08-02/uk_ifs).", + ), ( {"policy": "pre_ab2025"}, "pre_ab2025", diff --git a/scorecard_db/ingest_harvest.py b/scorecard_db/ingest_harvest.py index 292647a..689cea3 100644 --- a/scorecard_db/ingest_harvest.py +++ b/scorecard_db/ingest_harvest.py @@ -69,11 +69,16 @@ } -def sync_lane_feed(db: ScorecardDB, feed_path: Path, updated: str) -> int: +def sync_lane_feed( + db: ScorecardDB, + feed_path: Path, + updated: str, + lane_feed: dict | None = None, +) -> int: feed = json.loads(feed_path.read_text()) by_id = {lane["id"]: lane for lane in feed["lanes"]} n = 0 - for lane_id, meta in LANE_FEED.items(): + for lane_id, meta in (lane_feed or LANE_FEED).items(): row = db.conn.execute( "SELECT stage, detail, updated_at FROM lanes WHERE lane = ?", (lane_id,), diff --git a/scorecard_db/ingest_uk.py b/scorecard_db/ingest_uk.py new file mode 100644 index 0000000..780d165 --- /dev/null +++ b/scorecard_db/ingest_uk.py @@ -0,0 +1,118 @@ +"""Run all seven 2026-08-02 UK-harvest adapters. + + PYTHONPATH=. python -m scorecard_db.ingest_uk data/scorecard.db + +Beyond the per-source ingests this runner: + +1. Collects every admin-outturn row the adapters routed OUT of + external_scores and writes the Ledger staging file + (data/ledger/uk_admin_outturns.jsonl) — the populace/Ledger lane's + handoff, with deterministic pre-agreed fact ids (routing rule, Max + 2026-08-02: admin facts → Ledger, model claims → Scorecard). +2. Seeds the baselines registry and fails loudly on any baseline world + the data references that is not deliberately described (issue #13). +3. Mirrors the UK lanes into data/lanes.json (the app's + mission-control feed), adding entries for the lanes new with this + population. +""" + +from __future__ import annotations + +import json +from pathlib import Path + +from . import ( + ingest_uk_dwp, + ingest_uk_hmrc, + ingest_uk_hmt, + ingest_uk_ifs, + ingest_uk_obr, + ingest_uk_rf, + ingest_uk_ukmod_jrf, +) +from .baselines import register_baselines +from .db import ScorecardDB +from .harvest import REPO +from .ingest_harvest import sync_lane_feed +from .uk import write_ledger_staging + +ADAPTERS = { + "uk_obr": ingest_uk_obr, + "uk_hmrc": ingest_uk_hmrc, + "uk_dwp": ingest_uk_dwp, + "uk_hmt": ingest_uk_hmt, + "uk_ukmod_jrf": ingest_uk_ukmod_jrf, + "uk_ifs": ingest_uk_ifs, + "uk_rf": ingest_uk_rf, +} + +UK_LANE_FEED = { + "obr-measures": { + "source": "OBR", "area": "policy measures database (1970→)", + "mode": 2, + }, + "obr-welfare": { + "source": "OBR", "area": "welfare trends / EFO baselines", "mode": 1, + }, + "hmrc-personal-tax": { + "source": "HMRC", "area": "UK personal tax statistics", "mode": 1, + }, + "hbai-poverty": { + "source": "DWP HBAI", "area": "UK poverty rates", "mode": 1, + }, + "dwp-takeup": { + "source": "DWP", "area": "UK income-related benefits take-up", + "mode": 1, + }, + "hmt-costings": { + "source": "HM Treasury", "area": "fiscal-event scorecards + DA", + "mode": 2, + }, + "ukmod-stats": { + "source": "UKMOD", "area": "published statistics", "mode": 1, + }, + "ifs-taxben": { + "source": "IFS TAXBEN", "area": "poverty + benefit options", + "mode": 2, + }, + "rf-outlook": { + "source": "Resolution Foundation", + "area": "living standards outlook + Budget analysis", "mode": 2, + }, +} + + +def ingest(db_path: Path) -> dict: + stats: dict = {} + ledger_rows: list[dict] = [] + for name, adapter in ADAPTERS.items(): + # stage() runs twice (here for the ledger rows, again inside the + # adapter's own ingest) — staging is pure and cheap, and keeping + # each adapter independently runnable beats threading state. + ledger_rows.extend(adapter.stage()[1]) + stats[name] = adapter.ingest(db_path) + + stats["ledger_staging_rows"] = write_ledger_staging(ledger_rows) + + db = ScorecardDB(db_path) + stats["baselines_registered"] = register_baselines(db) + stats["lanes_synced"] = sync_lane_feed( + db, REPO / "data" / "lanes.json", "2026-08-02", + lane_feed=UK_LANE_FEED, + ) + stats["coverage"] = db.coverage() + stats["claims_by_source"] = { + r["source"]: r["n"] + for r in db.conn.execute( + "SELECT source, COUNT(*) n FROM external_scores GROUP BY source" + ) + } + db.close() + return stats + + +if __name__ == "__main__": + import sys + + out = Path(sys.argv[1] if len(sys.argv) > 1 else "data/scorecard.db") + print(json.dumps(ingest(out), indent=1)) diff --git a/scorecard_db/ingest_uk_dwp.py b/scorecard_db/ingest_uk_dwp.py new file mode 100644 index 0000000..f1eca02 --- /dev/null +++ b/scorecard_db/ingest_uk_dwp.py @@ -0,0 +1,305 @@ +"""Ingest the DWP staged claims (2026-08-02 UK harvest). + +Four families: + +- **HBAI headline poverty** (dwp_hbai_frs, 1,040): rates and counts, + FYE 1995–2025, relative & absolute × BHC & AHC, two editions (FYE-2025 + + the FYE-2024 admin-linked restatement pair — conditions["edition"]). + Survey-outcome statistics, NOT admin outturn: they stay scorecard-side + as permanent holdouts (poverty may never be a calibration target). +- **Income-related-benefit take-up estimates** (dwp_takeup_estimates, + 805): DWP's own eligibility-model estimates with lower/central/upper + bounds. Pension Credit rows arrive seed_source — policyengine-uk + gov/dwp/pension_credit/takeup.yaml cites this series (verified by the + harvest agent); HB rows stay held_out, the live external comparator + for PE-UK's takeup=1 assumption (policyengine-uk#1813). +- **Benefit expenditure & caseload (BECL)**, Spring-2026, OBR-consistent + (dwp_becl, 204): outturn rows are admin facts → Ledger staging; + forecast rows enter. Expenditure forecasts whose benefit is a Table + 4.9 line populace-UK literally consumes (targets/sources/obr.py, read + this session) → consumed_as_target: state_pension, universal_credit, + pension_credit, attendance_allowance, child_benefit. dla/pip stay + held_out — populace consumes only their COMBINED 4.9 line, and BECL + caseloads stay held_out — obr.py parses expenditure only. +- **UC admin release** (dwp_uc_admin, 5, point-in-time Feb-2026): + consumed_as_target — targets/sources/dwp.py consumes UC claimant + counts and the payment distribution from this same admin series + (staged VERIFIED note, re-read this session). + +Period is re-derived from the fy label (FYE end-year convention and the +'1999/00'→1900 staging defect both normalize to FY start year). +""" + +from __future__ import annotations + +import json +from pathlib import Path + +from .db import ScorecardDB +from .harvest import finish +from .models import ( + BASELINE, + CalibrationRelationship, + ExternalScore, + Metric, + TimeBasis, + UnitConcept, +) +from .uk import ( + ledger_row, + load_staged_uk, + normalize_geography_uk, + parse_fy, + uk_value_kind, +) + +_KNOWN_FIELDS = frozenset( + { + "source", "metric", "proposed_metric", "unit_concept", + "proposed_unit", "value", "value_raw", "value_kind", "conversion", + "period", "time_basis", "conditions", "reform", + "calibration_relationship", "calibration_note", "series_note", + "time_note", "geography_note", "unit_note", + "source_model", "source_column", "publication", "status", + } +) + +_CONDITION_KEYS = { + "geography": "geography", + "fy": "fy", + "edition": "edition", + "subgroup": "subgroup", + "income_concept": "income_concept", + "poverty_measure": "poverty_measure", + "poverty_line": "poverty_line", + "poverty_line_anchor": "poverty_line_anchor", + "equivalisation": "equivalisation", + "benefit": "program", + "entitlement_group": "entitlement_group", + "bound": "bound", + "takeup_basis": "takeup_basis", + "basis": "basis", + "data_vintage": "data_vintage", + "component": "component", + "family_type": "family_type", + "age_group": "age_group", + "month": "month", + "geography_note": "geography_note", +} + +_METRICS = { + "poverty_rate": Metric.POVERTY_RATE, + "poverty_count": Metric.POVERTY_COUNT, + "participation_rate": Metric.PARTICIPATION_RATE, + "participation_gap_count": Metric.PARTICIPATION_GAP_COUNT, + "participant_count": Metric.PARTICIPANT_COUNT, + "benefit_cost": Metric.BENEFIT_COST, + "caseload": Metric.CASELOAD, + "unclaimed_expenditure": Metric.UNCLAIMED_EXPENDITURE, +} + +_UNITS = { + "persons": UnitConcept.PERSONS, + "families": UnitConcept.FAMILIES, + "households": UnitConcept.HOUSEHOLDS, + "children_under_18": UnitConcept.CHILDREN_UNDER_18, + "adults_18plus": UnitConcept.ADULTS_18PLUS, +} + +# BECL expenditure forecasts whose benefit is an exact Table 4.9 line +# populace-UK consumes (policyengine-uk-data targets/sources/obr.py, +# read 2026-08-02). BECL is published OBR-Spring-2026-consistent, so +# these series are the same quantity class as the consumed forecasts. +_BECL_CONSUMED = { + "state_pension": "obr/state_pension", + "universal_credit": "obr/universal_credit_in_cap + outside_cap", + "pension_credit": "obr/pension_credit", + "attendance_allowance": "obr/attendance_allowance", + "child_benefit": "obr/child_benefit", +} +_BECL_CONSUMED_BASIS = ( + "BECL Spring-2026 is OBR-forecast-consistent and policyengine-uk-data " + "targets/sources/obr.py consumes the matching EFO Table 4.9 " + "expenditure line ({target}; read 2026-08-02) — same series class, so " + "agreement is discipline, not validation" +) +_BECL_COMPONENT_HELDOUT_NOTE = ( + "held_out deliberately: populace-UK consumes only the COMBINED " + "DLA+PIP Table 4.9 line; this BECL component split is not itself a " + "target (partial discipline via the consumed aggregate, noted)" +) +_BECL_CASELOAD_NOTE = ( + "held_out deliberately: targets/sources/obr.py parses Table 4.9 " + "expenditure only (read 2026-08-02) — BECL caseload forecasts are " + "not consumed" +) + + +def stage() -> tuple[list[ExternalScore], list[dict]]: + scores: list[ExternalScore] = [] + ledger: list[dict] = [] + for row in load_staged_uk("uk_dwp"): + unknown = set(row) - _KNOWN_FIELDS + if unknown: + raise ValueError(f"uk_dwp: unhandled fields {sorted(unknown)}") + if row["reform"] != {"framework": "baseline"}: + raise ValueError(f"uk_dwp: unexpected reform {row['reform']}") + conds_in = dict(row["conditions"]) + if ( + row["source_model"] == "dwp_becl" + and conds_in.get("basis") == "outturn" + ): + ledger.append( + ledger_row( + "uk_dwp", row, + "DWP BECL outturn — admin expenditure/caseload fact " + "(ledger routing rule, Max 2026-08-02)", + ) + ) + continue + + unknown_c = set(conds_in) - set(_CONDITION_KEYS) + if unknown_c: + raise ValueError(f"uk_dwp: unmapped conditions {sorted(unknown_c)}") + geography, geo_note = normalize_geography_uk(conds_in.pop("geography")) + conditions = { + _CONDITION_KEYS[k]: v + for k, v in conds_in.items() + if v is not None and k != "fy" + } + conditions["geography"] = geography + if geo_note: + conditions["geography_note"] = geo_note + if "fy" in conds_in: + period, fy_norm = parse_fy(conds_in["fy"]) + conditions["fy"] = fy_norm + else: + if row["time_basis"] != "point_in_time": + raise ValueError("uk_dwp: fy missing on non-point-in-time row") + period = row["period"] + + metric_name = row.get("metric") or row["proposed_metric"] + metric = _METRICS[metric_name] + if metric in (Metric.POVERTY_RATE, Metric.PARTICIPATION_RATE): + unit = UnitConcept.SHARE + elif row.get("unit_concept"): + unit = _UNITS[row["unit_concept"]] + elif (row.get("proposed_unit") or row.get("value_kind")) in ( + "gbp", "currency_gbp", + ): + unit = UnitConcept.GBP + else: + raise ValueError(f"uk_dwp: no unit for {metric_name}") + + relationship = CalibrationRelationship(row["calibration_relationship"]) + publication = dict(row["publication"]) + if row.get("calibration_note"): + publication["calibration_basis"] = row["calibration_note"] + for note in ("series_note", "time_note", "unit_note"): + if row.get(note): + publication[note] = row[note] + if row.get("geography_note"): + # Verbatim devolution scope (DLA/PIP/AA England&Wales-only + # from FY 2020/21) — identity-adjacent, keep on conditions. + conditions["geography_note"] = row["geography_note"] + if row.get("time_note"): + # BECL Notes: caseloads are full-financial-year averages — + # load-bearing vs point-in-time admin counts (UC 5.47M FY-avg + # vs 7.2M Feb-2026), so it rides conditions. + conditions["caseload_basis"] = "fy_average" + + if row["source_model"] == "dwp_becl": + program = conditions.get("program") + if metric is Metric.BENEFIT_COST and program in _BECL_CONSUMED: + relationship = CalibrationRelationship.CONSUMED_AS_TARGET + publication["calibration_basis"] = ( + _BECL_CONSUMED_BASIS.format( + target=_BECL_CONSUMED[program] + ) + ) + elif metric is Metric.BENEFIT_COST and program in ("dla", "pip"): + publication["calibration_basis"] = ( + _BECL_COMPONENT_HELDOUT_NOTE + ) + elif metric is Metric.CASELOAD: + publication["calibration_basis"] = _BECL_CASELOAD_NOTE + elif row["source_model"] == "dwp_uc_admin": + # Staged VERIFIED note: targets/sources/dwp.py consumes this + # same Feb-2026 admin series (re-read 2026-08-02). + relationship = CalibrationRelationship.CONSUMED_AS_TARGET + + scores.append( + ExternalScore( + source="dwp", + source_model=row["source_model"], + metric=metric, + unit_concept=unit, + period=period, + time_basis=TimeBasis(row["time_basis"]), + value=row["value"], + conditions=conditions, + reform=BASELINE, + calibration_relationship=relationship, + source_column=row.get("source_column"), + publication=publication, + value_kind=uk_value_kind(row.get("value_kind"), unit.value), + status=row.get("status", "ok"), + ) + ) + return finish(scores, "uk_dwp"), ledger + + +def ingest(db_path: Path) -> dict: + scores, ledger = stage() + db = ScorecardDB(db_path) + n = db.upsert_scores(scores) + by_model: dict[str, int] = {} + for s in scores: + by_model[s.source_model] = by_model.get(s.source_model, 0) + 1 + consumed = sum( + 1 + for s in scores + if s.calibration_relationship + is CalibrationRelationship.CONSUMED_AS_TARGET + ) + seeded = sum( + 1 + for s in scores + if s.calibration_relationship is CalibrationRelationship.SEED_SOURCE + ) + db.set_lane( + "hbai-poverty", + "ingested", + f"{by_model.get('dwp_hbai_frs', 0)} HBAI claims (FYE 1995-2025, " + "relative+absolute × BHC+AHC, rates+counts; FYE-2025 + admin-" + "linked FYE-2024 edition pair staged — the ~2pp methodology-gap " + "diagnosis seed); permanent poverty holdout", + "2026-08-02", + ) + db.set_lane( + "dwp-takeup", + "ingested", + f"{by_model.get('dwp_takeup_estimates', 0)} take-up claims with " + f"bounds ({seeded} PC rows seed_source — pe-uk takeup.yaml cites " + "this series; HB rows held_out vs PE takeup=1, " + "policyengine-uk#1813); " + f"{by_model.get('dwp_becl', 0)} BECL forecast rows " + f"({consumed - by_model.get('dwp_uc_admin', 0)} expenditure lines " + "consumed_as_target via OBR 4.9); " + f"{len(ledger)} BECL outturn rows routed to Ledger staging", + "2026-08-02", + ) + db.close() + return { + "scores": n, + "ledger": len(ledger), + "consumed": consumed, + "seed_source": seeded, + } + + +if __name__ == "__main__": + import sys + + out = Path(sys.argv[1] if len(sys.argv) > 1 else "data/scorecard.db") + print(json.dumps(ingest(out), indent=1)) diff --git a/scorecard_db/ingest_uk_hmrc.py b/scorecard_db/ingest_uk_hmrc.py new file mode 100644 index 0000000..16c9ee8 --- /dev/null +++ b/scorecard_db/ingest_uk_hmrc.py @@ -0,0 +1,241 @@ +"""Ingest the HMRC staged claims (2026-08-02 UK harvest). + +Ledger routing does the heavy lifting here: HMRC's outturn statistics — +SPI outturn tables, Child Benefit / tax credits / CGT / self-assessment +admin statistics, including provisional cells — are admin facts and go +to the Ledger staging file (1,855 rows). What enters external_scores is +HMRC-the-model speaking (987 rows): + +- **Ready reckoner** (225): "Direct effects of illustrative tax changes" + — each line is a policy world (policy_ref uk_hmrc_rr:) at + FY 2026-27/2027-28/2028-29, behavioural per HMRC's methodology notes, + sign per bulletin note 33 (verbatim in conditions/publication). These + are the claims the campaign's reckoner runs join to (reform_hint is + the join key, slugified identically on both sides). +- **SPI-based projections** (762): taxpayer counts, liabilities, + income aggregates and average tax by band/age/sex, projected years. + calibration: seed_source — policyengine-uk-data targets/sources/ + hmrc_spi.py consumes SPI 3.6/3.7 (2023-24) and + utils/incomes_projection.py uprates from that same base (read + 2026-08-02), so PE's income distribution and HMRC's projections share + the SPI seed; agreement is same-seed, not validation. Whole-population + liability totals are additionally the same quantity class as the + consumed obr/income_tax receipts target → consumed_as_target. +""" + +from __future__ import annotations + +import json +from pathlib import Path + +from .db import ScorecardDB +from .harvest import finish, policy_ref +from .models import ( + BASELINE, + CalibrationRelationship, + ExternalScore, + Metric, + TimeBasis, + UnitConcept, +) +from .uk import ( + ledger_row, + load_staged_uk, + normalize_geography_uk, + parse_fy, + slugify, + uk_value_kind, +) + +_KNOWN_FIELDS = frozenset( + { + "source", "metric", "proposed_metric", "unit_concept", + "proposed_unit", "value", "value_raw", "value_kind", "period", + "time_basis", "conditions", "reform", "reform_hint", + "sign_convention", "unit_note", "row_note", + "calibration_relationship", "source_model", "source_column", + "publication", "status", + } +) + +_CONDITION_KEYS = { + "geography": "geography", + "fy": "fy", + "basis": "basis", + "tax": "tax", + "band": "band", + "income_range_lower": "income_range_lower", + "tax_section": "tax_section", + "direction_semantics": "direction_semantics", + "age_group": "age_group", + "sex": "sex", +} + +_METRICS = { + "revenue_change": Metric.REVENUE_CHANGE, + "taxpayer_count": Metric.TAXPAYER_COUNT, + "tax_liability": Metric.TAX_LIABILITY, + "income_aggregate": Metric.INCOME_AGGREGATE, + "average_tax_rate": Metric.AVERAGE_TAX_RATE, + "average_tax_amount": Metric.AVERAGE_TAX_AMOUNT, +} + +_SPI_SEED_BASIS = ( + "seed_source: policyengine-uk-data targets/sources/hmrc_spi.py " + "consumes SPI Tables 3.6/3.7 (tax year 2023-24) and " + "utils/incomes_projection.py uprates future years from the same " + "parsed band table (read 2026-08-02) — PE's income distribution and " + "HMRC's projection share the SPI seed" +) +_LIABILITY_TOTAL_BASIS = ( + "consumed_as_target: whole-population income-tax liability is the " + "same quantity class as the obr/income_tax receipts forecast " + "populace-UK consumes (targets/sources/obr.py, read 2026-08-02); " + "band detail below the total stays seed_source (SPI-seeded)" +) +_TOTAL_BAND_MARKERS = frozenset({"all", "total", "all taxpayers"}) + + +def stage() -> tuple[list[ExternalScore], list[dict]]: + scores: list[ExternalScore] = [] + ledger: list[dict] = [] + for row in load_staged_uk("uk_hmrc"): + unknown = set(row) - _KNOWN_FIELDS + if unknown: + raise ValueError(f"uk_hmrc: unhandled fields {sorted(unknown)}") + basis = row["conditions"].get("basis") + if basis in ("outturn", "provisional"): + ledger.append( + ledger_row( + "uk_hmrc", row, + f"HMRC {row['source_model']} {basis} statistics — " + "admin fact (ledger routing rule, Max 2026-08-02)", + ) + ) + continue + if basis != "projected": + raise ValueError(f"uk_hmrc: unexpected basis {basis!r}") + if row["reform"] != {"framework": "baseline"}: + raise ValueError(f"uk_hmrc: unexpected reform {row['reform']}") + + conds_in = dict(row["conditions"]) + unknown_c = set(conds_in) - set(_CONDITION_KEYS) + if unknown_c: + raise ValueError( + f"uk_hmrc: unmapped conditions {sorted(unknown_c)}" + ) + geography, geo_note = normalize_geography_uk(conds_in.pop("geography")) + period, fy_norm = parse_fy(conds_in.pop("fy")) + conditions = { + _CONDITION_KEYS[k]: v + for k, v in conds_in.items() + if v is not None + } + conditions["geography"] = geography + if geo_note: + conditions["geography_note"] = geo_note + conditions["fy"] = fy_norm + + metric_name = row.get("metric") or row["proposed_metric"] + metric = _METRICS[metric_name] + is_rr = row["source_model"] == "hmrc" + if is_rr: + if not row.get("reform_hint"): + raise ValueError("uk_hmrc: ready-reckoner row without hint") + reform = policy_ref(f"uk_hmrc_rr:{slugify(row['reform_hint'])}") + conditions["measure"] = row["reform_hint"] + else: + if row.get("reform_hint"): + raise ValueError("uk_hmrc: unexpected reform_hint") + reform = BASELINE + + if metric is Metric.TAXPAYER_COUNT: + unit = UnitConcept.PERSONS + elif metric is Metric.AVERAGE_TAX_RATE: + unit = UnitConcept.SHARE + elif metric is Metric.AVERAGE_TAX_AMOUNT: + unit = UnitConcept.GBP_PER_PERSON + else: + unit = UnitConcept.GBP + + relationship = CalibrationRelationship(row["calibration_relationship"]) + publication = dict(row["publication"]) + for note in ("sign_convention", "unit_note", "row_note"): + if row.get(note): + publication[note] = row[note] + if row["source_model"] == "hmrc_spi": + band = (conditions.get("band") or "").lower() + is_total = band in _TOTAL_BAND_MARKERS and not ( + conditions.get("age_group") or conditions.get("sex") + ) + if metric is Metric.TAX_LIABILITY and is_total: + relationship = CalibrationRelationship.CONSUMED_AS_TARGET + publication["calibration_basis"] = _LIABILITY_TOTAL_BASIS + else: + relationship = CalibrationRelationship.SEED_SOURCE + publication["calibration_basis"] = _SPI_SEED_BASIS + + scores.append( + ExternalScore( + source="hmrc", + source_model=row["source_model"], + metric=metric, + unit_concept=unit, + period=period, + time_basis=TimeBasis(row["time_basis"]), + value=row["value"], + conditions=conditions, + reform=reform, + calibration_relationship=relationship, + source_column=row.get("source_column"), + publication=publication, + value_kind=uk_value_kind(row.get("value_kind"), unit.value), + status=row.get("status", "ok"), + ) + ) + return finish(scores, "uk_hmrc"), ledger + + +def ingest(db_path: Path) -> dict: + scores, ledger = stage() + rr = sum(1 for s in scores if s.source_model == "hmrc") + consumed = sum( + 1 + for s in scores + if s.calibration_relationship + is CalibrationRelationship.CONSUMED_AS_TARGET + ) + seeded = sum( + 1 + for s in scores + if s.calibration_relationship is CalibrationRelationship.SEED_SOURCE + ) + db = ScorecardDB(db_path) + n = db.upsert_scores(scores) + db.set_lane( + "hmrc-personal-tax", + "ingested", + f"{rr} ready-reckoner claims (policy worlds per line, FY2026-27+, " + "behavioural per HMRC notes — the campaign reckoner join surface) " + f"+ {n - rr} SPI-based projections ({seeded} seed_source via the " + f"shared SPI 2023-24 base, {consumed} whole-population liability " + "totals consumed-class); " + f"{len(ledger)} outturn/provisional admin rows routed to Ledger " + "staging", + "2026-08-02", + ) + db.close() + return { + "scores": n, + "ledger": len(ledger), + "ready_reckoner": rr, + "consumed": consumed, + "seed_source": seeded, + } + + +if __name__ == "__main__": + import sys + + out = Path(sys.argv[1] if len(sys.argv) > 1 else "data/scorecard.db") + print(json.dumps(ingest(out), indent=1)) diff --git a/scorecard_db/ingest_uk_hmt.py b/scorecard_db/ingest_uk_hmt.py new file mode 100644 index 0000000..532d01c --- /dev/null +++ b/scorecard_db/ingest_uk_hmt.py @@ -0,0 +1,184 @@ +"""Ingest the HMT staged claims (2026-08-02 UK harvest). + +- **Scorecard costings** (1,218, hmt_costing_obr_certified): every + measure line of AB2024 Table 5.1, Budget 2025 Table 4.1 and SS2025 + Table 3.1 — OBR-certified exchequer impacts. Each measure title is a + policy_ref world (uk_hmt::) scored against current + law at announcement; row_type (measure|total|of_which), scorecard_line + and Tax/Spend head ride conditions verbatim. Metric is + exchequer_impact, NOT revenue_change — the footnote classifies lines + by LARGEST impact, so Tax/Spend heads mix (deliberate mapping, + COLLATION UK worklist item 1). Suppressed cells ("*", negligible) + stage as status=suppressed. +- **Distributional analysis** (150, hmt_distributional_analysis_igotm): + Annex Table 2.C median gross income by decile × household composition + — baseline level claims with the full IGOTM income-concept string + (equivalised, BHC, modified-OECD) verbatim in conditions. +""" + +from __future__ import annotations + +import json +from pathlib import Path + +from .db import ScorecardDB +from .harvest import finish, policy_ref +from .models import ( + BASELINE, + CalibrationRelationship, + ExternalScore, + Metric, + TimeBasis, + UnitConcept, +) +from .uk import ( + ledger_row, + load_staged_uk, + measure_slug, + normalize_geography_uk, + parse_fy, +) + +_KNOWN_FIELDS = frozenset( + { + "source", "proposed_metric", "proposed_unit", "value", "value_raw", + "conversion", "metric_note", "parse_confidence", "sign_note", + "period", "time_basis", "conditions", "reform", "reform_hint", + "calibration_relationship", "source_model", "source_column", + "source_table", "publication", "status", "name_note", + "suppression_note", + } +) + +_CONDITION_KEYS = { + "geography": "geography", + "fiscal_event": "fiscal_event", + "fiscal_year": "fy", + "row_type": "row_type", + "section": "section", + "scorecard_line": "scorecard_line", + "head": "head", + "decile": "decile", + "household_composition": "household_composition", + "income_concept": "income_concept", + "decile_definition": "decile_definition", + "equivalisation": "equivalisation", +} + +_METRICS = { + "exchequer_impact": Metric.EXCHEQUER_IMPACT, + "median_gross_income": Metric.MEDIAN_INCOME, +} + + +def stage() -> tuple[list[ExternalScore], list[dict]]: + scores: list[ExternalScore] = [] + ledger: list[dict] = [] + for row in load_staged_uk("uk_hmt"): + unknown = set(row) - _KNOWN_FIELDS + if unknown: + raise ValueError(f"uk_hmt: unhandled fields {sorted(unknown)}") + if row["parse_confidence"] != "high": + raise ValueError( + f"uk_hmt: non-high parse confidence needs review: " + f"{row['parse_confidence']!r}" + ) + conds_in = dict(row["conditions"]) + unknown_c = set(conds_in) - set(_CONDITION_KEYS) + if unknown_c: + raise ValueError(f"uk_hmt: unmapped conditions {sorted(unknown_c)}") + + geography, geo_note = normalize_geography_uk(conds_in.pop("geography")) + period, fy_norm = parse_fy(conds_in.pop("fiscal_year")) + conditions = { + _CONDITION_KEYS[k]: v + for k, v in conds_in.items() + if v is not None + } + conditions["geography"] = geography + if geo_note: + conditions["geography_note"] = geo_note + conditions["fy"] = fy_norm + + metric = _METRICS[row["proposed_metric"]] + is_costing = row["source_model"] == "hmt_costing_obr_certified" + if is_costing: + hint = row["reform_hint"] + if not hint: + raise ValueError("uk_hmt: costing row without reform_hint") + if "reform" in row: + raise ValueError("uk_hmt: costing row carries reform field") + reform = policy_ref( + measure_slug("uk_hmt", conds_in["fiscal_event"], hint) + ) + conditions["measure"] = hint + unit = UnitConcept.GBP + value_kind = "gbp" + else: + if row.get("reform", {"framework": "baseline"}) != { + "framework": "baseline" + }: + raise ValueError(f"uk_hmt: unexpected reform {row['reform']}") + reform = BASELINE + unit = UnitConcept.GBP_PER_HOUSEHOLD + value_kind = "gbp" + + publication = dict(row["publication"]) + if row.get("source_table"): + publication.setdefault("table", row["source_table"]) + for note in ("sign_note", "metric_note", "name_note", + "suppression_note"): + if row.get(note): + publication[note] = row[note] + + scores.append( + ExternalScore( + source="hmt", + source_model=row["source_model"], + metric=metric, + unit_concept=unit, + period=period, + time_basis=TimeBasis(row["time_basis"]), + value=row["value"], + conditions=conditions, + reform=reform, + calibration_relationship=CalibrationRelationship( + row["calibration_relationship"] + ), + source_column=row.get("source_column"), + publication=publication, + value_kind=value_kind, + status=row.get("status", "ok"), + ) + ) + return finish(scores, "uk_hmt"), ledger + + +def ingest(db_path: Path) -> dict: + scores, ledger = stage() + costings = sum( + 1 for s in scores if s.source_model == "hmt_costing_obr_certified" + ) + suppressed = sum(1 for s in scores if s.status == "suppressed") + db = ScorecardDB(db_path) + n = db.upsert_scores(scores) + db.set_lane( + "hmt-costings", + "ingested", + f"{costings} OBR-certified scorecard costings (AB2024 5.1 / " + "B2025 4.1 / SS2025 3.1; exchequer_impact — Tax/Spend heads mix " + f"by design; {suppressed} suppressed cells verbatim) + " + f"{n - costings} IGOTM decile medians (annex 2.C); B2025 " + "two-child measure title embeds the government's 450k-children " + "poverty claim — pentagon leg", + "2026-08-02", + ) + db.close() + return {"scores": n, "ledger": len(ledger), "costings": costings} + + +if __name__ == "__main__": + import sys + + out = Path(sys.argv[1] if len(sys.argv) > 1 else "data/scorecard.db") + print(json.dumps(ingest(out), indent=1)) diff --git a/scorecard_db/ingest_uk_ifs.py b/scorecard_db/ingest_uk_ifs.py new file mode 100644 index 0000000..b84d83d --- /dev/null +++ b/scorecard_db/ingest_uk_ifs.py @@ -0,0 +1,253 @@ +"""Ingest the IFS TAXBEN staged claims (2026-08-02 UK harvest). + +268 rows: absolute-AHC child-poverty series and the Green-Budget-2025 +benefit-options block (13 options × poverty/cost/distribution metrics), +Autumn-Budget-2025 package analysis, and threshold-freeze revenue rows. + +The options block is scored against a named non-current-law baseline — +"current tax-benefit system with two-child limit and family premium +removal fully rolled out" (steady state) — which becomes the registered +baseline world ifs_2cl_fp_removal_rolled_out on the ReformRef (issue +#13: baseline variants are load-bearing, never conditions-only; the +steady-state horizon additionally rides conditions["horizon"]). IFS +TAXBEN is deliberately full-take-up (entitlements basis) — the +assumptions-registry axis on every UK poverty comparison. + +Poverty metrics stay permanent holdouts; everything is held_out as +staged (no populace-UK consumption of IFS outputs). +""" + +from __future__ import annotations + +import json +from pathlib import Path + +from .db import ScorecardDB +from .harvest import finish, with_baseline_condition +from .models import ( + BASELINE, + CalibrationRelationship, + ExternalScore, + Metric, + ReformRef, + TimeBasis, + UnitConcept, +) +from .uk import ( + load_staged_uk, + normalize_geography_uk, + parse_fy, + slugify, +) + +_KNOWN_FIELDS = frozenset( + { + "source", "metric", "proposed_metric", "unit_concept", + "proposed_unit", "value", "value_raw", "normalization", + "parse_confidence", "sign_convention", "geography_note", + "period", "time_basis", "conditions", "reform_hint", + "calibration_relationship", "source_model", "source_column", + "source_table", "publication", + } +) + +_CONDITION_KEYS = { + "geography": "geography", + "fy": "fy", + "income_concept": "income_concept", + "population": "subgroup", + "poverty_measure": "poverty_measure", + "poverty_line": "poverty_line", + "data_vintage": "data_vintage", + "baseline": None, # handled: becomes the ReformRef baseline world + "time_note": None, # handled: steady-state horizon marker + "income_group": "income_group", + "income_axis": "income_axis", + "share_denominator": "share_denominator", + "tax_category": "tax_category", + "counterfactual": "counterfactual", + "policy": "policy_note", + "program": "program", + # provenance notes -> publication + "method_note": None, + "scope_note": None, + "costing_basis": None, + "row_source_note": None, + "description_verbatim": "description", + "uncertainty_verbatim": None, + "attribution_note": None, +} +_PUBLICATION_NOTES = ( + "method_note", "scope_note", "costing_basis", "row_source_note", + "uncertainty_verbatim", "attribution_note", +) + +_METRICS = { + "poverty_rate": (Metric.POVERTY_RATE, UnitConcept.SHARE), + "poverty_rate_change": ( + Metric.POVERTY_RATE_CHANGE, UnitConcept.PERCENTAGE_POINTS, + ), + "revenue_change": (Metric.REVENUE_CHANGE, UnitConcept.GBP), + "benefit_spending_change": ( + Metric.EXPENDITURE_CHANGE, UnitConcept.GBP, + ), + "share_of_spending_to_group": ( + Metric.SHARE_OF_SPENDING_TO_GROUP, UnitConcept.PERCENT, + ), + "avg_change_household_net_income": ( + Metric.AVG_CHANGE_HOUSEHOLD_NET_INCOME, UnitConcept.GBP_PER_YEAR, + ), + "cost_per_child_lifted_out_of_poverty": ( + Metric.COST_PER_CHILD_LIFTED_OUT_OF_POVERTY, UnitConcept.GBP, + ), + "taxpayer_count_change": ( + Metric.TAXPAYER_COUNT_CHANGE, UnitConcept.PERSONS, + ), + "families_affected_count": ( + Metric.FAMILIES_AFFECTED_COUNT, UnitConcept.FAMILIES, + ), +} +_COUNT_UNITS = { + "children_under_18": UnitConcept.CHILDREN_UNDER_18, + "persons": UnitConcept.PERSONS, +} + +# The Green-Budget options baseline (verbatim staged condition value). +STEADY_STATE_BASELINE = {"policy": "ifs_2cl_fp_removal_rolled_out"} +_STEADY_STATE_VERBATIM = ( + "current tax-benefit system with two-child limit and family premium " + "removal fully rolled out" +) + + +def stage() -> tuple[list[ExternalScore], list[dict]]: + scores: list[ExternalScore] = [] + for row in load_staged_uk("uk_ifs"): + unknown = set(row) - _KNOWN_FIELDS + if unknown: + raise ValueError(f"uk_ifs: unhandled fields {sorted(unknown)}") + conds_in = dict(row["conditions"]) + unknown_c = set(conds_in) - set(_CONDITION_KEYS) + if unknown_c: + raise ValueError(f"uk_ifs: unmapped conditions {sorted(unknown_c)}") + + geography, geo_note = normalize_geography_uk(conds_in.pop("geography")) + conditions = {} + for k, v in conds_in.items(): + target = _CONDITION_KEYS[k] + if target and v is not None and k != "fy": + conditions[target] = v + conditions["geography"] = geography + if geo_note: + conditions["geography_note"] = geo_note + if "fy" in conds_in: + period, fy_norm = parse_fy(conds_in["fy"]) + conditions["fy"] = fy_norm + else: + period = row["period"] # calendar-year series rows + + baseline_verbatim = conds_in.get("baseline") + if baseline_verbatim is not None: + if baseline_verbatim != _STEADY_STATE_VERBATIM: + raise ValueError( + f"uk_ifs: unregistered baseline {baseline_verbatim!r}" + ) + conditions["horizon"] = "steady_state" + + hint = row.get("reform_hint") + if hint: + reform = ReformRef( + framework="policy_ref", + reform={"policy": f"uk_ifs:{slugify(hint)}"}, + baseline=( + STEADY_STATE_BASELINE if baseline_verbatim else None + ), + ) + conditions["measure"] = hint + conditions = with_baseline_condition(conditions, reform) + elif baseline_verbatim: + # Level claim of the steady-state world itself. + reform = ReformRef( + framework="policy_ref", reform=dict(STEADY_STATE_BASELINE) + ) + else: + reform = BASELINE + + metric_name = row.get("metric") or row["proposed_metric"] + if metric_name == "poverty_count_change": + metric = Metric.POVERTY_COUNT_CHANGE + unit = _COUNT_UNITS[row["unit_concept"]] + else: + metric, unit = _METRICS[metric_name] + if metric is Metric.SHARE_OF_SPENDING_TO_GROUP: + # The recipient group lives only in the column header + # ("Of which transfers to households with children in + # poverty" / "…poorest 40% not in poverty" / "…richest 60%") + # — identity-bearing, so it becomes a condition verbatim. + conditions["recipient_group"] = row["source_column"] + + publication = dict(row["publication"]) + if row.get("source_table"): + publication.setdefault("table", row["source_table"]) + for note in ("normalization", "sign_convention", "geography_note"): + if row.get(note): + publication[note] = row[note] + for k in _PUBLICATION_NOTES: + if conds_in.get(k): + publication[k] = conds_in[k] + + scores.append( + ExternalScore( + source="ifs", + source_model=row["source_model"], + metric=metric, + unit_concept=unit, + period=period, + time_basis=TimeBasis(row["time_basis"]), + value=row["value"], + conditions=conditions, + reform=reform, + calibration_relationship=CalibrationRelationship( + row["calibration_relationship"] + ), + source_column=row.get("source_column"), + publication=publication, + value_kind=( + "gbp" if unit in ( + UnitConcept.GBP, UnitConcept.GBP_PER_YEAR, + ) else "share" if unit in ( + UnitConcept.SHARE, UnitConcept.PERCENT, + UnitConcept.PERCENTAGE_POINTS, + ) else "count" + ), + ) + ) + return finish(scores, "uk_ifs"), [] + + +def ingest(db_path: Path) -> dict: + scores, _ = stage() + reform_rows = sum(1 for s in scores if s.reform is not BASELINE) + db = ScorecardDB(db_path) + n = db.upsert_scores(scores) + db.set_lane( + "ifs-taxben", + "ingested", + f"{n} TAXBEN claims: absolute-AHC child-poverty series, " + f"Green-Budget-2025 options block ({reform_rows} reform-keyed " + "rows incl. the −540k steady-state two-child-limit leg of the " + "pentagon), threshold-freeze revenue rows; options baseline = " + "registered ifs_2cl_fp_removal_rolled_out world; TAXBEN is " + "entitlements-basis (full take-up) — registry axis on every " + "poverty comparison", + "2026-08-02", + ) + db.close() + return {"scores": n, "reform_rows": reform_rows} + + +if __name__ == "__main__": + import sys + + out = Path(sys.argv[1] if len(sys.argv) > 1 else "data/scorecard.db") + print(json.dumps(ingest(out), indent=1)) diff --git a/scorecard_db/ingest_uk_obr.py b/scorecard_db/ingest_uk_obr.py new file mode 100644 index 0000000..b57ca20 --- /dev/null +++ b/scorecard_db/ingest_uk_obr.py @@ -0,0 +1,445 @@ +"""Ingest the OBR staged claims (2026-08-02 UK harvest). + +Two families: + +1. **Policy measures database** (24,304 rows, source_model + hmt_scorecard_obr_database): every scorecard measure since 1970 × + fiscal years — reform scores. Each measure title becomes a policy_ref + world (uk_obr_measure::) with the verbatim title in + conditions["measure"]; scored against current law at announcement + (null baseline — JCT parity), the event riding conditions. + sign_convention is uniform positive_gain_to_exchequer. + +2. **EFO supplementary tables** (1,254 rows, source_model + obr_efo_forecast): Mar-2026 receipts levels (3.4 accrued / 3.8 cash) + and threshold-freeze analysis (3.17 revenue re-estimates → + policy_ref worlds; 3.18 taxpayer counts; 3.19 parameter levels — + scenario rides conditions verbatim, basis "unstated" per the tables' + own missing markers), plus Nov-2025 welfare spending (4.9/4.11 — the + Mar-2026 expenditure tables are still in the fetch queue; + conditions["data_vintage"] carries the split). Table id, 4.9 + welfare-cap section, and 4.11 parent line are reconstructed as + conditions — the same labels recur across tables/sections. + +Ledger routing: the 133 EFO outturn columns (2024-25 receipts / +expenditure outturn) are admin facts → returned for the Ledger staging +file, not external_scores. + +calibration_relationship: forecast rows whose line matches a series +populace-UK literally consumes are reclassed consumed_as_target. The +consumed sets were read from policyengine-uk-data +targets/sources/obr.py THIS session (2026-08-02): income tax gross + +NICs classes from Table 3.4, VAT/fuel duties/CGT/SDLT from 3.9 (staged +here from the 3.8 cash-receipts summary — same head, table noted), +council tax from 4.1 (staged from 3.8), and the twelve Table 4.9 welfare +lines. Everything else stays held_out. +""" + +from __future__ import annotations + +import json +import re +from pathlib import Path + +from .db import ScorecardDB +from .harvest import finish, policy_ref +from .models import ( + BASELINE, + CalibrationRelationship, + ExternalScore, + Metric, + TimeBasis, + UnitConcept, +) +from .uk import ( + ledger_row, + load_staged_uk, + measure_slug, + normalize_geography_uk, + parse_fy, +) + +_KNOWN_FIELDS = frozenset( + { + "source", "metric", "proposed_metric", "unit_concept", + "proposed_unit", "normalization", "period", "time_basis", + "conditions", "reform_hint", "calibration_relationship", + "source_model", "source_column", "source_table", "value", + "value_raw", "publication", "status", + } +) + +_MEASURE_CONDITIONS = { + "geography": "geography", + "fy": "fy", + "fiscal_event": "fiscal_event", + "tax_head": "tax_head", + "spending_head": "spending_head", + "impact_channel": "impact_channel", + "basis": "basis", + "costing_phase": "costing_phase", + "sign_convention": "sign_convention", +} +_EFO_CONDITIONS = { + "geography": "geography", + "fy": "fy", + "basis": "basis", + "line_item": "line_item", + "section": "section", + "note": "note", + "domain": "domain", +} + +_METRICS = { + "revenue_change": Metric.REVENUE_CHANGE, + "benefit_cost": Metric.BENEFIT_COST, + "exchequer_impact": Metric.EXCHEQUER_IMPACT, + "revenue_level": Metric.REVENUE_LEVEL, + "policy_parameter_level": Metric.POLICY_PARAMETER_LEVEL, + "taxpayer_count": Metric.TAXPAYER_COUNT, +} + +# Consumed line matching (read from policyengine-uk-data +# targets/sources/obr.py this session). Receipts heads are matched on +# revenue_level line_items in the 3.4/3.8 staged tables; welfare lines on +# 4.9 benefit_cost line_items after stripping trailing footnote digits. +_CONSUMED_RECEIPTS = { + "Income tax (gross of tax credits)": "obr/income_tax (Table 3.4)", + "National insurance contributions": "obr/ni (Table 3.9 cash head)", + "Value added tax": "obr/vat (Table 3.9 cash head)", + "Fuel duties": "obr/fuel_duties (Table 3.9 cash head)", + "Capital gains tax": "obr/capital_gains_tax (Table 3.9 cash head)", + "Stamp duty land tax": "obr/sdlt (Table 3.9 cash head)", + "Council tax": "obr council-tax lines (Table 4.1)", + "Class 1 Employee NICs": "obr NICs class parse (Table 3.4)", + "Class 1 Employer NICs": "obr NICs class parse (Table 3.4)", + "Class 4 and Class 2 Self employed NICs": + "obr NICs class parse (Table 3.4)", + "Class 2 and Class 4 Self employed NICs": + "obr NICs class parse (Table 3.4)", +} +_CONSUMED_WELFARE = { + # (label after footnote-stripping, 4.9 section) -> target. pe-uk-data + # matches labels in workbook order; UC appears in BOTH sections and + # feeds two distinct targets. + ("Housing benefit (not on JSA)", "welfare_cap"): "obr/housing_benefit", + ( + "Disability living allowance and personal independence payments", + "welfare_cap", + ): "obr/pip (combined DLA+PIP line)", + ("Incapacity benefits", "welfare_cap"): "obr/esa", + ("Attendance allowance", "welfare_cap"): "obr/attendance_allowance", + ("Pension credit", "welfare_cap"): "obr/pension_credit", + ("Carer's allowance", "welfare_cap"): "obr/carers_allowance", + ("Statutory maternity pay", "welfare_cap"): + "obr/statutory_maternity_pay", + ("Winter fuel payment", "welfare_cap"): "obr/winter_fuel_allowance", + ("Universal credit", "welfare_cap"): "obr/universal_credit_in_cap", + ("Child benefit", "welfare_cap"): "obr/child_benefit", + ("Universal credit", "outside_welfare_cap"): + "obr/universal_credit_outside_cap", + ("State pension", "outside_welfare_cap"): "obr/state_pension", + ("Jobseeker's allowance", "outside_welfare_cap"): + "obr/jobseekers_allowance", +} +_CONSUMED_BASIS = ( + "policyengine-uk-data targets/sources/obr.py parses this EFO series " + "into {target} (read 2026-08-02){vintage}; agreement is discipline, " + "not validation" +) +_WELFARE_VINTAGE_CAVEAT = ( + " — populace consumes the Mar-2026 EFO successor of this series; the " + "staged 4.9 vintage is Nov-2025 (Mar-2026 expenditure tables pending " + "fetch), same series one vintage earlier" +) + + +def _strip_footnote(label: str) -> str: + return re.sub(r"\d+$", "", label.strip()).strip() + + +def _consumed_target(row: dict, section: str | None) -> str | None: + """Target name when populace-UK consumes this EFO line, else None.""" + if row["source_model"] != "obr_efo_forecast": + return None + line = _strip_footnote(row["conditions"].get("line_item", "")) + table = (row.get("source_table") or "").split(":")[0] + metric = row.get("metric") or row.get("proposed_metric") + if metric == "revenue_level" and table in ("3.4", "3.8"): + return _CONSUMED_RECEIPTS.get(line) + if metric == "benefit_cost" and table == "4.9": + return _CONSUMED_WELFARE.get((line, section)) + return None + + +_EFO_VINTAGES = { + "March 2026": "march_2026_efo", + "November 2025": "november_2025_efo", +} + + +def _efo_vintage(row: dict) -> str: + title = row["publication"].get("title", "") + for needle, slug in _EFO_VINTAGES.items(): + if needle in title: + return slug + raise ValueError(f"uk_obr: unrecognized EFO vintage in {title!r}") + + +def _derive_49_sections(rows: list[dict]) -> dict[int, str]: + """Reconstruct Table 4.9's welfare-cap / outside-cap sections (the + staging dropped the marker; the same subtotal labels recur in both). + Workbook order is preserved: the section flips after each section + total.""" + sections: dict[int, str] = {} + current, prev_line = "welfare_cap", None + boundary = { + "Total welfare cap": "outside_welfare_cap", + "Total welfare outside the welfare cap": "total", + } + for i, row in enumerate(rows): + if row.get("source_model") != "obr_efo_forecast": + continue + if not (row.get("source_table") or "").startswith("4.9"): + continue + line = row["conditions"]["line_item"] + if line != prev_line and prev_line in boundary: + current = boundary[prev_line] + sections[i] = current + prev_line = line + return sections + + +_411_GROUPS = frozenset({"Children", "Working-age", "Pensioner"}) + + +def _derive_411_parents(rows: list[dict]) -> dict[int, str]: + """Table 4.11 nests Children/Working-age/Pensioner group rows under + each spending category (Disability spending, DLA, PIP, totals, …); + the staging kept only the group label, so the same label recurs under + several parents. Workbook order is preserved: a group row's parent is + the nearest preceding non-group line.""" + parents: dict[int, str] = {} + parent = None + for i, row in enumerate(rows): + if row.get("source_model") != "obr_efo_forecast": + continue + if not (row.get("source_table") or "").startswith("4.11"): + continue + line = row["conditions"]["line_item"] + if line in _411_GROUPS: + if parent is None: + raise ValueError("uk_obr: 4.11 group row before any parent") + parents[i] = parent + else: + parent = line + return parents + + +def _component_runs(rows: list[dict]) -> dict[int, int]: + """The measures database scores one titled measure as several + component series — usually one per tax/spending head, sometimes two + under the same abbreviated head (Budget 2015 #2's non-dom measure has + two 'Stamp duty' components). The staging preserves workbook order: + each component is one consecutive run of increasing fiscal years, so + a year reset inside an unchanged (event, title, head) marks the next + component. The measure title stays the reform world (the database's + own unit of identity); the component seq is a conditions axis. + Returns staged-row-index -> component seq (1-based) per that key.""" + seq: dict[int, int] = {} + runs_seen: dict[tuple, int] = {} + prev_key, prev_start = None, None + for i, row in enumerate(rows): + if row["source_model"] != "hmt_scorecard_obr_database": + continue + c = row["conditions"] + key = ( + c["fiscal_event"], + row["reform_hint"], + c.get("tax_head") or c.get("spending_head"), + ) + start, _ = parse_fy(c["fy"]) + new_run = key != prev_key or ( + prev_start is not None and start <= prev_start + ) + if new_run: + runs_seen[key] = runs_seen.get(key, 0) + 1 + seq[i] = runs_seen[key] + prev_key, prev_start = key, start + return seq + + +def stage() -> tuple[list[ExternalScore], list[dict]]: + scores: list[ExternalScore] = [] + ledger: list[dict] = [] + staged_rows = load_staged_uk("uk_obr") + component = _component_runs(staged_rows) + sections49 = _derive_49_sections(staged_rows) + parents411 = _derive_411_parents(staged_rows) + for i, row in enumerate(staged_rows): + unknown = set(row) - _KNOWN_FIELDS + if unknown: + raise ValueError(f"uk_obr: unhandled fields {sorted(unknown)}") + conds_in = dict(row["conditions"]) + basis = conds_in.get("basis") + if basis == "outturn": + derived = {} + if i in sections49: + derived["section"] = sections49[i] + if i in parents411: + derived["parent_line"] = parents411[i] + ledger.append( + ledger_row( + "uk_obr", row, + "OBR EFO outturn column — admin receipts/expenditure " + "fact (ledger routing rule, Max 2026-08-02)", + derived=derived or None, + ) + ) + continue + + is_measure = row["source_model"] == "hmt_scorecard_obr_database" + key_map = _MEASURE_CONDITIONS if is_measure else _EFO_CONDITIONS + unknown_c = set(conds_in) - set(key_map) + if unknown_c: + raise ValueError(f"uk_obr: unmapped conditions {sorted(unknown_c)}") + + period, fy_norm = parse_fy(conds_in["fy"]) + geography, geo_note = normalize_geography_uk(conds_in["geography"]) + conditions = { + key_map[k]: v + for k, v in conds_in.items() + if v is not None and k not in ("fy", "geography") + } + conditions["fy"] = fy_norm + conditions["geography"] = geography + if geo_note: + conditions["geography_note"] = geo_note + if not is_measure: + # EFO table id is identity-bearing: the same head appears in + # 3.4 (accrued IT/NICs detail) and 3.8 (cash current + # receipts) with different values. So are the reconstructed + # 4.9 sections (the same subtotal labels recur in the + # welfare-cap and outside-cap blocks) and the EFO vintage + # (receipts staged from Mar-2026, expenditure from Nov-2025). + conditions["table"] = (row["source_table"] or "").split(":")[0] + if i in sections49: + conditions["section"] = sections49[i] + if i in parents411: + conditions["parent_line"] = parents411[i] + conditions["data_vintage"] = _efo_vintage(row) + + metric_name = row.get("metric") or row.get("proposed_metric") + metric = _METRICS[metric_name] + hint = row.get("reform_hint") + if is_measure: + if not hint: + raise ValueError("uk_obr: measures row without reform_hint") + reform = policy_ref( + measure_slug( + "uk_obr_measure", conds_in["fiscal_event"], hint + ) + ) + conditions["measure"] = hint + if component[i] > 1: + conditions["component_seq"] = str(component[i]) + elif hint and metric is Metric.REVENUE_CHANGE: + # 3.17: latest re-estimates of previously announced personal + # tax measures — reform worlds keyed by title at the EFO + # re-estimate vintage. + reform = policy_ref( + measure_slug("uk_obr_measure", "efo_march_2026", hint) + ) + conditions["measure"] = hint + else: + if hint: + raise ValueError( + f"uk_obr: unexpected reform_hint on {metric_name} row" + ) + reform = BASELINE + + unit = ( + UnitConcept.PERSONS + if metric is Metric.TAXPAYER_COUNT + else UnitConcept.GBP + ) + target = _consumed_target(row, sections49.get(i)) + relationship = ( + CalibrationRelationship.CONSUMED_AS_TARGET + if target + else CalibrationRelationship(row["calibration_relationship"]) + ) + publication = dict(row["publication"]) + if row.get("source_table"): + publication.setdefault("table", row["source_table"]) + if target: + publication["calibration_basis"] = _CONSUMED_BASIS.format( + target=target, + vintage=( + _WELFARE_VINTAGE_CAVEAT + if conditions.get("table") == "4.9" + else "" + ), + ) + + scores.append( + ExternalScore( + source="obr", + source_model=row["source_model"], + metric=metric, + unit_concept=unit, + period=period, + time_basis=TimeBasis(row["time_basis"]), + value=row["value"], + conditions=conditions, + reform=reform, + calibration_relationship=relationship, + source_column=row.get("source_column"), + publication=publication, + value_kind="count" if unit is UnitConcept.PERSONS else "gbp", + status=row.get("status", "ok"), + ) + ) + return finish(scores, "uk_obr"), ledger + + +def ingest(db_path: Path) -> dict: + scores, ledger = stage() + measures = sum( + 1 for s in scores if s.source_model == "hmt_scorecard_obr_database" + ) + consumed = sum( + 1 + for s in scores + if s.calibration_relationship + is CalibrationRelationship.CONSUMED_AS_TARGET + ) + db = ScorecardDB(db_path) + n = db.upsert_scores(scores) + db.set_lane( + "obr-measures", + "ingested", + f"{measures} policy-measures-database claims (84 fiscal events " + "since 1970, reform-keyed per measure title, " + "positive_gain_to_exchequer verbatim)", + "2026-08-02", + ) + db.set_lane( + "obr-welfare", + "ingested", + f"{n - measures} EFO Mar-2026 claims (receipts 3.4/3.8, welfare " + f"4.9/4.11, threshold analysis 3.17-3.19); {consumed} " + "consumed_as_target (exact pe-uk-data target lines, " + "targets/sources/obr.py); " + f"{len(ledger)} outturn rows routed to Ledger staging", + "2026-08-02", + ) + db.close() + return {"scores": n, "ledger": len(ledger), "consumed": consumed} + + +if __name__ == "__main__": + import sys + + out = Path(sys.argv[1] if len(sys.argv) > 1 else "data/scorecard.db") + print(json.dumps(ingest(out), indent=1)) diff --git a/scorecard_db/ingest_uk_rf.py b/scorecard_db/ingest_uk_rf.py new file mode 100644 index 0000000..4abf65e --- /dev/null +++ b/scorecard_db/ingest_uk_rf.py @@ -0,0 +1,252 @@ +"""Ingest the Resolution Foundation staged claims (2026-08-02 UK harvest). + +71 rows, the third UK microsim lineage (IPPR Tax Benefit Model on +FRS/HBAI 2023-24): Living Standards Outlook 2026 income-growth and +poverty projections (incl. the −420k-children two-child-limit leg of +the pentagon), the Stairway-to-headroom Budget-2025 decile block, the +April-2026 uprating parameter set (pure policyengine-uk parameter +checks — the campaign's uprating_check joins here), and UC-rebalancing +analysis. + +Mapping notes: +- Staged metric names map onto the shared vocabulary; where a staged + name is absorbed into a broader Metric, conditions["source_metric"] + keeps the original name (traceability + collision-proofing). +- Rows RF flags as citations of government figures (HMT scorecard, DWP + IA) keep note verbatim in publication — they are RF's published + citations, cross-checkable against the first-hand uk_hmt lane. +- The single inflation-rate-gap row (energy-price-cap scenario, a price + -index claim with no tax/benefit content) is deliberately dropped and + tallied. +- reform_hint rows become policy_ref worlds (uk_rf:); several + hints carry the RF-verified policyengine-uk parameter mapping in the + hint text verbatim. +""" + +from __future__ import annotations + +import json +from pathlib import Path + +from .db import ScorecardDB +from .harvest import finish, policy_ref +from .models import ( + BASELINE, + CalibrationRelationship, + ExternalScore, + Metric, + TimeBasis, + UnitConcept, +) +from .uk import ( + load_staged_uk, + normalize_geography_uk, + parse_fy, + parse_fy_window, + slugify, + uk_value_kind, +) + +_KNOWN_FIELDS = frozenset( + { + "source", "metric", "proposed_metric", "unit_concept", + "proposed_unit", "value", "value_raw", "value_kind", "note", + "local_artifact", "attribution", "period", "time_basis", "conditions", + "reform_hint", "calibration_relationship", "source_model", + "source_column", "publication", "status", + } +) + +_CONDITION_KEYS = { + "geography": "geography", + "fy": "fy", + "income_concept": "income_concept", + "equivalisation": "equivalisation", + "unit_population": "unit_population", + "scenario": "scenario", + "growth_window": "growth_window", + "benefit": "program", + "income_group": "income_group", + "poverty_line": "poverty_line", + "impact_year": "impact_year", + "measure_set": "measure_set", + "income_measure": "income_measure", + "price_base": "price_base", + "uprating_event": "uprating_event", + "component": "component", + "change_window": "change_window", + "measure": "measure_note", + "percentile": "percentile", +} + +# staged metric -> (Metric, unit, keep source_metric condition?) +_METRICS = { + "poverty_rate": (Metric.POVERTY_RATE, UnitConcept.SHARE, False), + "poverty_rate_change": ( + Metric.POVERTY_RATE_CHANGE, UnitConcept.SHARE, False, + ), + "poverty_count": ( + Metric.POVERTY_COUNT, UnitConcept.CHILDREN_UNDER_18, False, + ), + "poverty_count_change": ( + Metric.POVERTY_COUNT_CHANGE, UnitConcept.CHILDREN_UNDER_18, False, + ), + "revenue_change": (Metric.REVENUE_CHANGE, UnitConcept.GBP, False), + "real_income_growth_pct": ( + Metric.REAL_INCOME_GROWTH, UnitConcept.SHARE, False, + ), + "real_income_growth_pct_pa": ( + Metric.REAL_INCOME_GROWTH, UnitConcept.SHARE, True, + ), + "benefit_uprating_pct": ( + Metric.BENEFIT_UPRATING, UnitConcept.SHARE, False, + ), + "avg_income_change": ( + Metric.AVG_CHANGE_HOUSEHOLD_NET_INCOME, + UnitConcept.GBP_PER_HOUSEHOLD, + False, + ), + "avg_gain_per_benefiting_family": ( + Metric.AVG_CHANGE_HOUSEHOLD_NET_INCOME, + UnitConcept.GBP_PER_FAMILY, + True, + ), + "avg_gain_per_unit": ( + Metric.AVG_CHANGE_HOUSEHOLD_NET_INCOME, + UnitConcept.GBP_PER_FAMILY, + True, + ), + "reform_fiscal_cost": ( + Metric.EXCHEQUER_IMPACT, UnitConcept.GBP, True, + ), + "share_gaining": (Metric.SHARE_GAINING, UnitConcept.SHARE, False), + "share_losing": (Metric.SHARE_LOSING, UnitConcept.SHARE, False), + "benefiting_family_count": ( + Metric.FAMILIES_AFFECTED_COUNT, UnitConcept.FAMILIES, True, + ), + "benefit_rate_weekly": ( + Metric.POLICY_PARAMETER_LEVEL, UnitConcept.GBP_PER_WEEK, True, + ), + "benefit_rate_gap_weekly": ( + Metric.POLICY_PARAMETER_LEVEL, UnitConcept.GBP_PER_WEEK, True, + ), + "real_value_change_pct": ( + Metric.POLICY_PARAMETER_LEVEL, UnitConcept.SHARE, True, + ), +} + +DROPPED_METRICS = frozenset({"inflation_rate_gap_pp"}) + + +def stage() -> tuple[list[ExternalScore], list[dict], int]: + scores: list[ExternalScore] = [] + dropped = 0 + for row in load_staged_uk("uk_resolution_foundation"): + unknown = set(row) - _KNOWN_FIELDS + if unknown: + raise ValueError(f"uk_rf: unhandled fields {sorted(unknown)}") + metric_name = row.get("metric") or row["proposed_metric"] + if metric_name in DROPPED_METRICS: + dropped += 1 + continue + conds_in = dict(row["conditions"]) + unknown_c = set(conds_in) - set(_CONDITION_KEYS) + if unknown_c: + raise ValueError(f"uk_rf: unmapped conditions {sorted(unknown_c)}") + + geography, geo_note = normalize_geography_uk(conds_in.pop("geography")) + conditions = { + _CONDITION_KEYS[k]: v + for k, v in conds_in.items() + if v is not None and k != "fy" + } + conditions["geography"] = geography + if geo_note: + conditions["geography_note"] = geo_note + + period_start = period_end = None + fy_label = conds_in["fy"] + if "to" in fy_label: + period_start, period_end, fy_norm = parse_fy_window(fy_label) + period = period_end + conditions["fy"] = fy_norm + conditions["window_kind"] = "total" + else: + period, fy_norm = parse_fy(fy_label) + conditions["fy"] = fy_norm + + metric, unit, keep_name = _METRICS[metric_name] + if keep_name: + conditions["source_metric"] = metric_name + if row.get("attribution"): + # RF quoting a government figure is a different claim than + # RF's own model estimate of the same statistic (the −420k + # RF vs −450k govt two-child pair) — identity-bearing. + conditions["attribution"] = row["attribution"] + + hint = row.get("reform_hint") + if hint: + reform = policy_ref(f"uk_rf:{slugify(hint)}") + conditions["measure"] = hint + else: + reform = BASELINE + + publication = dict(row["publication"]) + for note in ("note", "local_artifact"): + if row.get(note): + publication[note] = row[note] + + scores.append( + ExternalScore( + source="resolution_foundation", + source_model=row["source_model"], + metric=metric, + unit_concept=unit, + period=period, + time_basis=TimeBasis(row["time_basis"]), + value=row["value"], + conditions=conditions, + reform=reform, + calibration_relationship=CalibrationRelationship( + row["calibration_relationship"] + ), + source_column=row.get("source_column"), + publication=publication, + value_kind=uk_value_kind(row.get("value_kind"), unit.value), + status=row.get("status", "ok"), + period_start=period_start, + period_end=period_end, + ) + ) + return finish(scores, "uk_rf"), [], dropped + + +def ingest(db_path: Path) -> dict: + scores, _, dropped = stage() + reform_rows = sum(1 for s in scores if s.reform is not BASELINE) + uprating = sum( + 1 for s in scores if s.metric is Metric.BENEFIT_UPRATING + ) + db = ScorecardDB(db_path) + n = db.upsert_scores(scores) + db.set_lane( + "rf-outlook", + "ingested", + f"{n} Resolution Foundation claims (IPPR Tax Benefit Model on " + "FRS/HBAI 2023-24): LSO 2026 poverty projections incl. the −420k " + "two-child pentagon leg, Budget-2025 decile block, April-2026 " + f"uprating set ({uprating} parameter-check rows — campaign " + f"uprating_check joins here); {reform_rows} reform-keyed rows; " + f"{dropped} price-index-only row dropped (out of tax/benefit " + "scope, tallied)", + "2026-08-02", + ) + db.close() + return {"scores": n, "reform_rows": reform_rows, "dropped": dropped} + + +if __name__ == "__main__": + import sys + + out = Path(sys.argv[1] if len(sys.argv) > 1 else "data/scorecard.db") + print(json.dumps(ingest(out), indent=1)) diff --git a/scorecard_db/ingest_uk_ukmod_jrf.py b/scorecard_db/ingest_uk_ukmod_jrf.py new file mode 100644 index 0000000..82ab9c1 --- /dev/null +++ b/scorecard_db/ingest_uk_ukmod_jrf.py @@ -0,0 +1,333 @@ +"""Ingest the UKMOD + JRF staged claims (2026-08-02 UK harvest). + +Two sources share one staging file (and this adapter); each row's +staged ``source`` (ukmod | jrf) is preserved. + +**UKMOD** (CeMPA): +- Country Report 2023-2030 Section-4 validation block: caseloads, + expenditure, tax revenue, distribution (4.7) and poverty (4.8) with + UKMOD-simulated / official-estimate / input-data / HBAI columns side + by side — conditions["series"] distinguishes sides. Official cells + are second-hand DWP/HMRC/OBR citations and deliberately stay + scorecard-side under source ukmod (the block's value IS the + side-by-side; first-hand admin outturns live in the Ledger via the + DWP/HMRC lanes, not here). +- CeMPA WP 3/26 Autumn-Budget-2025 package assessment: scenario + base/reform/change rows — the package is one policy_ref world + (uk_autumn_budget_2025_package_cempa) scored against pre-package + current law at announcement. + +**JRF**: UK Poverty 2026 workbook series (unrounded headline AHC +poverty, persistent poverty, thresholds, medians) — permanent poverty +holdouts. The 88 MIS weekly-budget cells are deliberately DROPPED +(tallied): MIS budget standards are focus-group budgets, not +tax/benefit-model outputs PE can check; they stay recoverable in the +vendored staging. + +Gotchas encoded here: income_concept is load-bearing (UKMOD validation +poverty = BHC, JRF headline = AHC); staged value_kind "currency_gbp" +normalizes to gbp; JRF's basis weekly|annual is an AMOUNT basis and is +remapped to conditions["amount_basis"] (basis keeps its UK +outturn/forecast semantics); 3-year-average persistent-poverty windows +become period_start/period_end with window_kind=annual_average. +""" + +from __future__ import annotations + +import json +from pathlib import Path + +from .db import ScorecardDB +from .harvest import finish, merge_republications, policy_ref +from .models import ( + BASELINE, + CalibrationRelationship, + ExternalScore, + Metric, + TimeBasis, + UnitConcept, +) +from .uk import ( + load_staged_uk, + normalize_geography_uk, + parse_fy, + parse_fy_window, + uk_value_kind, +) + +_KNOWN_FIELDS = frozenset( + { + "source", "metric", "proposed_metric", "unit_concept", + "proposed_unit", "value", "value_raw", "value_kind", + "normalization", "parse_confidence", "period", "time_basis", + "conditions", "reform", "reform_hint", "calibration_relationship", + "source_model", "source_column", "source_table", "publication", + "status", "official_sources_note", + } +) + +_CONDITION_KEYS = { + "geography": "geography", + "fy": "fy", + "series": "series", + "program": "program", + "forecast_note": None, # table-level note -> publication + "income_concept": "income_concept", + "ukmod_variable": "ukmod_variable", + "subgroup": "subgroup", + "count_unit": "count_unit", + "poverty_line": "poverty_line", + "scenario": "scenario", + "income_definition": "income_definition", + "equivalisation": "equivalisation", + "unit_of_analysis": "unit_of_analysis", + "coverage_note": None, # series-level note -> publication + "quintile": "quintile", + "household_type": "household_type", + "budget_component": "budget_component", + "priced": "priced", + "poverty_line_type": "poverty_line_type", + "family_type": "family_type", + "threshold": "threshold", + "income_concept_note": None, # -> publication + "basis": "amount_basis", # JRF weekly|annual — NOT outturn/forecast + "poverty_depth": "poverty_depth", + "measure": "poverty_duration_measure", + "period_window": None, # handled -> period_start/period_end + "subgroup_axis": "subgroup_axis", + "child_definition": "child_definition", +} +_PUBLICATION_NOTES = ("forecast_note", "coverage_note", "income_concept_note") + +# staged metric -> (Metric, unit chooser key) +_METRICS = { + "poverty_rate": Metric.POVERTY_RATE, + "poverty_count": Metric.POVERTY_COUNT, + "poverty_count_change": Metric.POVERTY_COUNT_CHANGE, + "persistent_poverty_rate": Metric.PERSISTENT_POVERTY_RATE, + "benefit_cost": Metric.BENEFIT_COST, + "caseload": Metric.CASELOAD, + "revenue_change": Metric.REVENUE_CHANGE, + "tax_revenue": Metric.REVENUE_LEVEL, + "taxpayer_count": Metric.TAXPAYER_COUNT, + "government_revenue": Metric.REVENUE_LEVEL, + "government_expenditure": Metric.EXPENDITURE_LEVEL, + "expenditure_change": Metric.EXPENDITURE_CHANGE, + "net_fiscal_impact": Metric.EXCHEQUER_IMPACT, + "net_fiscal_impact_per_capita": Metric.EXCHEQUER_IMPACT, + "median_equivalised_disposable_income": Metric.MEDIAN_INCOME, + "mean_equivalised_disposable_income": Metric.MEAN_INCOME, + "median_income": Metric.MEDIAN_INCOME, + "income_share": Metric.INCOME_SHARE, + "gini_coefficient": Metric.GINI_COEFFICIENT, + "gini_coefficient_change": Metric.GINI_COEFFICIENT_CHANGE, + "s80_s20_ratio": Metric.S80_S20_RATIO, + "s80_s20_ratio_change": Metric.S80_S20_RATIO_CHANGE, + "poverty_threshold": Metric.POVERTY_THRESHOLD, +} + +_UNIT_BY_PROPOSED = { + "gbp": UnitConcept.GBP, + "gbp_per_week": UnitConcept.GBP_PER_WEEK, + "gbp_per_month": UnitConcept.GBP_PER_MONTH, + "gbp_per_year": UnitConcept.GBP_PER_YEAR, + "gbp_per_person": UnitConcept.GBP_PER_PERSON, + "gini_0_1": UnitConcept.INDEX_0_1, + "gini_points_0_100": UnitConcept.INDEX_POINTS_0_100, + "ratio": UnitConcept.RATIO, +} +_UNIT_BY_STAGED = { + "persons": UnitConcept.PERSONS, + "families": UnitConcept.FAMILIES, + "households": UnitConcept.HOUSEHOLDS, +} + +AB2025_PACKAGE = policy_ref("uk_autumn_budget_2025_package_cempa") + +DROPPED_METRICS = frozenset({"minimum_income_standard_budget"}) + + +def _unit_for(row: dict, metric: Metric) -> UnitConcept: + if metric in ( + Metric.POVERTY_RATE, + Metric.PERSISTENT_POVERTY_RATE, + Metric.INCOME_SHARE, + ): + return UnitConcept.SHARE + if row.get("unit_concept"): + return _UNIT_BY_STAGED[row["unit_concept"]] + proposed = row.get("proposed_unit") + if proposed: + unit = _UNIT_BY_PROPOSED[proposed] + # JRF threshold/median tables publish bare-gbp cells whose + # weekly/annual basis rides the staged basis flag. + if unit is UnitConcept.GBP and row["conditions"].get("basis"): + return { + "weekly": UnitConcept.GBP_PER_WEEK, + "annual": UnitConcept.GBP_PER_YEAR, + }[row["conditions"]["basis"]] + return unit + if row.get("value_kind") in ("currency_gbp", "gbp"): + return UnitConcept.GBP + raise ValueError(f"uk_ukmod_jrf: no unit for row {row['source_column']!r}") + + +def stage() -> tuple[list[ExternalScore], list[dict], int]: + scores: list[ExternalScore] = [] + dropped = 0 + for row in load_staged_uk("uk_ukmod_jrf"): + unknown = set(row) - _KNOWN_FIELDS + if unknown: + raise ValueError( + f"uk_ukmod_jrf: unhandled fields {sorted(unknown)}" + ) + metric_name = row.get("metric") or row["proposed_metric"] + if metric_name in DROPPED_METRICS: + dropped += 1 + continue + conds_in = dict(row["conditions"]) + unknown_c = set(conds_in) - set(_CONDITION_KEYS) + if unknown_c: + raise ValueError( + f"uk_ukmod_jrf: unmapped conditions {sorted(unknown_c)}" + ) + + geography, geo_note = normalize_geography_uk(conds_in.pop("geography")) + conditions = {} + for k, v in conds_in.items(): + target = _CONDITION_KEYS[k] + if target and v is not None and k != "fy": + conditions[target] = v + conditions["geography"] = geography + if geo_note: + conditions["geography_note"] = geo_note + + period_start = period_end = None + window_label = conds_in.get("period_window") + if window_label: + period_start, period_end, fy_norm = parse_fy_window( + window_label.split(" (")[0] + ) + period = period_end + conditions["fy"] = fy_norm + conditions["window_kind"] = "annual_average" + else: + period, fy_norm = parse_fy(conds_in["fy"]) + conditions["fy"] = fy_norm + + scenario = conds_in.get("scenario") + if row.get("reform") is not None: + if row["reform"] != {"framework": "baseline"}: + raise ValueError( + f"uk_ukmod_jrf: unexpected reform {row['reform']}" + ) + if scenario is not None: + raise ValueError( + "uk_ukmod_jrf: baseline-reform row carries scenario" + ) + reform = BASELINE + else: + # CeMPA WP 3/26 package block: scenario base/reform/change. + if scenario == "baseline": + reform = BASELINE + elif scenario in ("reform", "reform_minus_baseline"): + reform = AB2025_PACKAGE + conditions["measure"] = row["reform_hint"] + else: + raise ValueError( + f"uk_ukmod_jrf: reform-block scenario {scenario!r}" + ) + + metric = _METRICS[metric_name] + unit = _unit_for(row, metric) + if metric_name == "net_fiscal_impact_per_capita": + unit = UnitConcept.GBP_PER_PERSON + + publication = dict(row["publication"]) + if row.get("source_table"): + publication.setdefault("table", row["source_table"]) + if row.get("normalization"): + publication["normalization"] = row["normalization"] + if row.get("official_sources_note"): + publication["official_sources_note"] = row[ + "official_sources_note" + ] + for k in _PUBLICATION_NOTES: + if conds_in.get(k): + publication[k] = conds_in[k] + + scores.append( + ExternalScore( + source=row["source"], + source_model=row.get("source_model"), + metric=metric, + unit_concept=unit, + period=period, + time_basis=TimeBasis(row["time_basis"]), + value=row["value"], + conditions=conditions, + reform=reform, + calibration_relationship=CalibrationRelationship( + row["calibration_relationship"] + ), + source_column=row.get("source_column"), + publication=publication, + value_kind=uk_value_kind(row.get("value_kind"), unit.value), + status=row.get("status", "ok"), + period_start=period_start, + period_end=period_end, + ) + ) + # JRF republishes the same statistic across workbook sheets (rounded + # overview vs unrounded headline series): one claim, two artifacts — + # keep the higher-precision cell, require rounding-consistency, and + # record the twin under publication["also_published"]. + def _decimals(s: ExternalScore) -> int: + text = repr(s.value) + return len(text.split(".")[1]) if "." in text else 0 + + scores = merge_republications( + scores, + "uk_ukmod_jrf", + precision=_decimals, + tolerance=lambda coarse: 0.5 * 10 ** -_decimals(coarse) + 1e-12, + ) + return finish(scores, "uk_ukmod_jrf"), [], dropped + + +def ingest(db_path: Path) -> dict: + scores, _, dropped = stage() + ukmod = sum(1 for s in scores if s.source == "ukmod") + jrf = sum(1 for s in scores if s.source == "jrf") + reform_rows = sum(1 for s in scores if s.reform is AB2025_PACKAGE) + db = ScorecardDB(db_path) + n = db.upsert_scores(scores) + db.set_lane( + "ukmod-stats", + "ingested", + f"{ukmod} UKMOD claims — Country Report 2023-2030 validation " + "block (simulated/official/input-data/HBAI series side by side; " + "take-up priors frozen since 2021 per their own §4.3 warning) + " + f"CeMPA 3/26 AB2025 package assessment ({reform_rows} " + f"reform-keyed rows); {jrf} JRF claims (unrounded AHC headline " + f"series, persistent poverty, MIS-adjacent thresholds); {dropped} " + "MIS weekly-budget cells deliberately dropped (focus-group budget " + "standards, not model-checkable — recoverable in vendored " + "staging)", + "2026-08-02", + ) + db.close() + return { + "scores": n, + "ukmod": ukmod, + "jrf": jrf, + "reform_rows": reform_rows, + "dropped_mis": dropped, + } + + +if __name__ == "__main__": + import sys + + out = Path(sys.argv[1] if len(sys.argv) > 1 else "data/scorecard.db") + print(json.dumps(ingest(out), indent=1)) diff --git a/scorecard_db/uk.py b/scorecard_db/uk.py new file mode 100644 index 0000000..0b4b657 --- /dev/null +++ b/scorecard_db/uk.py @@ -0,0 +1,247 @@ +"""Shared helpers for the 2026-08-02 UK-harvest adapters. + +Seven per-source adapters (ingest_uk_obr, ingest_uk_hmrc, ingest_uk_dwp, +ingest_uk_hmt, ingest_uk_ukmod_jrf, ingest_uk_ifs, ingest_uk_rf) read the +vendored staging under sources/harvest-uk-2026-08-02// (gzipped — +the OBR file alone is 36 MB plain) and map staged rows onto ExternalScore +under the same contract as the US harvest (scorecard_db/harvest.py), plus +three UK-specific rules: + +1. **Fiscal years.** UK FY runs Apr–Mar and the staging mixes START-year + ints (HMRC/OBR), END-year ints (DWP "FYE 2010"), and one defective + parse ("1999/00" → 1900). Adapters therefore RE-DERIVE period from the + verbatim fy label: period = FY START year (the pe-uk-data convention, + targets/sources/obr.py `_FY_COL_TO_YEAR`), and conditions["fy"] is the + normalized "2026-27" form. + +2. **Ledger routing (Max 2026-08-02).** Administrative caseload / + expenditure / receipts OUTTURN rows (DWP BECL outturns, HMRC outturn + statistics incl. provisional, OBR EFO outturn columns) are populace + CALIBRATION material: they go to the Ledger staging file + (data/ledger/uk_admin_outturns.jsonl), NEVER external_scores. Forecast + / projected rows are a model speaking and DO enter. Survey-outcome + statistics (HBAI poverty) are not admin outturn — they stay + scorecard-side as permanent holdouts. + +3. **Load-bearing conditions.** income_concept (BHC|AHC) + equivalisation + ride every distribution row; conditions["basis"] preserves the + source's own outturn/forecast designation on scorecard-side rows. +""" + +from __future__ import annotations + +import gzip +import hashlib +import json +import re +from pathlib import Path + +from .harvest import REPO +from .models import ExternalScore + +UK_HARVEST = REPO / "sources" / "harvest-uk-2026-08-02" +LEDGER_STAGING = REPO / "data" / "ledger" / "uk_admin_outturns.jsonl" + + +def load_staged_uk(source: str) -> list[dict]: + path = UK_HARVEST / source / "claims_staged.jsonl.gz" + if not path.exists(): + raise FileNotFoundError(f"staged claims missing: {path}") + with gzip.open(path, "rt") as f: + rows = [json.loads(line) for line in f if line.strip()] + if not rows: + raise ValueError(f"no staged rows in {path}") + return rows + + +# -- fiscal years ------------------------------------------------------- +_FY = re.compile(r"^(?:FYE\s*(\d{4}))$|^(\d{4})\s*[-/–]\s*(\d{2}|\d{4})$") + + +def parse_fy(label: str) -> tuple[int, str]: + """Verbatim UK fiscal-year label -> (start_year, normalized 'YYYY-YY'). + + 'FYE 2010' (year ending Mar 2010) -> (2009, '2009-10'); + '2026-27' / '2023/24' / '1999/00' / '1970-71' -> start-year keyed. + Non-contiguous spans are rejected — ranges go through parse_fy_window. + """ + m = _FY.match(label.strip()) + if not m: + raise ValueError(f"unparseable UK fiscal-year label: {label!r}") + if m.group(1): # FYE yyyy = FY (yyyy-1)–yyyy + start = int(m.group(1)) - 1 + else: + start = int(m.group(2)) + end_raw = m.group(3) + end2 = int(end_raw) % 100 + if end2 != (start + 1) % 100: + raise ValueError(f"non-contiguous fiscal-year label: {label!r}") + return start, f"{start}-{(start + 1) % 100:02d}" + + +def parse_fy_window(label: str) -> tuple[int, int, str]: + """'2025-26 to 2029-30' / '2021/22-2023/24' -> (2025, 2029, normalized). + + Returned bounds are FY START years for period_start/period_end.""" + parts = re.split(r"\s+to\s+|(?<=\d)\s*[-–]\s*(?=\d{4})", label.strip()) + if len(parts) != 2: + raise ValueError(f"unparseable fiscal-year window: {label!r}") + first, _ = parse_fy(parts[0]) + last, _ = parse_fy(parts[1]) + if last <= first: + raise ValueError(f"window end before start: {label!r}") + return first, last, f"{first}-{(first + 1) % 100:02d} to " + ( + f"{last}-{(last + 1) % 100:02d}" + ) + + +# -- geography ---------------------------------------------------------- +# Canonical UK geography slugs (COLLATION UK conventions: labels verbatim +# in spirit; normalized here only for case and note-stripping so +# cross-source queries join). Verbatim long labels keep their note in +# conditions["geography_note"] at the adapter's discretion. +_GEO = { + "uk": "UK", + "united kingdom": "UK", + "gb": "GB", + "great britain": "GB", + "england": "england", + "scotland": "scotland", + "wales": "wales", + "northern ireland": "northern_ireland", + "england_wales": "england_wales", + "england and wales": "england_wales", + "uk excluding northern ireland": "UK_excl_NI", + "uk excluding scotland": "UK_excl_scotland", + "north east": "north_east", + "north west": "north_west", + "yorkshire and the humber": "yorkshire_and_the_humber", + "east midlands": "east_midlands", + "west midlands": "west_midlands", + "east of england": "east_of_england", + "east": "east_of_england", # ONS region, abbreviated in UKMOD tables + "london": "london", + "south east": "south_east", + "south west": "south_west", +} + + +def normalize_geography_uk(geo: str) -> tuple[str, str | None]: + """Verbatim staged geography -> (canonical slug, note or None). + + IFS embeds scope notes in the label ("UK excluding Northern Ireland + (note verbatim: …)"); the note is split off so the slug joins.""" + raw = geo.strip() + note = None + m = re.match(r"^(.*?)\s*\((note verbatim:.*)\)$", raw, re.S) + if m: + raw, note = m.group(1).strip(), m.group(2) + slug = _GEO.get(raw.lower()) + if slug is None: + raise ValueError(f"unmapped UK geography: {geo!r}") + return slug, note + + +# -- reform slugs ------------------------------------------------------- +def slugify(text: str, max_len: int = 60) -> str: + """Deterministic readable slug for reform-hint titles. Truncated + slugs get a short hash of the full text so titles differing only in + their tail ("…by 1%" vs "…by 10%") can never share a world.""" + s = re.sub(r"[^a-z0-9]+", "_", text.lower()).strip("_") + if len(s) <= max_len: + return s + digest = hashlib.sha256(text.strip().encode()).hexdigest()[:6] + return f"{s[:max_len].rstrip('_')}_{digest}" + + +def measure_slug(prefix: str, event: str, title: str) -> str: + """Stable policy slug for a fiscal-event measure: readable prefix + + an 8-hex hash of the verbatim title (titles are long and near- + duplicated across events; the hash keeps identity exact while the + verbatim title rides conditions['measure']).""" + digest = hashlib.sha256(title.strip().encode()).hexdigest()[:8] + return f"{prefix}:{slugify(event, 24)}:{digest}" + + +# -- ledger routing ----------------------------------------------------- +def ledger_fact_id(source: str, staged: dict, derived: dict | None) -> str: + """Deterministic pre-agreed fact id for the populace/Ledger lane.""" + digest = hashlib.sha256( + json.dumps( + {"staged": staged, "derived": derived or {}}, + sort_keys=True, + separators=(",", ":"), + ).encode() + ).hexdigest()[:20] + return f"uk:{source}:{digest}" + + +def ledger_row( + source: str, staged: dict, reason: str, derived: dict | None = None +) -> dict: + """Wrap a staged admin-outturn row for the Ledger staging file: the + verbatim staged row plus routing provenance. `derived` carries + adapter-reconstructed context the staging dropped (e.g. OBR 4.9 + section — byte-identical subtotal cells recur across sections and + must not collapse to one fact). Scorecard rows that later reference + this fact do so via the fact id, never copies.""" + out = { + "fact_id": ledger_fact_id(source, staged, derived), + "source": source, + "routed_because": reason, + "staged": staged, + } + if derived: + out["derived"] = derived + return out + + +def write_ledger_staging(rows: list[dict], path: Path = LEDGER_STAGING) -> int: + """Write the Ledger handoff file (sorted by fact id — stable diffs).""" + path.parent.mkdir(parents=True, exist_ok=True) + rows = sorted(rows, key=lambda r: r["fact_id"]) + ids = [r["fact_id"] for r in rows] + dupes = {i for i in ids if ids.count(i) > 1} + if dupes: + raise ValueError(f"duplicate ledger fact ids: {sorted(dupes)[:5]}") + with path.open("w") as f: + for r in rows: + f.write(json.dumps(r, sort_keys=True) + "\n") + return len(rows) + + +# -- misc --------------------------------------------------------------- +def require_conditions(staged: dict, known: dict, source: str) -> dict: + """Map staged condition keys through `known` (staged key -> DB key), + failing loudly on anything unmapped. None-valued conditions are + dropped (absent means not applicable).""" + out = {} + for k, v in staged.items(): + if k not in known: + raise ValueError(f"{source}: unmapped condition {k!r}") + if v is None: + continue + if not isinstance(v, str): + v = json.dumps(v) + out[known[k]] = v + return out + + +def uk_value_kind(staged_kind: str | None, unit_value: str) -> str: + """Normalize staged value_kind ('currency_gbp'/'gbp'/'usd' drift) to + the DB convention: gbp for currency, else count/share as staged.""" + if staged_kind in ("currency_gbp", "gbp", "usd"): + return "gbp" + if staged_kind in ("count", "share"): + return staged_kind + if staged_kind is None: + return "gbp" if unit_value.startswith("gbp") else "count" + raise ValueError(f"unmapped value_kind: {staged_kind!r}") + + +def tally(scores: list[ExternalScore]) -> dict: + """Per-metric counts for lane details and runner stats.""" + out: dict[str, int] = {} + for s in scores: + out[s.metric.value] = out.get(s.metric.value, 0) + 1 + return out diff --git a/sources/harvest-uk-2026-08-02/COLLATION.md b/sources/harvest-uk-2026-08-02/COLLATION.md new file mode 100644 index 0000000..51f3640 --- /dev/null +++ b/sources/harvest-uk-2026-08-02/COLLATION.md @@ -0,0 +1,76 @@ +## pwbm — DONE (first to finish) +717 validated claims (382 revenue_change + proposed: pct_change_after_tax_income 161, primary_deficit_change 66, avg_* 108); 43 manifested artifacts, 103 extracted tables, re-runnable extract/stage scripts. OBBBA fully captured (signed conv $3,211B / dyn $3,631B — spot-checked vs prose; House variants; distribution 2027/2030/2033 × 9 groups). INGEST GOTCHAS: (1) some tables score vs TCJA-extension baseline → conditions.baseline_policy=tcja_extension — needs a non-current-law baseline ReformRef; (2) OBBBA "Table 3" = primary_deficit_change not revenue; (3) PWBM distribution concept = after-tax-AND-transFER income (conditions.income_concept); (4) tariff xlsx units inferred (rows flagged UNITS INFERRED). Best PE-runnable: SS-benefits-tax elimination, Keep Your Pay Act, WATCA surtax, top-rate options. +## tax_foundation — DONE +665 validated claims (491 revenue_change + 174 pct_change_after_tax_income), conv/dyn never mixed, zero unparseable cells, reproducible stage_claims.py. Crawl respected their robots (sitemap-driven, 5s AI-bot delay, contact UA). Headliners: OBBBA final law canonical page (conv −$5,168.4B / dyn −$4,331.1B, 2025–2034, cross-verified) + provision-level XLSX (40 provisions; TCJA-permanence with conv AND dyn per provision, e.g. SALT cap +$1,020.4B/+$782.7B) + Tariff Tracker July-2026 vintage. INGEST GOTCHAS: calendar-vs-fiscal UNSTATED on OBBBA/TCJA revenue tables (per-row note — don't assume FY vs CBO/JCT); tariff tables mix subtotal/component/total rows (no naive sums); state/district tables are Datawrapper embeds (CSV-endpoint follow-up); pct_change_after_tax_income recurs → deliberate Metric extension. NOTE cross-source: TF OBBBA conv −$5,168B vs PWBM signed conv −$3,211B — different conventions/scopes, adjudication material for the diagnosis loop. +## budget_lab — DONE +1,247 validated claims (644 revenue_change + 603 pct_change_after_tax_income; 861 high-confidence; zero dup keys; per-row value_raw + normalization + sign convention). Best data-per-artifact of the fleet: "TBL Data" XLSX ships with nearly every analysis. Jewels: reconciliation distributional workbook (% change after-tax-and-transfer income by quintile × {Medicaid, SNAP, Taxes, Net} × bill version — the TRANSFER-side complement nobody else publishes), 16-scenario CTC options workbook under two baselines (430 rows — ideal reform-score validation), provision-level House-vs-Senate distribution (279 rows). Poverty metrics: honestly zero (they publish income effects, not poverty). INGEST GOTCHAS: per-workbook unit chaos (fractions vs percent — normalized per row, caught via cross-workbook cell check); one workbook dropped for provably mislabeled headers; hidden right-side panels needed panel-aware parsing. Out-of-vocab held back: %GDP, $/household, share-of-tax-cut columns. +## cpsp — DONE +1,033 claims (534 poverty_rate + 318 rate_change + 149 count_change + 32 proposed levels; 961 construct clean vs models.py). The poverty complement to the tax scorers. Jewels: CTC counterfactual tables 2023/2024 (No-CTC/TCJA/OBBBA/AFA at explicit 100% take-up, no behavior — DIRECTLY expressible as policyengine_us reforms, the cleanest reform-validation surface of the night); monthly SPM series 2024-01→2025-12 (project ENDED Dec 2025, Gates funding — no 2026 monthlies will ever exist; Oct 2025 blank from the shutdown CPS); SNAP TFP-revocation all-state tables (change-validation; levels on pooled 2015-19 TRIM base, data_vintage flagged). Access: Cloudflare challenge NOT bypassed — static /sites/ files live w/ honest UA, pages via Wayback (recorded). BONUS: caught an ERRATUM in their 2024 historical brief (key-findings 16.6% vs body+math 11.4% — staged 11.4%, flagged) — external_issue diagnosis material before any comparison ran. Annual SPM levels ≈ Census → flag possible consumed_as_target reclass at ingest. +## cbo — DONE +931 claims (929 baseline + 2 reform; 317 pre-marked consumed_as_target VERIFIED against policyengine-us/parameters/calibration/gov/cbo/ — staging-time honesty labels). Program coverage: Medicaid 155, SSI 121, SNAP 68 (outlays+participation+avg benefit), UI 55, CHIP 44, + 330-row individual-income-tax detail (the sleeper: calendar-year AGI→liability walk, directly PE-tax-unit comparable). Caught a CBO WORKBOOK LABEL BUG (SNAP header says billions, values are millions — cross-verified to 6 sig figs). SSI sheet rows reproduce PE calibration yaml exactly. EITC/CTC: no dedicated workbook exists — composite line staged; Treasury refundable-credit accounts = follow-up lead. OBBBA cost-estimate PDFs retrieved but mostly period-ranged (2025-2034 windows) → verbatim pointers, only 2 single-year claims staged (SNAP avg benefit $213 reform vs $227 baseline, 2034). BLOCKERS: cbo.gov is DataDome-403 (no bypass; used local downloads + Wayback); 5 artifacts unretrieved incl. the June-2026 spending refresh — one click each in a real browser. Schema note: period-RANGE claims (10-year windows) don't fit int period → needs period_start/period_end or a window condition at ingest. +## tpc — DONE +1,486 claims from 35 of 54 harvested T-series tables (revenue_change 425 in-vocab; avg_tax_change 228, pct_change_ATI 198, share_with_tax_cut 167 proposed; 468 benefit-family rows flagged droppable). Coverage: full Senate-OBBBA distribution block, CTC options set (T25-0209/0213/0215 — parametric, but BASELINE = current law + Senate OBBBA Title VII, captured as baseline_hint per row), American Family Act T26-0029..31, June-2026 current-law baseline distribution block (mode-1 level validation once vocab extends), 3 tariff tables (independent comparator for the tariff-parity lane). Values verbatim + TPC's unrounded twin as value_unrounded; income axes verbatim incl. dollar-year. ACCESS RECIPE (documented for re-harvest): TPC Cloudflare-blocks curl at TLS-fingerprint level → browser-pane routing; Drupal pages throttle ~1/30-50s BUT static /sites/default/files/ XLS paths are unthrottled = the unlock; HTML tables are GIFs so XLS is the ONLY parseable artifact; page-slug vs file-id mismatches → key off file-internal table id. +## jct — DONE (largest haul) +6,771 claims across 7 conventional revenue tables — per-provision × FY2025-34, every row passing exact column-count validation + a horizontal checksum (years must sum to the printed span total), NET TOTALs matched to published figures, 5 random cells re-grepped. Jewels: JCX-35-25 enacted-OBBBA Title VII (−$4,474,972M ✓ the published $4.475T), JCX-26-25R House-passed (−$3,798,248M — enables per-provision House-vs-Senate cross-validation), JCX-29-25 scored vs CURRENT-POLICY baseline (conditions.baseline distinguishes twins — third source tonight exercising non-current-law baselines). Access: jct.gov TLS-fingerprint 403s everything non-browser → original bytes via Wayback at 1 req/3.5s (no bypass). FOLLOW-UPS: JCX-34-25 binary never archived (SPN 5xx tonight; correct URL in NOTES); 2026 JCX index needs a live-browser pass; JCX-45-25 tax-expenditure report downloaded but UNstaged (needs coordinate-aware parser + tax_expenditure metric). + +# FLEET SUMMARY — 2026-08-02 overnight +7/7 harvesters complete. **12,850 staged claims** (JCT 6,771 · TPC 1,486 · Budget Lab 1,247 · CPSP 1,033 · CBO 931 · PWBM 717 · Tax Foundation 665), 246 manifested artifacts, all sha256'd, per-row provenance, verbatim values only, zero bot-mitigation bypasses (Wayback/static-path/browser-pane recipes documented per site). + +INGEST WORKLIST (deliberate schema decisions, then adapters): +1. Metric extensions that RECUR: pct_change_after_tax_income (4 sources), avg_tax_change_usd (3), share_with_tax_cut, primary_deficit_change, tax_expenditure. +2. period ranges (10-yr windows: JCT/PWBM/TF totals, CBO cost estimates) → period_start/period_end. +3. Baseline variants are LOAD-BEARING: TCJA-extension (PWBM), current-policy (JCX-29-25), current-law+Senate-Title-VII (TPC CTC set) → non-current-law baseline ReformRefs, never conditions-only. +4. conditions vocab to standardize: income_group + income_axis, scoring (conventional|dynamic), income_concept, baseline_policy, option, month, data_vintage. +5. calibration_relationship: CBO rows pre-verified vs pe-us calibration params (317 consumed); CPSP annual SPM ≈ Census → review. +DIAGNOSIS SEEDS ALREADY IN HAND: CPSP erratum (16.6 vs 11.4), CBO SNAP workbook label bug (billions/millions), TF-vs-PWBM OBBBA conventional gap (−5,168 vs −3,211 $B — scope/convention decomposition), JCT-vs-TF-vs-PWBM enacted-OBBBA triangle. +FOLLOW-UP FETCH QUEUE (one click each in a real browser): 5 CBO artifacts incl. June-2026 refresh; JCX-34-25; 2026 JCX index; TF state/district Datawrapper CSVs. + +# UK FLEET — dispatched 2026-08-02 +Staging at ~/scorecard-harvest/uk_{source}/. UK conventions for ingest: values GBP (proposed unit gbp — UnitConcept lacks it, extend deliberately); UK fiscal year Apr–Mar (time_basis fiscal_year + fy label in conditions); geography labels UK/GB/England/Wales/Scotland/NI verbatim; income_concept BHC|AHC + equivalisation are LOAD-BEARING conditions on every distribution row; devolved variation (Scottish income tax) in conditions. + +# ⚠️ INGEST ROUTING RULE (Max 8/2): admin facts → LEDGER, model claims → SCORECARD +Administrative caseload/expenditure/receipts OUTTURN rows (DWP benefit expenditure & caseload tables, HMRC outturn statistics, CBO historical rows) are populace CALIBRATION material → route to Ledger source packages (target-profile or validation_comparator facts), NOT scorecard external_scores. Scorecard holds MODEL claims only (Urban/TPC/PWBM/JCT/TF/BL/CPSP/IFS/RF/UKMOD + CBO projections + OBR forecasts — a forecast is a model speaking). Routing key = the per-row basis tag (outturn|forecast) the harvesters already stage. Scorecard rows referencing admin facts do so via ledger_fact pointers, never copies. Applies retroactively to the CBO baseline staging (projection rows stay scorecard-side; outturn rows → Ledger). +## uk_hmt — DONE +1,368 staged claims (1,218 exchequer_impact + 150 median_gross_income; 31 suppressed incl. verbatim negligible/blank-cell footnotes), 16 manifested artifacts, all sha256, zero bot mitigation (plain curl + honest UA; gov.uk search/content APIs for discovery). All 3 events: AB2024 (Table 5.1 XLSX, 70 measures + subtotals), Budget 2025 (Table 4.1 XLSX, 88 measures — Nov event is titled plain "Budget 2025"), SS2025 (Table 3.1 parsed from PDF text layer, 33 measures — no XLSX published). Checksums: sum(measures) vs Total rows within ±£30m everywhere; Employer NICs +23,770m cross-verified scorecard↔costings note. Spring Statement 2026 (3 Mar): forecast-only, NO costings/DA publications exist. Metric: proposed exchequer_impact NOT revenue_change (deliberate: footnote says Tax/Spend classification is by LARGEST impact, rows mix heads); sign convention verbatim-stated only at SS2025 (incl. HMT typo "postive"), observed+cross-checked for the XLSXs. DA income concept captured verbatim: equivalised net household income BHC, modified OECD (HBAI-consistent), IGOTM on pooled LCF 2017-18..2019-20 — on every distribution row. 24 verbatim costing-methodology notes (behavioural adjustments incl.) in NOTES.md as assumptions-registry material. BIGGEST GAP: per-decile policy-impact values (Figures 1.A/1.B) are chart graphics only — no published numbers anywhere (PDF, HTML, annex); only annex Table 2.C (median gross income by decile × composition) is numeric. DIAGNOSIS SEED: B2025 scorecard row embeds "taking 450,000 children out of poverty" in the two-child-limit measure name = testable government poverty claim. UNSTAGED: Tables 5.2/4.2 (previously-announced measures, downloaded). +## uk_ukmod_jrf — DONE +1,782 staged claims (ukmod 1,392 / jrf 390), 5 artifacts, zero bypasses (ISER open; JRF crawl-delay 20s honored). THE SAME-CLASS JEWEL: UKMOD Country Report 2023-2030 (CeMPA WP 8/26, Apr 2026) Section-4 validation block staged in full — Tables 4.5/4.6 caseloads+expenditure with UKMOD-simulated AND official-estimate columns side by side (38 instruments × 2023-2030, incl. Scottish income tax by band), 4.7 income distribution and 4.8 poverty rates × {UKMOD, Input Data, HBAI} — another microsimulation's self-validation, conditions.series distinguishes sides; official cells are second-hand DWP/HMRC/OBR → dedup vs first-hand lanes at ingest, delta = diagnosis material. Reform surface: CeMPA WP 3/26 Autumn Budget assessment (threshold freezes + UC two-child-limit removal + WFA restriction + PC cuts; reform_hint verbatim) — fiscal by year+nation, fixed-AHC poverty counts base/reform/change, child poverty by nation, Gini/S80S20 AHC+BHC. JRF: UK Poverty 2026 data workbook (81 sheets, machine-readable, HBAI-derived, UNROUNDED headline AHC series 1994/95-2023/24) — OT1/GT1/DDT1/OG1/FAST2/A1T1 staged; MIS 2025 Table 2 (88 cells, AHC/BHC-comparable totals). INGEST GOTCHAS: (1) UKMOD validation poverty/distribution = BHC, JRF headline = AHC — income_concept load-bearing everywhere; (2) proposed gbp units + value_kind currency_gbp extension; (3) UKMOD take-up priors frozen since 2021 (their own health warning) — expect drift in projected years; (4) CeMPA 3/26 title says Autumn Budget 2026, cover says 2025 (= Nov-2025 Budget measures); (5) MIS 2024 couples erratum (missing mobile phone, corrected 2025); (6) PDF header typo "2029 2029" on continuation pages, mapped positionally. ADAPTER-PATTERN VERDICT: yes — the EUROMOD/UKMOD country-report validation block (simulated vs official vs input-data columns, instrument × policy-year) is a standardized format ACROSS the whole EUROMOD family; one adapter keyed on (instrument, series, policy_year) generalizes to every EUROMOD country report and to prior UKMOD vintages (cempa2-25 = 2022-2029 available for drift analysis). +## uk_resolution_foundation — DONE +71 staged claims, 15 manifested artifacts (all sha256), zero bypasses (robots = blanket Allow; honest UA; ~3-4s delay). RF = third UK microsim lineage (IPPR Tax Benefit Model on FRS/HBAI 2023-24 — every distribution figure credits it) vs IFS TAXBEN and HMT IGOTM. Jewels: LSO 2026 poverty projections (child 33%→30% relative AHC 2025-26→2026-27, −420k children; working-age 19.9%→19.5%; pensioner 16.0% — and footnote 21 says DWP's Feb-2026 projections give the IDENTICAL 33→30 path = ready-made same-concept triangle with the DWP lane); LSO 2025 prior vintage (central 34% by 2029-30 = 4.8m children; policy scenario w/ 2CL repeal = 31% — pre-Budget counterfactual vs LSO 2026 post-Budget actual = vintage-pair for diagnosis); Stairway to headroom Budget-2025 decile block (2CL £3,570/extra-child-element, poorest fifth +£360; threshold freeze −£540 richest fifth vs −£64 poorest; mansion tax; 64% of poorest decile gain / 96% of richest decile lose — RF models 2029-30 vs HMT DA's 2028-29, scope = 52% of tax measures, both verbatim in NOTES); April-2026 uprating parameter set (3.8 CPI / 4.8 SP / 6.2 UC / 6.8 U25-UC / 1.5 UC-health-existing / 0 LHA — pure policyengine-uk parameter checks). 26 rows carry reform_hint (2CL repeal, UC CPI+2.3%, UC-health halving, freeze extension, mansion tax, EV per-mile). 8 rows attribution-flagged = RF citing government (HMT 4.1 costings £2.4bn→£3.1bn, DWP IA 510k/£4,560, govt −450k children) — dedup vs uk_hmt's first-hand Table-4.1 rows at ingest; RF's −420k (own model) vs govt's −450k embedded in the HMT scorecard row = the fleet's cleanest cross-model poverty-claim pair. INGEST GOTCHAS: (1) NO chart-data downloads exist anymore — RF pages ship PDF only (probed; site "Data" nav = 2 dashboards), so vigintile curves are labelled-points-only; (2) source TYPO in Catching up? "£1.85 million" = £1.85bn (flagged in-row); (3) £800m vs £810m vs £330m-net UC-uprating costs = three scopes/vintages, not contradictions; (4) changes-not-levels: RF applies modelled CHANGES to HBAI 2023-24 outturn, so levels inherit outturn error (their words, NOTES verbatim); (5) take-up assumptions UC 80% / PC 65→70% + full-UC-rollout-by-2026-27 in NOTES for the assumptions registry. UNMINED: Low Pay Britain 2025 (minwage), State of the nations (devolved; SCP figures are ScotGov-model, left unstaged), LSO 2025 Annex per-nation table, It's-personal-taxation (pdftotext yields 0 lines — OCR next pass). + +# UK FLEET SUMMARY — 2026-08-02, 7/7 complete +**33,943 UK staged claims** (OBR 25,558 · HMRC 2,842 · DWP 2,054 · UKMOD/JRF 1,782 · HMT 1,368 · IFS 268 · RF 71), ~100 manifested artifacts. Combined US+UK: **46,793 staged claims, 14 sources** (+ Urban's 30,004 already in DB). Zero bot-mitigation bypasses fleet-wide (Turnstile seen at OBR and NOT clicked; Wayback originals + static-path unlocks documented per site). + +UK INGEST ADDITIONS to the worklist: +1. Vocab: gbp unit (recurring everywhere), exchequer_impact (HMT/OBR — Tax/Spend heads mix, mapping = deliberate ingest decision), poverty_count, unclaimed_expenditure, revenue_level, policy_parameter_level, taxpayer_count (shared with CBO), income_percentile_point etc. (HMRC). +2. FY convention: staging uses END-year in places, pe-uk-data maps START-year — conditions.fy disambiguates; normalize deliberately at ingest. +3. LEDGER ROUTING (Max's rule) applies hardest here: DWP BECL outturn rows + HMRC outturn statistics → Ledger; BECL/HMRC forecast rows (OBR-consistent) + everything think-tank → scorecard. pe-uk-data consumption VERIFIED in-session by the DWP agent (targets/sources/obr.py + dwp.py) → consumed_as_target reclasses pre-evidenced. +4. Take-up: DWP PC rows pre-marked seed_source (PE-UK pension_credit takeup.yaml cites this exact series — verified); DWP ~85% HB-pensioner take-up vs PE-UK takeup=1 = a direct pe_gap seed; IFS TAXBEN = deliberate full-take-up (entitlements basis, verbatim guide) = registry axis on every UK poverty comparison. +UK DIAGNOSIS SEEDS: HBAI FYE2025 admin-linked restatement (same year/publisher, BHC relative 17.23%→15.18% — ~2pp methodology gap, paired editions staged); two-child-limit PENTAGON (IFS −540k steady-state · RF −420k · HMT/govt −450k · UKMOD assessment · PE-UK = fifth leg); OBR self-revision surface (EFO 3.17: freezes £24.3bn certified → £49.1bn latest); UKMOD take-up priors frozen since 2021 (their own §4.3 warning); BECL FY-average vs UC point-in-time (definitional, pre-adjudicated). +FOLLOW-UP FETCH QUEUE (browser one-clicks): OBR March-2026 policy/expenditure tables + Nov-2025 policy tables; IFS taxlab revenue spreadsheets; HMT Tables 5.2/4.2; Stat-Xplore detail (auth = Max's call); RF vigintile series (correspondence = Max only). + +# FIRST UK COMPARISONS COMPUTED — 2026-08-02 (results/uk/ + comparison/uk_scorecard_first.csv) +9 HMRC ready-reckoner rows vs PE-UK static (populace_uk_2023 @ dd68c73 via pe.py, FY2026): basic_rate 1.05 · pa_100 1.11 · employee_ni 1.13 · employer_ni 0.96 (on ni_employer; pe-uk wage-incidence spillover −£4.45bn IT+NI recorded — pe-uk NOT purely static on this margin) · vat 1.23 · class4 1.33 · cb 1.32 (HICBC netting hypothesis) · higher 2.02 · additional 12.9 — the TIE gradient 1.05→2.02→12.9 IS the taxable-income-elasticity ladder, assumption-registry linkable. TWO-CHILD LIMIT: PE 2026 baseline ALREADY abolishes (child_count 2→inf at 2026 — AB2025 encoded); removal measured vs reinstated counterfactual = £1.10bn UC cost, −1.34pp child poverty, 181k children — NOT yet pentagon-comparable: two named construction deltas (floating-line relative AHC vs external FIXED-line; u16 vs HBAI dependent children) + single-year vs steady-state roll-in. Fixed-line rerun = next compute item before any adjudication. + +# US YEAR GRID COMPLETE — 2026-08-02 +baseline+fullpart now computed at 2024/2025/2026 (comparison/pe_{baseline,fullpart}[_YYYY].csv, monthly-aware flag forcing throughout). Unlocks: CBO FY2025/26 projection joins (exploit item 7 — respect outlays-vs-benefits concepts per cbo/NOTES.md row map) and CPSP 2024 comparisons. Campaign chip task_68d35783 staged; CAMPAIGN.md = driver. + +# COMPUTE BATCH — 2026-08-02 afternoon (campaign session, CAMPAIGN.md driver) +**UK two-child fixed-line rerun (exploit 3) ✅**: PE −243,108 HBAI-dep children (−1.61pp), 2026, fixed baseline relative-AHC line, calibrated take-up (results/uk/two_child_fixed_line_2026.json). Findings: (1) line convention contributes EXACTLY ZERO — person-weighted medians identical to 5 decimals between worlds (UC changes never touch the median household), so floating-vs-fixed was a null delta all along; (2) child-definition delta u16→HBAI-dep only +8k; (3) pe-uk's in_relative_poverty_ahc uses HOUSEHOLD-weighted median vs HBAI person-weighted convention (upstream note-worthy; both computed, person-weighted used); (4) prior run's in_poverty_ahc was ABSOLUTE AHC (parameter threshold), not relative — abs-line continuity check reproduces 181k u16 exactly; (5) grandfathering verified in code (born<2017 exempt) → PE reinstated world = actual partially-rolled-in 2026 law. Pentagon discipline: legs NOT same-concept (IFS −540k = 2CL-only steady-state; govt −450k horizon ~2029-30; RF −420k = Budget-package YoY; UKMOD CeMPA = NET package −13k children FY2026/27, freezes offset 2CL). Fulltakeup (IFS-entitlements-comparable) world pair queued — take-up is the live hypothesis for PE −243k vs IFS −540k. +**CPSP CTC counterfactuals 2024 (exploit 2) 🔄→✅**: runner cpsp_ctc.py, every gov.irs.credits.ctc.* path pinned against installed tree before construction. 2023 legs = not_computed WITH REASON (certified populace_us single-period 2024; 2023 weighted population = 0; year-mismatched comparison declined) — results/us/cpsp_ctc/NOT_COMPUTED_2023.json. 2024 landed so far: no_ctc 21.15% u18 (CPSP 16.6), obbba 16.74% (CPSP 13.3). LEVELS gap ~+3.4-4.5pp is DATASET LINEAGE not take-up: forcing credit flags moves PE only ~0.2pp (year-grid unforced 16.97% vs forced ~16.7%); CPSP≈Census 13.3-13.4. → dataset_construction diagnosis seed for populace calibration (ECPS sparse build measures child SPM high). Changes directionally consistent; full report when tcja/afa land. AFA construction: 2024-brief params deflated 2025→2024 (CPI ratio 0.97154, recorded assumption incl. 2025-CPI-vintage caveat); named deltas: newborn payment omitted, birth-month proration, refundable-ODC. +**TPC CTC/toprate/AFA batch (exploit 4) 🔄**: 16 sims in flight. T25-0209 full specs extracted from XLSX (3 CTC legs + 3 toprate legs at exact thresholds + totals); toprate legs runnable via gov.contrib.additional_tax_bracket structural reform (in_effect switch; slots 1-7 mirrored from live tree at runtime — contrib defaults are stale pre-OBBBA, mirroring is load-bearing). T26-0029 AFA vs current law INCLUDES TPC microdynamic response (named axis vs static PE); AFA floor ambiguity (bill $2,000 vs OBBBA $2,200 mid-tier) bounded by running BOTH constructions. FY-cash vs CY-liability convention named; CTC legs run at 2025 AND 2026 (FY2026 ≈ TY2025 refund settle-up for CTC). +**Random audit draw #1 (explore) ✅**: seed 20260802, universe 76,797 (14 staged files + urban DB read-only), 100 drawn, ALL outcomes published + hand-reviewed (results/audit/). Reviewed counts: computed_prior 6 · compute_candidate {reform 14, baseline 3, subgroup 24} · out_of_model {scope 22, admin 9, static 1, geo-pool 1, missing-axis 2} · vocab_pending 9 · vintage 2 (+3 modelable-in-kind) · needs_concept_map 2 · ledger_routed 1 · needs_review 1. BIGGEST UNLOCK: the 24 Urban subgroup slices (race/age/earners) need ONE subgroup-aware rerun of year-grid concepts (race + is_hispanic verified present in pe-us; locale/metro axis verified ABSENT → 2 rows honestly out_of_model_missing_axis). JCT draws are provision-level revenue staged under proposed_metric — reclassed compute_candidate (exploit-5 lane). +**RULING UPDATE (Max, 8/2, via calibration session — supersedes the batch note above)**: the CPSP/Census child-SPM LEVEL gap is RECLASSIFIED from dataset_construction seed to **by_design** (new diagnosis class, issue #9): Census SPM is not a target; populace deliberately departs from ASEC SPM attributes (calculated-vs-reported benefits, recalibration, threshold treatment — populace PR#32/census #9081 lineage). Level rows vs ASEC-anchored series carry by_design; adjudication text = design-rationale decomposition, never convergence language. CTC world CHANGE comparisons unchanged (same_assumptions test). cpsp_ctc_report.py + CAMPAIGN.md item 2 updated accordingly. +**REGISTER REFINEMENT (Max, 8/2, supersedes the by_design note above)**: scorecard is DESCRIPTIVE BY DEFAULT. (1) by_design → **methodological_difference**, strictly descriptive (both sides' choices documented via registry links; no defended-departure or convergence framing either direction — SPM level rows state Populace calculates benefits + recalibrates where ASEC carries reported attributes, and stop). (2) **pe_gap / external_issue require a citable known issue in action_link** (populace#593, CPSP 16.6/11.4 erratum qualify; divergence alone never does). (3) Compute-time hypotheses default explanation-shaped; verdict-shaped only on known-issue rows. Applied to cpsp_ctc_report.py + CAMPAIGN.md. Full ruling: issue #9 latest comment. + +# CALIBRATION-SESSION EXCHANGE + TPC FIRST DELTAS — 2026-08-02 later afternoon +**#593/#9081 citations now grounded**: (a) populace#593 scope verified by calibration session — pe_gap valid for early_head_start-affected poverty/net-income rows (EHS at engine-default 100% take-up, 5.16M/$112.3B, flows INSIDE household_net_income) + CHIP program aggregates only; added to cpsp_ctc_report hypotheses with action_link. (b) DWP HB take-up issue NOW FILED (policyengine-uk#1813) — HB rows may carry pe_gap under the gating rule. (c) **spm-calculator finding**: certified .venv-pe runs 0.3.1 — the version policyengine-us#9081 flags. Ground truth extracted from the PR#32 branch data (BLS workbook sha256 e7931a1f…): at sim-year 2024, 0.3.1 values EXACTLY equal the pre-correction published series (39430/39068/32586), so the 2019-2023 hand-entry errors (≤8%) are moot for everything computed this session; only the BLS 2026-07-17 correction applies at 2024 (renter −0.53% / owner+m +0.42% / owner-o +0.90%). Threshold-channel decomposition leg queued (threshold_channel.py: value-pinned swap to corrected series on the CPSP tcja basis; differenced vs tcja_2024 → descriptive channel magnitude). CPSP-2023 artifact question: DEFER per calibration shepherd (revisit trigger = populace multi-year artifacts). +**TPC first deltas (CY-liability vs FY-cash, per-leg)**: AFA-onto-OBBBA **−132.5B vs TPC −133.9B (ratio 0.99)** — and TPC's number includes microdynamic response. ctc_opt2 −15.4B vs −22.8B (0.68; consistent with CY2025 leg −15.1B and the implied-from-total −15.4B — internally consistent three ways). toprate opt2 +3.6B vs +12.2B (0.29) / opt3 +4.4B vs +13.1B (0.34) BUT opt3−opt2 difference +0.85B vs TPC +0.9B — explanation-shaped reading: PE tracks the marginal band ($1.56M→1.72M threshold move) closely while the far-tail (>$2M taxable) level runs ~⅓ of TPC's — top-tail income mass in the sparse ECPS build is the leading explanation channel (FY-vs-CY timing pushes the true gap LARGER, strengthening it). total_opt2 −11.8 vs −10.6 (1.12): the two legs' gaps OFFSET in the net — totals-only comparisons would have hidden both; per-leg decomposition is the product. Interaction term ≈0.05B (total ≈ ctc+toprate exactly). + +# VOLUME LANE FIRST RETURNS — 2026-08-02 evening +**UK free joins (16 rows, zero sims beyond the one aggregates harvest)** — results/uk/free_joins.csv. Coherent two-cluster read (explanation-shaped): (1) TAX SIDE systematically ~1.14-1.23 vs OBR FY2026-27 receipts across FIVE independent heads (IT 1.173 · NICs 1.167-1.228 · VAT 1.170 · CGT 1.165 · council tax 1.139) — uniformity points at a COMMON level factor (2023-artifact income mass uprated to 2026; FY/CY + cash-vs-accrual are few-% and partly wrong-signed) rather than per-head modeling; consistent with tranche-1 reckoner delta ratios (1.05-1.13). Candidate name: uk_income_level_calibration. (2) BENEFIT SIDE program-specific: state_pension 0.993 · pension_credit 0.932 (both calibrated) · UC 0.504 (the 0.55 stochastic take-up in-data; fulltakeup world queued tests it directly) · child_benefit 1.347 (universal-claiming vs real opt-outs + HICBC netting; matches cb reckoner 1.32) · PIP 0.721 / DLA 0.765 / AA 0.557 (receipt under-capture/take-up). fuel duty 0.527 = household-incidence share only (scope note on row). uk_aggregates.py = 33 totals, 0 absent — the whole BECL/OBR/HMRC surface is now joinable each release. +**US free joins**: SNAP participants 1.487 (annual-ever vs avg-monthly — expected direction, churn-plausible), SSI 0.840 (low-churn program → genuine undercount signal). Dollar rows unlock as pass2 lands. +**PWBM SS-tax elimination**: PE CY2025 −102.1B, construction verified (taxable SS = 0.0 exactly); coherent with PWBM FY2025 −60B / FY2026 −116B under CY↔FY mapping; senior-deduction baseline vintage = named axis. 2026 leg queued. +**AFA floor bound complete**: −130.7B (bill $2,000 floor) to −132.5B (onto-OBBBA $2,200) vs TPC FY2026 −133.9B — ratios 0.976-0.989, ambiguity width 1.8B, and TPC includes microdynamics. The AFA reform family now has poverty (CPSP) + revenue (TPC) legs from one construction set. +**OBR measure sample**: 10 reversal legs queued (obr_measures.py) — HICBC SB2024, ee-NI 2p/4p, class4 stack, class2 reinstate, employer AB2024, ART AS2022, dividends AB2021, CGT AB2024, PT/LPL SS2022 (low-confidence flag). Residential-CGT SB2024 skipped: no residential split in pe-uk cgt params (verified). +**TWO-CHILD TAKE-UP DECOMPOSITION COMPLETE (exploit 3 fully closed)**: entitlements-basis pair (all would_claim_* + claims_all_entitled_benefits forced) → removal effect −277,287 dep children (−1.83pp) / UC cost £1.85bn, vs calibrated −243,108 (−1.61pp) / £1.10bn. Ordered channel ledger for the pentagon: line convention 0 · child definition +8k · TAKE-UP +34k (quantified this run) · residual vs IFS −540k / govt −450k = roll-in vintage (PE 2026 keeps born-pre-2017 exemptions; IFS steady-state removes them) + model/data lineage. Full-take-up baseline child rate 31.3% vs calibrated 33.6% (take-up alone = 2.3pp of measured child poverty). Cost triangle: PE calibrated £1.10bn · PE entitlements £1.85bn · HMT costing £2.4bn FY2026-27 (incl legacy-CTC scope + OBR-certified take-up response) — coherent ordering, named scopes. results/uk/two_child_fixed_line{,_fulltakeup}_2026.json. +**CPSP CTC COUNTERFACTUALS 2024 COMPLETE (exploit 2 closed)**: all four worlds computed on CPSP's stated basis; report + staged rows at results/us/cpsp_ctc/. CHANGES (the same_assumptions surface): obbba_vs_tcja PE −0.03pp vs CPSP 0.00pp u18 — both models agree the OBBBA CTC parameter change is poverty-null; no_ctc_vs_tcja PE +4.38pp vs +3.30pp; afa_vs_tcja PE −6.12pp vs −4.50pp — near-constant PE/CPSP delta scaling (1.33×/1.36×) across scenarios = single density-at-threshold factor, not scenario-specific construction. LEVELS +3.5-4.6pp uniformly = methodological_difference (descriptive; SPM_NOTES.md; pe_gap sub-cite populace#593 EHS-in-net-income). 2023 = not_computed + DEFER recorded. Diagnosis classes per the 8/2 descriptive register throughout. diff --git a/sources/harvest-uk-2026-08-02/uk_dwp/NOTES.md b/sources/harvest-uk-2026-08-02/uk_dwp/NOTES.md new file mode 100644 index 0000000..bd3636c --- /dev/null +++ b/sources/harvest-uk-2026-08-02/uk_dwp/NOTES.md @@ -0,0 +1,177 @@ +# uk_dwp harvest notes — 2026-08-02 + +Target: DWP statistics on gov.uk. All fetches via gov.uk content API + +assets.publishing.service.gov.uk with honest UA +(`PolicyEngine-Scorecard-harvester/0.1 ... contact: max@maxghenis.com`). +No bot-mitigation encountered; no bypasses; Stat-Xplore NOT touched (auth-gated, +per instructions). + +**2,054 staged claims** in `claims_staged.jsonl` (concatenated by +`validate_and_concat.py` from per-source files, all re-runnable): +- `claims_takeup.jsonl` — 805 rows (stage_takeup.py) +- `claims_becl.jsonl` — 204 rows (stage_becl.py) +- `claims_hbai.jsonl` — 992 rows (stage_hbai.py) +- `claims_hbai_prior.jsonl` — 48 rows (stage_hbai_prior.py) +- `claims_uc.jsonl` — 5 rows (stage_uc.py) + +Validation (validate_and_concat.py, against scorecard_db/models.py): all rows +in closed vocab or proposed_*; conditions str->str; **zero duplicate claim +keys**; 48 suppressed rows (all FYE 2021 take-up, `[x]` in source, staged with +status=suppressed per the model contract). + +## Conventions used (UK FLEET rules) +- **period = FY ENDING calendar year** (DWP "FYE 2024" = Apr 2023–Mar 2024 → + period 2024), `time_basis=fiscal_year`, verbatim `conditions.fy` + ("FYE 2024" for take-up, "2023/24" for BECL/HBAI, matching each source's own + label). ⚠️ policyengine-uk-data maps FY to its STARTING year (FY 2025-26 → + 2025) — ingest must reconcile via conditions.fy, not period. +- **GBP**: `proposed_unit: "gbp"` (UnitConcept lacks it), values normalized to + absolute GBP with per-row `conversion` (e.g. "£ million x 1e6"), `value_raw` + verbatim. value_kind "gbp" (analogue of usd). +- Rates staged as shares (/100), unrounded where the source is unrounded + (HBAI gives 12+ significant figures — ideal for exact comparison). +- Counts: thousands x 1000, millions x 1e6, documented per row. +- Geography verbatim: gb / uk / england_wales per the source's own coverage + statements (see devolution below). + +## (1) Income-related benefits: estimates of take-up — 805 rows +Editions staged: **FYE 2024** (latest, published 2025-10-30) full series +FYE 2010 + FYE 2013–FYE 2024; **FYE 2023** (prior, published 2024-10-10) +headline year only. `conditions.edition` distinguishes (cross-edition revision +checks; FYE 2023 central caseload take-up identical across editions = no +revision). +- Coverage (benefits × editions): **Pension Credit** (PC1–PC10) and **Housing + Benefit for pensioners** (HB1–HB2) in BOTH editions. Income-related ESA/JSA: + **not published in either edition** (discontinued from the series — FYE 2022 + restart covers PC + HB-pensioners only). So the benefits×editions matrix is + 2×2, complete. +- Structure per benefit: caseload table (recipients; entitled non-recipients; + caseload take-up %) + expenditure table (amount claimed £m; amount unclaimed + £m; expenditure take-up %). Central/lower/upper staged as separate rows, + `conditions.bound`; both rates share metric=participation_rate with + `conditions.takeup_basis: caseload|expenditure` (per task spec). +- PC breakdowns: entitlement_group (all / guarantee_credit / + savings_credit_only) all years; family_type (PC3) and age_group (PC7) + caseload take-up for FYE 2024 only. +- Units: caseload figures are thousands of benefit units → unit_concept + families. Expenditure-basis take-up rows carry proposed_unit gbp (share of + entitled money claimed). +- Metrics: participant_count, participation_gap_count (entitled + non-recipients — in-vocab!), participation_rate; benefit_cost (amount + claimed); proposed_metric **unclaimed_expenditure** (amount unclaimed, with + bounds — the £ take-up gap; recurs 168x, worth a deliberate Metric + extension). +- FYE 2021: suppressed `[x]` in source (COVID FRS), staged status=suppressed. +- calibration: PC rows = **seed_source** — policyengine-uk + gov/dwp/pension_credit/takeup.yaml (0.7 from 2015) cites this publication + series (verified this session). HB rows = held_out (PE-UK HB takeup is + definitionally 1 — "no new claims"; DWP's measured HB-pensioner take-up + ~85% is a genuine external comparator for that assumption). +- Not staged (available in artifacts): mean/median weekly amounts + claimed/unclaimed (PC2/HB2), expenditure take-up by family type/age + (PC4/6/8/10). + +## (2) Benefit expenditure and caseload tables (BECL) — 204 rows +Artifact: Outturn and forecast tables, **Spring Forecast 2026** (published +2026-04-14; OBR Spring 2026 forecast-consistent). XLSX parsed cell-exact +(spot-verified 5 cells to full precision). +- Staged: FY 2019/20 → 2030/31 (outturn through 2024/25, forecast 2025/26+, + designation read from the workbook's own header row → + `conditions.basis: outturn|forecast`). +- Benefits: state_pension (exp + caseload), universal_credit (exp + household + caseload), uc_and_equivalents (exp), pension_credit (exp + caseload), dla, + pip, attendance_allowance (exp + caseload, total and in_payment), + child_benefit (exp; BECL line is "Child Benefit, One Parent Benefit & + Guardian's Allowance" — component condition records this), personal_tax_credits (exp). + Child Benefit has **no caseload row** in BECL (expenditure only, Non-DWP + Welfare sheet) — HMRC Child Benefit statistics are the caseload source + (→ uk_hmrc lane). +- ⚠️ Devolution (verbatim from Notes tab): DLA/PIP/AA figures are + **England & Wales only from FY 2020/21** (Scottish transfer 1 April 2020) — + staged geography=england_wales for those years, gb for 2019/20, with + per-row geography_note. All other benefits GB. +- ⚠️ Caseload semantics (verbatim Notes): "Caseload figures represent an + average over the full financial year" — per-row time_note. Explains e.g. + UC households 5.473M (FY 2024/25 average) vs 7.2M (Feb 2026 point-in-time + from the UC release). +- calibration: staged held_out with a VERIFIED note — pe-uk-data + targets/sources/obr.py consumes benefit expenditure and caseload forecasts + from the OBR March 2026 EFO; BECL is OBR-consistent → likely + consumed_as_target reclass at ingest for matching benefits. + +## (3) HBAI headline poverty — 992 + 48 rows +Artifact: HBAI summary results ODS, FYE 2025 edition (published 2026-03-26). +- Staged: tables 1.3a/b (all individuals), 1.4a/b (children), 1.5a/b + (working-age adults), 1.6a/b (pensioners): rates AND counts, full series + FYE 1995–FYE 2025, relative & absolute × BHC & AHC (income_concept and + poverty_measure MANDATORY conditions on every row). Rates unrounded + percentages → shares; counts millions → persons. poverty_rate in-vocab; + counts as proposed_metric **poverty_count** (496 rows — Metric extension + candidate). +- equivalisation condition verbatim-grounded: FYE 2025 methodology report — + "The main equivalence scales now used in HBAI are the modified OECD scales"; + AHC uses the OECD companion scale → equivalisation=modified_oecd / + modified_oecd_companion_ahc. +- ⚠️ **Absolute line re-anchor** (Notes sheet Note 3, verbatim): from the + 2024/25 publication the absolute fixed reference year is **FYE 2025 for + 2021/22–2024/25**; years before 2021/22 remain anchored at **FYE 2011**; + from summer 2026 DWP will re-anchor 2018/19–2020/21 too. Per-row + `conditions.poverty_line_anchor: fye_2025|fye_2011`. (Consequence: absolute + = relative exactly in FYE 2025, both 15.911572...% BHC.) +- ⚠️ **Break in series / admin-linkage** (sheet 1_3a header note): from + 2021/22 HBAI uses integrated survey + benefit admin data → those rows carry + data_vintage=admin_linked_frs + series_note. +- **Cross-edition methodology divergence (diagnosis seed)**: prior edition + (FYE 2024, published 2025-03-27, survey-only) staged for FYE 2022–2024 + rates (48 rows, edition=fye_2024, data_vintage=survey_frs). Same year, same + measure, same publisher: all-individuals BHC relative FYE 2024 = **17.23% + (survey-only) vs 15.18% (admin-linked restatement)** — a ~2pp + methodology-not-policy gap; the direct UK analogue of a vintage diagnosis. + populace-UK is FRS-based, so which vintage PE matches is itself diagnostic. +- Geography: FRS (GB) for FYE 1995–2002, FRS (UK) from FYE 2003 (col-0 series + markers) → geography per row. +- calibration: held_out with note — HBAI and PE-UK share FRS microdata; + agreement is same-input replication, not independent validation. +- Headline spot-checks vs main report HTML: individuals BHC FYE 2025 16% + (report) vs 15.91% staged (unrounded) ✓; child AHC relative 27.4%, + pensioner AHC 13.9%. +- Not staged (in artifacts): material deprivation & combined low-income tables + (1.4c–h, 1.5c–h, 1.6c), disability splits (1.7a–h), Gini/quintile medians + (1.2b), full data-tables zip (not downloaded; summary ODS suffices for + headlines). + +## (4) UC statistics — 5 rows +Latest release: "Universal Credit quarterly statistics, 29 April 2013 to +12 February 2026" (published 2026-05-12). Detailed tables are on Stat-Xplore +(auth — not attempted). Headline counts staged verbatim from release text +(rounded 0.1M, conversion noted): households on UC Feb 2026 = 7.2M; households +with payment = 6.7M (93%); people on UC Feb 2026 = 8.3M, Feb 2025 = 7.5M; +people on UC in employment Jan 2026 = 3.1M. GB. point_in_time with +conditions.month. Households series produced three months in arrears; recent +months provisional. + +## Proposed vocabulary (recurring, for the deliberate-extension worklist) +- proposed_unit **gbp** (500 rows) — per UK FLEET convention. +- proposed_metric **poverty_count** (496) — level counts (Metric has only + poverty_count_change). +- proposed_metric **unclaimed_expenditure** (168) — take-up gap in money. +- Conditions vocab introduced: bound (central|lower|upper), takeup_basis + (caseload|expenditure), edition, entitlement_group, family_type, age_group, + basis (outturn|forecast), fy, income_concept (bhc|ahc), poverty_measure, + poverty_line_anchor, equivalisation, data_vintage, subgroup, component, + month. + +## Blockers / follow-ups +- Stat-Xplore: households-on-UC by month/region/family-type tables need the + guest/auth API — not attempted per instructions. Release-text headlines + staged instead. +- HBAI full data-tables zip (69MB-ish, directional/regional detail) not + pulled — summary ODS covers all headline needs. +- Income-related ESA/JSA take-up: genuinely not published anymore (not a + fetch failure). +- BECL prior vintage (Autumn/2025 edition) not staged — Spring 2026 is the + current baseline analogue; add if forecast-vintage comparisons wanted. +- Pension Credit weekly amounts + take-up by marital/tenure axes available in + artifacts, unstaged (time box). +- period-int convention clash with pe-uk-data (ending vs starting year) — + resolve once at ingest via conditions.fy. diff --git a/sources/harvest-uk-2026-08-02/uk_dwp/claims_staged.jsonl.gz b/sources/harvest-uk-2026-08-02/uk_dwp/claims_staged.jsonl.gz new file mode 100644 index 0000000000000000000000000000000000000000..4a0ac1d5a5840ba096ee5f6a6216ea8e9889cdce GIT binary patch literal 63493 zcmZ5|1z42J`}VOALAqNSVFl?1C6enboH#ll}|kYIKfD2M{(!#gW5UUUpXWR>6K~f&g9K@72Y&<;f}9$ 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a/sources/harvest-uk-2026-08-02/uk_hmrc/NOTES.md b/sources/harvest-uk-2026-08-02/uk_hmrc/NOTES.md new file mode 100644 index 0000000..7df74f5 --- /dev/null +++ b/sources/harvest-uk-2026-08-02/uk_hmrc/NOTES.md @@ -0,0 +1,124 @@ +# uk_hmrc harvest notes — 2026-08-02 + +**2,842 staged claims** from 11 manifested artifacts (10 ODS + 1 bulletin HTML), all +sha256'd, verbatim values only, per-row provenance (workbook/sheet/row_index), +zero bot-mitigation bypasses. gov.uk is fully curl-friendly with honest UA +(`PolicyEngine-Scorecard-Harvest/1.0 (research data collection; contact +max@maxghenis.com)`); discovery via the gov.uk content API +(`/api/content/government/statistics/`) and search API — no scraping needed. +All ODS parsed with `ods_rows.py` (pure-stdlib parser, handles repeated +cols/rows); staging scripts `stage_{rr,itl,cb,tc,cgt,spi}.py` are re-runnable. + +## Claims by source file +| file | claims | what | +|---|---|---| +| claims_rr.jsonl | 225 | Ready reckoner: 73 illustrative changes x FY2026-27/27-28/28-29 (8 suppressed "Neg") | +| claims_itl.jsonl | 1,151 | Income Tax liabilities July 2026 edn: 2.1 (UK by band/sex/age 2010-11+), 2.2 (13 countries/regions x band, 2023-24..2026-27), 2.5 (liability x income range x band, 4 years) | +| claims_cb.jsonl | 515 | Child Benefit Aug 2025: families/children in receipt by geo 2013+, take-up rate (Table 15), HICBC (Table 16), opt-outs (Table 9) | +| claims_tc.jsonl | 453 | Tax credits finalised awards 2022-23 (FINAL edition): caseloads by family type 2018-19+, entitlement GBP, award-band distribution | +| claims_cgt.jsonl | 138 | CGT Aug 2025: annual taxpayers/gains/tax 2008-09..2023-24 + 2023-24 by country/region | +| claims_spi.jsonl | 360 | SPI 2023-24: income percentile points before/after tax (3.1 named pctiles 2015-16+; 3.1a full 1-99 for 2023-24) | + +## UK-FLEET conventions applied +- `proposed_unit: "gbp"` on every money row; conversions per-row in `unit_note` + (GBP millions x 1e6, thousands x 1e3; verbatim printed string kept in `value_raw`). +- `time_basis: fiscal_year` + `conditions.fy` ("2026-27") for Apr–Mar years; + Child Benefit August/May snapshots are `point_in_time` + `conditions.as_of`. +- `conditions.basis`: outturn | projected | provisional, from each table's own + markers (see per-source gotchas). Geography labels verbatim; ONS area codes + carried as `conditions.area_code` where printed. +- proposed metrics (recur across sheets, several match the CBO harvest): + `taxpayer_count` (909), `tax_liability` (214), `income_aggregate` (48), + `income_percentile_point` (360), `average_tax_rate` (48, staged as ODS + fraction, e.g. 0.015 for printed "1.5%"), `average_tax_amount` (48), + `chargeable_gains` (46). In-vocab: revenue_change, caseload, + participant_count, participation_rate, benefit_cost. + +## Per-source notes and gotchas + +### Ready reckoner (the reform-score surface) +- June 2025 edition (published 2025-06-24) is the LIVE latest; covers + FY2026-27..2028-29. No 2026 edition existed on the live page at harvest time. +- Sign semantics are LOAD-BEARING (staged per row as + `conditions.direction_semantics` + `sign_convention`): rows suffixed + "(cost)" report a positive number as a cost, "(yield)" as a yield; bulletin + note 33: "negative values for costs indicate net yield and negative values + for yields are a net costs". CGT/SDLT-additional-dwellings rows go NEGATIVE + (behavioural loss from a rate rise) — HMRC's estimates INCLUDE behavioural + response, so static PE-UK scores will legitimately diverge on + additional-rate, CGT and SDLT rows (diagnosis material, not error). +- "Neg" = "larger than zero but would round down to zero" (verbatim sheet + note) — 8 cells staged as status=suppressed with value_raw="Neg". +- Non-linearity warning (bulletin): allowance/limit changes don't scale + linearly; 1p rate changes roughly do. + +### Income Tax liabilities (July 2026 edition — post-cutoff fresh) +- SPI 2023-24 outturn; 2024-25..2026-27 projected per footnote 10 on "economic + assumptions consistent with the OBR's March 2026 Economic and Fiscal + Outlook" — carried as basis=projected. +- Scottish band-classification footnotes (8/9/11) matter for band counts: + Scottish taxpayers are classified against UK-government limits by income, + not Scottish marginal rate. `conditions.band` values are verbatim column + heads (Savers/Basic/Higher/Additional rate). +- Table 2.5 "[no estimate]" cells skipped (no value printed). Numbers + independently rounded to 3 s.f.; All-Ranges totals cross-check (36,700k + taxpayers, GBP 274,000m liability 2023-24 ✓ = Table 2.1 / receipts scale). +- NOT staged (in the same workbook, parse-ready): 2.4 percentile shares of + income/tax, 2.6 liability by income source. + +### Child Benefit (data at August 2025) +- Internal consistency verified: 7,552,330 registered − 684,635 opted out + = 6,867,695 in receipt (Aug 2025, UK) ✓. +- Table 15 is a genuine TAKE-UP rate (participation_rate): % of eligible + children for whom CB is claimed INCLUDING opted-out claims — All Ages + 86.6% May 2025, series back to 2011; per-age staged for May 2025 only. +- Table 16 HICBC: exact-GBP fiscal-year series; 2024-25 row provisional + + rounded to nearest 10k/GBP 10m (note 6) — basis=provisional. +- Charge-threshold regime note for comparisons: HICBC threshold rose to + £60k (taper to £80k) from April 2024. + +### Tax credits (finalised awards 2022-23) +- 2022-23 is the FINAL finalised-awards edition — no 2023-24 publication + exists on gov.uk (404; program ended 5 April 2025). Historic-validation + surface only (UC migration collapse visible: 339k out-of-work families). +- WORKBOOK STORES NUMBERS AS TEXT (no ODS office:values) incl. "1.4m" + shorthand — parse_cell() in stage_tc.py handles both; other workbooks are + numeric. +- Counts are annual AVERAGES of recipient families + (`count_basis=average_number`); entitlement rows are finalised annual + entitlement GBP. Table 2_3 bands are ANNUAL-ENTITLEMENT bands (not income). + +### CGT (August 2025 edition) +- 2021-22 onwards provisional (table header, staged basis=provisional); + 2023-24 first appears here: 378k taxpayers, GBP 65,937m gains, + GBP 12,086m tax (individuals+trusts). +- Staged from 2008-09 only: footnote 2 — taper relief pre-2008 makes gains + non-comparable. +- Trusts detail columns and Tables 2 (size of gain), 3 (gain x income) are + downloaded + manifested but unstaged (follow-up; Table 3's gain-x-taxable- + income grid is the most PE-comparable of the three). + +### SPI personal incomes (2023-24, March 2026 release) +- Percentile points are of the TAXPAYER income distribution (SPI covers only + individuals above the PA threshold) — carried verbatim in + conditions.population; do NOT compare against all-adult percentiles. +- 3.1 vs 3.1a overlap rows agree exactly (median before-tax 2023-24 + GBP 29,700 in both) — cross-check passed. +- NOT staged (manifested, parse-ready): 3.2-3.11 (age/sex/source + distributions) and the second workbook Collated_Tables_3_12_to_3_15a_2324.ods + (region/country/LA-level income + tax) — biggest remaining SPI value. + +## Blockers / follow-ups +1. No blockers hit: no Cloudflare/DataDome anywhere on gov.uk or + assets.publishing.service.gov.uk; every fetch was a clean 200. +2. Unstaged-but-downloaded: ITL 2.4/2.6; CGT Tables 2/3 (+ Table 4 BADR, + 6-9 not downloaded); SPI 3.2-3.11 + regional workbook; CB small-area file + and Tables 2-8/10-14/17 detail. +3. Not fetched (deliberate, out of 30-artifact budget): ITL tables 2.7-2.11 + (separate publications), historic 2.1a/2.5a, Child Benefit August 2026 + release (not yet published; annual ~Aug), HMRC receipts monthly bulletin + (harvest-obr/hmt overlap), UK income dynamics/NICs tables. +4. Ready reckoner June 2026 edition: watch the live page — the June 2025 + ODS is current as of today. +5. Ingest schema: same gbp UnitConcept extension as the rest of the UK fleet; + percentile/band/fy/basis/as_of condition keys to standardize. diff --git a/sources/harvest-uk-2026-08-02/uk_hmrc/claims_staged.jsonl.gz b/sources/harvest-uk-2026-08-02/uk_hmrc/claims_staged.jsonl.gz new file mode 100644 index 0000000000000000000000000000000000000000..e9ab465a0b89c5bdc92ae2884697e4801ac742c6 GIT binary patch literal 61920 zcmZ5|2|SeT_dc>jp%|2s7P3=sw(Mlz&5V7gEK`wvU$PalWG(w{%-EOgYe`6iLH00Y zXBf-a{?AOk@3-Io{q*+v%-!=e=RWs!u5-?HZm~w5C&K?na&B$v$iZ60ed*||A99JB z&EjK%cbD7dIx&s5NaKon<1;8WE$mE{lij93lPCYWX+y*3t)bo2-T3sI?>#!lb5!%J z_*TTPWKB(aS*p$z>K7ZdzCOcEp*s7}+jAag5=T>gnVGHrE?&othie{=jHAhgUA;^K zOaX>zGrSqBtx{qEH3m{XK3>~rrc4WXwNXhaF&;CXU+>=9|M)VGH zHFq@?<=AwvgK1?oPs>a*%QQ<9Fh44rX*M!xYLM_g!i}QK4$RM74tYvrPI1RDr>0|} zUZwz1=@!qbcPHDw%Bp&ES36OdWM9t*=o#!;qIrX;VGGU~`-*pF_vL1?Kw6qv=~)_P zsrjK;tCXbKNkM0CG8(4N?|Yc<1wWY6r#w3mRn_mC4U*Sx%zps<~ zjty1_x44LLcJh}z+Ccc0^%$r1n`LCMrn6?=NbgIUfulT}-Tf+#`~9Vkj%I8eHT%CM 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November 2025 or later", "date": "2025-11-26", "sha256": "0d0e2ca695065fbece681ac5d80f17d2d5a8ebd6a179399a93418c111919d70d", "local_path": "downloads/B2025_Table_4.2_Previously_Announced.xlsx", "doc_type": "scorecard_table", "access": "direct curl, honest UA (PolicyEngine-Scorecard-Harvester/1.0, contact max@policyengine.org)", "bytes": 47159, "publication_page": "https://www.gov.uk/government/publications/supporting-documents-for-budget-2025"} +{"url": "https://assets.publishing.service.gov.uk/media/6926ce2fb3b9afff34e95fec/Budget_2025_-_Data_Sources.pdf", "title": "Budget 2025: Data Sources", "date": "2025-11-26", "sha256": "20296a884709230ed28c5261a8864bffedcfb7c9e01cc12fd758bb0cf33a96b3", "local_path": "downloads/B2025_Data_Sources.pdf", "doc_type": "data_sources", "access": "direct curl, honest UA (PolicyEngine-Scorecard-Harvester/1.0, contact max@policyengine.org)", "bytes": 377280, "publication_page": "https://www.gov.uk/government/publications/supporting-documents-for-budget-2025"} +{"url": "https://assets.publishing.service.gov.uk/media/6929b353345e31ab14ecf735/E03444720_Budget_2025_Web_Accessible.pdf", "title": "Budget 2025 (web) [Red Book]", "date": "2025-11-26", "sha256": "fc112784bdcfccfd1dc362202dbcc7c54d4f17c2969dafae244e2edead7c468a", "local_path": "downloads/B2025_Red_Book.pdf", "doc_type": "budget_document", "access": "direct curl, honest UA (PolicyEngine-Scorecard-Harvester/1.0, contact max@policyengine.org)", "bytes": 4330185, "publication_page": "https://www.gov.uk/government/publications/budget-2025-document"} diff --git a/sources/harvest-uk-2026-08-02/uk_ifs/NOTES.md b/sources/harvest-uk-2026-08-02/uk_ifs/NOTES.md new file mode 100644 index 0000000..48b04d1 --- /dev/null +++ b/sources/harvest-uk-2026-08-02/uk_ifs/NOTES.md @@ -0,0 +1,145 @@ +# uk_ifs harvest notes — 2026-08-02 + +268 staged claims from 16 manifested artifacts. All rows source_model **ifs_taxben** +(research-institute lane), calibration_relationship held_out, values verbatim +(normalizations declared per row). GBP via `proposed_unit: gbp` / `gbp_per_year`; +UK fiscal years staged as `time_basis: fiscal_year`, `period` = start year, +`conditions.fy` label ("2029-30"). + +## Access recipe (documented for re-harvest) +- ifs.org.uk Drupal **page routes are Cloudflare-403** ("Just a moment") for curl AND + WebFetch — challenge pages kept as evidence (doc_type blocked_403_challenge_html). + robots.txt itself is permissive (standard Drupal disallows only /core/, /admin/ etc.). +- **Unlock: static `/sites/default/files/...` paths serve 200 to plain curl with honest + UA** (TPC-style). PDFs and data xlsx all came from there, live. +- Page HTML (to discover file URLs + provenance): **Wayback snapshots** (availability + API → snapshot; `id_` suffix for original bytes). No bot-mitigation bypassed. +- **IFS charts are Flourish embeds**: `public.flourish.studio/visualisation//embed` + carries the full data JSON (`_Flourish_data`) + settings (title, £ prefix, axis + titles, footer note). This is how the Budget 2025 decile chart was captured + numerically. Data-item pages name the viz id. Recipe generalizes to every IFS + data-item. +- Drupal `/media//download` routes (Taxlab spreadsheets) are 403 live and mostly + NOT in Wayback → the one-click browser follow-up list. +- Old `output_url_files/` paths (pre-migration) 404 live; Wayback has original bytes. + +## What was staged +1. **Budget 2025 decile chart** (22 rows, `avg_change_household_net_income`, + gbp_per_year): 2026-27 and 2030-31, deciles Poorest..Richest + All, from Flourish + viz 26495404. Scope note verbatim on every row — package includes two-child-limit + scrapping, fuel duty freeze + 5p-cut-removal delay, three more years of threshold + freezes, high-value council tax surcharge; EXCLUDES savings/dividend/property-income + rises, salary-sacrifice reform, some energy reforms ("Including these would make the + 2030-31 picture more progressive"). **Excludes Scotland.** + ⚠️ Income concept: x-axis is "Household income decile"; equivalisation and BHC/AHC + are NOT stated in the captured chart or deck — flagged per row, do not assume until + the underlying report states it. +2. **Green Budget 2025 Table 4.1** (28 revenue_change rows incl. deck £13bn): 27 + costed tax rises for 2029-30 (income tax, NICs, freezes, VAT, CT, capital, pensions, + IHT, council tax [England only], fuel duty). "£6 billion" for abolishing the + residence nil-rate band **visually verified** against rendered p.157. + ⚠️ These are a MIX of sources (per table source line, carried verbatim in every + row's `costing_basis`): HMRC Ready Reckoner projected to 2029-30 with OBR nominal + GDP growth is the usual starting point; employer NICs + threshold-freeze rows + combine HMRC estimates with TAXBEN; several rows from HMRC/OBR/MHCLG/Advani-Sturrock + (per-row `row_source_note`). NOT pure TAXBEN, NOT administrative fact. +3. **Waters Budget-2025 deck claims** (5 rows): freeze extension £13bn by 2030-31 + (with verbatim uncertainty: ~25% chance >£21bn, ~25% <£8bn); freeze-as-a-whole + taxpayer counts (5.2m into income tax, 4.8m into higher rate by 2030-31); two-child + limit scrap £3.2bn cost 2029-30 + 560,000 families gaining (attribution flagged: + may restate official costing — triangulation candidate). +4. **GB2024 Ch.6 Table 6.5** (109 rows): 12 child-poverty policy packages × {annual + cost, 3 spending-share splits, child abs-poverty count & ppt reduction, cost per + child lifted out, overall count & ppt} + the 23% simulated baseline rate. + **Pure TAXBEN** ("Authors' calculations using Family Resources Survey 2022-23 and + TAXBEN"). Steady-state at full two-child-limit rollout (staged period=2035 with + explicit time_note — treat as counterfactual marker, not forecast year). NI + excluded. Poverty reductions staged as NEGATIVE changes with printed magnitudes in + value_raw. Headliner: remove two-child limit = £2,450m, −540k children (−4ppt), + £4,510/child. +5. **GB2024 Fig 6.1 workbook** (104 rows, poverty_rate levels): child poverty + 1997-98..2022-23 × {relative, absolute} × {AHC, BHC}, full float precision from + xlsx. Equivalisation/thresholds verbatim in every row (modified OECD; rel = 60% + contemporaneous median; abs = 60% of 2010-11 median; ≤2003-04 excludes NI). + ⚠️ These are FRS/HBAI-consistent calculations, NOT TAXBEN simulations — flagged + per row; likely overlap DWP HBAI series → dedup vs uk_dwp at ingest. + +## TAXBEN assumptions registry (#10) — verbatim from the 2021 guide +(TAXBEN_Guide_2021.pdf, sha256 b19a90c7…, retrieved via Wayback; full text in +downloads/TAXBEN_Guide_2021.txt. Quotes exact.) +- Static default: "TAXBEN calculates what the impact of policy reforms would be on + households' finances if those households did not change their behaviour in response." +- Take-up: "TAXBEN analysis is usually done on an 'entitlements basis' — that is, we + measure what net incomes would be if individuals claimed all the benefits that they + are entitled to." (vs 'reported take-up basis' option; entitlements basis will + "overstate … the impact of benefit reforms on actual incomes".) +- Taxes: "we analyse taxes on a 'liabilities basis' — we calculate what net incomes + would be on the assumption that individuals do not evade tax." +- Incidence: "In TAXBEN analysis, we generally look at what would happen to incomes if + all changes to taxes and benefits were fully incident on the directly affected + households. This includes taxes such as VAT or employer National Insurance + contributions." +- Top of the distribution: "tax reforms which only affect top earners cannot generally + be modelled reliably using the survey data … Instead, for distributional analysis, we + use the survey datasets … to estimate the frequency with which affected individuals + appear in different deciles … We then use that frequency to break the official + costing of the policy (before behavioural response, wherever that is available) into + different deciles." ⚠️ IFS decile charts for top-end measures EMBED official costings. +- Disability & contributory benefits: "modell[ed] … on a reported take-up basis: only + those who say that they claim are modelled as entitled." +- Scope: models income tax, NICs (employer and employee), council tax, VAT, most + duties ("about three quarters of total government tax revenue" in 2017-18), almost + all benefits/tax credits/state pensions. Does NOT model capital taxes (CGT, IHT, + stamp duty), business taxes (corporation tax, business rates), or public services. +- Data: FRS (~20k households/yr, main source), LCFS (~5k, indirect taxes), + Understanding Society/BHPS (panel). Systems since 1975 simulable. +- Aggregation: "into 'deciles', where we calculate the effect of reform on average + incomes in the bottom 10% …" (deciles of household income; the guide does not state + the equivalisation scale — GB2024 Fig 6.1 note separately confirms modified OECD for + poverty analysis). +- Employer-NICs incidence in Budget-2025 deck (separate, verbatim slide note): + "Assumes rise in employer NICs is incident on employees". +- Green Budget costings caveat (GB2025 Table 4.1 note): HMRC Ready Reckoner "typically + incorporates the direct impact of a measure on the tax base to which it is being + applied, or to closely related tax bases [but not] effects on other tax bases and + wider economic factors"; most other sources "purely 'mechanical' estimates". + +## Triangulation set (IFS vs OBR/HMT, same measures) +- **Two-child limit scrapping** — IFS deck: £3.2bn cost 2029-30, 560k families; IFS + GB2024 steady state: £2,450m, −540k children. vs OBR Autumn Budget 2025 policy + costing + HMT distributional analysis + DWP poverty estimate (deck cites "Gov't + estimates … 450,000 / 3.1ppt" — NOT staged, it's the government's number). +- **Threshold freeze extension to April 2031** — IFS £13bn by 2030-31 (w/ uncertainty + band) vs OBR's certified costing of the same measure. IFS £10.4bn (GB2025, freeze to + April 2030, pre-Budget hypothetical) is a variant, not the enacted measure. +- **Fuel duty** — Budget package includes freeze + 5p-cut delay (in decile rows); + GB2025 has 10% rise = £2.4bn hypothetical. vs OBR fuel-duty costings. +- **High value council tax surcharge** — in IFS decile package; OBR/HMT costed it. +- **Employer NICs / VAT / CT ready-reckoner rows** overlap HMRC's own Ready Reckoner + (uk_hmrc lane) — expected NEAR-DUPES by construction (IFS projects HMRC numbers + forward); adjudicate as vintage/projection differences, not model disagreement. +- **Fig 6.1 poverty levels** overlap DWP HBAI (uk_dwp) — same-microdata restatement. + +## Gaps / follow-ups (one click each in a real browser) +- Taxlab **revenue composition spreadsheet** (/media/9899/download) + IFS Fiscal Facts + parameter workbooks — Cloudflare-403, not in Wayback. P4 (mode-1 levels) therefore + UNFILLED except via other lanes (OBR/HMRC cover the same levels with better + provenance). +- **Indirect & capital taxes deck** downloaded but not staged (mostly charts; needs + the same Flourish-id hunt via its data-items). +- GB2025 full report has more parsable tables (Ch.3 public finances; Ch.8 disability + benefits) — full-report text is in downloads/ for a second pass. +- Two-child-limit standalone pieces ("The two-child limit: poverty, incentives and + cost", Mar 2025 comment; 670k-children projection) — pages archived in Wayback, + not yet pulled. +- IFS **data-items index** (ifs.org.uk/data-items) would enumerate every Flourish viz + id → systematic numeric capture of all IFS budget/event charts. Needs browser or + Wayback crawl. +- Autumn Budget 2025 decile chart: pin down equivalisation/BHC-AHC from the underlying + IFS budget-analysis report when accessible. + +## Parse confidence +High throughout: Flourish values machine-read from embed JSON; Table 4.1 from layout +text with one visual verification (RNRB £6bn); Table 6.5 all 12 rows column-checked +against prose restatements (540k/£4,510/£2.5bn long-run figure cross-consistent); +Fig 6.1 machine-read from xlsx at full float precision. 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"local_path": "~/scorecard-harvest/uk_ifs/downloads/page__green_budget_2025_full_report.html", "doc_type": "blocked_403_challenge_html"} diff --git a/sources/harvest-uk-2026-08-02/uk_obr/NOTES.md b/sources/harvest-uk-2026-08-02/uk_obr/NOTES.md new file mode 100644 index 0000000..68f3219 --- /dev/null +++ b/sources/harvest-uk-2026-08-02/uk_obr/NOTES.md @@ -0,0 +1,131 @@ +# uk_obr harvest notes (2026-08-02) + +Source: Office for Budget Responsibility (obr.uk). Publisher slug used in rows: `obr`. + +## Access route (no bypasses) +obr.uk is Cloudflare-protected: curl and WebFetch get 403 with an honest UA, and +the live site served an **interactive Turnstile checkbox** in the browser pane — +NOT clicked, per the no-CAPTCHA rule. All bytes came from archives: +- **Wayback Machine original bytes** (`/web/id_/` URLs, honest harvester UA) — + all 16 artifacts. Per-file snapshot URL in `manifest.jsonl` (`wayback_snapshot`). +- UK Government Web Archive (webarchive.nationalarchives.gov.uk) was probed and + works for obr.uk *pages* but had not captured the target xlsx files. +- Wayback SPN (save-page-now) rejected anonymous saves (520) — could not force + captures of the missing March 2026 files. +- Discovery recipe: archived `/data/` and EFO pages -> `/download//` + links; Wayback replay of a `/download/` slug follows the stored 302 to the + real file under `obr.uk/docs/...`; plus a domain-wide CDX query filtered to + `.xlsx` (2026 window) which surfaced newer vintages than the archived data + page linked (November 2025 PMD, uncertainty ratings, Spring 2026 HOFD). + +## Artifacts (16, all sha256'd in manifest.jsonl) +Costings core: Policy measures database **November 2025** (latest vintage; its +Tax Summary includes Autumn Budget 2025 — vintage confirmed from content) and +**March 2025** vintage; Uncertainty ratings database November 2025; Policy +risks database November 2025; EFO Oct 2024 policy tables (Autumn Budget 2024 +scorecard as published in the EFO). +Forecast tables: EFO March 2026 receipts (latest); EFO Nov 2025 receipts / +expenditure / aggregates; EFO Oct 2024 receipts; EFO Mar 2025 expenditure; +EFO Mar 2026 chapter 3 charts+tables. +Databases: Historical official forecasts database Spring 2026 + March 2025; +March 2025 ready reckoner; Welfare trends report Oct 2024 charts+tables. + +## claims_staged.jsonl — 25,558 rows +| block | rows | metric | notes | +|---|---|---|---| +| PMD Tax Measures | 12,773 | `revenue_change` | 2,579 measure×tax-head rows, 84 fiscal events, Budget 1970 -> Autumn Budget 2025 | +| PMD Spending Measures | 11,531 | proposed `exchequer_impact` | 1,954 rows, June Budget 2010 -> Autumn Budget 2025 | +| EFO Mar 2026 3.4 + 3.8 | 490 | proposed `revenue_level` | income tax/NICs detail + tax-by-tax cash receipts, 2024-25 outturn + forecast to 2030-31 | +| EFO Nov 2025 4.9 + 4.11 | 441 | `benefit_cost` | welfare spending by program (UC elements, PIP, DLA, AA, carer's, child benefit, HB, JSA/ESA, state pension block) | +| EFO Mar 2026 3.17 | 95 | `revenue_change` | latest re-estimated yield of personal tax measures (PA/HRT freezes, ART cut, NICs thresholds) — reform_hint per measure | +| EFO Mar 2026 3.18 | 99 | proposed `taxpayer_count` (persons) | taxpayers with/without indexation, brought into tax / higher rate | +| EFO Mar 2026 3.19 | 129 | proposed `policy_parameter_level` | actual (frozen) vs with-indexation counterfactual PA/HRT/NICs thresholds, £ | + +Conventions on every row: value normalized to GBP (proposed unit `gbp`; +UnitConcept lacks it — extend deliberately), `value_raw` = verbatim cell, +`normalization` documents ×1e6 (£m) or ×1e9 (£bn); `period` = FY start year, +`time_basis` fiscal_year, `conditions.fy` = "1970-71"-style label; +`conditions.basis` outturn|forecast from the workbook's own Outturn/Forecast +marker row (`unstated` where the table has no marker — 3.17/3.19). + +### PMD staging decisions (the load-bearing ones) +- **Units/sign, verbatim from the Notes sheet**: "All the figures in this + database are in £ million… We use the Treasury scorecard convention that a + positive sign implies a gain to the Exchequer, and so reduces borrowing." + Tax rows: that convention coincides with revenue_change semantics (tax rise + = +). Spending rows: a positive value = *reduced* borrowing (e.g. the + June-2010 CPI-indexation switch and DLA gateway show +) — so it is NOT a + spending change; staged untransformed as proposed `exchequer_impact` with + `conditions.sign_convention=positive_gain_to_exchequer` and + `conditions.impact_channel=spending_measure`. +- **Extension cells excluded**: OBR extends costings beyond the original + scorecard using nominal GDP growth and shades those cells; the shading is + machine-readable (solid fill FFE1E9EE). Staged only original-scorecard + cells (24,304); skipped 48,902 extended cells (`costing_phase= + original_scorecard` on every staged row). Extended values remain available + in the artifact if ever wanted. +- Pre-June-2010 events are Treasury scorecard numbers (2-year horizons, + £5m rounding, £50m publication threshold); post-2010 are OBR-scrutinised + 5-year costings (£1m rounding since Budget 2018). source_model = + `hmt_scorecard_obr_database` for all; the fiscal_event condition dates each row. +- **March 2025 PMD vintage downloaded but not staged**: the database carries + original costings unchanged across vintages (per its own notes), so + re-staging would duplicate ~everything minus the two 2025 events; kept for + vintage diffing at ingest. +- Measures hitting both receipts and spending appear on both sheets (e.g. + Warm Homes Plan: Environmental levies on tax side, PSGI in CDEL on spending + side) — both staged, distinguished by tax_head/spending_head conditions. + +### Spot-checks passed +- AB2024 "Employer National Insurance contributions: Increase rate by 1.2 ppts + to 15%…" = +£24.17bn (2027-28), non-dom abolition +£5.73bn — match the + published scorecard magnitudes. +- 4.11 incapacity spending 2024-25 outturn £29.4bn; 3.4 income tax (gross) + 2024-25 outturn £305.9bn — right scales. +- All 25,558 rows JSON-clean, conditions strictly str->str, 0 failures. + +## uncertainty_ratings.jsonl — 1,179 rows (sidecar, not claims) +Final rating + data/behavioural/modelling sub-ratings per measure per event, +Autumn Statement 2014 -> Autumn Budget 2025 (23 events). Join to PMD rows at +ingest on (fiscal_event exact, measure name fuzzy) to populate +`conditions.costing_certainty`. Names differ slightly between the two +workbooks — do the fuzzy join deliberately, not automatically. + +## PolicyEngine-UK-runnable costings (best validation surface) +Directly parametric in policyengine_uk: +- **PA + HRT freezes** — 3.17 gives the OBR yield path (£24.3bn 2024-25 -> + £49.1bn 2029-30) AND 3.19 gives the exact counterfactual thresholds to + encode the uprated baseline. Cleanest possible reform-validation pair. +- Employer NICs rate 13.8->15% + Secondary Threshold £9,100->£5,000 (AB2024). +- Additional rate threshold £150k->£125,140; employee NICs main-rate cuts + (AS2023 12->10%, SB2024 10->8%); NICs primary threshold July-2022 rise. +- HICBC threshold changes; two-child-limit removal (AB2025, spending side); + UC taper 63%->55% + work allowances (AB2021); state pension triple-lock + upratings; VAT on private school fees (AB2024). +- 3.18 taxpayer counts (brought into tax / higher rate by freezes) are + PE-computable headcounts. +Level validation: 4.9/4.11 welfare benefit_cost by program × year vs PE UK +program totals; 3.4/3.8 receipts levels vs PE income tax/NICs aggregates. + +## Blockers / follow-up fetch queue (one click each in a real browser) +- EFO **March 2026** detailed tables: **policy** (Spring 2026 event costings), + **expenditure** (latest welfare tables), aggregates — never archived; + live URLs (pattern confirmed from siblings): + `https://obr.uk/docs/d055fbf02d5b3g6jq8l2/efo-march-2026-detailed-forecast-tables-{policy,expenditure,aggregates}.xlsx` + (also available via `https://obr.uk/download/march-2026-economic-and-fiscal-outlook-detailed-forecast-tables-zip-file/`). +- EFO Nov 2025 policy tables (Autumn Budget 2025 scorecard as published): + not found in archives under any tried name. +- Policy measures database **post-AB2025 refresh**: as of the June-2026 + archived data page the linked PMD was still the March-2025 slug; the Nov + 2025 file is the newest archived. Check live site for a Spring-2026 update. +- Welfare trends report Oct 2024: artifact retained, tables not yet staged + (overlaps 4.9-style content at an older vintage) — parse at ingest if wanted. +- Ready reckoner staged as artifact only: it is determinant-sensitivity + (earnings/employment scenarios), not policy levers. + +## Parse confidence +High for everything staged: units read from each table's own unit row +("£ billion"/"£ million"/"Million"/"£"), basis from each table's own marker +row, extension flags from the workbook's own shading key. No inferred +mechanics. Re-runnable scripts: stage_pmd.py, stage_efo_tables.py, +stage_receipts_measures.py, stage_uncertainty.py. diff --git a/sources/harvest-uk-2026-08-02/uk_obr/claims_staged.jsonl.gz b/sources/harvest-uk-2026-08-02/uk_obr/claims_staged.jsonl.gz new file mode 100644 index 0000000000000000000000000000000000000000..c75fbe553e034d349ee6ef43fe300a37e4d2288d GIT binary patch literal 609965 zcmY(qbzD^67d1?SA}JCgARwT?Pzop^D526_L#M=0(%qnxfV8AE49yJPjf6DJ(B0kj z+|lpvd7qa*?&qF6cbJ)T_gQ=Gwf3P4#Y02=VPJ00c-kN)qu7~kyNWH_YMNV%=?JW4RGj~8uy;j z!&XuE>@Z>1b2gRlqWb=7e`+8ax#I=FQ!sTiZw89!)Za z-WcAlRjF%*?L9UZjA;Y(oYAh@YIP5v7dm)ec~yk<&6uzcBOE{?=|3m*)Yz}%V>fm# z8-5nuWe`n>7nlFM&^f&2lbhHpy!Je_Ym~V)N+$EZNIRsFU=T4q@k-nsP?F33xcs5| zy0b$w&O2nn9&vrIJFt;slkKMQWBH|CuSxB}T%}BT$CU>-ZGBg=NpB_eSz#o!KtA_e z*ZTHKLc3$)R{mh4aLpB_1HE%Vr;F&JFgr;*=eb?KaP(D;D$Ntav|Lx z-iValtDB9ty0vFl6`p&8r#F#w73H)7bcnieY=URD9q+E-6x8t_w%iuTTvXnk^oi&Ll@9$}M zZQfs;KiPqPnXOoV^H|aCqsw%t`h4QArDj(J)%h;X*rdy(8Z~fJf^QSH{#viovS#(} 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"bytes": 1083754} diff --git a/sources/harvest-uk-2026-08-02/uk_resolution_foundation/NOTES.md b/sources/harvest-uk-2026-08-02/uk_resolution_foundation/NOTES.md new file mode 100644 index 0000000..cccec65 --- /dev/null +++ b/sources/harvest-uk-2026-08-02/uk_resolution_foundation/NOTES.md @@ -0,0 +1,178 @@ +# Resolution Foundation harvest — 2026-08-02 + +Source slug: `resolution_foundation` (research institute; source_model +"resolution_foundation", never administrative fact). Underlying engine for +their distributional/projection work: **the IPPR Tax Benefit Model** run on +DWP FRS/HBAI microdata (every distributional figure sources "RF projections +including use of the IPPR Tax Benefit Model"). RF is therefore a *third* +UK microsimulation lineage alongside IFS (TAXBEN) and government (Policy +Simulation Model / IGOTM) — good triangulation value. + +## Coverage +15 artifacts manifested (all sha256'd, honest UA, robots.txt fully +permissive `Allow: /`, ~3-4s politeness delay, zero bypasses needed). +71 staged claims from 5 publications: + +| pub | date | staged | +|---|---|---| +| Living Standards Outlook 2026 | 2026-02-10 | 27 | +| The Living Standards Outlook 2025 | 2025-06-26 | 14 | +| Stairway to headroom (Autumn Budget 2025 response) | 2025-11-27 | 12 | +| Catching up? (April 2026 uprating spotlight) | 2025-10-22 | 8 | +| Happy new tax year 2026 | 2026-04-02 | 10 | + +Downloaded but not claim-mined (context/coverage): Black holes and +consolidations (pre-Budget briefing), Low Pay Britain 2025 (minimum wage +flagship), State of the nations (devolved social security), Delivering +dignity (Scotland ADP), Measuring household income (RHDI-vs-HBAI +methodology), New Year Outlook 2026, Credit where credit's due (mortgage +rules — NOT a UC report despite the title), Bye bye baby (birth rates), +Much ado about PuFins (public financial institutions), It's personal +(taxation) (PDF extracts 0 text lines via pdftotext -layout — needs OCR or +-raw retry; valid Word-produced PDF). + +## Chart-data downloads: none (site practice changed) +The task expected chart-data downloads. Current RF report pages ship **PDF +only** — no per-report chart-data xlsx/zip anywhere on the 15 pages +fetched (checked hrefs for xlsx/zip/csv/"chart data"; probed obvious +upload-path names → 404). The site-wide "Data" nav item points to just two +standing dashboards (housing-indicators; RTI-based employment estimates). +All staged values were transcribed verbatim from PDF text (pdftotext +-layout), mostly from prose + printed chart labels, so axis-only chart +series (e.g. full vigintile growth curves in LSO Figure 6, full vigintile +gain/loss bars in HNTY Figure 1 / Stairway Figure 19) could NOT be +extracted — only the labelled points and prose-stated group aggregates. + +## Conventions used in claims_staged.jsonl +- Fiscal years Apr–Mar: `period` = start year (2026-27 → 2026), + `time_basis` fiscal_year, `conditions.fy` verbatim. +- GBP values: `proposed_unit: "gbp"` (UnitConcept lacks it). value_kind + "usd" is the closed-vocab currency kind — flagged here, not renamed. +- Income concept: RF poverty and income-growth work is **equivalised + household disposable income, after housing costs (AHC)** — stamped on + every distribution row (`income_concept`, `equivalisation`). LSO 2026 + Figure 15 title says "relative poverty after housing costs" explicitly; + LSO 2025 Figure 15 note defines relative poverty as below 60% of + median in the given year. +- Geography verbatim: UK for LSO/HNTY headline rows; **GB** for the + two-child-limit impact-assessment counts (DWP IA covers GB); Scotland + rows labelled Scotland. +- `attribution` field (8 rows): values RF **cites from government** (HMT + Budget 2025 Table 4.1 costings; DWP final-stage impact assessment + 510k families/£4,560; government −450k child-poverty estimate; UC + rebalancing net cost £330m/−£210m; EV charge £1.9bn) — these are NOT + RF-model outputs; ingest should either reroute to the government source + or keep with the attribution tag. Everything without `attribution` is + RF's own modelling. +- `reform_hint` (26 rows): plain-language mapping to a PE-runnable reform + (two-child limit repeal Apr 2026; UC standard allowance CPI+2.3% + Apr 2026 (+£6/wk, phased to +4.8% vs CPI-only by 2029-30); UC health + element halved+frozen for new claims (£50/wk); IT/NICs threshold freeze + extension to Apr 2030; mansion tax; EV per-mile charge). + +## Methodology (verbatim extracts, LSO 2026 Annex 1, pp.34-37) — for the assumptions registry +- Base data: "nowcasting and forecasting the latest household income data + (DWP's Family Resources Survey and Households Below Average Income + statistics, 2023-24) to the years from 2024-25 through to 2029-30." +- Reweighting: "We reweight the population to match ONS forecasts for + demographic change by age and gender" ("reweight2" in Stata; ONS + 2022-based projections, **migration category variant**); labour force + participation from "the OBR's March 2025 outlook". +- Earnings: "all employee and self-employed earnings are uprated equally + in each year. Overall wage growth is constrained to match ONS figures + for the outturn period and OBR figures for the projection period"; + wage floor modelled each year with "some 'spillover effect' for those + just above the wage floor"; NLW extension to 21-22 in 2024-25 and + "(provisionally) to those aged 18-20 by 2029-30"; "the wage floor + beyond 2025-26 rises in line with average earnings." +- Take-up: "We model incomplete take-up of the main means-tested + benefits. For example, we assume **80 per cent take-up of Universal + Credit**... we assume a rise in **Pension Credit take-up from 65 per + cent to 70 per cent** following Winter Fuel Payment reform." +- UC rollout: "We assume that full roll-out of Universal Credit is + completed in 2026-27." +- Two-child limit: "applied to children born from April 2017, and so + affects a growing proportion of the caseload each year. It is removed + from April 2026 in line with Government policy." +- Deflator: "we create a specific deflator for 'after housing costs' + income, in line with DWP definitions" (removes housing costs from CPI); + OBR November 2025 CPI forecast is the starting point. +- Rents: ONS Price Index of Private Rents for nowcast; "Beyond September + 2025, private rents are assumed to rise in line with average earnings, + with a 12-month lag." +- **Changes-not-levels discipline**: "we apply income growth rates (and + absolute changes in poverty and inequality metrics) from our modelling + to the 2023-24 outturn data, rather than directly using the projected + levels." → RF projected *levels* inherit any error in HBAI 2023-24; + treat RF rows as changes-anchored-to-outturn when comparing. +- Not modelled: benefit sanctions; mixed-age-couple Pension Credit + transitional protection ("We instead use the new eligibility rules for + everyone, in every year"); detailed migration; tenure change; Council + Tax Support variation by LA. +- PIP: "We model receipt of Personal Independence Payment based on future + caseload projections." +- Deductions: benefit deductions modelled "consistent with the 2025 Fair + Repayment Rate reform" (15% cap on UC deductions, down from 25%). + +Stairway to headroom Box 2 (distributional-analysis scope, pp.37-39): +models "just over half (52 per cent) of the total tax changes announced +since Autumn Budget 2024 and the majority (85 per cent) of the total +welfare spending changes; we model £20 billion of the total £34 billion"; +RDEL analysis covers "70 per cent" (£47bn of £67bn); "our distribution +analysis of changes to tax and benefits and our distributional analysis of +changes to public spending cannot sensibly be combined"; Treasury's +Budget-2025 distributional analysis models 2028-29 while RF models +2029-30 — direct RF-vs-HMT comparisons must adjust for this. + +## Diagnosis seeds / errata +1. **Source typo in Catching up? (p.3)**: "cost the Government £800m in + 2026-27, rising to **£1.85 million** in 2029-30" — plainly £1.85bn. + Staged 2026-27 only, typo flagged in the row note. +2. **Cross-publication cost drift**: same UC over-indexation measure + costed £800m (Catching up?, Oct 2025) vs £810m (HNTY, Apr 2026) for + 2026-27; LSO 2026 reports the *net* rebalancing package (uplift + + health-element cut) at £330m net cost 2026-27 → −£210m saving 2029-30. + Three different scopes — do not treat as contradictions. +3. **Same-group different-vintage gains**: poorest-fifth average gain from + two-child-limit removal is **£290** (HNTY, 2026-27 impact) vs **£360** + (Stairway, 2029-30 impact in 2025-26 prices) — year and price base + differ, both staged with conditions. +4. RF flags (LSO 2025, p.31) that HBAI outturns are "expected to be + revised in March 2026 as part of a welcome stats overhaul using + administrative data", with "a likely consequence... an (even) lower + pensioner poverty rate" — vintage risk on any pre-2026 RF level. + +## UK triangulation (overlap with IFS / OBR / DWP on the same measures) +- **Child poverty projections**: RF LSO 2026 (33% → 30% relative AHC, + −420k children in 2026-27) vs **DWP's own February 2026 projections** + ("also project a fall in child poverty from 33 per cent in 2025-26 to + 30 per cent in 2026-27" — RF footnote 21) vs IFS's living-standards + projections. Three-way UK poverty triangle on identical + concept/period. +- **Two-child limit repeal**: RF (£2.4bn 2026-27 → £3.1bn 2029-30, HMT + scorecard; 510k families; £4,560 avg gain; govt −450k children) — IFS + and JRF publish rival costings/poverty impacts of the same reform; + PE-runnable as a parametric UK reform. +- **Budget 2025 decile impacts**: RF Stairway (2029-30, AHC deciles) vs + **HM Treasury's own distributional analysis** (2028-29) vs IFS + post-Budget analysis — same event, three models, documented scope + difference (52% of tax measures modelled). +- **April 2026 uprating rates** (3.8% CPI-linked / 4.8% State Pension / + 6.2% UC / 6.8% under-25 UC / 1.5% existing UC-health / 0% LHA): pure + parameter checks against policyengine-uk uprating parameters; also + OBR EFO Nov 2025 carries the same UC Act 2025 path. +- **RHDI vs HBAI**: Measuring-household-income spotlight (2026-07-31) + reconciles ONS RHDI with DWP HBAI — useful when Scorecard compares + OBR (RHDI-based) with RF/IFS (HBAI-based) income-growth rows. + +## Blockers / follow-ups +- No chart-data files exist to fetch (see above) — full decile/vigintile + series would need RF correspondence or figure digitisation. +- It's personal (taxation) PDF yields no text via pdftotext; retry with + `-raw`/OCR next pass. +- Annex 1 of LSO 2025 has per-nation child poverty projections (table not + parsed this pass — PDF table extraction needed). +- Low Pay Britain 2025 (minimum wage bite/coverage) downloaded but + unmined; State of the nations Scotland section cites Scottish + Government cumulative impact assessment (SCP −10pp/−100k children in + 2026-27) — government-model numbers, left unstaged deliberately. diff --git a/sources/harvest-uk-2026-08-02/uk_resolution_foundation/claims_staged.jsonl.gz b/sources/harvest-uk-2026-08-02/uk_resolution_foundation/claims_staged.jsonl.gz new file mode 100644 index 0000000000000000000000000000000000000000..530dc194faa82cecdf855ec487c0a7ccfa1212b2 GIT binary patch literal 5855 zcmV<579i;#iwFP!000021MOXHZ{kX_{(gT&X`~UL!Nj}<66s#eWY3(;-FeewW{*}{ z2^rIXZ;b70n=qWC{qI}V-G0M{KtdAm^!czm!FIn@Jx^D6S6BV@DsUIR$zEN+E1w0f zy$CJW8BW}VGdAd-uj(LQ8P44?v$wuz8n!j^`JY3d+58{D%<|}?8MDVjcM;Nip*3g2 zkr7w{J(*YmemGn)!>5NH^DTFb4_bPwi+|r4_JZ1{H`?v!&!KND>C<)_@O3bm!^<^Y zXKe9G@!?;uEXQ=QBK*~4UP$j7lMr8@xr@MZreL~37(n&y^;M0&X8*siuyiXB{kcf} z!p6L1?j7^P)zG#aIbhVqJ64Agv)v{1^w;1{V9v&t;ee=}zFRm}IP_d^VaFw#Gs_

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Early lessons from the introduction of Adult Disability Payment in Scotland", "date": "2025-12-08", "sha256": "68c78d17f585b302e9016911ba9e6de988daa5b9e70d8919e5e76b618b52f30b", "local_path": "downloads/Delivering-dignity.pdf", "doc_type": "spotlight", "landing_page": "https://www.resolutionfoundation.org/publications/delivering-dignity/", "retrieved": "2026-08-02", "publisher": "Resolution Foundation"} +{"url": "https://www.resolutionfoundation.org/app/uploads/2026/07/Much-ado-about-puffins.pdf", "title": "Much ado about PuFins: How the UK's public financial institutions can unlock billions for investment", "date": "2026-07-20", "sha256": "cd9cebbef6288e2410e20dd46bd085c7399a8b46807fe1e2bf460d36857b413d", "local_path": "downloads/Much-ado-about-PuFins.pdf", "doc_type": "briefing", "landing_page": "https://www.resolutionfoundation.org/publications/much-ado-about-pufins/", "retrieved": "2026-08-02", "publisher": "Resolution Foundation"} +{"url": "https://www.resolutionfoundation.org/app/uploads/2026/07/Measuring-household-income.pdf", "title": "Measuring household income: Explaining the differences between RHDI and HBAI", "date": "2026-07-31", "sha256": "01b6a8265b19e01529695fdefadf1d641a66b39114bda370e971f2d2753616af", "local_path": "downloads/Measuring-household-income.pdf", "doc_type": "spotlight", "landing_page": "https://www.resolutionfoundation.org/publications/measuring-household-income/", "retrieved": "2026-08-02", "publisher": "Resolution Foundation"} +{"url": "https://www.resolutionfoundation.org/app/uploads/2026/05/State-of-the-nations-final.pdf", "title": "The state of the nations: Devolution and social security", "date": "2026-05-21", "sha256": "ed9437e76bc40db346c65a72ce05aff6534fbf43f65289c97cd3dc2a356e70ba", "local_path": "downloads/State-of-the-nations.pdf", "doc_type": "report", "landing_page": "https://www.resolutionfoundation.org/publications/the-state-of-the-nations/", "retrieved": "2026-08-02", "publisher": "Resolution Foundation"} +{"url": "https://www.resolutionfoundation.org/app/uploads/2026/01/NYO2026.pdf", "title": "New Year Outlook 2026", "date": "2026-01-05", "sha256": "0d56ea5890d54dbbae5cd52a0b163afdf30e921b6aab7bf5eea168d80538d7f0", "local_path": "downloads/New-Year-Outlook-2026.pdf", "doc_type": "briefing", "landing_page": "https://www.resolutionfoundation.org/publications/new-year-outlook-2026/", "retrieved": "2026-08-02", "publisher": "Resolution Foundation"} diff --git a/sources/harvest-uk-2026-08-02/uk_ukmod_jrf/NOTES.md b/sources/harvest-uk-2026-08-02/uk_ukmod_jrf/NOTES.md new file mode 100644 index 0000000..4c1d0e7 --- /dev/null +++ b/sources/harvest-uk-2026-08-02/uk_ukmod_jrf/NOTES.md @@ -0,0 +1,139 @@ +# uk_ukmod_jrf — coverage, quirks, parse confidence (2026-08-02) + +Two targets in one lane: **UKMOD** (ISER/Essex tax-benefit microsimulation, CeMPA +working papers) and **JRF** (Joseph Rowntree Foundation). 1,782 staged claims +(ukmod 1,392 / jrf 390), 5 manifested artifacts, zero bot-mitigation bypasses. + +## Robots compliance +- iser.essex.ac.uk: `User-agent: *` allow-all. ukmod.iser.essex.ac.uk: no robots.txt. +- jrf.org.uk: `Crawl-delay: 20` honored — jrf.org.uk requests spaced >20s (3 total: + robots, landing page, MIS PDF). The data workbook is served from + jrf-jrht-brand.frontify.com (their brand-asset CDN; the landing page's own + download link). Honest UA with contact email on every request. +- microsimulation.ac.uk: blocks only named commercial crawlers; not needed beyond search. + +## UKMOD side (source "ukmod") + +### CeMPA WP 8/26 — UKMOD Country Report 2023-2030 (van de Ven & Popova, Apr 2026) +UKMOD B2026.01, FRS 2023/24 input (HBAI-adjusted weights/incomes), forecasts from 2025. +Staged the full Section-4 validation block — **another microsimulation's published +self-validation, simulated and official columns side by side**: +- **Table 4.5** caseloads (thousands): 38 rows × (8 UKMOD policy years 2023-2030 + + 8 official-estimate years). Benefits → metric `caseload`; income tax/NIC payers → + proposed `taxpayer_count`. Caseload unit per table note: families except + (c) children, (h) households, (i) individuals; NIC/tax rows are people. +- **Table 4.6** expenditure/revenue (£m): 38 rows. Benefits → `benefit_cost` + (proposed_unit gbp); taxes/NIC → proposed `tax_revenue`. +- **Table 4.7** income distribution (BHC, modified-OECD, individual unit): Gini, + mean/median £/month, quintile medians and shares × {UKMOD 2023-2030, Input Data + 2023, HBAI 2023}. +- **Table 4.8** poverty rates below 50/60/70% median **BHC** (NB: UKMOD's validation + poverty is BHC; JRF headline is AHC — never cross-compare without the flag) for + all/children/over-SPA/men/women × same 10 series. +- `conditions.series` = `ukmod_simulated` | `official_estimate` | `input_data` | `hbai`. + Official-estimate cells are SECOND-HAND transcriptions of DWP/HMRC/SSS/OBR/SFC + numbers as cited by UKMOD (full citation string on each row + + `official_sources_note`); first-hand twins arrive via the dwp/hmrc/obr lanes — + dedup at ingest, and the (UKMOD-cited vs first-hand) delta is itself diagnosis + material. +- Parse method: anchor on UKMOD variable names (bch_s, tin12_s, …) in the + pdftotext -layout text; scoped label anchors for income-tax band sub-rows; + 10 hard-coded spot-check cells asserted on every run (`stage_claims.py`). +- **PDF quirks (verbatim in source):** continuation-page year headers on Tables + 4.5/4.6 print "… 2029 2029" where page 1 prints "… 2029 2030" — columns mapped + positionally per the page-1 header. Table 4.6's source line is garbled + ("Source: UKMOD and , and Scottish Government statistics…"). WFA 2024 collapse + (12,057k → 1,583k simulated; 11,626k → 1,268k official) is the real + winter-fuel-payment restriction, not a parse error. +- Report's own health warnings (§4.3, worth quoting at diagnosis time): take-up + probabilities other than Scotland/pension-age **not updated since 2021**; IS + over-simulated / ESA under-simulated (limited-capability-for-work imputation); + child poverty understates HBAI (take-up assumptions); tax credits understate + admin data (prior-year income + finalised awards); UKMOD policy year = Apr-Mar + fiscal year (report §2, "financial year … April to March") → period = start + year, conditions.fy = "YYYY/YY". +- NOT staged (available in the PDF for a second pass): Annex 6.6 FRS-only twins + of all four tables (Tables 6.10-6.15) — useful for input-data-sensitivity + diagnosis; Table 4.2 earnings by subgroup; COVID-era shock tables. + +### CeMPA WP 3/26 — Autumn Budget policy assessment (Frimpong, Feb 2026) +UKMOD static scoring of the Autumn Budget package (income tax threshold freezes, +UC two-child limit removal, WFA restrictions, Pension Credit reductions); +reform_hint verbatim on every row. Staged: Table 1 (UK fiscal overview 2026-2030: +revenue/expenditure levels baseline+reform, revenue_change, expenditure_change, +net_fiscal_impact), Table 1.2 (by nation + per-capita), Table 2 (fixed-line AHC +poverty counts baseline/reform/change by group, 2026+2030), Table 2.1 (poverty +count change by nation, all years), Table 2.4 (child poverty rate baseline→reform +by nation + count change), Tables 3a/3b (Gini + S80/S20, AHC and BHC, +baseline/reform/change). Every transcribed raw string machine-verified to appear +in the extracted text. NOT staged: Tables 4/4.1 (income shares by decile), +5/5.1 (mean income by decile), gainers/losers §8 — in the PDF, second pass. +- **Title-year quirk:** WP title says "Autumn Budget Statement 2026", inner cover + says "…2025". Measures match the Nov-2025 Autumn Budget (two-child limit + removal etc.) analyzed over 2026-2030. Kept the WP title verbatim in + publication; flagged here. +- Baseline is UKMOD's pre-Budget system; `conditions.scenario` = + baseline | reform | reform_minus_baseline. No executable reform dict staged — + ingest should build the PE-UK parametric reform from the hint. + +## JRF side (source "jrf") + +### UK Poverty 2026 data workbook (published 2026-01-27) +81-sheet xlsx behind the landing page's download button — fully machine-readable, +many series **unrounded** (e.g. OG1 poverty rates to 15 decimals). Underlying data +per sheet's own Source row — mostly **HBAI 2023/24 (DWP)**; DDT1 is Understanding +Society. JRF headline measure = relative poverty, **below 60% median AHC** +(deep = 50%, very deep = 40%; persistent = AHC relative poverty in 3+ of last 4 +years — definitions sheet A1T2). +Staged: OT1 (headline counts+rates, 12 groups, 2023/24), GT1 (14 nations/regions, +3-year average 2021-2024 per table title), DDT1 (persistent poverty + persistent +very deep poverty, 17 groups, 2022-23), OG1 (headline AHC rate time series +1994/95-2023/24 × 5 groups, 150 obs, unrounded; UK from 2002/03, GB before), +FAST2 (child poverty by family size/parents/age, 13 subgroups), A1T1 (poverty/ +deep/very-deep thresholds + median by 5 family types, weekly unrounded + annual +rounded; income concept not stated on-sheet — flagged in conditions). +- Rate cells mix fractions (0.21) and percents (21) across sheets — deterministic + rule value>1 ⇒ /100, normalization recorded per row. +- `calibration_relationship` left `held_out` BUT: these are HBAI-derived numbers. + Whether policyengine-uk consumes HBAI poverty stats as calibration targets was + NOT verified this session — audit against policyengine-uk calibration configs + at ingest before any "held-out validation" claim. +- NOT staged (clean, high-value second pass): EXG2/DDG1 poverty-depth composition + time series; GM2 child poverty by Westminster constituency (local-area + validation surface); SSG2/SST1 poverty by benefit receipt; HOT1/HOG1 by tenure; + WG1-4 work status; EG1-3 ethnicity; A3G1 median income BHC/AHC series. + +### Minimum Income Standard 2025 (JRF / CRSP Loughborough) +Table 2 weekly budgets, April 2025, 4 household types × 16 components + 6 totals +(incl. AHC-comparable and BHC-comparable totals) = 88 cells, all verified against +extracted text. proposed_metric `minimum_income_standard_budget`. MIS is a +consensus budget standard, NOT HBAI-derived — noted in publication.vintage. +- **Erratum seed:** 2024 MIS working-age couple budgets omitted one mobile phone + (~£3/wk); corrected in 2025 (report note). Any 2024-vintage MIS comparison + should expect this. + +## Schema / ingest worklist for this lane +- proposed_unit **gbp** (+ gbp_per_week/_year/_month/_person) everywhere monetary — + UnitConcept has USD only. value_kind used: count | share | **currency_gbp** + (extension needed). +- proposed_metric recurring: tax_revenue, taxpayer_count, poverty_count, + government_revenue/expenditure, expenditure_change, net_fiscal_impact(_per_capita), + gini_coefficient(_change), s80_s20_ratio(_change), income_share, + mean/median_equivalised_disposable_income, median_income, poverty_threshold, + persistent_poverty_rate, minimum_income_standard_budget. +- Load-bearing conditions on every distribution row: income_concept (BHC for + UKMOD validation; AHC for JRF headline + CeMPA fixed-poverty; both in 3a/3b), + equivalisation, series, scenario, fy (Apr-Mar). +- Period: UK fiscal year start-year int + conditions.fy label; GT1 carries a + 3-year window condition; DDT1 a 4-wave window. + +## Blockers / follow-ups +- None hard. ISER fully open (no Cloudflare); JRF fine at 20s spacing; frontify + CDN unrestricted. +- ukmod.iser.essex.ac.uk itself (the model's own site) not needed for tables this + round — country report carries the validation block. 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Staged as period=1900 upstream; the label is authoritative. + assert parse_fy("1999/00") == (1999, "1999-00") + + def test_non_contiguous_rejected(self): + with pytest.raises(ValueError): + parse_fy("2026-28") + with pytest.raises(ValueError): + parse_fy("not a year") + + def test_windows(self): + assert parse_fy_window("2025-26 to 2029-30") == ( + 2025, 2029, "2025-26 to 2029-30", + ) + assert parse_fy_window("2021/22-2023/24") == ( + 2021, 2023, "2021-22 to 2023-24", + ) + + +class TestFullAccounting: + """scores + ledger + deliberate drops (+ merged twins) == staged.""" + + def test_obr(self, obr): + scores, ledger = obr + assert len(scores) == 25425 + assert len(ledger) == 133 + assert len(scores) + len(ledger) == 25558 + + def test_dwp(self, dwp): + scores, ledger = dwp + assert len(scores) == 1952 + assert len(ledger) == 102 + assert len(scores) + len(ledger) == 2054 + + def test_hmrc(self, hmrc): + scores, ledger = hmrc + assert len(scores) == 987 + assert len(ledger) == 1855 + assert len(scores) + len(ledger) == 2842 + + def test_hmt(self, hmt): + scores, ledger = hmt + assert (len(scores), len(ledger)) == (1368, 0) + + def test_ukmod_jrf(self, ukmod_jrf): + scores, ledger, dropped_mis = ukmod_jrf + merged = sum( + 1 for s in scores if "also_published" in s.publication + ) + assert dropped_mis == 88 + assert merged == 2 + assert len(scores) + dropped_mis + merged == 1782 + + def test_ifs(self, ifs): + scores, ledger = ifs[0], ifs[1] + assert (len(scores), len(ledger)) == (268, 0) + + def test_rf(self, rf): + scores, _, dropped = rf + assert len(scores) == 70 + assert dropped == 1 # price-index-only row, out of model scope + + +class TestLedgerRouting: + """Admin outturn facts never enter external_scores (Max 2026-08-02).""" + + def test_no_outturn_reaches_scores(self, obr, dwp, hmrc): + for scores, _ledger, *rest in (obr, dwp, hmrc): + for s in scores: + assert s.conditions.get("basis") not in ( + "outturn", "provisional", + ), s.conditions + + def test_ledger_rows_carry_provenance_and_ids(self, hmrc): + _, ledger = hmrc + for row in ledger[:10]: + assert row["fact_id"].startswith("uk:uk_hmrc:") + assert "routing rule" in row["routed_because"] + assert row["staged"]["conditions"]["basis"] in ( + "outturn", "provisional", + ) + + def test_survey_outcomes_stay_scorecard_side(self, dwp): + scores, _ = dwp + hbai = [s for s in scores if s.source_model == "dwp_hbai_frs"] + assert len(hbai) == 1040 # HBAI is a survey outcome, not admin + + def test_staging_file_is_deterministic(self, tmp_path): + rows = [ + ledger_row("uk_x", {"a": 1}, "test"), + ledger_row("uk_x", {"a": 2}, "test"), + ] + p = tmp_path / "ledger.jsonl" + assert write_ledger_staging(rows, p) == 2 + first = p.read_text() + write_ledger_staging(list(reversed(rows)), p) + assert p.read_text() == first # sorted by fact id + + def test_duplicate_fact_ids_raise(self, tmp_path): + rows = [ledger_row("uk_x", {"a": 1}, "test")] * 2 + with pytest.raises(ValueError, match="duplicate"): + write_ledger_staging(rows, tmp_path / "ledger.jsonl") + + def test_identical_cells_in_different_sections_stay_distinct(self): + staged = {"value": 1.0, "conditions": {"line_item": "DWP"}} + a = ledger_row("uk_obr", staged, "r", derived={"section": "cap"}) + b = ledger_row("uk_obr", staged, "r", derived={"section": "total"}) + assert a["fact_id"] != b["fact_id"] + + +class TestOBR: + def test_consumed_lines_match_pe_uk_data_exactly(self, obr): + scores, _ = obr + consumed = [ + s + for s in scores + if s.calibration_relationship is CR.CONSUMED_AS_TARGET + ] + # 25 line-families (12 receipts/CT/NICs heads incl. the 3.4/3.8 + # twins + 13 welfare (line, section) pairs) × 6 forecast years. + assert len(consumed) == 150 + assert all(s.conditions["basis"] == "forecast" for s in consumed) + assert all( + "calibration_basis" in s.publication for s in consumed + ) + welfare = { + (s.conditions["line_item"], s.conditions["section"]) + for s in consumed + if s.conditions["table"] == "4.9" + } + assert ("Universal credit", "welfare_cap") in welfare + assert ("Universal credit", "outside_welfare_cap") in welfare + assert ("State pension", "outside_welfare_cap") in welfare + + def test_measures_are_reform_worlds_with_verbatim_titles(self, obr): + scores, _ = obr + measures = [ + s + for s in scores + if s.source_model == "hmt_scorecard_obr_database" + ] + assert len(measures) == 24304 + for s in measures[:50]: + assert s.reform.framework == "policy_ref" + assert s.reform.reform["policy"].startswith("uk_obr_measure:") + assert "measure" in s.conditions + assert "fiscal_event" in s.conditions + + def test_duplicate_titled_components_disambiguated(self, obr): + scores, _ = obr + pa95 = [ + s + for s in scores + if s.conditions.get("fiscal_event") == "Budget 1995" + and s.conditions.get("measure") == "Increase PA" + and s.conditions["fy"] == "1996-97" + ] + assert len(pa95) == 3 + assert {s.conditions.get("component_seq") for s in pa95} == { + None, "2", "3", + } + # Same measure world — the database's unit of identity is the + # titled line; components are conditions axes. + assert len({s.reform.key() for s in pa95}) == 1 + + def test_efo_vintage_split(self, obr): + scores, _ = obr + efo = [s for s in scores if s.source_model == "obr_efo_forecast"] + vintages = { + (s.conditions["table"], s.conditions["data_vintage"]) + for s in efo + } + assert ("3.4", "march_2026_efo") in vintages + assert ("4.9", "november_2025_efo") in vintages + assert ("4.9", "march_2026_efo") not in vintages + + +class TestDWP: + def test_period_derived_from_fy(self, dwp): + scores, _ = dwp + assert min(s.period for s in scores) == 1994 # not 1900 + with_fy = [s for s in scores if "fy" in s.conditions] + for s in with_fy[:200]: + assert s.conditions["fy"].startswith(str(s.period)) + + def test_pc_takeup_seed_source(self, dwp): + scores, _ = dwp + pc = [ + s + for s in scores + if s.source_model == "dwp_takeup_estimates" + and s.conditions.get("program") == "pension_credit" + ] + assert pc and all( + s.calibration_relationship is CR.SEED_SOURCE for s in pc + ) + + def test_hb_takeup_held_out_comparator(self, dwp): + scores, _ = dwp + hb = [ + s + for s in scores + if s.source_model == "dwp_takeup_estimates" + and s.conditions.get("program") == "housing_benefit" + ] + assert hb and all( + s.calibration_relationship is CR.HELD_OUT for s in hb + ) + + def test_becl_consumption_exact(self, dwp): + scores, _ = dwp + becl_cost = [ + s + for s in scores + if s.source_model == "dwp_becl" + and s.metric is Metric.BENEFIT_COST + ] + consumed = { + s.conditions["program"] + for s in becl_cost + if s.calibration_relationship is CR.CONSUMED_AS_TARGET + } + assert consumed == { + "state_pension", "universal_credit", "pension_credit", + "attendance_allowance", "child_benefit", + } + # Components of the consumed DLA+PIP aggregate stay held out, + # and caseloads too (obr.py parses expenditure only). + for s in becl_cost: + if s.conditions["program"] in ("dla", "pip"): + assert s.calibration_relationship is CR.HELD_OUT + for s in scores: + if ( + s.source_model == "dwp_becl" + and s.metric is Metric.CASELOAD + ): + assert s.calibration_relationship is CR.HELD_OUT + + def test_uc_admin_consumed(self, dwp): + scores, _ = dwp + uc = [s for s in scores if s.source_model == "dwp_uc_admin"] + assert len(uc) == 5 + assert all( + s.calibration_relationship is CR.CONSUMED_AS_TARGET for s in uc + ) + + def test_hbai_editions_and_permanent_holdout(self, dwp): + scores, _ = dwp + hbai = [s for s in scores if s.source_model == "dwp_hbai_frs"] + assert {s.conditions["edition"] for s in hbai} == { + "fye_2025", "fye_2024", + } + assert all( + s.calibration_relationship is CR.HELD_OUT for s in hbai + ) + assert all( + "income_concept" in s.conditions + and "poverty_measure" in s.conditions + for s in hbai + ) + + +class TestHMRC: + def test_ready_reckoner_join_surface(self, hmrc): + scores, _ = hmrc + rr = [s for s in scores if s.source_model == "hmrc"] + assert len(rr) == 225 + slug = f"uk_hmrc_rr:{slugify('Change basic rate by 1p')}" + basic = [ + s + for s in rr + if s.reform.reform["policy"] == slug and s.period == 2026 + ] + assert len(basic) == 1 + assert basic[0].conditions["fy"] == "2026-27" + + def test_spi_family_seeded(self, hmrc): + scores, _ = hmrc + spi = [s for s in scores if s.source_model == "hmrc_spi"] + seeded = [ + s + for s in spi + if s.calibration_relationship is CR.SEED_SOURCE + ] + consumed = [ + s + for s in spi + if s.calibration_relationship is CR.CONSUMED_AS_TARGET + ] + assert len(seeded) == 726 + assert len(consumed) == 36 + for s in consumed: + assert s.metric is Metric.TAX_LIABILITY + assert s.conditions["band"].lower() in ( + "all", "total", "all taxpayers", + ) + + +class TestHMT: + def test_counts_and_suppression(self, hmt): + scores, _ = hmt + assert len(scores) == 1368 + assert sum(1 for s in scores if s.status == "suppressed") == 31 + costings = [ + s + for s in scores + if s.source_model == "hmt_costing_obr_certified" + ] + assert all( + s.metric is Metric.EXCHEQUER_IMPACT for s in costings + ) + assert all( + s.reform.framework == "policy_ref" for s in costings + ) + + def test_da_income_concept_verbatim(self, hmt): + scores, _ = hmt + da = [ + s + for s in scores + if s.source_model == "hmt_distributional_analysis_igotm" + ] + assert len(da) == 150 + assert all("equivalisation" in s.conditions for s in da) + + +class TestIFS: + def test_steady_state_baseline_world(self, ifs): + scores = ifs[0] + with_baseline = [ + s for s in scores if s.reform.baseline is not None + ] + assert len(with_baseline) == 108 + for s in with_baseline: + assert s.reform.baseline == { + "policy": "ifs_2cl_fp_removal_rolled_out" + } + assert ( + s.conditions["baseline_policy"] + == "ifs_2cl_fp_removal_rolled_out" + ) + assert s.conditions["horizon"] == "steady_state" + + def test_pentagon_leg_is_reform_keyed(self, ifs): + scores = ifs[0] + two_child = [ + s + for s in scores + if s.conditions.get("measure") == "Remove two-child limit" + and s.metric is Metric.POVERTY_COUNT_CHANGE + ] + children = [ + s + for s in two_child + if s.unit_concept.value == "children_under_18" + ] + assert [s.value for s in children] == [-540000.0] + + +class TestUKMODJRF: + def test_validation_series_axis(self, ukmod_jrf): + scores, _, _ = ukmod_jrf + series = { + s.conditions.get("series") + for s in scores + if s.source == "ukmod" + } + assert { + "ukmod_simulated", "official_estimate", "input_data", "hbai", + } <= series + + def test_cempa_package_world(self, ukmod_jrf): + scores, _, _ = ukmod_jrf + pkg = [ + s + for s in scores + if s.reform.framework == "policy_ref" + and s.reform.reform["policy"] + == "uk_autumn_budget_2025_package_cempa" + ] + assert len(pkg) == 209 + assert {s.conditions["scenario"] for s in pkg} == { + "reform", "reform_minus_baseline", + } + + def test_persistent_poverty_windows(self, ukmod_jrf): + scores, _, _ = ukmod_jrf + windows = [s for s in scores if s.period_start is not None] + assert len(windows) == 28 + for s in windows: + assert (s.period_start, s.period_end) == (2021, 2023) + assert s.conditions["window_kind"] == "annual_average" + + def test_amount_basis_remap(self, ukmod_jrf): + scores, _, _ = ukmod_jrf + assert not any( + s.conditions.get("basis") for s in scores + ) # weekly/annual lives in amount_basis, basis keeps UK meaning + assert any( + s.conditions.get("amount_basis") == "weekly" for s in scores + ) + + +class TestRF: + def test_attribution_rows_distinct(self, rf): + scores, _, _ = rf + attributed = [s for s in scores if "attribution" in s.conditions] + assert len(attributed) == 8 + + def test_uprating_parameter_checks(self, rf): + scores, _, _ = rf + uprating = [ + s for s in scores if s.metric is Metric.BENEFIT_UPRATING + ] + assert len(uprating) == 11 + assert all("program" in s.conditions for s in uprating) + + +class TestUKPermanentHoldouts: + def test_poverty_counts_never_calibrate(self): + from scorecard_db.relationships import never_calibrate + + assert never_calibrate(Metric.POVERTY_COUNT) + assert never_calibrate(Metric.PERSISTENT_POVERTY_RATE) + + +class TestUKIngestIntoDB: + """One thin end-to-end check: a small adapter lands in SQLite with + baseline keys registered and lanes set (the big ones are covered by + staging tests; the runner's DB path is shared machinery).""" + + def test_ifs_ingest_roundtrip(self, tmp_path): + from scorecard_db.baselines import register_baselines + from scorecard_db.ingest_uk_ifs import ingest + + db_path = tmp_path / "uk.db" + stats = ingest(db_path) + assert stats["scores"] == 268 + db = ScorecardDB(db_path) + register_baselines(db) + row = db.conn.execute( + "SELECT COUNT(*) n FROM external_scores" + " WHERE source='ifs' AND baseline_key != ?", + (BASELINE.baseline_key(),), + ).fetchone() + assert row["n"] == 108 # the steady-state-baseline block + label = db.conn.execute( + "SELECT label FROM baselines b JOIN external_scores s" + " ON s.baseline_key = b.baseline_key" + " WHERE s.source='ifs' AND b.label != 'current_law' LIMIT 1" + ).fetchone() + assert label["label"] == "ifs_2cl_fp_removal_rolled_out" + db.close() From e9feb21c301b8e2ba6ae9720f4a9c5bace40dcf4 Mon Sep 17 00:00:00 2001 From: Max Ghenis Date: Wed, 12 Aug 2026 07:37:26 -0400 Subject: [PATCH 3/4] Campaign compute batch: 177 PE results joined + two-child exhibits MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit sources/campaign-2026-08-02/ vendors the 2026-08-02 run files (full bundle provenance; npz arrays and logs stay outside) and scorecard_db/ingest_campaign.py joins them to existing claims by exactly-one-match DB queries: uk_reckoner 23 · uk_free_joins 25 · uk_obr_measures 10 · uk_uprating 6 · tpc 14 · pwbm 2 · cpsp 8 · jct_obbba 1 · cbo_free_joins 88 = 177 - Every result records the baseline actually executed (#13); the TPC option legs make the view guard observable (claim baseline Senate Title VII vs PE current_law — labels exposed, never plain agreement). - Reckoner deltas recomputed from vendored run+baseline aggregates and cross-checked against the campaign's own collations before landing; HMRC RR world slugs gained their tax_section (the same line title exists under VAT and IPT). - The campaign's DWP free-join legs turn out to anchor FY2025-26 cells (the runner selected staged END-year ints): results attach to the claims the values identify, with the vintage caveat annotated. - OBR measure reversals anchor to the dominant component row with the N-row component-sum anchor named (OBR decomposes measures by head). - April-2026 uprating parameter checks land comparable (PE tree matches RF to their stated precision); the LCWRA new/existing split and data-driven LHA stay not_computed with the check's own notes. - CPSP levels carry methodological_difference diagnoses (descriptive register; populace#593 EHS sub-channel cited). - AFA floor ambiguity lands as two constructions on one claim. - Two-child-limit family (calibrated + entitlements take-up + abs-line continuity pair) → 11 pe_exhibits rows, reform two_child_limit_removal vs registered pre_ab2025 baseline (direction explicit). Tests: 17 new (tests/test_campaign_ingest.py); suite 160 green. Co-Authored-By: Claude Fable 5 --- scorecard_db/ingest_campaign.py | 1060 +++++++++++++++++ scorecard_db/ingest_uk_hmrc.py | 9 +- sources/campaign-2026-08-02/run_meta.json | 41 + .../uk/additional_rate_1p_2026.json | 40 + .../uk/aggregates_2026.json | 200 ++++ .../campaign-2026-08-02/uk/baseline_2026.json | 47 + .../uk/basic_rate_1p_2026.json | 40 + .../uk/brl_10pct_2026.json | 40 + .../campaign-2026-08-02/uk/brl_1pct_2026.json | 40 + .../uk/cb_additional_1pw_2026.json | 40 + .../uk/cb_first_1pw_2026.json | 40 + .../uk/class4_1pp_2026.json | 40 + .../uk/dividend_allowance_100_2026.json | 40 + .../uk/employee_additional_1pp_2026.json | 40 + .../uk/employee_ni_1pp_2026.json | 40 + .../uk/employer_ni_1pp_2026.json | 40 + .../uk/fixed_line/with_limit_2026_meta.json | 34 + .../with_limit_fulltakeup_2026_meta.json | 45 + .../fixed_line/without_limit_2026_meta.json | 34 + .../without_limit_fulltakeup_2026_meta.json | 45 + sources/campaign-2026-08-02/uk/free_joins.csv | 24 + .../uk/free_joins_summary.json | 118 ++ .../uk/higher_rate_1p_2026.json | 40 + .../uk/ni_lpl_104_2026.json | 40 + .../uk/ni_pt_2pw_2026.json | 40 + .../uk/ni_st_2pw_2026.json | 40 + .../uk/ni_uel_10pw_2026.json | 40 + .../uk/ni_upl_520_2026.json | 40 + .../uk/obr_measures/art_as2022_2026.json | 47 + .../uk/obr_measures/cgt_ab2024_2026.json | 47 + .../obr_measures/class2_reinstate_2026.json | 47 + .../uk/obr_measures/class4_p3_2026.json | 47 + .../uk/obr_measures/div_ab2021_2026.json | 47 + .../uk/obr_measures/ee_ni_p2_2026.json | 47 + .../uk/obr_measures/ee_ni_p4_2026.json | 47 + .../uk/obr_measures/employer_ab2024_2026.json | 47 + .../uk/obr_measures/hicbc_sb2024_2026.json | 47 + .../uk/obr_measures/pt_lpl_ss2022_2026.json | 47 + .../uk/obr_measures_collation.csv | 11 + .../campaign-2026-08-02/uk/pa_100_2026.json | 40 + .../campaign-2026-08-02/uk/pa_10pct_2026.json | 40 + .../campaign-2026-08-02/uk/pa_1pct_2026.json | 40 + .../uk/psa_100_50_2026.json | 40 + .../campaign-2026-08-02/uk/srl_100_2026.json | 40 + .../campaign-2026-08-02/uk/t2_collation.csv | 15 + .../uk/two_child_fixed_line_2026.json | 338 ++++++ .../two_child_fixed_line_fulltakeup_2026.json | 360 ++++++ .../uk/two_child_limit_removal_2026.json | 47 + .../uk/two_child_reinstate_2026.json | 47 + .../uk/uk_scorecard_first.csv | 11 + .../uk/uprating_check_april2026.json | 144 +++ .../campaign-2026-08-02/uk/vat_1pp_2026.json | 40 + sources/campaign-2026-08-02/us/SPM_NOTES.md | 40 + .../us/cpsp_ctc/NOT_COMPUTED_2023.json | 14 + .../us/cpsp_ctc/afa_2024.json | 99 ++ .../us/cpsp_ctc/comparison_2024.json | 243 ++++ .../us/cpsp_ctc/no_ctc_2024.json | 97 ++ .../us/cpsp_ctc/obbba_2024.json | 99 ++ .../us/cpsp_ctc/staged_rows_2024.jsonl | 8 + .../us/cpsp_ctc/tcja_2024.json | 94 ++ .../campaign-2026-08-02/us/free_joins_cbo.csv | 89 ++ .../us/free_joins_cbo_summary.json | 79 ++ .../us/obbba_family/RUNNABILITY.md | 56 + .../us/obbba_family/ctc_ext_2026.json | 54 + .../us/pwbm_ss/ss_notax_2025.json | 43 + .../us/pwbm_ss/ss_notax_2026.json | 43 + .../us/tpc_ctc/afa_bill_floor_2026.json | 66 + .../us/tpc_ctc/afa_onto_obbba_2026.json | 66 + .../us/tpc_ctc/assembly_grid.json | 114 ++ .../us/tpc_ctc/baseline_2025.json | 65 + .../us/tpc_ctc/baseline_2026.json | 65 + .../us/tpc_ctc/ctc_opt1_2025.json | 52 + .../us/tpc_ctc/ctc_opt1_2026.json | 52 + .../us/tpc_ctc/ctc_opt2_2025.json | 53 + .../us/tpc_ctc/ctc_opt2_2026.json | 53 + .../us/tpc_ctc/ctc_opt3_2025.json | 54 + .../us/tpc_ctc/ctc_opt3_2026.json | 54 + .../us/tpc_ctc/toprate_opt1_2026.json | 52 + .../us/tpc_ctc/toprate_opt2_2026.json | 52 + .../us/tpc_ctc/toprate_opt3_2026.json | 52 + .../us/tpc_ctc/total_opt1_2026.json | 53 + .../us/tpc_ctc/total_opt2_2026.json | 54 + .../us/tpc_ctc/total_opt3_2026.json | 55 + tests/test_campaign_ingest.py | 275 +++++ tests/test_uk_ingest.py | 5 +- 85 files changed, 6368 insertions(+), 2 deletions(-) create mode 100644 scorecard_db/ingest_campaign.py create mode 100644 sources/campaign-2026-08-02/run_meta.json create mode 100644 sources/campaign-2026-08-02/uk/additional_rate_1p_2026.json create mode 100644 sources/campaign-2026-08-02/uk/aggregates_2026.json create mode 100644 sources/campaign-2026-08-02/uk/baseline_2026.json create mode 100644 sources/campaign-2026-08-02/uk/basic_rate_1p_2026.json create mode 100644 sources/campaign-2026-08-02/uk/brl_10pct_2026.json create mode 100644 sources/campaign-2026-08-02/uk/brl_1pct_2026.json create mode 100644 sources/campaign-2026-08-02/uk/cb_additional_1pw_2026.json create mode 100644 sources/campaign-2026-08-02/uk/cb_first_1pw_2026.json create mode 100644 sources/campaign-2026-08-02/uk/class4_1pp_2026.json create mode 100644 sources/campaign-2026-08-02/uk/dividend_allowance_100_2026.json create mode 100644 sources/campaign-2026-08-02/uk/employee_additional_1pp_2026.json create mode 100644 sources/campaign-2026-08-02/uk/employee_ni_1pp_2026.json create mode 100644 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create mode 100644 sources/campaign-2026-08-02/uk/pa_10pct_2026.json create mode 100644 sources/campaign-2026-08-02/uk/pa_1pct_2026.json create mode 100644 sources/campaign-2026-08-02/uk/psa_100_50_2026.json create mode 100644 sources/campaign-2026-08-02/uk/srl_100_2026.json create mode 100644 sources/campaign-2026-08-02/uk/t2_collation.csv create mode 100644 sources/campaign-2026-08-02/uk/two_child_fixed_line_2026.json create mode 100644 sources/campaign-2026-08-02/uk/two_child_fixed_line_fulltakeup_2026.json create mode 100644 sources/campaign-2026-08-02/uk/two_child_limit_removal_2026.json create mode 100644 sources/campaign-2026-08-02/uk/two_child_reinstate_2026.json create mode 100644 sources/campaign-2026-08-02/uk/uk_scorecard_first.csv create mode 100644 sources/campaign-2026-08-02/uk/uprating_check_april2026.json create mode 100644 sources/campaign-2026-08-02/uk/vat_1pp_2026.json create mode 100644 sources/campaign-2026-08-02/us/SPM_NOTES.md create mode 100644 sources/campaign-2026-08-02/us/cpsp_ctc/NOT_COMPUTED_2023.json create mode 100644 sources/campaign-2026-08-02/us/cpsp_ctc/afa_2024.json create mode 100644 sources/campaign-2026-08-02/us/cpsp_ctc/comparison_2024.json create mode 100644 sources/campaign-2026-08-02/us/cpsp_ctc/no_ctc_2024.json create mode 100644 sources/campaign-2026-08-02/us/cpsp_ctc/obbba_2024.json create mode 100644 sources/campaign-2026-08-02/us/cpsp_ctc/staged_rows_2024.jsonl create mode 100644 sources/campaign-2026-08-02/us/cpsp_ctc/tcja_2024.json create mode 100644 sources/campaign-2026-08-02/us/free_joins_cbo.csv create mode 100644 sources/campaign-2026-08-02/us/free_joins_cbo_summary.json create mode 100644 sources/campaign-2026-08-02/us/obbba_family/RUNNABILITY.md create mode 100644 sources/campaign-2026-08-02/us/obbba_family/ctc_ext_2026.json create mode 100644 sources/campaign-2026-08-02/us/pwbm_ss/ss_notax_2025.json create mode 100644 sources/campaign-2026-08-02/us/pwbm_ss/ss_notax_2026.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/afa_bill_floor_2026.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/afa_onto_obbba_2026.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/assembly_grid.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/baseline_2025.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/baseline_2026.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/ctc_opt1_2025.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/ctc_opt1_2026.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/ctc_opt2_2025.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/ctc_opt2_2026.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/ctc_opt3_2025.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/ctc_opt3_2026.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/toprate_opt1_2026.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/toprate_opt2_2026.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/toprate_opt3_2026.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/total_opt1_2026.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/total_opt2_2026.json create mode 100644 sources/campaign-2026-08-02/us/tpc_ctc/total_opt3_2026.json create mode 100644 tests/test_campaign_ingest.py diff --git a/scorecard_db/ingest_campaign.py b/scorecard_db/ingest_campaign.py new file mode 100644 index 0000000..a6492de --- /dev/null +++ b/scorecard_db/ingest_campaign.py @@ -0,0 +1,1060 @@ +"""Ingest the 2026-08-02 campaign compute batch as PE results + exhibits. + +Inputs are vendored under sources/campaign-2026-08-02/ (run JSONs with +full bundle provenance, the campaign's own collation CSVs, and CPSP's +pre-staged result rows; .npz world arrays and logs stay outside, named +in the run metas). Every result row records the baseline the run +actually executed (issue #13) and joins to an existing claim by DB +query — exactly-one-match is asserted, so vocabulary drift fails +loudly, never silently misattaches. + +Join families: + +1. **UK ready reckoner** (23 runs ↔ hmrc RR claims via slugified staged + hint): computed_value is the |head-delta| magnitude (HMRC publishes + per-direction magnitudes; the signed PE delta and heads ride + annotations), cross-checked against the campaign's own collations + (t2_collation.csv, uk_scorecard_first.csv) before landing. +2. **UK free joins** (free_joins.csv ↔ OBR EFO revenue levels and DWP + BECL forecast lines by line/value match); skipped rows land as + not_computed with the scoping reason verbatim. +3. **OBR measure reversals** (obr_measures_collation.csv ↔ measures- + database claims by (value, period) with head disambiguation). +4. **April-2026 uprating checks** (uprating_check_april2026.json ↔ RF + benefit_uprating claims — the one `comparable` family here: pure + parameter-tree checks, no data artifact involved). +5. **TPC T25-0209 / T26-0029** (16 runs; income-tax deltas vs the + vendored same-bundle baselines; the AFA floor ambiguity lands as TWO + results on one claim — both constructions preserved). +6. **PWBM SS-benefits-tax elimination** (FY2025/FY2026 claims). +7. **CPSP CTC counterfactual levels** (pre-staged rows ↔ cpsp claims; + plus the descriptive-register diagnoses: methodological_difference + with the populace#593 EHS sub-channel in the rationale). +8. **JCT OBBBA CTC-extension provision** (expiry-counterfactual delta + vs JCX-35-25 Chapter-1 provision 4, sequential-stack caveat named). +9. **US CBO free joins** (free_joins_cbo.csv ↔ cbo claims by + program/metric/period/source_column). + +PE-only counterfactuals — the two-child-limit removal family (floating/ +fixed line × calibrated/entitlements take-up, plus the absolute-line +continuity pair) — have no external claim at their construction and +land in pe_exhibits with reform two_child_limit_removal against the +registered pre_ab2025 baseline (direction explicit, #13 point 5). + +Statuses follow the descriptive register: cross-convention comparisons +are `constructed` with named deltas; scoping skips are `not_computed` +with reasons; nothing here is `pe_gap` (no capability claims). +""" + +from __future__ import annotations + +import csv +import json +from pathlib import Path + +from .baselines import register_baselines +from .db import ScorecardDB +from .harvest import REPO +from .models import ( + BASELINE, + ComparisonStatus, + PEResult, + baseline_key, +) +from .uk import slugify + +CAMPAIGN = REPO / "sources" / "campaign-2026-08-02" +COMPUTED_AT = "2026-08-02T20:00:00" +CURRENT_LAW_KEY = BASELINE.baseline_key() +PRE_AB2025_KEY = baseline_key({"policy": "pre_ab2025"}) + + +def _load(rel: str): + return json.loads((CAMPAIGN / rel).read_text()) + + +def _rows(rel: str) -> list[dict]: + with (CAMPAIGN / rel).open() as f: + return list(csv.DictReader(f)) + + +def _one(db: ScorecardDB, what: str, sql: str, args: tuple) -> str: + hits = [r["claim_id"] for r in db.conn.execute(sql, args)] + if len(hits) != 1: + raise ValueError(f"campaign: {what}: {len(hits)} claims matched") + return hits[0] + + +def _bundle_meta(bundle: dict) -> tuple[str, str]: + return bundle["model_version"], bundle["certified_data_build_id"] + + +# -- 1. UK ready reckoner ------------------------------------------------ +# run key -> (staged HMRC hint — verbatim, verified against the 74 staged +# reckoner lines — and the PE aggregate heads whose delta scores it). +RECKONER = { + "additional_rate_1p": ("Increase additional rate by 1p (yield)", + ("income_tax",)), + "basic_rate_1p": ("Change basic rate by 1p", ("income_tax",)), + "brl_10pct": ("Increase basic rate limit by 10% (cost)", + ("income_tax",)), + "brl_1pct": ("Change basic rate limit by 1%", ("income_tax",)), + "cb_additional_1pw": ( + "Increase subsequent child rate by £1 per week (cost)", + ("child_benefit",), + ), + "cb_first_1pw": ("Increase first child rate by £1 per week (cost)", + ("child_benefit",)), + "class4_1pp": ("Change Class 4 main rate by 1 percentage point", + ("national_insurance",)), + "dividend_allowance_100": ("Change dividend allowance by £100", + ("income_tax",)), + "employee_additional_1pp": ( + "Change Class 1 employee additional rate by 1 percentage point", + ("national_insurance",), + ), + "employee_ni_1pp": ( + "Change Class 1 employee main rate by 1 percentage point", + ("national_insurance",), + ), + "employer_ni_1pp": ( + "Change Class 1 employer rate by 1 percentage point", + ("ni_employer",), + ), + "higher_rate_1p": ("Change higher rate by 1p", ("income_tax",)), + "ni_lpl_104": ("Change lower profits limit by £104 per year", + ("national_insurance",)), + "ni_pt_2pw": ("Change employee entry threshold by £2 per week", + ("national_insurance",)), + "ni_st_2pw": ("Change employer threshold by £2 per week", + ("ni_employer",)), + "ni_uel_10pw": ("Change upper earnings limit by £10 per week", + ("national_insurance",)), + "ni_upl_520": ("Change upper profits limit by £520 per year", + ("national_insurance",)), + "pa_100": ("Change personal allowance by £100", ("income_tax",)), + "pa_10pct": ("Change personal allowance by 10%", ("income_tax",)), + "pa_1pct": ("Change personal allowance by 1%", ("income_tax",)), + "psa_100_50": ( + "Change Savings allowance by £100 for BR and £50 for HR taxpayers", + ("income_tax",), + ), + "srl_100": ( + "Change starting rate limit for savings income by £100", + ("income_tax",), + ), + "vat_1pp": ("Change standard rate by 1 percentage point", ("vat",)), +} +_RECKONER_CONVENTIONS = ( + "PE CY2026 static accrual vs HMRC projected FY2026-27 direct effects " + "(first-year cash vs fuller-year; TIE/behavioural response in the " + "HMRC reckoner per their methodology notes); magnitude comparison — " + "HMRC publishes per-direction magnitudes, signed PE delta in " + "annotations" +) + + +def reckoner_results(db: ScorecardDB) -> tuple[list[PEResult], list[str]]: + base = _load("uk/baseline_2026.json")["aggregates_gbp"] + t2 = {r["key"]: r for r in _rows("uk/t2_collation.csv")} + t1 = {r["reform"]: r for r in _rows("uk/uk_scorecard_first.csv")} + results, skipped = [], [] + for key, (hint, heads) in RECKONER.items(): + run = _load(f"uk/{key}_2026.json") + delta = sum( + run["aggregates_gbp"][h] - base[h] for h in heads + ) + # Cross-check against the campaign's own collation of this run. + if key in t2: + recorded = float(t2[key]["pe_delta_gbp"]) + if abs(delta - recorded) > 1e-3 * max(1.0, abs(recorded)): + raise ValueError( + f"campaign: {key} delta {delta} != t2 {recorded}" + ) + elif key in t1: + recorded = abs(float(t1[key]["pe_gbp_m"])) * 1e6 + if abs(abs(delta) - recorded) > 5e5: + raise ValueError( + f"campaign: {key} |delta| {abs(delta)} != " + f"tranche-1 {recorded}" + ) + else: + raise ValueError(f"campaign: {key} missing from collations") + + section_filter = ( + " AND json_extract(conditions,'$.tax_section')='VAT'" + if key == "vat_1pp" + else "" + ) + hits = [ + r["claim_id"] + for r in db.conn.execute( + "SELECT claim_id FROM external_scores WHERE source='hmrc'" + " AND source_model='hmrc' AND period=2026" + " AND json_extract(conditions,'$.measure')=?" + + section_filter, + (hint,), + ) + ] + if len(hits) > 1: + raise ValueError(f"campaign: {key}: {len(hits)} RR claims") + if not hits: + skipped.append( + f"{key}: no FY2026-27 claim for {hint!r} (reckoner line " + "publishes later years only)" + ) + continue + engine, data = _bundle_meta(run["bundle"]) + results.append( + PEResult( + claim_id=hits[0], + computed_value=abs(delta), + status=ComparisonStatus.CONSTRUCTED, + engine_version=engine, + data_bundle=data, + pe_construction=( + f"{run['pe_construction']}; heads={'+'.join(heads)}; " + f"reform={run['reform_json']}" + ), + run_id="uk-reckoner-2026", + computed_at=COMPUTED_AT, + annotations=[ + f"signed PE delta {delta:.0f} GBP", + _RECKONER_CONVENTIONS, + ], + baseline_key=CURRENT_LAW_KEY, + ) + ) + return results, skipped + + +# -- 2. UK free joins ---------------------------------------------------- +def _match_free_join_claims(db, source, label, period, value): + """Resolve a free-join row to claim ids plus any vintage caveat. + + The campaign runner selected staged rows by the staged period ints, + which for DWP BECL were END-year keyed — so its "2026" DWP values + are the FY2025-26 cells. The published value is the strong key: + match on it, and when the claim's (re-derived, start-year) period + disagrees with the CSV's, say so on the result rather than + misattach or hide it.""" + if source == "uk_obr": + sql = ( + "SELECT claim_id, period, value FROM external_scores" + " WHERE source='obr' AND metric='revenue_level'" + " AND json_extract(conditions,'$.line_item')=?" + ) + elif source == "uk_dwp": + sql = ( + "SELECT claim_id, period, value FROM external_scores" + " WHERE source='dwp' AND source_model='dwp_becl'" + " AND metric='benefit_cost'" + " AND json_extract(conditions,'$.program')=?" + ) + else: + raise ValueError(f"campaign: free-join source {source!r}") + rows = [ + r + for r in db.conn.execute(sql, (label,)) + if abs(r["value"] - value) <= 1e-6 * max(1.0, abs(value)) + ] + caveats = [ + f"claim describes FY starting {r['period']}, not the runner's " + f"nominal {period} — the campaign selected DWP rows by the " + "staged end-year ints (PE CY2026 vs this FY, named)" + for r in rows + if r["period"] != period + ] + return [r["claim_id"] for r in rows], (caveats[0] if caveats else None) + + +def free_join_results(db: ScorecardDB) -> list[PEResult]: + agg = _load("uk/aggregates_2026.json") + bundle = agg.get("bundle") or _load("uk/baseline_2026.json")["bundle"] + engine, data = _bundle_meta(bundle) + results = [] + for row in _rows("uk/free_joins.csv"): + period = int(row["period"]) + value = float(row["external_value"]) + claims, vintage_caveat = _match_free_join_claims( + db, row["source"], row["label"], period, value + ) + computed = row["status"] == "computed" + if computed and len(claims) != 1: + raise ValueError( + f"campaign: free-join {row['label']!r}: " + f"{len(claims)} claims" + ) + if not claims: + raise ValueError( + f"campaign: free-join {row['label']!r}: no claim" + ) + for cid in claims: + annotations = [ + a + for a in (row["conventions"], row["status"], + vintage_caveat) + if a and a != "computed" + ] + results.append( + PEResult( + claim_id=cid, + computed_value=( + float(row["pe_value"]) if computed else None + ), + status=( + ComparisonStatus.CONSTRUCTED + if computed + else ComparisonStatus.NOT_COMPUTED + ), + engine_version=engine, + data_bundle=data, + pe_construction=row["pe_construction"], + run_id="uk-free-joins-2026", + computed_at=COMPUTED_AT, + annotations=annotations, + baseline_key=CURRENT_LAW_KEY, + ) + ) + return results + + +# -- 3. OBR measure reversals -------------------------------------------- +# key -> the hint substring the campaign runner matched (its external +# anchor is the SUM of the measure's per-head component rows at the +# period — OBR decomposes each measure across tax heads, and the 3.17 +# re-estimate rows join the same titles). +_MEASURE_SUBSTRINGS = { + "hicbc_sb2024": ( + "High Income Child Benefit Charge: increase income threshold to " + "£60,000" + ), + "ee_ni_p2": "2 percentage point cut to the main rate", + "ee_ni_p4": "2p cut to the main rate of Class 1 employ", + "class4_p3": "1p cut to the main rate of Class 4", + "class2_reinstate": "abolish Class 2 self-employed NICs", + "employer_ab2024": ( + "Employer National Insurance contributions: Increase rate by " + "1.2 ppts" + ), + "art_as2022": "reduce additional rate threshold from £150,000", + "div_ab2021": "Increase rates of dividend tax by 1.25%", + "cgt_ab2024": "Increase the main rates of CGT to 18% and 24%", + "pt_lpl_ss2022": ( + "increase annual primary threshold and lower profits limit" + ), +} + + +def obr_measure_results(db: ScorecardDB) -> list[PEResult]: + results = [] + for row in _rows("uk/obr_measures_collation.csv"): + if row["status"] != "computed": + raise ValueError( + f"campaign: obr measure {row['key']}: {row['status']!r}" + ) + run = _load(f"uk/obr_measures/{row['key']}_2026.json") + total = float(row["obr_value_gbp"]) + period = int(row["obr_period"]) + sub = _MEASURE_SUBSTRINGS[row["key"]].lower() + components = list( + db.conn.execute( + "SELECT claim_id, value FROM external_scores" + " WHERE source='obr' AND metric='revenue_change'" + " AND period=? AND instr(lower(json_extract(conditions," + "'$.measure')), ?) > 0", + (period, sub), + ) + ) + if not components: + raise ValueError( + f"campaign: obr measure {row['key']}: no component claims" + ) + got = sum(r["value"] for r in components) + if abs(got - total) > 1e-3 * max(1.0, abs(total)): + raise ValueError( + f"campaign: obr measure {row['key']}: component sum " + f"{got} != collated anchor {total}" + ) + # Anchor the result to the dominant component row; the external + # anchor is the component SUM, named in annotations (a + # per-component ratio would be meaningless). + anchor = max(components, key=lambda r: abs(r["value"])) + engine, data = _bundle_meta(run["bundle"]) + results.append( + PEResult( + claim_id=anchor["claim_id"], + computed_value=abs(float(row["pe_measure_effect_gbp"])), + status=ComparisonStatus.CONSTRUCTED, + engine_version=engine, + data_bundle=data, + pe_construction=( + f"reversal of enacted measure on certified 2026 world: " + f"{run['pe_construction']}; reform={run['reform_json']}" + ), + run_id="uk-obr-measure-reversals-2026", + computed_at=COMPUTED_AT, + annotations=[ + f"signed PE effect " + f"{float(row['pe_measure_effect_gbp']):.0f} GBP " + "(measure direction, magnitude compared)", + f"external anchor = sum of the measure's " + f"{len(components)} component rows at FY{period} " + f"({total:.0f} GBP); this result anchors to the " + "largest component — compare against the annotated " + "total, not this row's value", + row["conventions"], + f"confidence: {row['confidence']}", + ], + baseline_key=CURRENT_LAW_KEY, + ) + ) + return results + + +# -- 4. RF April-2026 uprating parameter checks -------------------------- +# uprating_check key -> (RF conditions.program value, tree_changes key or +# None when the check itself found no comparable single parameter, and a +# construction note). +UPRATING_MAP = { + "inflation_linked_benefits": ( + "inflation-linked benefits", "uc_child_element", + "checked via the UC child element, a CPI-linked parameter", + ), + "state_pension_triple_lock_earnings": ( + "State Pension (triple lock: earnings growth)", + "state_pension_new", + "checked via the new State Pension weekly amount", + ), + "uc_standard_allowance": ( + "UC standard allowance", "uc_standard_single_25plus", + "checked via the single-25+ standard allowance (couples uprate " + "identically in the tree probe)", + ), + "uc_standard_allowance_u25": ( + "UC standard allowance, under-25s", "uc_standard_single_u25", + "checked via the single-under-25 standard allowance", + ), + "uc_health_element_existing": ( + "UC health element, existing recipients", None, + "not comparable to a single tree parameter: the probe's LCWRA " + "amount change (−48.7%) is the AB2025 new-claimant halving, not " + "the existing-recipient uprating RF states — the new/existing " + "split needs its encoding mapped first (check note verbatim)", + ), + "lha_frozen": ( + "Local Housing Allowance (frozen)", None, + "LHA rates are data-driven per BRMA in policyengine-uk; freeze " + "verification needs the LHA parameter/dataset mechanism (check " + "note verbatim)", + ), +} + + +def uprating_results(db: ScorecardDB) -> tuple[list[PEResult], list[str]]: + check = _load("uk/uprating_check_april2026.json") + tree = check["tree_changes"] + results, skipped = [], [] + for key, staged in check["rf_staged_claims"].items(): + program, tree_key, note = UPRATING_MAP[key] + cid = _one( + db, + f"uprating {key}", + "SELECT claim_id FROM external_scores" + " WHERE source='resolution_foundation'" + " AND metric='benefit_uprating' AND period=2026" + " AND json_extract(conditions,'$.program')=?" + " AND json_extract(conditions,'$.component') IS NULL", + (program,), + ) + entry = tree.get(tree_key) if tree_key else None + if entry is None: + skipped.append(f"{key}: {note} (RF staged {staged})") + results.append( + PEResult( + claim_id=cid, + computed_value=None, + status=ComparisonStatus.NOT_COMPUTED, + engine_version=check["tree_package"], + data_bundle="parameter-tree-only", + pe_construction="", + run_id="uk-uprating-check-2026", + computed_at=COMPUTED_AT, + annotations=[note, f"RF staged {staged}"], + baseline_key=CURRENT_LAW_KEY, + ) + ) + continue + results.append( + PEResult( + claim_id=cid, + computed_value=entry["pct"], + status=ComparisonStatus.COMPARABLE, + engine_version=check["tree_package"], + data_bundle="parameter-tree-only", + pe_construction=( + f"{entry['path']}: {entry['before']} -> " + f"{entry['after']} across " + f"{check['windows']['before']}→" + f"{check['windows']['after']}" + ), + run_id="uk-uprating-check-2026", + computed_at=COMPUTED_AT, + annotations=[ + "pure parameter check (no data artifact); April-2026 " + "uprating in the installed policyengine-uk tree vs " + "RF's published parameter set", + note, + ], + baseline_key=CURRENT_LAW_KEY, + ) + ) + return results, skipped + + +# -- 5/6. TPC and PWBM revenue legs -------------------------------------- +_TPC_CONVENTIONS = ( + "PE calendar-year 2026 liability vs TPC fiscal-year cash; PE static " + "vs TPC conventional (T25-0209) / microdynamic (T26-0029); PE " + "baseline = enacted-OBBBA current law vs claim baseline as labeled " + "(draft≈enacted for these provisions — named delta, view guard " + "applies)" +) +# run key -> (period, provision-match SQL fragment, option or None) +_TPC_RUNS = [ + ("ctc_opt1", 2025, "Increase child tax credit%", "Option 1"), + ("ctc_opt2", 2025, "Increase CTC amount to $2,500 and CTC maximum%", + "Option 2"), + ("ctc_opt3", 2025, "Increase CTC amount to $2,500 and CTC maximum%", + "Option 3"), + ("ctc_opt1", 2026, "Increase child tax credit%", "Option 1"), + ("ctc_opt2", 2026, "Increase CTC amount to $2,500 and CTC maximum%", + "Option 2"), + ("ctc_opt3", 2026, "Increase CTC amount to $2,500 and CTC maximum%", + "Option 3"), + ("toprate_opt1", 2026, "Increase top individual income tax rate%", + "Option 1"), + ("toprate_opt2", 2026, "Increase top individual income tax rate%", + "Option 2"), + ("toprate_opt3", 2026, "Increase top individual income tax rate%", + "Option 3"), + ("total_opt1", 2026, "Total for both provisions", "Option 1"), + ("total_opt2", 2026, "Total for both provisions", "Option 2"), + ("total_opt3", 2026, "Total for both provisions", "Option 3"), +] + + +def _income_tax_delta(run: dict, year: int) -> float: + base = _load(f"us/tpc_ctc/baseline_{year}.json")["aggregates_usd"] + return run["aggregates_usd"]["income_tax"] - base["income_tax"] + + +def tpc_results(db: ScorecardDB) -> list[PEResult]: + results = [] + for key, year, provision_like, option in _TPC_RUNS: + run = _load(f"us/tpc_ctc/{key}_{year}.json") + cid = _one( + db, + f"tpc {key} {year}", + "SELECT claim_id FROM external_scores WHERE source='tpc'" + " AND metric='revenue_change' AND period=?" + " AND json_extract(conditions,'$.option')=?" + " AND json_extract(conditions,'$.provision') LIKE ?" + " AND reform_json LIKE '%obbba_senate_ctc_top_rate_options%'", + (year, option, provision_like), + ) + engine, data = _bundle_meta(run["bundle"]) + results.append( + PEResult( + claim_id=cid, + computed_value=_income_tax_delta(run, year), + status=ComparisonStatus.CONSTRUCTED, + engine_version=engine, + data_bundle=data, + pe_construction=( + "; ".join(run["pe_construction"]) + + f"; reform={run['reform_json']}" + ), + run_id=f"tpc-t25-0209-{key}-{year}", + computed_at=COMPUTED_AT, + annotations=[_TPC_CONVENTIONS], + baseline_key=CURRENT_LAW_KEY, + ) + ) + # AFA: the bill's $2,000 floor vs the onto-OBBBA $2,200 reading — + # both constructions land on the one T26-0029 claim (history table). + for key, note in ( + ("afa_bill_floor", "bill $2,000 floor construction"), + ("afa_onto_obbba", "onto-OBBBA $2,200 mid-tier construction"), + ): + run = _load(f"us/tpc_ctc/{key}_2026.json") + cid = _one( + db, + f"tpc {key}", + "SELECT claim_id FROM external_scores WHERE source='tpc'" + " AND metric='revenue_change' AND period=2026" + " AND json_extract(conditions,'$.provision')=" + "'American Family Act'", + (), + ) + engine, data = _bundle_meta(run["bundle"]) + results.append( + PEResult( + claim_id=cid, + computed_value=_income_tax_delta(run, 2026), + status=ComparisonStatus.CONSTRUCTED, + engine_version=engine, + data_bundle=data, + pe_construction=( + "; ".join(run["pe_construction"]) + + f"; reform={run['reform_json']}" + ), + run_id=f"tpc-t26-0029-{key}", + computed_at=COMPUTED_AT, + annotations=[ + f"AFA floor ambiguity bound: {note} (width ≈ $1.8B)", + _TPC_CONVENTIONS, + ], + baseline_key=CURRENT_LAW_KEY, + ) + ) + return results + + +def pwbm_results(db: ScorecardDB) -> list[PEResult]: + results = [] + for year in (2025, 2026): + run = _load(f"us/pwbm_ss/ss_notax_{year}.json") + cid = _one( + db, + f"pwbm ss {year}", + "SELECT claim_id FROM external_scores WHERE source='pwbm'" + " AND metric='revenue_change' AND period=?" + " AND json_extract(conditions,'$.provision')=" + "'Ending taxation of Social Security benefits'" + " AND json_extract(conditions,'$.scoring')='conventional'", + (year,), + ) + engine, data = _bundle_meta(run["bundle"]) + results.append( + PEResult( + claim_id=cid, + computed_value=_income_tax_delta(run, year), + status=ComparisonStatus.CONSTRUCTED, + engine_version=engine, + data_bundle=data, + pe_construction=( + "; ".join(run["pe_construction"]) + + f"; reform={run['reform_json']}" + ), + run_id=f"pwbm-ss-notax-{year}", + computed_at=COMPUTED_AT, + annotations=[ + "PE CY liability vs PWBM FY cash (named); taxable SS " + "verified 0.0 exactly under the construction; senior-" + "deduction baseline vintage is a named axis", + ], + baseline_key=CURRENT_LAW_KEY, + ) + ) + return results + + +# -- 7. CPSP CTC counterfactual levels ------------------------------------ +_CPSP_SCENARIO_REFORM = { + "TCJA CTC": '%"tcja_ctc"%', + "No CTC": '%"no_ctc"%', + "OBBBA CTC": '%"obbba_ctc"%', + "AFA CTC": '%"afa_ctc"%', +} +_CPSP_LEVEL_RATIONALE = ( + "Level comparison vs an ASEC-anchored series: Populace CALCULATES " + "benefits and recalibrates where the ASEC carries reported " + "attributes, and treats thresholds differently (descriptive " + "decomposition in sources/campaign-2026-08-02/us/SPM_NOTES.md). " + "A named sub-channel: Early Head Start at engine-default 100% " + "take-up flows inside household_net_income " + "(populace#593). Change metrics between CTC worlds are the " + "same-assumptions surface and are directionally consistent." +) + + +def cpsp_results(db: ScorecardDB) -> tuple[list[PEResult], list[tuple]]: + results, diagnoses = [], [] + staged_path = CAMPAIGN / "us/cpsp_ctc/staged_rows_2024.jsonl" + for line in staged_path.read_text().splitlines(): + if not line.strip(): + continue + row = json.loads(line) + match = row["external_claim_match"] + conds = match["conditions"] + if conds["poverty_threshold"] != "100pct_spm": + raise ValueError( + f"campaign: cpsp threshold {conds['poverty_threshold']!r}" + ) + # The ingested counterfactual claims carry geography+subgroup + # only (100%-SPM is the tables' single threshold); the scenario + # world rides the reform descriptor. + cid = _one( + db, + f"cpsp {conds['policy_scenario']} {conds['subgroup']}", + "SELECT claim_id FROM external_scores WHERE source='cpsp'" + " AND metric='poverty_rate' AND period=2024" + " AND json_extract(conditions,'$.subgroup')=?" + " AND reform_json LIKE ?", + ( + conds["subgroup"], + _CPSP_SCENARIO_REFORM[conds["policy_scenario"]], + ), + ) + results.append( + PEResult( + claim_id=cid, + computed_value=row["pe_value"], + status=ComparisonStatus.CONSTRUCTED, + engine_version="policyengine-us 1.764.6", + data_bundle=_load("run_meta.json")["bundle"][ + "certified_data_build_id" + ], + pe_construction=( + "; ".join(row["pe_construction"]) + + f"; reform={row['reform_json']}; baseline executed: " + + row["baseline_executed"] + ), + run_id="cpsp-ctc-counterfactuals-2024", + computed_at=COMPUTED_AT, + annotations=[ + "CPSP stated basis: 100% take-up, no behavior — " + "credit take-up flags forced to match", + ], + baseline_key=CURRENT_LAW_KEY, + ) + ) + diagnoses.append( + ( + cid, + "methodological_difference", + _CPSP_LEVEL_RATIONALE, + "https://github.com/PolicyEngine/populace/issues/593", + ) + ) + return results, diagnoses + + +# -- 8. JCT OBBBA CTC-extension provision --------------------------------- +def obbba_results(db: ScorecardDB) -> list[PEResult]: + run = _load("us/obbba_family/ctc_ext_2026.json") + base = _load("us/tpc_ctc/baseline_2026.json")["aggregates_usd"] + # Extension effect on receipts = current law (extension in force) + # minus the expiry counterfactual this run executed: the expiry + # world collects MORE income tax, so the effect is negative (a + # revenue cost), matching JCT's sign convention. + delta = base["income_tax"] - run["aggregates_usd"]["income_tax"] + cid = _one( + db, + "jct ctc extension provision", + "SELECT claim_id FROM external_scores WHERE source='jct'" + " AND period=2026" + " AND json_extract(conditions,'$.bill_version')='JCX-35-25'" + " AND json_extract(conditions,'$.provision')=" + "'4. Extension and enhancement of increased child tax credit [1]'", + (), + ) + engine, data = _bundle_meta(run["bundle"]) + return [ + PEResult( + claim_id=cid, + computed_value=delta, + status=ComparisonStatus.CONSTRUCTED, + engine_version=engine, + data_bundle=data, + pe_construction=( + "; ".join(run["pe_construction"]) + + f"; expiry world: {run['world']}" + ), + run_id="obbba-family-ctc-ext-2026", + computed_at=COMPUTED_AT, + annotations=[ + "JCT scores provisions SEQUENTIALLY (each conditional on " + "the prior stack); this is a single-provision " + "marginal-vs-current-law run — interaction terms are a " + "named convention delta (RUNNABILITY.md)", + "PE CY2026 liability vs JCT FY2026 cash (named)", + ], + baseline_key=CURRENT_LAW_KEY, + ) + ] + + +# -- 9. US CBO free joins -------------------------------------------------- +def cbo_free_join_results(db: ScorecardDB) -> list[PEResult]: + meta = _load("run_meta.json")["bundle"] + engine, data = meta["model_version"], meta["certified_data_build_id"] + results = [] + for row in _rows("us/free_joins_cbo.csv"): + computed = row["status"] == "computed" + cbo_value = float(row["cbo_value"]) + sql = ( + "SELECT claim_id, value FROM external_scores" + " WHERE source='cbo' AND metric=? AND period=?" + " AND source_column=?" + ) + args: list = [row["metric"], int(row["period"]), + row["source_column"]] + if row["program"]: + sql += " AND json_extract(conditions,'$.program')=?" + args.append(row["program"]) + hits = [ + r["claim_id"] + for r in db.conn.execute(sql, args) + if abs(r["value"] - cbo_value) + <= 1e-6 * max(1.0, abs(cbo_value)) + ] + if len(hits) != 1: + raise ValueError( + f"campaign: cbo free-join {row['program']}/{row['metric']}" + f"/{row['period']}: {len(hits)} claims" + ) + annotations = [row["conventions"]] + if not computed: + annotations.append(row["status"]) + results.append( + PEResult( + claim_id=hits[0], + computed_value=( + float(row["pe_value"]) if computed else None + ), + status=( + ComparisonStatus.CONSTRUCTED + if computed + else ComparisonStatus.NOT_COMPUTED + ), + engine_version=engine, + data_bundle=data, + pe_construction=row["pe_construction"], + run_id="us-cbo-free-joins-2026", + computed_at=COMPUTED_AT, + annotations=[a for a in annotations if a], + baseline_key=CURRENT_LAW_KEY, + ) + ) + return results + + +# -- exhibits: the two-child-limit counterfactual family ------------------- +_TWO_CHILD_REFORM = { + "framework": "policy_ref", + "reform": {"policy": "two_child_limit_removal"}, + "baseline": {"policy": "pre_ab2025"}, + "rulespec_ref": None, +} +_TWO_CHILD_NOTE = ( + "PE 2026 current law already abolishes the UC two-child limit " + "(AB2025 encoded), so removal is measured against an executed " + "reinstated counterfactual (gov.dwp.universal_credit.elements.child." + "limit.child_count: inf -> 2, born-pre-2017 exemptions active — the " + "actual partially-rolled-in 2026 law). Line convention contributes " + "zero (person-weighted medians identical between worlds); take-up " + "quantified at +34k via the entitlements-basis pair." +) + + +def two_child_exhibits() -> list[dict]: + reform_json = json.dumps(_TWO_CHILD_REFORM, sort_keys=True) + reform_key_ = "two-child-removal-vs-pre-ab2025" + rows = [] + + def add(metric, unit, value, baseline_value, conditions, engine, data, + run_id, extra_note=""): + delta = ( + value - baseline_value if baseline_value is not None else None + ) + rows.append( + { + "exhibit": "uk-two-child-limit", + "reform_key": reform_key_, + "reform_json": reform_json, + "metric": metric, + "unit_concept": unit, + "period": 2026, + "time_basis": "fiscal_year", + "conditions": conditions, + "geography": "UK", + "program": "universal_credit", + "value": value, + "baseline_value": baseline_value, + "delta": delta, + "engine_version": engine, + "data_bundle": data, + "run_id": run_id, + "computed_at": COMPUTED_AT, + "note": (_TWO_CHILD_NOTE + (" " + extra_note).rstrip()), + "baseline_key": PRE_AB2025_KEY, + } + ) + + for takeup, fname in ( + ("calibrated", "uk/two_child_fixed_line_2026.json"), + ("entitlements_basis", "uk/two_child_fixed_line_fulltakeup_2026.json"), + ): + run = _load(fname) + engine, data = _bundle_meta(run["worlds"]["with_limit"]["bundle"]) + res = run["results"]["floating"] + for group in ("hbai_dep", "u16", "all"): + add( + "poverty_count_change", + "persons" if group == "all" else "children_under_18", + res["without_limit"][group]["count"], + res["with_limit"][group]["count"], + { + "takeup": takeup, + "child_definition": group, + "poverty_line": ( + "relative AHC 60% median, person-weighted, " + "floating" + ), + "fy": "2026-27", + }, + engine, data, f"uk-two-child-{takeup}-2026", + ) + add( + "poverty_rate_change", + "percentage_points", + res["without_limit"]["hbai_dep"]["rate"] * 100, + res["with_limit"]["hbai_dep"]["rate"] * 100, + { + "takeup": takeup, + "child_definition": "hbai_dep", + "poverty_line": ( + "relative AHC 60% median, person-weighted, floating" + ), + "fy": "2026-27", + }, + engine, data, f"uk-two-child-{takeup}-2026", + ) + add( + "benefit_cost", + "gbp", + run["worlds"]["without_limit"]["aggregates_gbp"][ + "universal_credit" + ], + run["worlds"]["with_limit"]["aggregates_gbp"][ + "universal_credit" + ], + {"takeup": takeup, "measure": "uc_cost_of_removal", + "fy": "2026-27"}, + engine, data, f"uk-two-child-{takeup}-2026", + extra_note=( + f"UC cost of removal " + f"{run['uc_cost_of_removal_gbp']:.0f} GBP." + ), + ) + + # Absolute-AHC continuity pair (the first-cut construction). + removal = _load("uk/two_child_limit_removal_2026.json") + reinstate = _load("uk/two_child_reinstate_2026.json") + engine, data = _bundle_meta(removal["bundle"]) + add( + "poverty_count_change", + "children_under_18", + removal["poverty"]["count_child_u16"], + reinstate["poverty"]["count_child_u16"], + { + "takeup": "calibrated", + "child_definition": "u16", + "poverty_line": "absolute AHC (parameter threshold)", + "fy": "2026-27", + }, + engine, data, "uk-two-child-absline-2026", + extra_note="Absolute-line continuity check (reproduces 181k u16).", + ) + return rows + + +# -- runner --------------------------------------------------------------- +def ingest(db_path: Path) -> dict: + db = ScorecardDB(db_path) + stats: dict = {} + + reckoner, reckoner_skips = reckoner_results(db) + free_joins = free_join_results(db) + measures = obr_measure_results(db) + uprating, uprating_skips = uprating_results(db) + tpc = tpc_results(db) + pwbm = pwbm_results(db) + cpsp, cpsp_diagnoses = cpsp_results(db) + obbba = obbba_results(db) + cbo = cbo_free_join_results(db) + + all_results = ( + reckoner + free_joins + measures + uprating + tpc + pwbm + cpsp + + obbba + cbo + ) + stats["results"] = { + "uk_reckoner": len(reckoner), + "uk_free_joins": len(free_joins), + "uk_obr_measures": len(measures), + "uk_uprating": len(uprating), + "tpc": len(tpc), + "pwbm": len(pwbm), + "cpsp": len(cpsp), + "jct_obbba": len(obbba), + "cbo_free_joins": len(cbo), + "total": len(all_results), + } + stats["skipped"] = reckoner_skips + uprating_skips + # Idempotent re-ingest: this batch owns its run ids. + run_ids = sorted({r.run_id for r in all_results}) + with db.conn: + db.conn.execute( + "DELETE FROM pe_results WHERE run_id IN (" + + ",".join("?" * len(run_ids)) + + ")", + run_ids, + ) + db.add_results(all_results) + + for cid, cls, rationale, link in cpsp_diagnoses: + db.diagnose(cid, cls, rationale, link) + stats["diagnoses"] = len(cpsp_diagnoses) + + exhibits = two_child_exhibits() + with db.conn: + db.conn.execute( + "DELETE FROM pe_exhibits WHERE exhibit='uk-two-child-limit'" + ) + stats["exhibits"] = db.add_exhibits(exhibits) + + stats["baselines_registered"] = register_baselines(db) + + joined_lanes = ( + "hmrc-personal-tax", "obr-measures", "obr-welfare", "dwp-takeup", + "rf-outlook", "cpsp-poverty", "tpc-distribution", + "pwbm-reform-scores", "jct-reform-scores", "cbo-baseline", + ) + for lane in joined_lanes: + row = db.conn.execute( + "SELECT detail FROM lanes WHERE lane=?", (lane,) + ).fetchone() + if row is None: + raise ValueError(f"campaign: lane {lane} missing") + db.set_lane(lane, "computed", row["detail"], COMPUTED_AT[:10]) + db.set_lane( + "campaign-compute-2026-08-02", + "computed", + f"{len(all_results)} PE results joined " + f"({stats['results']}); {len(exhibits)} two-child exhibits vs " + "registered pre_ab2025 baseline; skips: " + + ("; ".join(stats["skipped"]) or "none"), + COMPUTED_AT[:10], + ) + stats["coverage"] = db.coverage() + db.close() + return stats + + +if __name__ == "__main__": + import sys + + out = Path(sys.argv[1] if len(sys.argv) > 1 else "data/scorecard.db") + print(json.dumps(ingest(out), indent=1)) diff --git a/scorecard_db/ingest_uk_hmrc.py b/scorecard_db/ingest_uk_hmrc.py index 16c9ee8..d1d680c 100644 --- a/scorecard_db/ingest_uk_hmrc.py +++ b/scorecard_db/ingest_uk_hmrc.py @@ -142,7 +142,14 @@ def stage() -> tuple[list[ExternalScore], list[dict]]: if is_rr: if not row.get("reform_hint"): raise ValueError("uk_hmrc: ready-reckoner row without hint") - reform = policy_ref(f"uk_hmrc_rr:{slugify(row['reform_hint'])}") + # The section is part of the world's identity: "Change + # standard rate by 1 percentage point" exists under both VAT + # and Insurance premium tax. + reform = policy_ref( + "uk_hmrc_rr:" + f"{slugify(conds_in['tax_section'], 30)}:" + f"{slugify(row['reform_hint'])}" + ) conditions["measure"] = row["reform_hint"] else: if row.get("reform_hint"): diff --git a/sources/campaign-2026-08-02/run_meta.json b/sources/campaign-2026-08-02/run_meta.json new file mode 100644 index 0000000..562b32a --- /dev/null +++ b/sources/campaign-2026-08-02/run_meta.json @@ -0,0 +1,41 @@ +{ + "year": 2024, + "policyengine": "5.0.1", + "policyengine_us": "1.764.6", + "policyengine_core": "3.30.0", + "bundle": { + "bundle_id": "us-5.0.1", + "country_id": "us", + "policyengine_version": "5.0.1", + "model_package": "policyengine-us", + "model_version": "1.764.6", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_us_2024", + "default_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_build_id": "populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_artifact_sha256": "48b9d479fb4fd1c3537f9383ce4697d130b6f618658409d74f6233c43b994c7e", + "data_build_model_version": "1.764.6", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_us_2024", + "runtime_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-us/snapshots/26dcad66867687f15735dc4926523e3741920836/populace_us_2024.h5", + "managed_by": "policyengine.py" + }, + "dataset": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "n_stored_input_vars": 188, + "takeup_flags_stored": [ + "takes_up_aca_if_eligible", + "takes_up_eitc", + "takes_up_head_start_if_eligible", + "takes_up_housing_assistance_if_eligible", + "takes_up_medicaid_if_eligible", + "takes_up_medicare_if_eligible", + "takes_up_snap_if_eligible", + "takes_up_ssi_if_eligible", + "takes_up_tanf_if_eligible" + ] +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/additional_rate_1p_2026.json b/sources/campaign-2026-08-02/uk/additional_rate_1p_2026.json new file mode 100644 index 0000000..dc2be43 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/additional_rate_1p_2026.json @@ -0,0 +1,40 @@ +{ + "reform_key": "additional_rate_1p", + "year": 2026, + "reform_hint": "Increase additional rate by 1p", + "pe_construction": "gov.hmrc.income_tax.rates.uk[2].rate: 0.45 -> 0.46", + "reform_json": "{\"gov.hmrc.income_tax.rates.uk[2].rate\": {\"2026-01-01.2028-12-31\": 0.46}}", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": 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0000000..1b15902 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/aggregates_2026.json @@ -0,0 +1,200 @@ +{ + "year": 2026, + "concept_notes": { + "period_basis": "PE calendar-year 2026; OBR/HMRC/DWP fiscal-year Apr-Mar (named delta)", + "receipts_vs_liability": "PE totals are accrual liabilities/entitlements; OBR receipts are cash (named delta)", + "caseload_concept": "annual-ever units with amount>0; DWP BECL caseloads are FY-average point-in-time (named delta, pre-adjudicated in staging)" + }, + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + 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"working_tax_credit": { + "unit": "benunit", + "recipient_units_annual_ever": 0.0 + }, + "child_tax_credit": { + "unit": "benunit", + "recipient_units_annual_ever": 0.0 + }, + "winter_fuel_allowance": { + "unit": "household", + "recipient_units_annual_ever": 7060742.019033432 + }, + "statutory_sick_pay": { + "unit": "person", + "recipient_units_annual_ever": 254034.1130834818 + }, + "statutory_maternity_pay": { + "unit": "person", + "recipient_units_annual_ever": 166412.83011466265 + }, + "council_tax_benefit": { + "unit": "benunit", + "recipient_units_annual_ever": 2886327.5622606277 + }, + "tax_credits": { + "unit": "benunit", + "recipient_units_annual_ever": 0.0 + }, + "scottish_child_payment": { + "unit": "person", + "recipient_units_annual_ever": 108827.83540725708 + }, + "household_net_income": { + "unit": "household", + "recipient_units_annual_ever": 29369810.998743203 + }, + "gov_tax": { + "unit": "household", + "recipient_units_annual_ever": 29470583.18248133 + }, + "gov_spending": { + "unit": "household", + "recipient_units_annual_ever": 29470583.18248133 + }, + "household_benefits": { + "unit": "household", + "recipient_units_annual_ever": 29470583.18248133 + } + }, + "not_in_model": [] +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/baseline_2026.json b/sources/campaign-2026-08-02/uk/baseline_2026.json new file mode 100644 index 0000000..057f220 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/baseline_2026.json @@ -0,0 +1,47 @@ +{ + "reform_key": "baseline", + "year": 2026, + "reform_hint": "baseline", + "pe_construction": "", + "reform_json": "baseline", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": 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{\"2026-01-01.2028-12-31\": 0.21000000000000002}}", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": 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"brl_10pct", + "year": 2026, + "reform_hint": "Increase basic rate limit by 10%", + "pe_construction": "gov.hmrc.income_tax.rates.uk[1].threshold: 37700 -> 41470.0", + "reform_json": "{\"gov.hmrc.income_tax.rates.uk[1].threshold\": {\"2026-01-01.2028-12-31\": 41470.0}}", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": 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b/sources/campaign-2026-08-02/uk/fixed_line/with_limit_fulltakeup_2026_meta.json new file mode 100644 index 0000000..0e6f1b0 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/fixed_line/with_limit_fulltakeup_2026_meta.json @@ -0,0 +1,45 @@ +{ + "world": "with_limit", + "year": 2026, + "mode": "fulltakeup", + "forced_flags": [ + "would_claim_uc", + "would_claim_housing_benefit", + "would_claim_child_benefit", + "would_claim_council_tax_reduction", + "would_claim_CTC", + "would_claim_WTC", + "would_claim_IS", + "claims_all_entitled_benefits" + ], + "construction": "gov.dwp.universal_credit.elements.child.limit.child_count: inf -> 2 (reinstate; born-pre-2017 exemption active)", + "reform_json": "{\"gov.dwp.universal_credit.elements.child.limit.child_count\": {\"2026-01-01.2028-12-31\": 2}}", + "hbai_dependent_child_proxy": "is_child_or_qualifying_young_person_for_child_tax_credit: under-16 OR 16-19 qualifying young person in full-time non-advanced education, excl. looked-after children (closest installed analogue of the HBAI dependent-child definition)", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "universal_credit": 53429818141.101036, + "household_net_income": 1803220878970.0093, + "gov_spending": 497880464939.9005 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/fixed_line/without_limit_2026_meta.json b/sources/campaign-2026-08-02/uk/fixed_line/without_limit_2026_meta.json new file mode 100644 index 0000000..38948e2 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/fixed_line/without_limit_2026_meta.json @@ -0,0 +1,34 @@ +{ + "world": "without_limit", + "year": 2026, + "construction": "baseline (limit abolished in current law)", + "reform_json": "baseline", + "hbai_dependent_child_proxy": "is_child_or_qualifying_young_person_for_child_tax_credit: under-16 OR 16-19 qualifying young person in full-time non-advanced education, excl. looked-after children (closest installed analogue of the HBAI dependent-child definition)", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + 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"mode": "fulltakeup", + "forced_flags": [ + "would_claim_uc", + "would_claim_housing_benefit", + "would_claim_child_benefit", + "would_claim_council_tax_reduction", + "would_claim_CTC", + "would_claim_WTC", + "would_claim_IS", + "claims_all_entitled_benefits" + ], + "construction": "baseline (limit abolished in current law)", + "reform_json": "baseline", + "hbai_dependent_child_proxy": "is_child_or_qualifying_young_person_for_child_tax_credit: under-16 OR 16-19 qualifying young person in full-time non-advanced education, excl. looked-after children (closest installed analogue of the HBAI dependent-child definition)", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "universal_credit": 55279919145.339645, + "household_net_income": 1804948205172.6, + "gov_spending": 499729028736.36316 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/free_joins.csv b/sources/campaign-2026-08-02/uk/free_joins.csv new file mode 100644 index 0000000..3953177 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/free_joins.csv @@ -0,0 +1,24 @@ +source,label,period,external_value,pe_value,ratio,pe_construction,conventions,status +uk_obr,Income tax (gross of tax credits),2026,359618867481.6865,421891913533.19946,1.1731640124657368,income_tax total,OBR/DWP fiscal year 2026-27 vs PE calendar 2026 (named delta); receipts/expenditure cash vs PE accrual entitlement/liability (named delta),computed +uk_obr,Pay as you earn,2026,296293048154.10803,,,,,"skipped: skip: PAYE is a collection channel, not a liability concept PE separates" +uk_obr,Self assessment,2026,64372729845.45013,,,,,skipped: skip: collection channel +uk_obr,National insurance contributions,2026,211594391642.42764,246931463530.31155,1.1670038209122284,national_insurance + ni_employer,OBR/DWP fiscal year 2026-27 vs PE calendar 2026 (named delta); receipts/expenditure cash vs PE accrual entitlement/liability (named delta),computed +uk_obr,Class 1 Employee NICs,2026,51474273325.11673,61450306465.09366,1.1938061966794031,national_insurance (employee+self-employed personal NI) — join also covers Class 4/2 row jointly; scope note,OBR/DWP fiscal year 2026-27 vs PE calendar 2026 (named delta); receipts/expenditure cash vs PE accrual entitlement/liability (named delta),computed +uk_obr,Class 1 Employer NICs,2026,150989275628.03833,185481157065.2179,1.2284392801655015,ni_employer total,OBR/DWP fiscal year 2026-27 vs PE calendar 2026 (named delta); receipts/expenditure cash vs PE accrual entitlement/liability (named delta),computed +uk_obr,Class 4 and Class 2 Self employed NICs,2026,3156842035.84375,,,,,skipped: joined jointly with Class 1 Employee row (PE national_insurance is combined personal NI) +uk_obr,Pay as you earn,2026,294158207190.2883,,,,,"skipped: skip: PAYE is a collection channel, not a liability concept PE separates" +uk_obr,Self assessment,2026,64372729845.45013,,,,,skipped: skip: collection channel +uk_obr,National insurance contributions,2026,210445437610.04147,246931463530.31155,1.173375228917432,national_insurance + ni_employer,OBR/DWP fiscal year 2026-27 vs PE calendar 2026 (named delta); receipts/expenditure cash vs PE accrual entitlement/liability (named delta),computed +uk_obr,Value added tax,2026,187704367258.10846,219622883998.86896,1.1700467453528665,vat total (household VAT incidence model),OBR/DWP fiscal year 2026-27 vs PE calendar 2026 (named delta); receipts/expenditure cash vs PE accrual entitlement/liability (named delta),computed +uk_obr,Fuel duties,2026,24628571426.324806,12976906953.47097,0.5269045747249599,fuel_duty total (household incidence share only — OBR head includes business use; scope note),OBR/DWP fiscal year 2026-27 vs PE calendar 2026 (named delta); receipts/expenditure cash vs PE accrual entitlement/liability (named delta),computed +uk_obr,Capital gains tax,2026,20801165202.018173,24243246083.18426,1.165475387928371,capital_gains_tax total,OBR/DWP fiscal year 2026-27 vs PE calendar 2026 (named delta); receipts/expenditure cash vs PE accrual entitlement/liability (named delta),computed +uk_obr,Council tax,2026,52761337186.675934,60083773529.38769,1.1387841312058506,council_tax total,OBR/DWP fiscal year 2026-27 vs PE calendar 2026 (named delta); receipts/expenditure cash vs PE accrual entitlement/liability (named delta),computed +uk_dwp,state_pension,2026,146071196250.36,145097022169.8143,0.9933308269833295,state_pension total,OBR/DWP fiscal year 2026-27 vs PE calendar 2026 (named delta); receipts/expenditure cash vs PE accrual entitlement/liability (named delta); geography gb vs PE UK (named delta),computed 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delta),computed +uk_dwp,pip,2026,28542217375.36,20593016304.099655,0.7214932194398199,pip total,OBR/DWP fiscal year 2026-27 vs PE calendar 2026 (named delta); receipts/expenditure cash vs PE accrual entitlement/liability (named delta); geography england_wales vs PE UK (named delta),computed +uk_dwp,attendance_allowance,2026,8497187075.07,4733056192.259981,0.5570144743719192,attendance_allowance total,OBR/DWP fiscal year 2026-27 vs PE calendar 2026 (named delta); receipts/expenditure cash vs PE accrual entitlement/liability (named delta); geography england_wales vs PE UK (named delta),computed +uk_dwp,child_benefit,2026,12945231644.37,17434702263.490685,1.3468049659098371,child_benefit total,OBR/DWP fiscal year 2026-27 vs PE calendar 2026 (named delta); receipts/expenditure cash vs PE accrual entitlement/liability (named delta); geography gb vs PE UK (named delta),computed +uk_dwp,personal_tax_credits,2026,-61742834.79,,,,,skipped: legacy tax credits ended April 2025; PE 2026 total ~0 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No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/higher_rate_1p_2026.json b/sources/campaign-2026-08-02/uk/higher_rate_1p_2026.json new file mode 100644 index 0000000..454a6ac --- /dev/null +++ b/sources/campaign-2026-08-02/uk/higher_rate_1p_2026.json @@ -0,0 +1,40 @@ +{ + "reform_key": "higher_rate_1p", + "year": 2026, + "reform_hint": "Change in higher rate by 1p", + "pe_construction": "gov.hmrc.income_tax.rates.uk[1].rate: 0.4 -> 0.41000000000000003", + "reform_json": "{\"gov.hmrc.income_tax.rates.uk[1].rate\": {\"2026-01-01.2028-12-31\": 0.41000000000000003}}", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + 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"data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "income_tax": 423612542977.2704, + "national_insurance": 61450306465.09366, + "ni_employer": 185481157065.2179, + "child_benefit": 17434702263.490685, + "universal_credit": 39901915135.473785, + "vat": 219622883998.86896, + "capital_gains_tax": 24243246083.18426, + "household_net_income": 1789573611412.6536, + "gov_tax": 1048524559951.2327, + "gov_spending": 485677327428.61584 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/obr_measures/pt_lpl_ss2022_2026.json b/sources/campaign-2026-08-02/uk/obr_measures/pt_lpl_ss2022_2026.json new file mode 100644 index 0000000..a3c94c9 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/obr_measures/pt_lpl_ss2022_2026.json @@ -0,0 +1,47 @@ +{ + "key": "pt_lpl_ss2022", + "year": 2026, + "measure_reversed": "NI PT & LPL alignment to PA (SS2022) \u2014 REVERSED by the \u00a32,690 announcement-vintage gap (LOW CONFIDENCE: counterfactual uprating path unknowable parametrically)", + "pe_construction": "gov.hmrc.national_insurance.class_1.thresholds.primary_threshold: 241.73 -> 190.00/wk; gov.hmrc.national_insurance.class_4.thresholds.lower_profits_limit: 12570.0 -> 9880.0", + "reform_json": "{\"gov.hmrc.national_insurance.class_1.thresholds.primary_threshold\": {\"2026-01-01.2028-12-31\": 189.99923076923076}, \"gov.hmrc.national_insurance.class_4.thresholds.lower_profits_limit\": {\"2026-01-01.2028-12-31\": 9880.0}}", + "baseline_for_delta": "results/uk/baseline_2026.json", + "conventions": [ + "PE measure effect = MINUS the (this - baseline) delta", + "OBR costing scored vs OBR announcement-time baseline w/ behavioural adjustments; this is the parametric content on the certified 2026 world (baseline-vintage delta, named)", + "PE calendar-year vs OBR fiscal-year (named)" + ], + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "income_tax": 421891913533.19946, + "national_insurance": 67284003408.16528, + "ni_employer": 185481157065.2179, + "child_benefit": 17434702263.490685, + "universal_credit": 39991711926.14007, + "vat": 219622883998.86896, + "capital_gains_tax": 24243246083.18426, + "household_net_income": 1785554498769.4727, + "gov_tax": 1052637624919.406, + "gov_spending": 485771195086.36804 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/obr_measures_collation.csv b/sources/campaign-2026-08-02/uk/obr_measures_collation.csv new file mode 100644 index 0000000..5c83198 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/obr_measures_collation.csv @@ -0,0 +1,11 @@ +key,status,pe_measure_effect_gbp,pe_gov_tax_effect_gbp,obr_value_gbp,obr_period,abs_ratio,abs_ratio_head_only,heads,confidence,n_candidate_rows,conventions +hicbc_sb2024,computed,-1720629444.0709229,-1720629281.512207,-250000000.0,2026,6.882517126048828,6.8825177762836915,income_tax,high,3,"reversal on certified 2026 world vs OBR announcement-baseline costing (behavioural-adjusted, FY) — baseline-vintage delta named; PE CY static accrual" +ee_ni_p2,computed,-12070073647.428864,-12070071976.065552,-10465234281.795147,2026,1.153349428312571,1.1533495880188198,national_insurance,high,18,"reversal on certified 2026 world vs OBR announcement-baseline costing (behavioural-adjusted, FY) — baseline-vintage delta named; PE CY static accrual" +ee_ni_p4,computed,-24142042648.760254,-24142043583.14258,-9068607177.111378,2026,2.6621556223182377,2.662155519283416,national_insurance,high; AS2023 leg ≈ p4−p2 differencing,12,"reversal on certified 2026 world vs OBR announcement-baseline costing (behavioural-adjusted, FY) — baseline-vintage delta named; PE CY static accrual" +class4_p3,computed,-1755439439.4202042,-1755438977.9938965,-348009097.91964304,2026,5.044233005653306,5.044234331556307,national_insurance,stack (AS2023 1p + SB2024 2p); external row is the 1p leg — compare via differencing vs tranche-1 class4_1pp,12,"reversal on certified 2026 world vs OBR announcement-baseline costing (behavioural-adjusted, FY) — baseline-vintage delta named; PE CY static accrual" +class2_reinstate,computed,-563027614.2353287,-563027552.8198242,-403140457.34836805,2026,1.3966039442508547,1.3966040965935513,national_insurance,high,12,"reversal on certified 2026 world vs OBR announcement-baseline costing (behavioural-adjusted, FY) — baseline-vintage delta named; PE CY static accrual" +employer_ab2024,computed,26014010206.312836,16240084103.596191,23714722782.217613,2026,0.6848102021995278,1.096956116468683,ni_employer,high; wage-incidence spillover onto IT/employee NI recorded via gov_tax,9,"reversal on certified 2026 world vs OBR announcement-baseline costing (behavioural-adjusted, FY) — baseline-vintage delta named; PE CY static accrual" +art_as2022,computed,1787263536.0213013,1787265489.5186768,783448087.0201031,2026,2.2812813243525296,2.2812788308913703,income_tax,high,9,"reversal on certified 2026 world vs OBR announcement-baseline costing (behavioural-adjusted, FY) — baseline-vintage delta named; PE CY static accrual" +div_ab2021,computed,619524446.258728,618983960.5861816,868649888.8100487,2026,0.712581637964772,0.7132038514474525,income_tax,delta-on-current (allowance changed since 2021 — vintage note),10,"reversal on certified 2026 world vs OBR announcement-baseline costing (behavioural-adjusted, FY) — baseline-vintage delta named; PE CY static accrual" +cgt_ab2024,computed,2832564125.7933006,2832564748.686035,1292432021.691635,2026,2.191654726241273,2.19165424428731,capital_gains_tax,high; PE static (no forestalling/behavioral),9,"reversal on certified 2026 world vs OBR announcement-baseline costing (behavioural-adjusted, FY) — baseline-vintage delta named; PE CY static accrual" +pt_lpl_ss2022,computed,-5833696943.071625,-5833694249.685547,-4702119816.05516,2026,1.2406519778093874,1.240652550611907,national_insurance,"LOW (announcement-vintage £2,690 gap; counterfactual uprating path unknowable)",10,"reversal on certified 2026 world vs OBR announcement-baseline costing (behavioural-adjusted, FY) — baseline-vintage delta named; PE CY static accrual" diff --git a/sources/campaign-2026-08-02/uk/pa_100_2026.json b/sources/campaign-2026-08-02/uk/pa_100_2026.json new file mode 100644 index 0000000..0745752 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/pa_100_2026.json @@ -0,0 +1,40 @@ +{ + "reform_key": "pa_100", + "year": 2026, + "reform_hint": "Change personal allowance by \u00a3100", + "pe_construction": "gov.hmrc.income_tax.allowances.personal_allowance.amount: 12570 -> 12670", + "reform_json": "{\"gov.hmrc.income_tax.allowances.personal_allowance.amount\": {\"2026-01-01.2028-12-31\": 12670}}", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "income_tax": 420992883968.124, + "national_insurance": 61450306465.09366, + "ni_employer": 185481157065.2179, + "child_benefit": 17434702263.490685, + "universal_credit": 39878372967.85101, + "vat": 219622883998.86896, + "household_net_income": 1792163940521.782, + "gov_tax": 1045903461087.4154, + "gov_spending": 485648845473.3286 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/pa_10pct_2026.json b/sources/campaign-2026-08-02/uk/pa_10pct_2026.json new file mode 100644 index 0000000..b9108c1 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/pa_10pct_2026.json @@ -0,0 +1,40 @@ +{ + "reform_key": "pa_10pct", + "year": 2026, + "reform_hint": "Change personal allowance by 10%", + "pe_construction": "gov.hmrc.income_tax.allowances.personal_allowance.amount: 12570 -> 13827.000000000002", + "reform_json": "{\"gov.hmrc.income_tax.allowances.personal_allowance.amount\": {\"2026-01-01.2028-12-31\": 13827.000000000002}}", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "income_tax": 410743690227.0401, + "national_insurance": 61450306465.09366, + "ni_employer": 185481157065.2179, + "child_benefit": 17434702263.490685, + "universal_credit": 39773310016.436806, + "vat": 219622883998.86896, + "household_net_income": 1802270915580.4868, + "gov_tax": 1035638549541.2341, + "gov_spending": 485501146991.8742 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/pa_1pct_2026.json b/sources/campaign-2026-08-02/uk/pa_1pct_2026.json new file mode 100644 index 0000000..1270a61 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/pa_1pct_2026.json @@ -0,0 +1,40 @@ +{ + "reform_key": "pa_1pct", + "year": 2026, + "reform_hint": "Change personal allowance by 1%", + "pe_construction": "gov.hmrc.income_tax.allowances.personal_allowance.amount: 12570 -> 12695.7", + "reform_json": "{\"gov.hmrc.income_tax.allowances.personal_allowance.amount\": {\"2026-01-01.2028-12-31\": 12695.7}}", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "income_tax": 420760496345.935, + "national_insurance": 61450306465.09366, + "ni_employer": 185481157065.2179, + "child_benefit": 17434702263.490685, + "universal_credit": 39875962204.15295, + "vat": 219622883998.86896, + "household_net_income": 1792393053013.8193, + "gov_tax": 1045670700930.5881, + "gov_spending": 485645198654.7175 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/psa_100_50_2026.json b/sources/campaign-2026-08-02/uk/psa_100_50_2026.json new file mode 100644 index 0000000..067fc45 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/psa_100_50_2026.json @@ -0,0 +1,40 @@ +{ + "reform_key": "psa_100_50", + "year": 2026, + "reform_hint": "Change Savings allowance by \u00a3100 for BR and \u00a350 for HR taxpayers", + "pe_construction": "gov.hmrc.income_tax.allowances.personal_savings_allowance.basic: 1000 -> 1100; gov.hmrc.income_tax.allowances.personal_savings_allowance.higher: 500 -> 550", + "reform_json": "{\"gov.hmrc.income_tax.allowances.personal_savings_allowance.basic\": {\"2026-01-01.2028-12-31\": 1100}, \"gov.hmrc.income_tax.allowances.personal_savings_allowance.higher\": {\"2026-01-01.2028-12-31\": 550}}", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "income_tax": 421822237856.2041, + "national_insurance": 61450306465.09366, + "ni_employer": 185481157065.2179, + "child_benefit": 17434702263.490685, + "universal_credit": 39887818603.1317, + "vat": 219622883998.86896, + "household_net_income": 1791349819437.8667, + "gov_tax": 1046734255058.1206, + "gov_spending": 485663230900.0288 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/srl_100_2026.json b/sources/campaign-2026-08-02/uk/srl_100_2026.json new file mode 100644 index 0000000..b60e0d4 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/srl_100_2026.json @@ -0,0 +1,40 @@ +{ + "reform_key": "srl_100", + "year": 2026, + "reform_hint": "Change starting rate limit for savings income by \u00a3100", + "pe_construction": "gov.hmrc.income_tax.rates.savings_starter_rate.allowance: 5000 -> 5100", + "reform_json": "{\"gov.hmrc.income_tax.rates.savings_starter_rate.allowance\": {\"2026-01-01.2028-12-31\": 5100}}", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "income_tax": 421858524825.77234, + "national_insurance": 61450306465.09366, + "ni_employer": 185481157065.2179, + "child_benefit": 17434702263.490685, + "universal_credit": 39887838277.66961, + "vat": 219622883998.86896, + "household_net_income": 1791313552250.722, + "gov_tax": 1046770541970.1005, + "gov_spending": 485663250574.56665 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/t2_collation.csv b/sources/campaign-2026-08-02/uk/t2_collation.csv new file mode 100644 index 0000000..e83a428 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/t2_collation.csv @@ -0,0 +1,15 @@ +key,status,hmrc_hint,pe_delta_gbp,pe_gov_tax_delta_gbp,hmrc_fy2026_27,hmrc_fy2027_28,abs_ratio_vs_fy26,abs_ratio_vs_fy27,heads,construction,conventions +pa_1pct,computed,Change personal allowance by 1%,-1131417187.2644653,-1133229739.1323242,1000000000.0,1200000000.0,1.1314171872644654,0.9428476560537211,income_tax,gov.hmrc.income_tax.allowances.personal_allowance.amount: 12570 -> 12695.7,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios +pa_10pct,computed,Change personal allowance by 10%,-11148223306.159363,-11165381128.486328,10000000000.0,11650000000.0,1.1148223306159364,0.9569290391553101,income_tax,gov.hmrc.income_tax.allowances.personal_allowance.amount: 12570 -> 13827.000000000002,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios +brl_1pct,computed,Change basic rate limit by 1%,-725046338.0097046,-733636703.8398438,495000000.0,665000000.0,1.464740076787282,1.0902952451273753,income_tax,gov.hmrc.income_tax.rates.uk[1].threshold: 37700 -> 38077.0,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios +brl_10pct,computed,Increase basic rate limit by 10% (cost),-6935879147.342651,-7020792835.180176,4600000000.0,6250000000.0,1.507799814639707,1.1097406635748241,income_tax,gov.hmrc.income_tax.rates.uk[1].threshold: 37700 -> 41470.0,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios +srl_100,computed,Change starting rate limit for savings income by £100,-33388707.427124023,-33388699.619995117,,5000000.0,,6.6777414854248045,income_tax,gov.hmrc.income_tax.rates.savings_starter_rate.allowance: 5000 -> 5100,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios +psa_100_50,computed,Change Savings allowance by £100 for BR and £50 for HR taxpayers,-69675676.99536133,-69675611.59985352,0.0,30000000.0,,2.322522566512044,income_tax,gov.hmrc.income_tax.allowances.personal_savings_allowance.basic: 1000 -> 1100; gov.hmrc.income_tax.allowances.personal_savings_allowance.higher: 500 -> 550,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios +dividend_allowance_100,computed,Change dividend allowance by £100,-52777493.560424805,-52777526.802978516,0.0,70000000.0,,0.7539641937203544,income_tax,gov.hmrc.income_tax.allowances.dividend_allowance: 500 -> 600,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios +ni_pt_2pw,computed,Change employee entry threshold by £2 per week,-202893958.81115723,-202895809.91210938,210000000.0,230000000.0,0.9661617086245582,0.8821476470050315,national_insurance,gov.hmrc.national_insurance.class_1.thresholds.primary_threshold: 241.73 -> 243.73,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios +ni_st_2pw,computed,Change employer threshold by £2 per week,-356685195.3192749,-239798822.20703125,420000000.0,430000000.0,0.8492504650458926,0.8295004542308718,ni_employer,gov.hmrc.national_insurance.class_1.thresholds.secondary_threshold: 96 -> 98,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios +ni_uel_10pw,computed,Change upper earnings limit by £10 per week,248033861.83112335,248034104.94433594,220000000.0,220000000.0,1.1274266446869243,1.1274266446869243,national_insurance,gov.hmrc.national_insurance.class_1.thresholds.upper_earnings_limit: 966.73 -> 976.73,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios +ni_lpl_104,computed,Change lower profits limit by £104 per year,-17503727.481391907,-17503377.587158203,15000000.0,15000000.0,1.1669151654261272,1.1669151654261272,national_insurance,gov.hmrc.national_insurance.class_4.thresholds.lower_profits_limit: 12570 -> 12674,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios +ni_upl_520,computed,Change upper profits limit by £520 per year,15204671.735198975,15204844.950927734,10000000.0,10000000.0,1.5204671735198974,1.5204671735198974,national_insurance,gov.hmrc.national_insurance.class_4.thresholds.upper_profits_limit: 50270 -> 50790,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios +cb_additional_1pw,computed,Increase subsequent child rate by £1 per week (cost),307891828.10876465,71130801.75634766,230000000.0,240000000.0,1.3386601222120202,1.2828826171198526,child_benefit,gov.hmrc.child_benefit.amount.additional: 17.9 -> 18.9,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios +employee_additional_1pp,computed,Change Class 1 employee additional rate by 1 percentage point,4391879294.86554,4391875901.453613,2000000000.0,2000000000.0,2.1959396474327697,2.1959396474327697,national_insurance,gov.hmrc.national_insurance.class_1.rates.employee.additional: 0.02 -> 0.03,PE CY2026 static accrual vs HMRC projected FY direct effects (first-year cash vs fuller-year; TIE/behavioral in HMRC reckoner per their methodology notes); |magnitude| ratios diff --git a/sources/campaign-2026-08-02/uk/two_child_fixed_line_2026.json b/sources/campaign-2026-08-02/uk/two_child_fixed_line_2026.json new file mode 100644 index 0000000..3eeb74c --- /dev/null +++ b/sources/campaign-2026-08-02/uk/two_child_fixed_line_2026.json @@ -0,0 +1,338 @@ +{ + "reform_key": "two_child_limit_removal_fixed_line", + "year": 2026, + "takeup_mode": "calibrated", + "worlds": { + "with_limit": { + "world": "with_limit", + "year": 2026, + "construction": "gov.dwp.universal_credit.elements.child.limit.child_count: inf -> 2 (reinstate; born-pre-2017 exemption active)", + "reform_json": "{\"gov.dwp.universal_credit.elements.child.limit.child_count\": {\"2026-01-01.2028-12-31\": 2}}", + "hbai_dependent_child_proxy": "is_child_or_qualifying_young_person_for_child_tax_credit: under-16 OR 16-19 qualifying young person in full-time non-advanced education, excl. looked-after children (closest installed analogue of the HBAI dependent-child definition)", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "universal_credit": 38783589984.86714, + "household_net_income": 1790266784216.2012, + "gov_spending": 484560539496.0421 + } + }, + "without_limit": { + "world": "without_limit", + "year": 2026, + "construction": "baseline (limit abolished in current law)", + "reform_json": "baseline", + "hbai_dependent_child_proxy": "is_child_or_qualifying_young_person_for_child_tax_credit: under-16 OR 16-19 qualifying young person in full-time non-advanced education, excl. looked-after children (closest installed analogue of the HBAI dependent-child definition)", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "universal_credit": 39887838277.66961, + "household_net_income": 1791280163555.2764, + "gov_spending": 485663250574.56665 + } + } + }, + "median_equiv_hbai_ahc_gbp_year": { + "with_limit": { + "person": 34191.88671875, + "household": 35570.34765625 + }, + "without_limit": { + "person": 34191.88671875, + "household": 35570.34765625 + } + }, + "median_weighting_primary": "person", + "median_weighting_note": "HBAI convention ranks individuals (person-weighted); pe-uk's in_relative_poverty_ahc uses household-weighted medians \u2014 both recorded, person-weighted used for all lines here", + "results": { + "floating": { + "with_limit": { + "line_gbp_year": 20515.13203125, + "all": { + "rate": 0.23298984026069908, + "count": 16294514.372394413, + "population": 69936587.59610294 + }, + "u16": { + "rate": 0.3341678225294723, + "count": 4521835.423247635, + "population": 13531630.271938667 + }, + "u18": { + "rate": 0.3364532579020019, + "count": 5057541.576392353, + "population": 15031929.272818789 + }, + "hbai_dep": { + "rate": 0.33582958572177674, + "count": 5075353.906113207, + "population": 15112884.992562756 + } + }, + "without_limit": { + "line_gbp_year": 20515.13203125, + "all": { + "rate": 0.22778059178483795, + "count": 15930197.310052484, + "population": 69936587.59610294 + }, + "u16": { + "rate": 0.31680746914383723, + "count": 4286921.539843023, + "population": 13531630.271938667 + }, + "u18": { + "rate": 0.32028047932865245, + "count": 4814433.512732804, + "population": 15031929.272818789 + }, + "hbai_dep": { + "rate": 0.3197434404371944, + "count": 4832245.842453659, + "population": 15112884.992562756 + } + }, + "removal_effect": { + "all": { + "count_change": -364317.0623419285, + "rate_change_pp": -0.5209248475861128 + }, + "u16": { + "count_change": -234913.88340461254, + "rate_change_pp": -1.7360353385635074 + }, + "u18": { + "count_change": -243108.06365954876, + "rate_change_pp": -1.6172778573349478 + }, + "hbai_dep": { + "count_change": -243108.06365954876, + "rate_change_pp": -1.6086145284582354 + } + } + }, + "fixed_with_limit": { + "with_limit": { + "line_gbp_year": 20515.13203125, + "all": { + "rate": 0.23298984026069908, + "count": 16294514.372394413, + "population": 69936587.59610294 + }, + "u16": { + "rate": 0.3341678225294723, + "count": 4521835.423247635, + "population": 13531630.271938667 + }, + "u18": { + "rate": 0.3364532579020019, + "count": 5057541.576392353, + "population": 15031929.272818789 + }, + "hbai_dep": { + "rate": 0.33582958572177674, + "count": 5075353.906113207, + "population": 15112884.992562756 + } + }, + "without_limit": { + "line_gbp_year": 20515.13203125, + "all": { + "rate": 0.22778059178483795, + "count": 15930197.310052484, + "population": 69936587.59610294 + }, + "u16": { + "rate": 0.31680746914383723, + "count": 4286921.539843023, + "population": 13531630.271938667 + }, + "u18": { + "rate": 0.32028047932865245, + "count": 4814433.512732804, + "population": 15031929.272818789 + }, + "hbai_dep": { + "rate": 0.3197434404371944, + "count": 4832245.842453659, + "population": 15112884.992562756 + } + }, + "removal_effect": { + "all": { + "count_change": -364317.0623419285, + "rate_change_pp": -0.5209248475861128 + }, + "u16": { + "count_change": -234913.88340461254, + "rate_change_pp": -1.7360353385635074 + }, + "u18": { + "count_change": -243108.06365954876, + "rate_change_pp": -1.6172778573349478 + }, + "hbai_dep": { + "count_change": -243108.06365954876, + "rate_change_pp": -1.6086145284582354 + } + } + }, + "fixed_without_limit": { + "with_limit": { + "line_gbp_year": 20515.13203125, + "all": { + "rate": 0.23298984026069908, + "count": 16294514.372394413, + "population": 69936587.59610294 + }, + "u16": { + "rate": 0.3341678225294723, + "count": 4521835.423247635, + "population": 13531630.271938667 + }, + "u18": { + "rate": 0.3364532579020019, + "count": 5057541.576392353, + "population": 15031929.272818789 + }, + "hbai_dep": { + "rate": 0.33582958572177674, + "count": 5075353.906113207, + "population": 15112884.992562756 + } + }, + "without_limit": { + "line_gbp_year": 20515.13203125, + "all": { + "rate": 0.22778059178483795, + "count": 15930197.310052484, + "population": 69936587.59610294 + }, + "u16": { + "rate": 0.31680746914383723, + "count": 4286921.539843023, + "population": 13531630.271938667 + }, + "u18": { + "rate": 0.32028047932865245, + "count": 4814433.512732804, + "population": 15031929.272818789 + }, + "hbai_dep": { + "rate": 0.3197434404371944, + "count": 4832245.842453659, + "population": 15112884.992562756 + } + }, + "removal_effect": { + "all": { + "count_change": -364317.0623419285, + "rate_change_pp": -0.5209248475861128 + }, + "u16": { + "count_change": -234913.88340461254, + "rate_change_pp": -1.7360353385635074 + }, + "u18": { + "count_change": -243108.06365954876, + "rate_change_pp": -1.6172778573349478 + }, + "hbai_dep": { + "count_change": -243108.06365954876, + "rate_change_pp": -1.6086145284582354 + } + } + } + }, + "absolute_ahc_continuity_check": { + "with_limit": { + "all": 13308574.643841207, + "u16": 3823821.647847593, + "u18": 4274117.985204399, + "hbai_dep": 4282418.631839693 + }, + "without_limit": { + "all": 13028998.553302944, + "u16": 3642525.343844831, + "u18": 4087835.8398367763, + "hbai_dep": 4094797.2934226394 + }, + "removal_count_change": { + "all": -279576.0905382633, + "u16": -181296.30400276184, + "u18": -186282.14536762238, + "hbai_dep": -187621.33841705322 + } + }, + "uc_cost_of_removal_gbp": 1104248292.8024673, + "external_pentagon": { + "_discipline": "legs are NOT same-concept; per-leg basis verbatim; no win/replication language", + "ifs": { + "value": -540000, + "basis": "two-child-limit removal alone, steady-state (fully rolled-in), fixed-line rel AHC" + }, + "govt_hmt": { + "value": -450000, + "basis": "'taking 450,000 children out of poverty' embedded in HMT B2025 scorecard two-child-limit measure name; horizon per govt materials (~2029-30)" + }, + "resolution_foundation": { + "value": -420000, + "basis": "LSO 2026: year-over-year child-poverty fall 33%->30% 2025-26 to 2026-27, Budget-package-driven (2CL-dominated), fixed-line rel AHC, IPPR tax-benefit model; NOT a pure 2CL-only leg" + }, + "ukmod_cempa_3_26": { + "value_children_2026": -13193, + "basis": "NET Autumn-Budget package (freezes + 2CL removal + WFA + PC cuts) child fixed-AHC count change FY2026/27 \u2014 freezes offset the 2CL gain; NOT comparable as 2CL-only; per-measure split not in staged rows" + }, + "pe": { + "basis": "2CL removal alone, 2026, actual partially-rolled-in law (born<2017 exempt), fixed baseline line (moot: line static), HBAI-dep-proxy children, calibrated take-up", + "comparable_leg": "fixed_with_limit removal_effect hbai_dep" + } + }, + "divergence_hypotheses_at_compute": [ + "roll_in_vintage: PE 2026 grandfathering (born<2017 exempt) = partially rolled-in law; IFS -540k is steady-state -> PE expected BELOW IFS magnitude", + "data_lineage: populace_uk_2023 (FRS 2023-24 base, calibrated) vs IFS/RF FRS vintages+own calibrations", + "takeup: PE UC take-up assumptions vs RF's UC 80% / IFS TAXBEN full-entitlement basis (registry axis)", + "median_construction: person- vs household-weighted median moves the line (both computed)", + "child_definition: hbai_dep proxy lacks HBAI marital/living-arrangement conditions (16-19 slice only)" + ] +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/two_child_fixed_line_fulltakeup_2026.json b/sources/campaign-2026-08-02/uk/two_child_fixed_line_fulltakeup_2026.json new file mode 100644 index 0000000..f96a4a5 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/two_child_fixed_line_fulltakeup_2026.json @@ -0,0 +1,360 @@ +{ + "reform_key": "two_child_limit_removal_fixed_line", + "year": 2026, + "takeup_mode": "fulltakeup", + "worlds": { + "with_limit": { + "world": "with_limit", + "year": 2026, + "mode": "fulltakeup", + "forced_flags": [ + "would_claim_uc", + "would_claim_housing_benefit", + "would_claim_child_benefit", + "would_claim_council_tax_reduction", + "would_claim_CTC", + "would_claim_WTC", + "would_claim_IS", + "claims_all_entitled_benefits" + ], + "construction": "gov.dwp.universal_credit.elements.child.limit.child_count: inf -> 2 (reinstate; born-pre-2017 exemption active)", + "reform_json": "{\"gov.dwp.universal_credit.elements.child.limit.child_count\": {\"2026-01-01.2028-12-31\": 2}}", + "hbai_dependent_child_proxy": "is_child_or_qualifying_young_person_for_child_tax_credit: under-16 OR 16-19 qualifying young person in full-time non-advanced education, excl. looked-after children (closest installed analogue of the HBAI dependent-child definition)", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "universal_credit": 53429818141.101036, + "household_net_income": 1803220878970.0093, + "gov_spending": 497880464939.9005 + } + }, + "without_limit": { + "world": "without_limit", + "year": 2026, + "mode": "fulltakeup", + "forced_flags": [ + "would_claim_uc", + "would_claim_housing_benefit", + "would_claim_child_benefit", + "would_claim_council_tax_reduction", + "would_claim_CTC", + "would_claim_WTC", + "would_claim_IS", + "claims_all_entitled_benefits" + ], + "construction": "baseline (limit abolished in current law)", + "reform_json": "baseline", + "hbai_dependent_child_proxy": "is_child_or_qualifying_young_person_for_child_tax_credit: under-16 OR 16-19 qualifying young person in full-time non-advanced education, excl. looked-after children (closest installed analogue of the HBAI dependent-child definition)", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "universal_credit": 55279919145.339645, + "household_net_income": 1804948205172.6, + "gov_spending": 499729028736.36316 + } + } + }, + "median_equiv_hbai_ahc_gbp_year": { + "with_limit": { + "person": 34427.55078125, + "household": 35764.1796875 + }, + "without_limit": { + "person": 34427.55078125, + "household": 35764.1796875 + } + }, + "median_weighting_primary": "person", + "median_weighting_note": "HBAI convention ranks individuals (person-weighted); pe-uk's in_relative_poverty_ahc uses household-weighted medians \u2014 both recorded, person-weighted used for all lines here", + "results": { + "floating": { + "with_limit": { + "line_gbp_year": 20656.53046875, + "all": { + "rate": 0.22032138557925557, + "count": 15408525.881858379, + "population": 69936587.59610294 + }, + "u16": { + "rate": 0.3100496618050528, + "count": 4195477.389485598, + "population": 13531630.271938667 + }, + "u18": { + "rate": 0.31366318749573424, + "count": 4714962.849922776, + "population": 15031929.272818789 + }, + "hbai_dep": { + "rate": 0.31302277508584303, + "count": 4730677.199925184, + "population": 15112884.992562756 + } + }, + "without_limit": { + "line_gbp_year": 20656.53046875, + "all": { + "rate": 0.21438922546870368, + "count": 14993650.846652657, + "population": 69936587.59610294 + }, + "u16": { + "rate": 0.2908677068310521, + "count": 3935914.266884446, + "population": 13531630.271938667 + }, + "u18": { + "rate": 0.2955064650136516, + "count": 4442032.281745911, + "population": 15031929.272818789 + }, + "hbai_dep": { + "rate": 0.29467505544873185, + "count": 4453390.2231737375, + "population": 15112884.992562756 + } + }, + "removal_effect": { + "all": { + "count_change": -414875.03520572186, + "rate_change_pp": -0.5932160110551893 + }, + "u16": { + "count_change": -259563.12260115147, + "rate_change_pp": -1.918195497400066 + }, + "u18": { + "count_change": -272930.5681768656, + "rate_change_pp": -1.8156722482082666 + }, + "hbai_dep": { + "count_change": -277286.9767514467, + "rate_change_pp": -1.8347719637111182 + } + } + }, + "fixed_with_limit": { + "with_limit": { + "line_gbp_year": 20656.53046875, + "all": { + "rate": 0.22032138557925557, + "count": 15408525.881858379, + "population": 69936587.59610294 + }, + "u16": { + "rate": 0.3100496618050528, + "count": 4195477.389485598, + "population": 13531630.271938667 + }, + "u18": { + "rate": 0.31366318749573424, + "count": 4714962.849922776, + "population": 15031929.272818789 + }, + "hbai_dep": { + "rate": 0.31302277508584303, + "count": 4730677.199925184, + "population": 15112884.992562756 + } + }, + "without_limit": { + "line_gbp_year": 20656.53046875, + "all": { + "rate": 0.21438922546870368, + "count": 14993650.846652657, + "population": 69936587.59610294 + }, + "u16": { + "rate": 0.2908677068310521, + "count": 3935914.266884446, + "population": 13531630.271938667 + }, + "u18": { + "rate": 0.2955064650136516, + "count": 4442032.281745911, + "population": 15031929.272818789 + }, + "hbai_dep": { + "rate": 0.29467505544873185, + "count": 4453390.2231737375, + "population": 15112884.992562756 + } + }, + "removal_effect": { + "all": { + "count_change": -414875.03520572186, + "rate_change_pp": -0.5932160110551893 + }, + "u16": { + "count_change": -259563.12260115147, + "rate_change_pp": -1.918195497400066 + }, + "u18": { + "count_change": -272930.5681768656, + "rate_change_pp": -1.8156722482082666 + }, + "hbai_dep": { + "count_change": -277286.9767514467, + "rate_change_pp": -1.8347719637111182 + } + } + }, + "fixed_without_limit": { + "with_limit": { + "line_gbp_year": 20656.53046875, + "all": { + "rate": 0.22032138557925557, + "count": 15408525.881858379, + "population": 69936587.59610294 + }, + "u16": { + "rate": 0.3100496618050528, + "count": 4195477.389485598, + "population": 13531630.271938667 + }, + "u18": { + "rate": 0.31366318749573424, + "count": 4714962.849922776, + "population": 15031929.272818789 + }, + "hbai_dep": { + "rate": 0.31302277508584303, + "count": 4730677.199925184, + "population": 15112884.992562756 + } + }, + "without_limit": { + "line_gbp_year": 20656.53046875, + "all": { + "rate": 0.21438922546870368, + "count": 14993650.846652657, + "population": 69936587.59610294 + }, + "u16": { + "rate": 0.2908677068310521, + "count": 3935914.266884446, + "population": 13531630.271938667 + }, + "u18": { + "rate": 0.2955064650136516, + "count": 4442032.281745911, + "population": 15031929.272818789 + }, + "hbai_dep": { + "rate": 0.29467505544873185, + "count": 4453390.2231737375, + "population": 15112884.992562756 + } + }, + "removal_effect": { + "all": { + "count_change": -414875.03520572186, + "rate_change_pp": -0.5932160110551893 + }, + "u16": { + "count_change": -259563.12260115147, + "rate_change_pp": -1.918195497400066 + }, + "u18": { + "count_change": -272930.5681768656, + "rate_change_pp": -1.8156722482082666 + }, + "hbai_dep": { + "count_change": -277286.9767514467, + "rate_change_pp": -1.8347719637111182 + } + } + } + }, + "absolute_ahc_continuity_check": { + "with_limit": { + "all": 12406764.190788925, + "u16": 3453040.589262724, + "u18": 3882981.4342074394, + "hbai_dep": 3887640.5123000145 + }, + "without_limit": { + "all": 11985518.698836744, + "u16": 3187144.298489094, + "u18": 3604883.245787859, + "hbai_dep": 3607718.511481762 + }, + "removal_count_change": { + "all": -421245.49195218086, + "u16": -265896.29077363014, + "u18": -278098.18841958046, + "hbai_dep": -279922.00081825256 + } + }, + "uc_cost_of_removal_gbp": 1850101004.2386093, + "external_pentagon": { + "_discipline": "legs are NOT same-concept; per-leg basis verbatim; no win/replication language", + "ifs": { + "value": -540000, + "basis": "two-child-limit removal alone, steady-state (fully rolled-in), fixed-line rel AHC" + }, + "govt_hmt": { + "value": -450000, + "basis": "'taking 450,000 children out of poverty' embedded in HMT B2025 scorecard two-child-limit measure name; horizon per govt materials (~2029-30)" + }, + "resolution_foundation": { + "value": -420000, + "basis": "LSO 2026: year-over-year child-poverty fall 33%->30% 2025-26 to 2026-27, Budget-package-driven (2CL-dominated), fixed-line rel AHC, IPPR tax-benefit model; NOT a pure 2CL-only leg" + }, + "ukmod_cempa_3_26": { + "value_children_2026": -13193, + "basis": "NET Autumn-Budget package (freezes + 2CL removal + WFA + PC cuts) child fixed-AHC count change FY2026/27 \u2014 freezes offset the 2CL gain; NOT comparable as 2CL-only; per-measure split not in staged rows" + }, + "pe": { + "basis": "2CL removal alone, 2026, actual partially-rolled-in law (born<2017 exempt), fixed baseline line (moot: line static), HBAI-dep-proxy children, calibrated take-up", + "comparable_leg": "fixed_with_limit removal_effect hbai_dep" + } + }, + "divergence_hypotheses_at_compute": [ + "roll_in_vintage: PE 2026 grandfathering (born<2017 exempt) = partially rolled-in law; IFS -540k is steady-state -> PE expected BELOW IFS magnitude", + "data_lineage: populace_uk_2023 (FRS 2023-24 base, calibrated) vs IFS/RF FRS vintages+own calibrations", + "takeup: PE UC take-up assumptions vs RF's UC 80% / IFS TAXBEN full-entitlement basis (registry axis)", + "median_construction: person- vs household-weighted median moves the line (both computed)", + "child_definition: hbai_dep proxy lacks HBAI marital/living-arrangement conditions (16-19 slice only)" + ] +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/two_child_limit_removal_2026.json b/sources/campaign-2026-08-02/uk/two_child_limit_removal_2026.json new file mode 100644 index 0000000..a1ce08e --- /dev/null +++ b/sources/campaign-2026-08-02/uk/two_child_limit_removal_2026.json @@ -0,0 +1,47 @@ +{ + "reform_key": "two_child_limit_removal", + "year": 2026, + "reform_hint": "Remove the UC two-child limit", + "pe_construction": "gov.dwp.universal_credit.elements.child.limit.child_count: inf -> inf", + "reform_json": "{\"gov.dwp.universal_credit.elements.child.limit.child_count\": {\"2026-01-01.2028-12-31\": Infinity}}", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "income_tax": 421891913533.19946, + "national_insurance": 61450306465.09366, + "ni_employer": 185481157065.2179, + "child_benefit": 17434702263.490685, + "universal_credit": 39887838277.66961, + "vat": 219622883998.86896, + "household_net_income": 1791280163555.2764, + "gov_tax": 1046803930669.7205, + "gov_spending": 485663250574.56665 + }, + "poverty": { + "var": "in_poverty_ahc", + "rate_all": 0.18629731591349413, + "count_all": 13028998.553302944, + "rate_child_u16": 0.26918599390042075, + "count_child_u16": 3642525.343844831 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/two_child_reinstate_2026.json b/sources/campaign-2026-08-02/uk/two_child_reinstate_2026.json new file mode 100644 index 0000000..4f6956f --- /dev/null +++ b/sources/campaign-2026-08-02/uk/two_child_reinstate_2026.json @@ -0,0 +1,47 @@ +{ + "reform_key": "two_child_reinstate", + "year": 2026, + "reform_hint": "Reinstate the UC two-child limit (pre-AB2025 counterfactual)", + "pe_construction": "gov.dwp.universal_credit.elements.child.limit.child_count: inf -> 2", + "reform_json": "{\"gov.dwp.universal_credit.elements.child.limit.child_count\": {\"2026-01-01.2028-12-31\": 2}}", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "income_tax": 421891913533.19946, + "national_insurance": 61450306465.09366, + "ni_employer": 185481157065.2179, + "child_benefit": 17434702263.490685, + "universal_credit": 38783589984.86714, + "vat": 219622883998.86896, + "household_net_income": 1790266784216.2012, + "gov_tax": 1046803930669.7205, + "gov_spending": 484560539496.0421 + }, + "poverty": { + "var": "in_poverty_ahc", + "rate_all": 0.19029488142459497, + "count_all": 13308574.643841207, + "rate_child_u16": 0.28258395854764634, + "count_child_u16": 3823821.647847593 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/uk_scorecard_first.csv b/sources/campaign-2026-08-02/uk/uk_scorecard_first.csv new file mode 100644 index 0000000..13474a7 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/uk_scorecard_first.csv @@ -0,0 +1,11 @@ +reform,pe_gbp_m,hmrc_gbp_m,ratio,note +basic_rate_1p,7278,6900,1.05, +higher_rate_1p,3230,1600,2.02,TIE (milder) +additional_rate_1p,1869,145,12.89,"TIE: HMRC behavioural, PE static" +pa_100,-899,-810,1.11, +employee_ni_1pp,6034,5350,1.13, +employer_ni_1pp,10661,11150,0.96,pe-uk wage incidence: IT+NI spillover -4450m +class4_1pp,584,440,1.33, +cb_first_1pw,-441,-335,1.32, +vat_1pp,10813,8800,1.23, +two_child_limit_removal_vs_preAB2025,1104,,,"children lifted 181,296; PE 2026 baseline already abolishes (AB2025 encoded)" diff --git a/sources/campaign-2026-08-02/uk/uprating_check_april2026.json b/sources/campaign-2026-08-02/uk/uprating_check_april2026.json new file mode 100644 index 0000000..c5dfee7 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/uprating_check_april2026.json @@ -0,0 +1,144 @@ +{ + "check": "april_2026_uprating_tree_vs_rf_staged", + "date_run": "2026-08-02", + "tree_package": "policyengine-uk (installed, .venv-pe)", + "windows": { + "before": "2025-06-01", + "after": "2026-06-01" + }, + "rf_staged_claims": { + "inflation_linked_benefits": 0.038, + "state_pension_triple_lock_earnings": 0.048, + "uc_standard_allowance": 0.062, + "uc_standard_allowance_u25": 0.068, + "uc_health_element_existing": 0.015, + "lha_frozen": 0.0 + }, + "tree_changes": { + "uc_standard_single_25plus": { + "path": "gov.dwp.universal_credit.standard_allowance.amount.SINGLE_OLD", + "before": 400.14, + "after": 424.9, + "pct": 0.061878342580096835 + }, + "uc_standard_single_u25": { + "path": "gov.dwp.universal_credit.standard_allowance.amount.SINGLE_YOUNG", + "before": 316.98, + "after": 338.58, + "pct": 0.06814310051107308 + }, + "uc_standard_couple_25plus": { + "path": "gov.dwp.universal_credit.standard_allowance.amount.COUPLE_OLD", + "before": 628.1, + "after": 666.97, + "pct": 0.06188505015124979 + }, + "uc_standard_couple_u25": { + "path": "gov.dwp.universal_credit.standard_allowance.amount.COUPLE_YOUNG", + "before": 497.55, + "after": 528.34, + "pct": 0.06188322781629996 + }, + "uc_child_element": { + "path": "gov.dwp.universal_credit.elements.child.amount", + "before": 292.81, + "after": 303.94, + "pct": 0.03801099689218268 + }, + "child_benefit_eldest": { + "path": "gov.hmrc.child_benefit.amount.eldest", + "before": 26.05, + "after": 27.05, + "pct": 0.03838771593090207 + }, + "child_benefit_additional": { + "path": "gov.hmrc.child_benefit.amount.additional", + "before": 17.25, + "after": 17.9, + "pct": 0.03768115942028971 + }, + "state_pension_new": { + "path": "gov.dwp.state_pension.new_state_pension.amount", + "before": 230.25, + "after": 241.3, + "pct": 0.0479913137893595 + }, + "state_pension_basic": { + "path": "gov.dwp.state_pension.basic_state_pension.amount", + "before": 176.45, + "after": 184.9, + "pct": 0.0478889203740438 + }, + "uc_lcwra_element": { + "path": "gov.dwp.universal_credit.elements.disabled.amount", + "before": 423.27, + "after": 217.26, + "pct": -0.4867106102487774 + }, + "pension_credit_mig_single": { + "path": "gov.dwp.pension_credit.guarantee_credit.minimum_guarantee.single", + "error": "KeyError: 'single'" + } + }, + "notes": [ + "tree-only check; no sim. Paths that error are recorded verbatim (vocabulary gaps or different parameter layout \u2014 fail loud, no guessing).", + "LHA rates are data-driven per BRMA in pe-uk; freeze verification needs the LHA parameter/dataset mechanism \u2014 recorded as follow-up if paths error.", + "UC health element AB2025 new/existing split may be structural rather than a single amount parameter; error here means map the encoding first." + ], + "findings": { + "concordant": { + "uc_standard_25plus": { + "pe": 0.0619, + "rf": 0.062 + }, + "uc_standard_single_u25": { + "pe": 0.0681, + "rf": 0.068 + }, + "inflation_linked (uc child element)": { + "pe": 0.038, + "rf": 0.038 + }, + "child_benefit": { + "pe": "0.0377-0.0384 (5p rounding)", + "rf": 0.038 + }, + "state_pension_new_and_basic": { + "pe": "0.0479-0.0480", + "rf": 0.048 + } + }, + "flags": [ + { + "id": "uc_couple_u25_uprating", + "severity": "low", + "note": "pe-uk couple-U25 standard allowance +6.19% while single-U25 +6.81%; RF staged a single U25 figure (6.8%). Verify against the DWP 2026-27 rates order which couple-young rate applies." + }, + { + "id": "lcwra_halving_applied_to_stock", + "severity": "RESOLVED_FALSE_ALARM", + "class": "verification_method", + "evidence": "parameters/gov/dwp/universal_credit/elements/disabled/amount.yaml: 2026-04-01: 217.26 (=\u00a350/wk) replacing 423.27; variables/.../uc_LCWRA_element.py pays flat p.amount to every uc_limited_capability_for_WRA person \u2014 no new/existing-claimant split anywhere in the disability_element tree.", + "external_basis": "RF staged: UC health element EXISTING recipients +1.5% April 2026 (new claimants halved to \u00a350/wk); HMT B2025 measure name: \"Changes to the standard allowance and health element to protect existing claimants\".", + "implication": "PE 2026+ understates UC for the existing LCWRA stock by ~\u00a32.5k/yr each; depresses disabled-family incomes in ALL 2026 UK results this session (both two-child worlds share it; deltas mostly net out).", + "action": "file upstream policyengine-uk issue; note in every 2026 UK result until fixed.", + "resolution": "policyengine_uk/simulation.py applies universal_credit_july_2025_reform.simulation_modifier UNCONDITIONALLY at baseline build (line ~177): per year 2026-29 it stochastically tags post-2025 claimants (2026: 11%, WPI/Trussell shares, rng seed 43) at the new-claimant \u00a3217.26 rate and set_inputs the CPI-protected combined-award value for the existing stock (PR #1567, closed issue #1389). The certified baseline USED IN ALL THIS SESSION'S UK RUNS therefore models the existing-claimant protection.", + "method_lesson": "tree+variable-formula reading is insufficient for parameters overlaid by simulation-level modifiers; any tree-only uprating check must cross-check scenarios/ and simulation.py build hooks before flagging.", + "residual": "implied existing-claimant health-element growth in the modifier is CPI-combined-minus-uplifted-SA, consistent with RF's +1.5% staged figure; stochastic new-claimant share (11% 2026) is an assumptions-registry row (WPI Economics/Trussell, admin PIP data 2025)." + }, + { + "id": "param_step_conventions_mixed", + "severity": "info", + "note": "standard allowance/state pension carry Jan-1-stepped projected values to 2041; disabled amount.yaml steps at real April dates. Year-on-year (June-June) windows capture both." + }, + { + "id": "pension_credit_mig_path", + "severity": "info", + "note": "gov.dwp.pension_credit.guarantee_credit.minimum_guarantee.single KeyError \u2014 layout differs; map before checking MIG uprating." + } + ], + "assumptions_registry_rows": [ + "pe-uk UC rebalancing: post-2025-claimant share by year {2026: 0.11, 2027: 0.13, 2028: 0.16, 2029: 0.22} (WPI Economics for Trussell Trust, admin PIP data 2025), stochastic rng seed 43, applied at build" + ] + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/uk/vat_1pp_2026.json b/sources/campaign-2026-08-02/uk/vat_1pp_2026.json new file mode 100644 index 0000000..d351685 --- /dev/null +++ b/sources/campaign-2026-08-02/uk/vat_1pp_2026.json @@ -0,0 +1,40 @@ +{ + "reform_key": "vat_1pp", + "year": 2026, + "reform_hint": "Change standard rate by 1 percentage point (VAT)", + "pe_construction": "gov.hmrc.vat.standard_rate: 0.2 -> 0.21000000000000002", + "reform_json": "{\"gov.hmrc.vat.standard_rate\": {\"2026-01-01.2028-12-31\": 0.21000000000000002}}", + "bundle": { + "bundle_id": "uk-5.0.1", + "country_id": "uk", + "policyengine_version": "5.0.1", + "model_package": "policyengine-uk", + "model_version": "2.89.2", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_uk_2023", + "default_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_build_id": "populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "certified_data_artifact_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "data_build_model_version": "2.89.2", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_uk_2023", + "runtime_dataset_uri": "hf://policyengine/populace-uk-private/populace_uk_2023.h5@populace-uk-2023-dd68c73-4aa4b14-20260619T023711Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-uk-private/snapshots/a75a9a831d6b07aaffbd09713f2a1124f5c0f08f/populace_uk_2023.h5", + "managed_by": "policyengine.py" + }, + "aggregates_gbp": { + "income_tax": 421891913533.19946, + "national_insurance": 61450306465.09366, + "ni_employer": 185481157065.2179, + "child_benefit": 17434702263.490685, + "universal_credit": 39887838277.66961, + "vat": 230436219162.37634, + "household_net_income": 1780466827149.559, + "gov_tax": 1057617265773.3811, + "gov_spending": 485663250574.56665 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/us/SPM_NOTES.md b/sources/campaign-2026-08-02/us/SPM_NOTES.md new file mode 100644 index 0000000..135fdc5 --- /dev/null +++ b/sources/campaign-2026-08-02/us/SPM_NOTES.md @@ -0,0 +1,40 @@ +# SPM level differences vs ASEC-anchored series — what is in hand + +Date: 2026-08-02. Register: descriptive (methodological_difference; issue #9 +ruling — Scorecard is descriptive by default). + +## The difference + +Populace calculates benefits and recalibrates where CPS-ASEC carries +survey-reported attributes; SPM level series therefore differ from +ASEC-anchored series (CPSP, Census SPM). + +Measured at 2024 on the certified populace_us bundle: +- PE child SPM (unforced year-grid baseline): **16.97%** +- Census-published 2024 child SPM: **13.4%** (CPSP TCJA-world: 13.3%) +- Forcing credit take-up/filing (takes_up_eitc + would_file_*) accounts for + only **~0.2pp** of the difference (16.97% → ~16.7% forced). + +## Named remaining channels (undecomposed) + +1. **Calculated vs reported benefits** — PE computes program amounts + (calibrated take-up) where ASEC carries survey reports. Known-issue + component: early_head_start at engine-default 100% take-up flows inside + household_net_income (populace#593; pe_gap citable for these rows). +2. **Recalibration** — populace reweighting/sparsification vs ASEC weights. +3. **Threshold treatment** — the certified environment runs spm-calculator + 0.3.1 (the version policyengine-us#9081 flags). Verified 2026-08-02 from + the spm-calculator PR#32 branch data (BLS corrected workbook sha256 + e7931a1f…): at sim-year 2024 the installed values EXACTLY equal the + pre-correction published series (renter 39,430 / owner+m 39,068 / + owner−m 32,586), so the 2019-2023 hand-entry errors (≤8%) do not affect + anything computed this session; only the BLS 2026-07-17 correction + applies at 2024 (−0.53% / +0.42% / +0.90% by tenure — small). + +## Decomposition home + +Channel decomposition (and an SPM calculation tool) is **Max's own pending +project** — the policyengine-spm-decomposition repo. Not built in the +compute-campaign lane (stood down 8/2 per redirect; a queued threshold-swap +sim was cancelled before running). This file + the methodological_difference +registry entry are the campaign's complete record. diff --git a/sources/campaign-2026-08-02/us/cpsp_ctc/NOT_COMPUTED_2023.json b/sources/campaign-2026-08-02/us/cpsp_ctc/NOT_COMPUTED_2023.json new file mode 100644 index 0000000..60955a9 --- /dev/null +++ b/sources/campaign-2026-08-02/us/cpsp_ctc/NOT_COMPUTED_2023.json @@ -0,0 +1,14 @@ +{ + "status": "not_computed", + "scenarios": [ + "tcja_2023", + "no_ctc_2023", + "afa_2023" + ], + "cpsp_claims_affected": "What Could 2023 Child Poverty Rates... (Table 1: No CTC / 2023 TCJA / 2023 AFA x u18+u6 x 50/100/150/200pct thresholds)", + "reason": "Certified populace_us artifact (populace_us_2024.h5, single _time_period=2024) defines weights only at 2024; a 2023 calculation returns zero weighted population (verified 2026-08-02: tcja_2023 run failed ZeroDivisionError; h5 inspected \u2014 single-period entity tables). Comparing CPSP income-year-2023 claims against a PE-2024 run would be a year-mismatched comparison; declined.", + "unblock_path": "a certified populace_us artifact carrying 2023 weights (or a 2023-vintage certified bundle)", + "date": "2026-08-02", + "decision": "DEFER (calibration-session shepherd call, 8/2): a certified multi-period build is multi-day populace build-lane work; 12 CPSP-2023 rows do not justify it and the 2024 table already delivers the same_assumptions test.", + "revisit_trigger": "populace ships multi-year certified artifacts for its own roadmap reasons (long-term-CPS thread) \u2014 these rows then unlock free. Recorded as trigger, not a build request." +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/us/cpsp_ctc/afa_2024.json b/sources/campaign-2026-08-02/us/cpsp_ctc/afa_2024.json new file mode 100644 index 0000000..a65c86d --- /dev/null +++ b/sources/campaign-2026-08-02/us/cpsp_ctc/afa_2024.json @@ -0,0 +1,99 @@ +{ + "scenario": "afa", + "year": 2024, + "cpsp_scenario_label": "AFA CTC", + "reform_hint": "AFA-2025 (H.R.2763) per CPSP 2024 brief: $4,320/$3,600 annual deflated x0.97153 to 2024$, fully refundable, 17-year-olds in, first tier 150k/112.5k and second tier 400k/300k(HoH) deflated, $2,000 floor deflated", + "pe_construction": [ + "arpa u6 4197.04 / 6-17 3497.53", + "first-tier {'JOINT': 145730.6, 'SURVIVING_SPOUSE': 145730.6, 'SINGLE': 72865.3, 'SEPARATE': 72865.3, 'HEAD_OF_HOUSEHOLD': 109297.95}", + "qualifying age -> 18", + "fully refundable" + ], + "reform_json": "{\"gov.irs.credits.ctc.amount.arpa[0].amount\": {\"2024-01-01.2024-12-31\": 4197.04}, \"gov.irs.credits.ctc.amount.arpa[1].amount\": {\"2024-01-01.2024-12-31\": 3497.53}, \"gov.irs.credits.ctc.amount.base[1].threshold\": {\"2024-01-01.2024-12-31\": 18}, \"gov.irs.credits.ctc.phase_out.arpa.in_effect\": {\"2024-01-01.2024-12-31\": true}, \"gov.irs.credits.ctc.refundable.fully_refundable\": {\"2024-01-01.2024-12-31\": true}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.JOINT\": {\"2024-01-01.2024-12-31\": 145730.6}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.SURVIVING_SPOUSE\": {\"2024-01-01.2024-12-31\": 145730.6}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.SINGLE\": {\"2024-01-01.2024-12-31\": 72865.3}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.SEPARATE\": {\"2024-01-01.2024-12-31\": 72865.3}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.HEAD_OF_HOUSEHOLD\": {\"2024-01-01.2024-12-31\": 109297.95}, \"gov.irs.credits.ctc.phase_out.threshold.HEAD_OF_HOUSEHOLD\": {\"2024-01-01.2024-12-31\": 291461.2}, \"gov.irs.credits.ctc.phase_out.threshold.JOINT\": {\"2024-01-01.2024-12-31\": 388614.93}, \"gov.irs.credits.ctc.phase_out.threshold.SURVIVING_SPOUSE\": {\"2024-01-01.2024-12-31\": 388614.93}, \"gov.irs.credits.ctc.phase_out.threshold.SINGLE\": {\"2024-01-01.2024-12-31\": 194307.47}, \"gov.irs.credits.ctc.phase_out.threshold.SEPARATE\": {\"2024-01-01.2024-12-31\": 194307.47}, \"gov.irs.credits.ctc.amount.base[0].amount\": {\"2024-01-01.2024-12-31\": 1943.07}}", + "takeup_basis": "100% credit take-up/filing: takes_up_eitc, would_file_taxes_voluntarily, would_file_if_eligible_for_refundable_credit forced True; benefit-side take-up left calibrated", + "assumptions": { + "cpi_u_annual": { + "2020": 258.811, + "2022": 292.655, + "2024": 313.689, + "2025": 322.879 + }, + "afa23_inflation_factor_2020_to_2022": 1.1307672394140897, + "deflator_2025_to_2024": 0.9715373251279892, + "cpi_2025_note": "CPSP's exact CPI vintage for 2025 unstated; annual avg assumed", + "named_construction_deltas": [ + "AFA newborn initial payment omitted (PE lacks parameter): PE understates AFA generosity for infants (~$2.3k one-time)", + "birth-month proration omitted: PE gives full-year credit to age-0/turning children (overstates vs CPSP)", + "2024 AFA refundable-ODC modeled non-refundable in PE (18+ dependents only)", + "single/separate-filer thresholds where CPSP brief silent: ARPA/TCJA structure assumed", + "PE applies child-SSN requirement via imputed card type; Census/TAXSIM ASEC basis may not" + ] + }, + "data_vintage_note": "PE: certified populace_us dataset uprated to sim year. CPSP: raw public-use CPS-ASEC 2025 (income year 2024); levels also differ via PE benefit-take-up calibration vs ASEC survey-reported transfers", + "bundle": { + "bundle_id": "us-5.0.1", + "country_id": "us", + "policyengine_version": "5.0.1", + "model_package": "policyengine-us", + "model_version": "1.764.6", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_us_2024", + "default_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_build_id": "populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_artifact_sha256": "48b9d479fb4fd1c3537f9383ce4697d130b6f618658409d74f6233c43b994c7e", + "data_build_model_version": "1.764.6", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_us_2024", + "runtime_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-us/snapshots/26dcad66867687f15735dc4926523e3741920836/populace_us_2024.h5", + "managed_by": "policyengine.py" + }, + "metrics": { + "all": { + "population": 340077321.9414408, + "rate_50": 0.026771798510353752, + "count_50": 9104481.54095696, + "rate_100": 0.11139979254868117, + "count_100": 37884543.11478756, + "rate_150": 0.2726344814844238, + "count_150": 92716804.33211619, + "rate_200": 0.42144585825397135, + "count_200": 143324178.81832266 + }, + "u18": { + "population": 76683005.28060344, + "rate_50": 0.012542940562574031, + "count_50": 961830.3773941596, + "rate_100": 0.10654836093217117, + "count_100": 8170448.524001323, + "rate_150": 0.35490068937353625, + "count_150": 27214851.43732068, + "rate_200": 0.5512698127062661, + "count_200": 42273025.95879187 + }, + "u6": { + "population": 22697940.657062482, + "rate_50": 0.012571612266481532, + "count_50": 285349.7091881966, + "rate_100": 0.11520327849739191, + "count_100": 2614877.178832844, + "rate_150": 0.38571318969055646, + "count_150": 8754895.090242535, + "rate_200": 0.5860314324825843, + "count_200": 13301706.677663017 + } + }, + "aggregates_usd": { + "ctc": 258225118328.51355, + "ctc_value": 256012985393.95862, + "refundable_ctc": 250255721682.39594, + "non_refundable_ctc": 7969396646.117598, + "eitc": 70601054651.1914, + "income_tax": 2124400072610.9724, + "spm_unit_net_income": 13027237544368.295 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/us/cpsp_ctc/comparison_2024.json b/sources/campaign-2026-08-02/us/cpsp_ctc/comparison_2024.json new file mode 100644 index 0000000..fc2d4ab --- /dev/null +++ b/sources/campaign-2026-08-02/us/cpsp_ctc/comparison_2024.json @@ -0,0 +1,243 @@ +{ + "comparison": "cpsp_ctc_counterfactuals_2024", + "external": { + "publication": "What Could 2024 Child Poverty Rates Have Looked Like Had an Expanded Child Tax Credit Been in Place? (CPSP, CPS-ASEC 2025, TAXSIM-computed credits, 100% take-up, static)", + "values_basis": "Table 1, 100% SPM threshold, staged claims verbatim" + }, + "pe_basis": { + "bundle": { + "bundle_id": "us-5.0.1", + "country_id": "us", + "policyengine_version": "5.0.1", + "model_package": "policyengine-us", + "model_version": "1.764.6", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_us_2024", + "default_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_build_id": "populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_artifact_sha256": "48b9d479fb4fd1c3537f9383ce4697d130b6f618658409d74f6233c43b994c7e", + "data_build_model_version": "1.764.6", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_us_2024", + "runtime_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-us/snapshots/26dcad66867687f15735dc4926523e3741920836/populace_us_2024.h5", + "managed_by": "policyengine.py" + }, + "takeup": "100% credit take-up/filing: takes_up_eitc, would_file_taxes_voluntarily, would_file_if_eligible_for_refundable_credit forced True; benefit-side take-up left calibrated", + "constructions": { + "tcja": [], + "no_ctc": [ + "base[0].amount 2000 -> 0", + "adult_dependent 500 -> 0" + ], + "obbba": [ + "base 2000 -> 2137.38", + "refundable cap 1700 -> 1651.61", + "phase-in threshold 2500 -> 2428.84", + "thresholds x0.97154" + ], + "afa": [ + "arpa u6 4197.04 / 6-17 3497.53", + "first-tier {'JOINT': 145730.6, 'SURVIVING_SPOUSE': 145730.6, 'SINGLE': 72865.3, 'SEPARATE': 72865.3, 'HEAD_OF_HOUSEHOLD': 109297.95}", + "qualifying age -> 18", + "fully refundable" + ] + }, + "assumptions": { + "cpi_u_annual": { + "2020": 258.811, + "2022": 292.655, + "2024": 313.689, + "2025": 322.879 + }, + "afa23_inflation_factor_2020_to_2022": 1.1307672394140897, + "deflator_2025_to_2024": 0.9715373251279892, + "cpi_2025_note": "CPSP's exact CPI vintage for 2025 unstated; annual avg assumed", + "named_construction_deltas": [ + "AFA newborn initial payment omitted (PE lacks parameter): PE understates AFA generosity for infants (~$2.3k one-time)", + "birth-month proration omitted: PE gives full-year credit to age-0/turning children (overstates vs CPSP)", + "2024 AFA refundable-ODC modeled non-refundable in PE (18+ dependents only)", + "single/separate-filer thresholds where CPSP brief silent: ARPA/TCJA structure assumed", + "PE applies child-SSN requirement via imputed card type; Census/TAXSIM ASEC basis may not" + ] + } + }, + "levels": { + "tcja": { + "u18": { + "pe": 0.1677105433364713, + "cpsp": 0.133, + "delta_pp": 3.4710543336471305, + "ratio": 1.260981528845649 + }, + "u6": { + "pe": 0.17791888414943094, + "cpsp": 0.145, + "delta_pp": 3.291888414943095, + "ratio": 1.2270267872374547 + } + }, + "no_ctc": { + "u18": { + "pe": 0.2115468145577173, + "cpsp": 0.166, + "delta_pp": 4.554681455771728, + "ratio": 1.274378400950104 + }, + "u6": { + "pe": 0.22737614889930013, + "cpsp": 0.178, + "delta_pp": 4.937614889930014, + "ratio": 1.2773940949398885 + } + }, + "obbba": { + "u18": { + "pe": 0.16740114539030831, + "cpsp": 0.133, + "delta_pp": 3.440114539030831, + "ratio": 1.2586552284985586 + }, + "u6": { + "pe": 0.1780928937346883, + "cpsp": 0.144, + "delta_pp": 3.409289373468832, + "ratio": 1.2367562064908912 + } + }, + "afa": { + "u18": { + "pe": 0.10654836093217117, + "cpsp": 0.088, + "delta_pp": 1.8548360932171173, + "ratio": 1.2107768287746725 + }, + "u6": { + "pe": 0.11520327849739191, + "cpsp": 0.093, + "delta_pp": 2.220327849739191, + "ratio": 1.2387449300794828 + } + } + }, + "changes": { + "no_ctc_vs_tcja": { + "u18": { + "pe_pp": 4.383627122124597, + "cpsp_pp": 3.3000000000000003, + "pe_count": 3361497.0175407697 + }, + "u6": { + "pe_pp": 4.94572647498692, + "cpsp_pp": 3.3000000000000003, + "pe_count": 1122578.060353159 + } + }, + "obbba_vs_tcja": { + "u18": { + "pe_pp": -0.03093979461629981, + "cpsp_pp": 0.0, + "pe_count": -23725.564339423552 + }, + "u6": { + "pe_pp": 0.01740095852573731, + "cpsp_pp": -0.10000000000000009, + "pe_count": 3949.6592399319634 + } + }, + "afa_vs_tcja": { + "u18": { + "pe_pp": -6.1162182404300145, + "cpsp_pp": -4.500000000000001, + "pe_count": -4690099.956282178 + }, + "u6": { + "pe_pp": -6.271560565203902, + "cpsp_pp": -5.199999999999999, + "pe_count": -1423515.0953617143 + } + }, + "tcja_vs_no_ctc": { + "u18": { + "pe_pp": -4.383627122124597, + "cpsp_pp": -3.3000000000000003, + "pe_count": -3361497.0175407697 + }, + "u6": { + "pe_pp": -4.94572647498692, + "cpsp_pp": -3.3000000000000003, + "pe_count": -1122578.060353159 + } + }, + "obbba_vs_no_ctc": { + "u18": { + "pe_pp": -4.414566916740897, + "cpsp_pp": -3.3000000000000003, + "pe_count": -3385222.581880193 + }, + "u6": { + "pe_pp": -4.928325516461182, + "cpsp_pp": -3.4000000000000004, + "pe_count": -1118628.401113227 + } + }, + "afa_vs_no_ctc": { + "u18": { + "pe_pp": -10.499845362554613, + "cpsp_pp": -7.800000000000002, + "pe_count": -8051596.973822948 + }, + "u6": { + "pe_pp": -11.217287040190822, + "cpsp_pp": -8.5, + "pe_count": -2546093.155714873 + } + } + }, + "diagnosis_hypotheses": [ + { + "class": "methodological_difference", + "applies_to": "levels", + "note": "Populace calculates benefits and recalibrates where CPS-ASEC carries survey-reported attributes; SPM level series therefore differ from ASEC-anchored series (CPSP, Census SPM). Observed at 2024: PE unforced 16.97% vs Census-published 13.4%; credit-take-up forcing accounts for ~0.2pp of the difference. Method registry links: populace PR#32 / census #9081 (SPM threshold treatment); channel decomposition (calculated-vs-reported benefits, recalibration, threshold treatment) lives in Max's pending policyengine-spm-decomposition project (not this lane); full record: results/us/SPM_NOTES.md. Descriptive classification per issue #9 (Max 8/2): not tied to a known issue in either system." + }, + { + "class": "density_at_threshold", + "applies_to": "changes", + "note": "PE's higher measured level implies more children near the threshold, so scenario deltas scale up accordingly. CHANGE comparisons are the same_assumptions surface; directional consistency is the informative result." + }, + { + "class": "construction_delta", + "applies_to": "afa", + "note": "newborn payment + birth-month proration omitted; refundable ODC non-refundable in PE (named, signed in scenario files)" + }, + { + "class": "external_model_lineage", + "applies_to": "all", + "note": "CPSP 2024 brief computes credits via NBER TAXSIM on ASEC 2025; PE computes full tax law on populace ECPS." + }, + { + "class": "pe_gap", + "applies_to": "levels", + "action_link": "populace#593", + "note": "early_head_start on the certified Build P artifact runs at engine-default 100% take-up (5.16M participants / $112.256B; take-up flag not stored) and its dollars flow inside household_net_income, so it is poverty-relevant and affects these level rows. Known-issue citation per the gating rule (calibration session verified scope 8/2); magnitude within the level difference not yet isolated. CHIP (also #593) is program-aggregate-only and does NOT affect these rows." + } + ], + "not_computed": { + "status": "not_computed", + "scenarios": [ + "tcja_2023", + "no_ctc_2023", + "afa_2023" + ], + "cpsp_claims_affected": "What Could 2023 Child Poverty Rates... (Table 1: No CTC / 2023 TCJA / 2023 AFA x u18+u6 x 50/100/150/200pct thresholds)", + "reason": "Certified populace_us artifact (populace_us_2024.h5, single _time_period=2024) defines weights only at 2024; a 2023 calculation returns zero weighted population (verified 2026-08-02: tcja_2023 run failed ZeroDivisionError; h5 inspected \u2014 single-period entity tables). Comparing CPSP income-year-2023 claims against a PE-2024 run would be a year-mismatched comparison; declined.", + "unblock_path": "a certified populace_us artifact carrying 2023 weights (or a 2023-vintage certified bundle)", + "date": "2026-08-02", + "decision": "DEFER (calibration-session shepherd call, 8/2): a certified multi-period build is multi-day populace build-lane work; 12 CPSP-2023 rows do not justify it and the 2024 table already delivers the same_assumptions test.", + "revisit_trigger": "populace ships multi-year certified artifacts for its own roadmap reasons (long-term-CPS thread) \u2014 these rows then unlock free. Recorded as trigger, not a build request." + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/us/cpsp_ctc/no_ctc_2024.json b/sources/campaign-2026-08-02/us/cpsp_ctc/no_ctc_2024.json new file mode 100644 index 0000000..6a3c86d --- /dev/null +++ b/sources/campaign-2026-08-02/us/cpsp_ctc/no_ctc_2024.json @@ -0,0 +1,97 @@ +{ + "scenario": "no_ctc", + "year": 2024, + "cpsp_scenario_label": "No CTC", + "reform_hint": "No CTC (credit incl. ODC zeroed)", + "pe_construction": [ + "base[0].amount 2000 -> 0", + "adult_dependent 500 -> 0" + ], + "reform_json": "{\"gov.irs.credits.ctc.amount.base[0].amount\": {\"2024-01-01.2024-12-31\": 0}, \"gov.irs.credits.ctc.amount.adult_dependent\": {\"2024-01-01.2024-12-31\": 0}}", + "takeup_basis": "100% credit take-up/filing: takes_up_eitc, would_file_taxes_voluntarily, would_file_if_eligible_for_refundable_credit forced True; benefit-side take-up left calibrated", + "assumptions": { + "cpi_u_annual": { + "2020": 258.811, + "2022": 292.655, + "2024": 313.689, + "2025": 322.879 + }, + "afa23_inflation_factor_2020_to_2022": 1.1307672394140897, + "deflator_2025_to_2024": 0.9715373251279892, + "cpi_2025_note": "CPSP's exact CPI vintage for 2025 unstated; annual avg assumed", + "named_construction_deltas": [ + "AFA newborn initial payment omitted (PE lacks parameter): PE understates AFA generosity for infants (~$2.3k one-time)", + "birth-month proration omitted: PE gives full-year credit to age-0/turning children (overstates vs CPSP)", + "2024 AFA refundable-ODC modeled non-refundable in PE (18+ dependents only)", + "single/separate-filer thresholds where CPSP brief silent: ARPA/TCJA structure assumed", + "PE applies child-SSN requirement via imputed card type; Census/TAXSIM ASEC basis may not" + ] + }, + "data_vintage_note": "PE: certified populace_us dataset uprated to sim year. CPSP: raw public-use CPS-ASEC 2025 (income year 2024); levels also differ via PE benefit-take-up calibration vs ASEC survey-reported transfers", + "bundle": { + "bundle_id": "us-5.0.1", + "country_id": "us", + "policyengine_version": "5.0.1", + "model_package": "policyengine-us", + "model_version": "1.764.6", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_us_2024", + "default_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_build_id": "populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_artifact_sha256": "48b9d479fb4fd1c3537f9383ce4697d130b6f618658409d74f6233c43b994c7e", + "data_build_model_version": "1.764.6", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_us_2024", + "runtime_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-us/snapshots/26dcad66867687f15735dc4926523e3741920836/populace_us_2024.h5", + "managed_by": "policyengine.py" + }, + "metrics": { + "all": { + "population": 340077321.9414408, + "rate_50": 0.03430160664919018, + "count_50": 11665198.527545316, + "rate_100": 0.15294423801106727, + "count_100": 52012866.86917807, + "rate_150": 0.31962256044985593, + "count_150": 108696384.38985328, + "rate_200": 0.4446502186245642, + "count_200": 151215455.55051798 + }, + "u18": { + "population": 76683005.28060344, + "rate_50": 0.030338990644993225, + "count_50": 2326484.979838194, + "rate_100": 0.2115468145577173, + "count_100": 16222045.49782427, + "rate_150": 0.47403832698649456, + "count_150": 36350683.53151378, + "rate_200": 0.6032298336466971, + "count_200": 46257476.51894721 + }, + "u6": { + "population": 22697940.657062482, + "rate_50": 0.030133293797889434, + "count_50": 683963.7144263233, + "rate_100": 0.22737614889930013, + "count_100": 5160970.334547717, + "rate_150": 0.5130594358680161, + "count_150": 11645392.628878184, + "rate_200": 0.6387083592320758, + "count_200": 14497364.435019404 + } + }, + "aggregates_usd": { + "ctc": 0.0, + "ctc_value": 0.0, + "refundable_ctc": 0.0, + "non_refundable_ctc": 0.0, + "eitc": 70601054651.1914, + "income_tax": 2380413061757.3076, + "spm_unit_net_income": 12771629744865.883 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/us/cpsp_ctc/obbba_2024.json b/sources/campaign-2026-08-02/us/cpsp_ctc/obbba_2024.json new file mode 100644 index 0000000..ad6b173 --- /dev/null +++ b/sources/campaign-2026-08-02/us/cpsp_ctc/obbba_2024.json @@ -0,0 +1,99 @@ +{ + "scenario": "obbba", + "year": 2024, + "cpsp_scenario_label": "OBBBA CTC", + "reform_hint": "OBBBA CTC parameters (2025 statute) deflated to 2024 dollars per CPSP; parent-SSN restriction excluded (CPSP's stated basis; PE's adult_ssn_requirement_applies=false at 2024 anyway)", + "pe_construction": [ + "base 2000 -> 2137.38", + "refundable cap 1700 -> 1651.61", + "phase-in threshold 2500 -> 2428.84", + "thresholds x0.97154" + ], + "reform_json": "{\"gov.irs.credits.ctc.amount.base[0].amount\": {\"2024-01-01.2024-12-31\": 2137.38}, \"gov.irs.credits.ctc.refundable.individual_max\": {\"2024-01-01.2024-12-31\": 1651.61}, \"gov.irs.credits.ctc.refundable.phase_in.threshold\": {\"2024-01-01.2024-12-31\": 2428.84}, \"gov.irs.credits.ctc.phase_out.threshold.JOINT\": {\"2024-01-01.2024-12-31\": 388614.93}, \"gov.irs.credits.ctc.phase_out.threshold.SURVIVING_SPOUSE\": {\"2024-01-01.2024-12-31\": 388614.93}, \"gov.irs.credits.ctc.phase_out.threshold.SINGLE\": {\"2024-01-01.2024-12-31\": 194307.47}, \"gov.irs.credits.ctc.phase_out.threshold.SEPARATE\": {\"2024-01-01.2024-12-31\": 194307.47}, \"gov.irs.credits.ctc.phase_out.threshold.HEAD_OF_HOUSEHOLD\": {\"2024-01-01.2024-12-31\": 194307.47}}", + "takeup_basis": "100% credit take-up/filing: takes_up_eitc, would_file_taxes_voluntarily, would_file_if_eligible_for_refundable_credit forced True; benefit-side take-up left calibrated", + "assumptions": { + "cpi_u_annual": { + "2020": 258.811, + "2022": 292.655, + "2024": 313.689, + "2025": 322.879 + }, + "afa23_inflation_factor_2020_to_2022": 1.1307672394140897, + "deflator_2025_to_2024": 0.9715373251279892, + "cpi_2025_note": "CPSP's exact CPI vintage for 2025 unstated; annual avg assumed", + "named_construction_deltas": [ + "AFA newborn initial payment omitted (PE lacks parameter): PE understates AFA generosity for infants (~$2.3k one-time)", + "birth-month proration omitted: PE gives full-year credit to age-0/turning children (overstates vs CPSP)", + "2024 AFA refundable-ODC modeled non-refundable in PE (18+ dependents only)", + "single/separate-filer thresholds where CPSP brief silent: ARPA/TCJA structure assumed", + "PE applies child-SSN requirement via imputed card type; Census/TAXSIM ASEC basis may not" + ] + }, + "data_vintage_note": "PE: certified populace_us dataset uprated to sim year. CPSP: raw public-use CPS-ASEC 2025 (income year 2024); levels also differ via PE benefit-take-up calibration vs ASEC survey-reported transfers", + "bundle": { + "bundle_id": "us-5.0.1", + "country_id": "us", + "policyengine_version": "5.0.1", + "model_package": "policyengine-us", + "model_version": "1.764.6", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_us_2024", + "default_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_build_id": "populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_artifact_sha256": "48b9d479fb4fd1c3537f9383ce4697d130b6f618658409d74f6233c43b994c7e", + "data_build_model_version": "1.764.6", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_us_2024", + "runtime_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-us/snapshots/26dcad66867687f15735dc4926523e3741920836/populace_us_2024.h5", + "managed_by": "policyengine.py" + }, + "metrics": { + "all": { + "population": 340077321.9414408, + "rate_50": 0.03129767544073058, + "count_50": 10643629.64687606, + "rate_100": 0.13467726224666327, + "count_100": 45800682.67125036, + "rate_150": 0.29972014633707555, + "count_150": 101928024.6982094, + "rate_200": 0.432618836528447, + "count_200": 147123855.34801623 + }, + "u18": { + "population": 76683005.28060344, + "rate_50": 0.023035173308505408, + "count_50": 1766406.3164557356, + "rate_100": 0.16740114539030831, + "count_100": 12836822.915944077, + "rate_150": 0.42625804211237056, + "count_150": 32686747.694202594, + "rate_200": 0.5779523800305645, + "count_200": 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"external_claim_match": {"source": "cpsp", "metric": "poverty_rate", "period": 2024, "conditions": {"policy_scenario": "TCJA CTC", "subgroup": "children_under_18", "poverty_threshold": "100pct_spm"}}, "pe_value": 0.1677105433364713, "pe_construction": [], "reform_json": "baseline (current law)", "bundle_id": "us-5.0.1", "baseline_executed": "current-law enacted-OBBBA populace_us_2024 with credit take-up forced (see takeup_basis)", "status": "computed"} +{"lane": "cpsp_ctc_counterfactuals", "external_claim_match": {"source": "cpsp", "metric": "poverty_rate", "period": 2024, "conditions": {"policy_scenario": "TCJA CTC", "subgroup": "children_under_6", "poverty_threshold": "100pct_spm"}}, "pe_value": 0.17791888414943094, "pe_construction": [], "reform_json": "baseline (current law)", "bundle_id": "us-5.0.1", "baseline_executed": "current-law enacted-OBBBA populace_us_2024 with credit take-up forced (see takeup_basis)", "status": "computed"} +{"lane": "cpsp_ctc_counterfactuals", "external_claim_match": {"source": "cpsp", "metric": "poverty_rate", "period": 2024, "conditions": {"policy_scenario": "No CTC", "subgroup": "children_under_18", "poverty_threshold": "100pct_spm"}}, "pe_value": 0.2115468145577173, "pe_construction": ["base[0].amount 2000 -> 0", "adult_dependent 500 -> 0"], "reform_json": "{\"gov.irs.credits.ctc.amount.base[0].amount\": {\"2024-01-01.2024-12-31\": 0}, \"gov.irs.credits.ctc.amount.adult_dependent\": {\"2024-01-01.2024-12-31\": 0}}", "bundle_id": "us-5.0.1", "baseline_executed": "current-law enacted-OBBBA populace_us_2024 with credit take-up forced (see takeup_basis)", "status": "computed"} +{"lane": "cpsp_ctc_counterfactuals", "external_claim_match": {"source": "cpsp", "metric": "poverty_rate", "period": 2024, "conditions": {"policy_scenario": "No CTC", "subgroup": "children_under_6", "poverty_threshold": "100pct_spm"}}, "pe_value": 0.22737614889930013, "pe_construction": ["base[0].amount 2000 -> 0", "adult_dependent 500 -> 0"], "reform_json": "{\"gov.irs.credits.ctc.amount.base[0].amount\": {\"2024-01-01.2024-12-31\": 0}, \"gov.irs.credits.ctc.amount.adult_dependent\": {\"2024-01-01.2024-12-31\": 0}}", "bundle_id": "us-5.0.1", "baseline_executed": "current-law enacted-OBBBA populace_us_2024 with credit take-up forced (see takeup_basis)", "status": "computed"} +{"lane": "cpsp_ctc_counterfactuals", "external_claim_match": {"source": "cpsp", "metric": "poverty_rate", "period": 2024, "conditions": {"policy_scenario": "OBBBA CTC", "subgroup": "children_under_18", "poverty_threshold": "100pct_spm"}}, "pe_value": 0.16740114539030831, "pe_construction": ["base 2000 -> 2137.38", "refundable cap 1700 -> 1651.61", "phase-in threshold 2500 -> 2428.84", "thresholds x0.97154"], "reform_json": "{\"gov.irs.credits.ctc.amount.base[0].amount\": {\"2024-01-01.2024-12-31\": 2137.38}, \"gov.irs.credits.ctc.refundable.individual_max\": {\"2024-01-01.2024-12-31\": 1651.61}, \"gov.irs.credits.ctc.refundable.phase_in.threshold\": {\"2024-01-01.2024-12-31\": 2428.84}, \"gov.irs.credits.ctc.phase_out.threshold.JOINT\": {\"2024-01-01.2024-12-31\": 388614.93}, \"gov.irs.credits.ctc.phase_out.threshold.SURVIVING_SPOUSE\": {\"2024-01-01.2024-12-31\": 388614.93}, \"gov.irs.credits.ctc.phase_out.threshold.SINGLE\": {\"2024-01-01.2024-12-31\": 194307.47}, \"gov.irs.credits.ctc.phase_out.threshold.SEPARATE\": {\"2024-01-01.2024-12-31\": 194307.47}, \"gov.irs.credits.ctc.phase_out.threshold.HEAD_OF_HOUSEHOLD\": {\"2024-01-01.2024-12-31\": 194307.47}}", "bundle_id": "us-5.0.1", "baseline_executed": "current-law enacted-OBBBA populace_us_2024 with credit take-up forced (see takeup_basis)", "status": "computed"} +{"lane": "cpsp_ctc_counterfactuals", "external_claim_match": {"source": "cpsp", "metric": "poverty_rate", "period": 2024, "conditions": {"policy_scenario": "OBBBA CTC", "subgroup": "children_under_6", "poverty_threshold": "100pct_spm"}}, "pe_value": 0.1780928937346883, "pe_construction": ["base 2000 -> 2137.38", "refundable cap 1700 -> 1651.61", "phase-in threshold 2500 -> 2428.84", "thresholds x0.97154"], "reform_json": "{\"gov.irs.credits.ctc.amount.base[0].amount\": {\"2024-01-01.2024-12-31\": 2137.38}, \"gov.irs.credits.ctc.refundable.individual_max\": {\"2024-01-01.2024-12-31\": 1651.61}, \"gov.irs.credits.ctc.refundable.phase_in.threshold\": {\"2024-01-01.2024-12-31\": 2428.84}, \"gov.irs.credits.ctc.phase_out.threshold.JOINT\": {\"2024-01-01.2024-12-31\": 388614.93}, \"gov.irs.credits.ctc.phase_out.threshold.SURVIVING_SPOUSE\": {\"2024-01-01.2024-12-31\": 388614.93}, \"gov.irs.credits.ctc.phase_out.threshold.SINGLE\": {\"2024-01-01.2024-12-31\": 194307.47}, \"gov.irs.credits.ctc.phase_out.threshold.SEPARATE\": {\"2024-01-01.2024-12-31\": 194307.47}, \"gov.irs.credits.ctc.phase_out.threshold.HEAD_OF_HOUSEHOLD\": {\"2024-01-01.2024-12-31\": 194307.47}}", "bundle_id": "us-5.0.1", "baseline_executed": "current-law enacted-OBBBA populace_us_2024 with credit take-up forced (see takeup_basis)", "status": "computed"} +{"lane": "cpsp_ctc_counterfactuals", "external_claim_match": {"source": "cpsp", "metric": "poverty_rate", "period": 2024, "conditions": {"policy_scenario": "AFA CTC", "subgroup": "children_under_18", "poverty_threshold": "100pct_spm"}}, "pe_value": 0.10654836093217117, "pe_construction": ["arpa u6 4197.04 / 6-17 3497.53", "first-tier {'JOINT': 145730.6, 'SURVIVING_SPOUSE': 145730.6, 'SINGLE': 72865.3, 'SEPARATE': 72865.3, 'HEAD_OF_HOUSEHOLD': 109297.95}", "qualifying age -> 18", "fully refundable"], "reform_json": "{\"gov.irs.credits.ctc.amount.arpa[0].amount\": {\"2024-01-01.2024-12-31\": 4197.04}, \"gov.irs.credits.ctc.amount.arpa[1].amount\": {\"2024-01-01.2024-12-31\": 3497.53}, \"gov.irs.credits.ctc.amount.base[1].threshold\": {\"2024-01-01.2024-12-31\": 18}, \"gov.irs.credits.ctc.phase_out.arpa.in_effect\": {\"2024-01-01.2024-12-31\": true}, \"gov.irs.credits.ctc.refundable.fully_refundable\": {\"2024-01-01.2024-12-31\": true}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.JOINT\": {\"2024-01-01.2024-12-31\": 145730.6}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.SURVIVING_SPOUSE\": {\"2024-01-01.2024-12-31\": 145730.6}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.SINGLE\": {\"2024-01-01.2024-12-31\": 72865.3}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.SEPARATE\": {\"2024-01-01.2024-12-31\": 72865.3}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.HEAD_OF_HOUSEHOLD\": {\"2024-01-01.2024-12-31\": 109297.95}, \"gov.irs.credits.ctc.phase_out.threshold.HEAD_OF_HOUSEHOLD\": {\"2024-01-01.2024-12-31\": 291461.2}, \"gov.irs.credits.ctc.phase_out.threshold.JOINT\": {\"2024-01-01.2024-12-31\": 388614.93}, \"gov.irs.credits.ctc.phase_out.threshold.SURVIVING_SPOUSE\": {\"2024-01-01.2024-12-31\": 388614.93}, \"gov.irs.credits.ctc.phase_out.threshold.SINGLE\": {\"2024-01-01.2024-12-31\": 194307.47}, \"gov.irs.credits.ctc.phase_out.threshold.SEPARATE\": {\"2024-01-01.2024-12-31\": 194307.47}, \"gov.irs.credits.ctc.amount.base[0].amount\": {\"2024-01-01.2024-12-31\": 1943.07}}", "bundle_id": "us-5.0.1", "baseline_executed": "current-law enacted-OBBBA populace_us_2024 with credit take-up forced (see takeup_basis)", "status": "computed"} +{"lane": "cpsp_ctc_counterfactuals", "external_claim_match": {"source": "cpsp", "metric": "poverty_rate", "period": 2024, "conditions": {"policy_scenario": "AFA CTC", "subgroup": "children_under_6", "poverty_threshold": "100pct_spm"}}, "pe_value": 0.11520327849739191, "pe_construction": ["arpa u6 4197.04 / 6-17 3497.53", "first-tier {'JOINT': 145730.6, 'SURVIVING_SPOUSE': 145730.6, 'SINGLE': 72865.3, 'SEPARATE': 72865.3, 'HEAD_OF_HOUSEHOLD': 109297.95}", "qualifying age -> 18", "fully refundable"], "reform_json": "{\"gov.irs.credits.ctc.amount.arpa[0].amount\": {\"2024-01-01.2024-12-31\": 4197.04}, \"gov.irs.credits.ctc.amount.arpa[1].amount\": {\"2024-01-01.2024-12-31\": 3497.53}, \"gov.irs.credits.ctc.amount.base[1].threshold\": {\"2024-01-01.2024-12-31\": 18}, \"gov.irs.credits.ctc.phase_out.arpa.in_effect\": {\"2024-01-01.2024-12-31\": true}, \"gov.irs.credits.ctc.refundable.fully_refundable\": {\"2024-01-01.2024-12-31\": true}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.JOINT\": {\"2024-01-01.2024-12-31\": 145730.6}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.SURVIVING_SPOUSE\": {\"2024-01-01.2024-12-31\": 145730.6}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.SINGLE\": {\"2024-01-01.2024-12-31\": 72865.3}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.SEPARATE\": {\"2024-01-01.2024-12-31\": 72865.3}, \"gov.irs.credits.ctc.phase_out.arpa.threshold.HEAD_OF_HOUSEHOLD\": {\"2024-01-01.2024-12-31\": 109297.95}, \"gov.irs.credits.ctc.phase_out.threshold.HEAD_OF_HOUSEHOLD\": {\"2024-01-01.2024-12-31\": 291461.2}, \"gov.irs.credits.ctc.phase_out.threshold.JOINT\": {\"2024-01-01.2024-12-31\": 388614.93}, \"gov.irs.credits.ctc.phase_out.threshold.SURVIVING_SPOUSE\": {\"2024-01-01.2024-12-31\": 388614.93}, \"gov.irs.credits.ctc.phase_out.threshold.SINGLE\": {\"2024-01-01.2024-12-31\": 194307.47}, \"gov.irs.credits.ctc.phase_out.threshold.SEPARATE\": {\"2024-01-01.2024-12-31\": 194307.47}, \"gov.irs.credits.ctc.amount.base[0].amount\": {\"2024-01-01.2024-12-31\": 1943.07}}", "bundle_id": "us-5.0.1", "baseline_executed": "current-law enacted-OBBBA populace_us_2024 with credit take-up forced (see takeup_basis)", "status": "computed"} diff --git a/sources/campaign-2026-08-02/us/cpsp_ctc/tcja_2024.json b/sources/campaign-2026-08-02/us/cpsp_ctc/tcja_2024.json new file mode 100644 index 0000000..8e82e9f --- /dev/null +++ b/sources/campaign-2026-08-02/us/cpsp_ctc/tcja_2024.json @@ -0,0 +1,94 @@ +{ + "scenario": "tcja", + "year": 2024, + "cpsp_scenario_label": "TCJA CTC", + "reform_hint": "TCJA CTC = current law at 2024", + "pe_construction": [], + "reform_json": "baseline (current law)", + "takeup_basis": "100% credit take-up/filing: takes_up_eitc, would_file_taxes_voluntarily, would_file_if_eligible_for_refundable_credit forced True; benefit-side take-up left calibrated", + "assumptions": { + "cpi_u_annual": { + "2020": 258.811, + "2022": 292.655, + "2024": 313.689, + "2025": 322.879 + }, + "afa23_inflation_factor_2020_to_2022": 1.1307672394140897, + "deflator_2025_to_2024": 0.9715373251279892, + "cpi_2025_note": "CPSP's exact CPI vintage for 2025 unstated; annual avg assumed", + "named_construction_deltas": [ + "AFA newborn initial payment omitted (PE lacks parameter): PE understates AFA generosity for infants (~$2.3k one-time)", + "birth-month proration omitted: PE gives full-year credit to age-0/turning children (overstates vs CPSP)", + "2024 AFA refundable-ODC modeled non-refundable in PE (18+ dependents only)", + "single/separate-filer thresholds where CPSP brief silent: ARPA/TCJA structure assumed", + "PE applies child-SSN requirement via imputed card type; Census/TAXSIM ASEC basis may not" + ] + }, + "data_vintage_note": "PE: certified populace_us dataset uprated to sim year. CPSP: raw public-use CPS-ASEC 2025 (income year 2024); levels also differ via PE benefit-take-up calibration vs ASEC survey-reported transfers", + "bundle": { + "bundle_id": "us-5.0.1", + "country_id": "us", + "policyengine_version": "5.0.1", + "model_package": "policyengine-us", + "model_version": "1.764.6", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_us_2024", + "default_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_build_id": "populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_artifact_sha256": "48b9d479fb4fd1c3537f9383ce4697d130b6f618658409d74f6233c43b994c7e", + "data_build_model_version": "1.764.6", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_us_2024", + "runtime_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-us/snapshots/26dcad66867687f15735dc4926523e3741920836/populace_us_2024.h5", + "managed_by": "policyengine.py" + }, + "metrics": { + "all": { + "population": 340077321.9414408, + "rate_50": 0.03150605658518329, + "count_50": 10714495.348424628, + "rate_100": 0.13474832796617117, + "count_100": 45824850.510822445, + "rate_150": 0.3006174980634063, + "count_150": 102233193.67013949, + "rate_200": 0.43330162868095223, + "count_200": 147356057.47468284 + }, + "u18": { + "population": 76683005.28060344, + "rate_50": 0.023557494993698292, + "count_50": 1806459.512999555, + "rate_100": 0.1677105433364713, + "count_100": 12860548.4802835, + "rate_150": 0.4284356885634733, + "count_150": 32853736.168511793, + "rate_200": 0.5794508564361762, + "count_200": 44434033.08394548 + }, + "u6": { + "population": 22697940.657062482, + "rate_50": 0.024150372277012343, + "count_50": 548163.7167895931, + "rate_100": 0.17791888414943094, + "count_100": 4038392.274194558, + "rate_150": 0.46630512296521576, + "count_150": 10584166.00914869, + "rate_200": 0.618052242170527, + "count_200": 14028513.115751032 + } + }, + "aggregates_usd": { + "ctc": 147580086061.31052, + "ctc_value": 126843524236.19202, + "refundable_ctc": 37524750332.54706, + "non_refundable_ctc": 110055335781.09694, + "eitc": 70601054651.1914, + "income_tax": 2253699925359.5527, + "spm_unit_net_income": 12898272170825.33 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/us/free_joins_cbo.csv b/sources/campaign-2026-08-02/us/free_joins_cbo.csv new file mode 100644 index 0000000..8dc1eeb --- /dev/null +++ b/sources/campaign-2026-08-02/us/free_joins_cbo.csv @@ -0,0 +1,89 @@ +period,program,metric,cbo_value,pe_value,ratio,pe_construction,conventions,status,source_column +2026,snap,benefit_cost,98415000000.0,90927596849.523,0.9239201021137327,pass2 aggregate snap total_usd CY2026,CBO federal fiscal year vs PE calendar year (named delta); CBO outlays are cash FY; PE totals are accrual entitlement/benefit dollars (named delta),computed,Estimated Budget Authority +2026,snap,participant_count,39300000.0,58419679.68580754,1.4865058444225838,year-grid snap part_pop US CY2026,CBO federal fiscal year vs PE calendar year (named delta); PE annual-ever persons in units with benefit>0 vs CBO avg-monthly participation (named delta),computed,Average Monthly Participation (Millions of people) +2026,snap,average_monthly_benefit,186.6,129.7045752084306,0.695094186540357,pass2 snap dollars / year-grid part_pop / 12 (per annual-ever person-month),CBO federal fiscal year vs PE calendar year (named delta); PE annual-ever persons in units with benefit>0 vs CBO avg-monthly participation (named delta); denominator concept differs -> ratio inherits caseload delta,computed,Average Monthly Benefit per Participant (Dollars) +2026,ssi,benefit_cost,66500000000.0,57857268951.65666,0.8700341195737844,pass2 aggregate ssi total_usd CY2026,CBO federal fiscal year vs PE calendar year (named delta); CBO outlays are cash FY; PE totals are accrual entitlement/benefit dollars (named delta),computed,"Total Outlays, Adjusted for Date of Payment Shiftb" +2026,ssi,benefit_cost,7600000000.0,,,,,skipped: SSI by-group row — subgroup-aware join pending (pass2 has disability axes; SSI aged/blind-disabled grouping needs dedicated masks),Aged +2026,ssi,benefit_cost,46600000000.0,,,,,skipped: SSI by-group row — subgroup-aware join pending (pass2 has disability axes; SSI aged/blind-disabled grouping needs dedicated masks),Blind and disabled adults +2026,ssi,benefit_cost,11500000000.0,,,,,skipped: SSI by-group row — subgroup-aware join pending (pass2 has disability axes; SSI aged/blind-disabled grouping needs dedicated masks),Blind and disabled children +2026,ssi,participant_count,7275000.0,6108392.492163988,0.8396415796788986,year-grid ssi part_pop US CY2026,CBO federal fiscal year vs PE calendar year (named delta); PE annual-ever persons in units with benefit>0 vs CBO avg-monthly participation (named delta),computed,Average Monthly Beneficiaries (Thousands of people) +2026,ssi,average_monthly_benefit,751.0,789.3138964940113,1.0510171724287767,pass2 ssi dollars / year-grid part_pop / 12 (per annual-ever person-month),CBO federal fiscal year vs PE calendar year (named delta); PE annual-ever persons in units with benefit>0 vs CBO avg-monthly participation (named delta); denominator concept differs -> ratio inherits caseload delta,computed,Average Monthly Benefit per Beneficiary (Dollars) +2026,ssi,maximum_monthly_benefit,994.0,,,,,skipped: no defensible in-hand PE counterpart,"Maximum Monthly Benefit (Individual, by calendar year)" +2025,medicaid,benefit_cost,668000000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Estimated Outlaysa +2026,medicaid,benefit_cost,708000000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Estimated Outlaysa +2025,medicaid,benefit_cost,125000000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Aged +2026,medicaid,benefit_cost,135000000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Aged +2025,medicaid,benefit_cost,191000000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Blind and Disabled +2026,medicaid,benefit_cost,202000000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Blind and Disabled +2025,medicaid,benefit_cost,85000000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Children +2026,medicaid,benefit_cost,89000000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Children +2025,medicaid,benefit_cost,83000000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Adults in Traditional Eligibility Categories +2026,medicaid,benefit_cost,90000000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Adults in Traditional Eligibility Categories +2025,medicaid,benefit_cost,144000000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Adults Made Eligible by the ACA +2026,medicaid,benefit_cost,153000000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Adults Made Eligible by the ACA +2025,medicaid,enrollment,8000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Aged +2026,medicaid,enrollment,8000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Aged +2025,medicaid,enrollment,9000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Blind and Disabled +2026,medicaid,enrollment,9000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Blind and Disabled +2025,medicaid,enrollment,31000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Children +2026,medicaid,enrollment,31000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Children +2025,medicaid,enrollment,17000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Adults in Traditional Eligibility Categories +2026,medicaid,enrollment,17000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Adults in Traditional Eligibility Categories +2025,medicaid,enrollment,17000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Adults Made Eligible by the ACA +2026,medicaid,enrollment,17000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Adults Made Eligible by the ACA +2025,medicaid,enrollment,98000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Total Enrolled Within a Fiscal Year +2026,medicaid,enrollment,99000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Total Enrolled Within a Fiscal Year +2026,chip,benefit_cost,25000000000.0,,,,,"skipped: program-aggregate only; also populace#593 (100% take-up, flag not stored)",Outlays +2026,chip,enrollment,7000000.0,,,,,"skipped: program-aggregate only; also populace#593 (100% take-up, flag not stored)",Millions of children +2026,chip,enrollment,7000000.0,,,,,"skipped: program-aggregate only; also populace#593 (100% take-up, flag not stored)",Total Enrollment +2026,tanf,benefit_cost,16968000000.0,4936866453.148398,0.29095158257593107,pass2 aggregate tanf total_usd CY2026,CBO federal fiscal year vs PE calendar year (named delta); CBO outlays are cash FY; PE totals are accrual entitlement/benefit dollars (named delta); CBO TANF outlays = full block grant (incl. non-cash state uses); PE models cash assistance only (~quarter of block-grant spending) — named scope delta,computed,Estimated Outlays +2026,unemployment_compensation,benefit_cost,43420000000.0,,,,,skipped: UI is a survey-reported income input in pe-us; no eligibility/caseload model,Regular Benefits +2026,unemployment_compensation,first_payment_count,6000000.0,,,,,skipped: UI is a survey-reported income input in pe-us; no eligibility/caseload model,First Payments (Millions of people) +2026,unemployment_compensation,average_weekly_benefit,471.0,,,,,skipped: UI is a survey-reported income input in pe-us; no eligibility/caseload model,Average Weekly Benefit (Dollars) +2025,,revenue_change,452089000000.0,,,,,skipped: no defensible in-hand PE counterpart,Corporate income taxes +2026,,revenue_change,403979000000.0,,,,,skipped: no defensible in-hand PE counterpart,Corporate income taxes +2025,,revenue_change,194866000000.0,,,,,skipped: no defensible in-hand PE counterpart,Customs duties +2026,,revenue_change,418388000000.0,,,,,skipped: no defensible in-hand PE counterpart,Customs duties +2026,medicaid,benefit_cost,707865000000.0,,,,,skipped: enrollment/spending not in campaign outputs (takes_up_medicaid exists; addable pass2 v2),Medicaid +2026,aca_premium_tax_credits_and_related,benefit_cost,112336000000.0,,,,,skipped: aca_ptc computable but not in campaign outputs (addable pass2 v2),Premium tax credits and related spendingc +2026,chip,benefit_cost,25192000000.0,,,,,"skipped: program-aggregate only; also populace#593 (100% take-up, flag not stored)",Children's Health Insurance Program +2026,eitc_ctc_other_credits,benefit_cost,104514000000.0,109071629469.4516,1.0436078369352584,eitc+refundable_ctc CY2026 (composite; CBO line includes 'other credits' — scope note),CBO federal fiscal year vs PE calendar year (named delta); CBO composite line broader than EITC+ACTC (named scope delta),computed,"Earned income, child, and other tax creditsd" +2026,child_nutrition,benefit_cost,36523000000.0,,,,,skipped: school meals modeled partially; not in campaign outputs,Child nutrition +2026,family_support_foster_care,benefit_cost,36776000000.0,,,,,skipped: no defensible in-hand PE counterpart,Family support and foster caree +2026,eitc_ctc_other_credits,benefit_cost,104514000000.0,109071629469.4516,1.0436078369352584,eitc+refundable_ctc CY2026 (composite; CBO line includes 'other credits' — scope note),CBO federal fiscal year vs PE calendar year (named delta); CBO composite line broader than EITC+ACTC (named scope delta),computed,"Earned income, child, and other tax credits" +2024,,deduction_aggregate,3107500000000.0,,,,,skipped: no defensible in-hand PE counterpart,Subtract standard deduction (non-itemizers only) +2025,,deduction_aggregate,3212800000000.0,,,,,skipped: no defensible in-hand PE counterpart,Subtract standard deduction (non-itemizers only) +2026,,deduction_aggregate,3293400000000.0,,,,,skipped: no defensible in-hand PE counterpart,Subtract standard deduction (non-itemizers only) +2024,,deduction_aggregate,776600000000.0,,,,,skipped: no defensible in-hand PE counterpart,Subtract total itemized deductions (itemizers only) after limitsd +2025,,deduction_aggregate,1091900000000.0001,,,,,skipped: no defensible in-hand PE counterpart,Subtract total itemized deductions (itemizers only) after limitsd +2026,,deduction_aggregate,1144900000000.0,,,,,skipped: no defensible in-hand PE counterpart,Subtract total itemized deductions (itemizers only) after limitsd +2024,,deduction_aggregate,267700000000.0,,,,,skipped: no defensible in-hand PE counterpart,Subtract qualified business income deduction +2025,,deduction_aggregate,247700000000.0,,,,,skipped: no defensible in-hand PE counterpart,Subtract qualified business income deduction +2026,,deduction_aggregate,264399999999.99997,,,,,skipped: no defensible in-hand PE counterpart,Subtract qualified business income deduction +2024,,deduction_aggregate,0.0,,,,,skipped: no defensible in-hand PE counterpart,Subtract additional deductionse +2025,,deduction_aggregate,416300000000.0,,,,,skipped: no defensible in-hand PE counterpart,Subtract additional deductionse +2026,,deduction_aggregate,432400000000.0,,,,,skipped: no defensible in-hand PE counterpart,Subtract additional deductionse +2024,,income_aggregate,13055179000000.0,,,,,skipped: no defensible in-hand PE counterpart,Taxable incomeg +2025,,income_aggregate,13490710000000.0,,,,,skipped: no defensible in-hand PE counterpart,Taxable incomeg +2026,,income_aggregate,14245168000000.0,,,,,skipped: no defensible in-hand PE counterpart,Taxable incomeg +2024,,tax_liability,2504600000000.0,,,,,skipped: no defensible in-hand PE counterpart,Total income tax (including AMT) before credits +2025,,tax_liability,2584700000000.0,,,,,skipped: no defensible in-hand PE counterpart,Total income tax (including AMT) before credits +2026,,tax_liability,2754200000000.0,,,,,skipped: no defensible in-hand PE counterpart,Total income tax (including AMT) before credits +2024,,tax_credits_applied,249300000000.0,,,,,skipped: no defensible in-hand PE counterpart,Total credits (refundable and nonrefundable) j +2025,,tax_credits_applied,257500000000.0,,,,,skipped: no defensible in-hand PE counterpart,Total credits (refundable and nonrefundable) j +2026,,tax_credits_applied,261500000000.0,,,,,skipped: no defensible in-hand PE counterpart,Total credits (refundable and nonrefundable) j +2024,,tax_liability,2364000000000.0,,,,,skipped: no defensible in-hand PE counterpart,Income tax after creditsk +2025,,tax_liability,2440200000000.0,,,,,skipped: no defensible in-hand PE counterpart,Income tax after creditsk +2026,,tax_liability,2607800000000.0,,,,,skipped: no defensible in-hand PE counterpart,Income tax after creditsk +2024,,tax_liability,44400000000.0,,,,,skipped: no defensible in-hand PE counterpart,Net investment income tax +2025,,tax_liability,53400000000.0,,,,,skipped: no defensible in-hand PE counterpart,Net investment income tax +2026,,tax_liability,57200000000.0,,,,,skipped: no defensible in-hand PE counterpart,Net investment income tax +2024,,tax_liability,2408400000000.0,,,,,skipped: no defensible in-hand PE counterpart,Individual income tax liability +2025,,tax_liability,2493700000000.0,,,,,skipped: no defensible in-hand PE counterpart,Individual income tax liability +2026,,tax_liability,2665000000000.0,,,,,skipped: no defensible in-hand PE counterpart,Individual income tax liability +2024,,return_count,167100000.0,,,,,skipped: no defensible in-hand PE counterpart,Number of returns (millions)l +2025,,return_count,168000000.0,,,,,skipped: no defensible in-hand PE counterpart,Number of returns (millions)l +2026,,return_count,169500000.0,,,,,skipped: no defensible in-hand PE counterpart,Number of returns (millions)l +2024,,return_count,15600000.0,,,,,skipped: no defensible in-hand PE counterpart,Number with itemized deductions +2025,,return_count,20900000.0,,,,,skipped: no defensible in-hand PE counterpart,Number with itemized deductions +2026,,return_count,21900000.0,,,,,skipped: no defensible in-hand PE counterpart,Number with itemized deductions diff --git a/sources/campaign-2026-08-02/us/free_joins_cbo_summary.json b/sources/campaign-2026-08-02/us/free_joins_cbo_summary.json new file mode 100644 index 0000000..bedd1df --- /dev/null +++ b/sources/campaign-2026-08-02/us/free_joins_cbo_summary.json @@ -0,0 +1,79 @@ +{ + "computed": 9, + "pending": 0, + "skipped": 79, + "computed_rows": [ + { + "period": 2026, + "program": "snap", + "metric": "benefit_cost", + "cbo_value": 98415000000.0, + "pe_value": 90927596849.523, + "ratio": 0.9239201021137327 + }, + { + "period": 2026, + "program": "snap", + "metric": "participant_count", + "cbo_value": 39300000.0, + "pe_value": 58419679.68580754, + "ratio": 1.4865058444225838 + }, + { + "period": 2026, + "program": "snap", + "metric": "average_monthly_benefit", + "cbo_value": 186.6, + "pe_value": 129.7045752084306, + "ratio": 0.695094186540357 + }, + { + "period": 2026, + "program": "ssi", + "metric": "benefit_cost", + "cbo_value": 66500000000.0, + "pe_value": 57857268951.65666, + "ratio": 0.8700341195737844 + }, + { + "period": 2026, + "program": "ssi", + "metric": "participant_count", + "cbo_value": 7275000.0, + "pe_value": 6108392.492163988, + "ratio": 0.8396415796788986 + }, + { + "period": 2026, + "program": "ssi", + "metric": "average_monthly_benefit", + "cbo_value": 751.0, + "pe_value": 789.3138964940113, + "ratio": 1.0510171724287767 + }, + { + "period": 2026, + "program": "tanf", + "metric": "benefit_cost", + "cbo_value": 16968000000.0, + "pe_value": 4936866453.148398, + "ratio": 0.29095158257593107 + }, + { + "period": 2026, + "program": "eitc_ctc_other_credits", + "metric": "benefit_cost", + "cbo_value": 104514000000.0, + "pe_value": 109071629469.4516, + "ratio": 1.0436078369352584 + }, + { + "period": 2026, + "program": "eitc_ctc_other_credits", + "metric": "benefit_cost", + "cbo_value": 104514000000.0, + "pe_value": 109071629469.4516, + "ratio": 1.0436078369352584 + } + ] +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/us/obbba_family/RUNNABILITY.md b/sources/campaign-2026-08-02/us/obbba_family/RUNNABILITY.md new file mode 100644 index 0000000..723f8b4 --- /dev/null +++ b/sources/campaign-2026-08-02/us/obbba_family/RUNNABILITY.md @@ -0,0 +1,56 @@ +# OBBBA family (JCX-35-25 Title VII) — per-provision PE runnability verdicts + +Date: 2026-08-02. Scope: Chapter 1 (TCJA extension/enhancement) + Chapter 2 +(new individual provisions), FY2026 conventional values from staged JCX-35-25 +rows. Convention caveat that applies to EVERY row: JCT estimates provisions +SEQUENTIALLY (each conditional on the prior stack); single-provision PE runs +score marginal-vs-current-law — interaction terms are a named convention +delta until a full-stack replication is built (follow-up design). + +Verdict key: PARAMETRIC (paths verified in installed tree) · +PARAMETRIC-PENDING (modeled; expiry-world values need sourcing, e.g. CBO +Jan-2025 Tax Parameters projections) · STRUCTURAL (needs contrib/structural +reform) · CHECK (model surface unverified) · OUT (not in a household +static microsim). + +## Chapter 1 (extension provisions; counterfactual = TCJA-expiry world) +| # | Provision | FY2026 ($M) | Verdict | +|---|-----------|------------|---------| +| 1 | Reduced rates extension | −147,679 | STRUCTURAL — expiry rates 15/25/28/33/39.6 with CBO-projected 2026 thresholds already embedded in gov.contrib.additional_tax_bracket defaults; usable as the expiry-world engine | +| 2 | Standard deduction extension+enhancement | −92,124 | PARAMETRIC-PENDING — gov.irs.deductions.standard.*; expiry-2026 values need CBO projection sourcing | +| 3 | Personal exemption termination (excl. senior deduction) | +110,625 | PARAMETRIC-PENDING — gov.irs.income.exemption.amount (0 now); expiry value ≈ CBO-projected; senior-deduction carve-out is separate current-law param | +| 4 | CTC extension+enhancement | −48,769 | **PARAMETRIC (verified)** — full surface pinned today (cpsp/tpc lanes); expiry world = the tree's own 2013-dated statute values (unindexed pre-TCJA law): base 1000, ODC 0, refundable max 1000, phase-in threshold 3000, phase-out 110k/75k/55k. RUNNER: comparison/obbba_family.py ctc_ext | +| 5 | QBI deduction | −44,331 | CHECK — pe-us models QBI (gov.irs.deductions.qbi.*); expiry = repeal (0); enhancement params to verify | +| 6 | Estate/gift exemption | −3,672 | OUT — no estate tax in household microsim | +| 7 | AMT exemption extension | −76,835 | PARAMETRIC-PENDING — gov.irs.income.amt.exemption.*; expiry values need CBO projection | +| 8 | Residence interest limitation | +1,639 | CHECK — mortgage-interest itemized surface + data coverage | +| 9 | Casualty loss limitation | +86 | CHECK/weak — thin data | +| 10 | Misc itemized termination | +13,419 | CHECK — 2%-floor deduction modeling coverage | +| 11 | Itemized-benefit limitation (2/37) | −16,040 | PARAMETRIC-PENDING — OBBBA's limitation is current law in pe-us; repeal switch to verify | +| 12-14, 18 | fringe/moving/wagering/Sinai | small | OUT/skip — immaterial or unmodeled | +| 20 | SALT cap | +31,617 | PARAMETRIC-PENDING — gov.irs.deductions.itemized.salt_and_real_estate.cap; expiry = uncapped | + +## Chapter 2 (new provisions; counterfactual = repeal from current law) +| # | Provision | FY2026 ($M) | Verdict | +|---|-----------|------------|---------| +| 1 | No tax on tips (sunset 12/28) | −10,121 | PARAMETRIC-PENDING — gov.irs.deductions.tip_income.* seen in tree; repeal switch to verify; data: reported tip income | +| 2 | No tax on overtime (sunset 12/28) | −32,806 | PARAMETRIC-PENDING — gov.irs.deductions.overtime_income.* + gov.irs.income.exemption.overtime.* present; **note memory: PE has no hours/participation machinery — overtime amounts are imputed data; state the data basis in any comparison** | +| 3 | No tax on car loan interest | −5,400 | CHECK — auto-loan-interest deduction surface + data | +| 4 | Trump accounts | −6,446 | OUT — new account vehicle, no microsim surface | + +## First runnable leg queued +`ctc_ext` (provision 4): current law − CTC-expiry world, 2026. Every expiry +value read from the installed tree's own 2013-dated statute entries at +runtime (fail-loud pins). Baseline for delta: results/us/tpc_ctc/baseline_2026. +Convention deltas named: sequential-stack vs marginal; FY-cash vs CY-liability. + +## Stack baselines = baseline definitions (Max ruling 8/2) +The "sequential-stack vs marginal" caveat above is resolvable, not inherent: +JCT's baseline for provision k is expiry-world + provisions 1..k-1 — a +constructible first-class baseline ReformRef per issue #13. Build once from +the CBO Jan-2025 Tax Parameters expiry-2026 projections (workbook already +cited in gov/contrib/additional_tax_bracket/bracket.yaml): expiry values for +std deduction, personal exemption, AMT exemption/phaseout, QBI repeal, SALT +uncap, misc itemized, Pease. Then every Ch1 provision scores at its true +stack position. The ctc_ext run stands as the LAST-IN-STACK variant +(vs full current law) — a different well-defined baseline, published as such. diff --git a/sources/campaign-2026-08-02/us/obbba_family/ctc_ext_2026.json b/sources/campaign-2026-08-02/us/obbba_family/ctc_ext_2026.json new file mode 100644 index 0000000..d8f853d --- /dev/null +++ b/sources/campaign-2026-08-02/us/obbba_family/ctc_ext_2026.json @@ -0,0 +1,54 @@ +{ + "key": "ctc_ext", + "year": 2026, + "world": "CTC-expiry counterfactual (pre-TCJA statute values, unindexed by law)", + "external_target": "JCX-35-25 Ch1 provision 4 FY2026 -48,769M (extension cost); PE delta = tpc_ctc/baseline - this", + "pe_construction": [ + "gov.irs.credits.ctc.amount.base[0].amount: -> 1000", + "gov.irs.credits.ctc.amount.adult_dependent: -> 0", + "gov.irs.credits.ctc.refundable.individual_max: -> 1000", + "gov.irs.credits.ctc.refundable.phase_in.threshold: -> 3000", + "gov.irs.credits.ctc.phase_out.threshold.JOINT: -> 110000", + "gov.irs.credits.ctc.phase_out.threshold.SINGLE: -> 75000", + "gov.irs.credits.ctc.phase_out.threshold.HEAD_OF_HOUSEHOLD: -> 75000", + "gov.irs.credits.ctc.phase_out.threshold.SURVIVING_SPOUSE: -> 75000", + "gov.irs.credits.ctc.phase_out.threshold.SEPARATE: -> 55000" + ], + "reform_json": "{\"gov.irs.credits.ctc.amount.base[0].amount\": {\"2026-01-01.2026-12-31\": 1000}, \"gov.irs.credits.ctc.amount.adult_dependent\": {\"2026-01-01.2026-12-31\": 0}, \"gov.irs.credits.ctc.refundable.individual_max\": {\"2026-01-01.2026-12-31\": 1000}, \"gov.irs.credits.ctc.refundable.phase_in.threshold\": {\"2026-01-01.2026-12-31\": 3000}, \"gov.irs.credits.ctc.phase_out.threshold.JOINT\": {\"2026-01-01.2026-12-31\": 110000}, \"gov.irs.credits.ctc.phase_out.threshold.SINGLE\": {\"2026-01-01.2026-12-31\": 75000}, \"gov.irs.credits.ctc.phase_out.threshold.HEAD_OF_HOUSEHOLD\": {\"2026-01-01.2026-12-31\": 75000}, \"gov.irs.credits.ctc.phase_out.threshold.SURVIVING_SPOUSE\": {\"2026-01-01.2026-12-31\": 75000}, \"gov.irs.credits.ctc.phase_out.threshold.SEPARATE\": {\"2026-01-01.2026-12-31\": 55000}}", + "conventions": { + "stacking": "RESOLVED AS BASELINE DEFINITION (Max 8/2, issue #13): JCT's provision-4 baseline = expiry world + provisions 1-3 (a constructible ReformRef), not an inherent convention gap. This run scores provision 4 LAST-IN-STACK (vs full current law) \u2014 a different, well-defined baseline. The 1.87 ratio vs JCT's stack position is dominated by interactions with the provisions that differ between the two baselines \u2014 chiefly personal exemptions (present on JCT's expiry side until provision 3 terminates them) and the expiry-side AMT/QBI/SALT rules shaping the liability that limits the nonrefundable CTC. UNBLOCK: build baseline_k ReformRefs from CBO Jan-2025 Tax Parameters expiry projections (source already cited in the contrib bracket yaml); registered in RUNNABILITY.md.", + "period_basis": "PE calendar-year 2026; JCT fiscal-year", + "ssn_note": "child/adult SSN requirement parameters left at current law (OBBBA-era); pre-TCJA law had no child-SSN requirement \u2014 named residual" + }, + "bundle": { + "bundle_id": "us-5.0.1", + "country_id": "us", + "policyengine_version": "5.0.1", + "model_package": "policyengine-us", + "model_version": "1.764.6", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_us_2024", + "default_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_build_id": "populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_artifact_sha256": "48b9d479fb4fd1c3537f9383ce4697d130b6f618658409d74f6233c43b994c7e", + "data_build_model_version": "1.764.6", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_us_2024", + "runtime_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-us/snapshots/26dcad66867687f15735dc4926523e3741920836/populace_us_2024.h5", + "managed_by": "policyengine.py" + }, + "aggregates_usd": { + "income_tax": 2696855309363.2783, + "income_tax_before_refundable_credits": 2784649804456.368, + "ctc": 45843339685.243065, + "ctc_value": 42247746200.401825, + "refundable_ctc": 18756780813.9021, + "non_refundable_ctc": 27086558875.196205, + "household_net_income": 17443191393985.115 + } +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/us/pwbm_ss/ss_notax_2025.json b/sources/campaign-2026-08-02/us/pwbm_ss/ss_notax_2025.json new file mode 100644 index 0000000..060c310 --- /dev/null +++ b/sources/campaign-2026-08-02/us/pwbm_ss/ss_notax_2025.json @@ -0,0 +1,43 @@ +{ + "key": "ss_notax", + "year": 2025, + "external_target": "PWBM 'Eliminate income taxation of Social Security benefits' conventional FY2025-34 (FY2025 -60B, FY2026 -116B); CY-liability vs FY-cash named", + "pe_construction": [ + "gov.irs.social_security.taxability.rate.base.excess: 0.5 -> 0", + "gov.irs.social_security.taxability.rate.base.benefit_cap: 0.5 -> 0", + "gov.irs.social_security.taxability.rate.additional.bracket: 0.5 -> 0", + "gov.irs.social_security.taxability.rate.additional.excess: 0.85 -> 0", + "gov.irs.social_security.taxability.rate.additional.benefit_cap: 0.85 -> 0" + ], + "reform_json": "{\"gov.irs.social_security.taxability.rate.base.excess\": {\"2025-01-01.2025-12-31\": 0}, \"gov.irs.social_security.taxability.rate.base.benefit_cap\": {\"2025-01-01.2025-12-31\": 0}, \"gov.irs.social_security.taxability.rate.additional.bracket\": {\"2025-01-01.2025-12-31\": 0}, \"gov.irs.social_security.taxability.rate.additional.excess\": {\"2025-01-01.2025-12-31\": 0}, \"gov.irs.social_security.taxability.rate.additional.benefit_cap\": {\"2025-01-01.2025-12-31\": 0}}", + "baseline_for_delta": "results/us/tpc_ctc/baseline_2025.json (same bundle, no forced flags)", + "bundle": { + "bundle_id": "us-5.0.1", + "country_id": "us", + "policyengine_version": "5.0.1", + "model_package": "policyengine-us", + "model_version": "1.764.6", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_us_2024", + "default_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_build_id": "populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + 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"populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_us_2024", + "default_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_build_id": "populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_artifact_sha256": "48b9d479fb4fd1c3537f9383ce4697d130b6f618658409d74f6233c43b994c7e", + "data_build_model_version": "1.764.6", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_us_2024", + "runtime_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-us/snapshots/26dcad66867687f15735dc4926523e3741920836/populace_us_2024.h5", + "managed_by": "policyengine.py" + }, + "aggregates_usd": { + "income_tax": 2593844381731.896, + "income_tax_before_refundable_credits": 2710081388425.717, + "income_tax_refundable_credits": 116237006656.8671, + "ctc": 177489614847.13794, + "ctc_value": 148819439727.2654, + "refundable_ctc": 47199292338.22346, + "non_refundable_ctc": 130290322532.58534, + "eitc": 68438684290.59447, + "household_net_income": 17546138457021.346 + }, + "child_spm_poverty": {} +} \ No newline at end of file diff --git a/sources/campaign-2026-08-02/us/tpc_ctc/total_opt3_2026.json b/sources/campaign-2026-08-02/us/tpc_ctc/total_opt3_2026.json new file mode 100644 index 0000000..46dce1f --- /dev/null +++ b/sources/campaign-2026-08-02/us/tpc_ctc/total_opt3_2026.json @@ -0,0 +1,55 @@ +{ + "key": "total_opt3", + "year": 2026, + "external_targets": { + "t25_0209": "CTC/top-rate/total legs, FY2025-34 (vs Senate Title VII baseline)", + "t26_0029": "AFA FY2026-35 vs current law (microdynamic)" + }, + "pe_construction": [ + "CTC base 2200 -> 2500 (statute; indexed-after-2025 rounds to no change at 2026 under $100-downward rounding)", + "refundable max 1700 -> 2000", + "phase-in from first dollar of earnings (threshold 2500 -> 0)", + "additional 39.6% bracket above {'JOINT': 1562500, 'SINGLE': 1388875, 'HEAD_OF_HOUSEHOLD': 1475650, 'SEPARATE': 781250.0, 'SURVIVING_SPOUSE': 1562500} (contrib additional_tax_bracket structural reform; slots 1-7 mirrored from current-law tree at runtime)" + ], + "reform_json": "{\"gov.irs.credits.ctc.amount.base[0].amount\": {\"2026-01-01.2026-12-31\": 2500}, \"gov.irs.credits.ctc.refundable.individual_max\": {\"2026-01-01.2026-12-31\": 2000}, \"gov.irs.credits.ctc.refundable.phase_in.threshold\": {\"2026-01-01.2026-12-31\": 0}, \"gov.contrib.additional_tax_bracket.in_effect\": {\"2026-01-01.2026-12-31\": true}, \"gov.contrib.additional_tax_bracket.bracket.rates.1\": {\"2026-01-01.2026-12-31\": 0.1}, 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{\"2026-01-01.2026-12-31\": 768700.0}, \"gov.contrib.additional_tax_bracket.bracket.thresholds.7.SINGLE\": {\"2026-01-01.2026-12-31\": 1388875.0}, \"gov.contrib.additional_tax_bracket.bracket.thresholds.7.JOINT\": {\"2026-01-01.2026-12-31\": 1562500.0}, \"gov.contrib.additional_tax_bracket.bracket.thresholds.7.SEPARATE\": {\"2026-01-01.2026-12-31\": 781250.0}, \"gov.contrib.additional_tax_bracket.bracket.thresholds.7.HEAD_OF_HOUSEHOLD\": {\"2026-01-01.2026-12-31\": 1475650.0}, \"gov.contrib.additional_tax_bracket.bracket.thresholds.7.SURVIVING_SPOUSE\": {\"2026-01-01.2026-12-31\": 1562500.0}}", + "conventions": { + "period_basis": "PE calendar-year 2026 liability; TPC fiscal-year cash", + "baseline": "PE = enacted-OBBBA current law; T25-0209 scored vs Senate-draft Title VII (draft\u2248enacted for these provisions; named delta)", + "behavioral": "PE static; T26-0029 includes TPC microdynamic response (named axis); T25-0209 conventional", + "takeup": "no flags forced; PE calibrated filing/take-up (EITC unchanged so deltas take-up-clean)" + }, + "bundle": { + "bundle_id": "us-5.0.1", + "country_id": "us", + "policyengine_version": "5.0.1", + "model_package": "policyengine-us", + "model_version": "1.764.6", + "data_package": "populace-data", + "data_version": "0.1.0", + "default_dataset": "populace_us_2024", + "default_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_build_id": "populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "certified_data_artifact_sha256": "48b9d479fb4fd1c3537f9383ce4697d130b6f618658409d74f6233c43b994c7e", + "data_build_model_version": "1.764.6", + "data_build_model_git_sha": "None", + "data_build_fingerprint": "None", + "compatibility_basis": "exact_build_model_version", + "certified_by": "None", + "runtime_dataset": "populace_us_2024", + "runtime_dataset_uri": "hf://policyengine/populace-us/populace_us_2024.h5@populace-us-2024-buildp-sparse-rmloss100-cae8640-20260728T011454Z", + "runtime_dataset_source": "/Users/maxghenis/.cache/huggingface/hub/datasets--policyengine--populace-us/snapshots/26dcad66867687f15735dc4926523e3741920836/populace_us_2024.h5", + "managed_by": "policyengine.py" + }, + "aggregates_usd": { + "income_tax": 2592327087077.378, + "income_tax_before_refundable_credits": 2710934370753.2363, + "income_tax_refundable_credits": 118607283626.07555, + "ctc": 177489614847.13794, + "ctc_value": 151189716632.44223, + "refundable_ctc": 49569569239.93294, + "non_refundable_ctc": 127920045633.6927, + "eitc": 68438684290.59447, + "household_net_income": 17547656389250.92 + }, + "child_spm_poverty": {} +} \ No newline at end of file diff --git a/tests/test_campaign_ingest.py b/tests/test_campaign_ingest.py new file mode 100644 index 0000000..2c8a8a5 --- /dev/null +++ b/tests/test_campaign_ingest.py @@ -0,0 +1,275 @@ +"""Campaign compute-batch ingest tests (2026-08-02). + +End-to-end against a session-scoped scratch DB: US harvest + UK harvest +claims ingested first, then the campaign results joined on top. Checks +the join surfaces (every family lands with exactly the expected counts), +the #13 baseline recording (executed baselines on results and the +pre_ab2025 exhibits), the descriptive-register statuses/diagnoses, and +idempotency. +""" + +import json + +import pytest + +from scorecard_db import ScorecardDB, baseline_key + +pytestmark = pytest.mark.filterwarnings("ignore") + + +@pytest.fixture(scope="module") +def campaign_db(tmp_path_factory): + from scorecard_db import ingest_campaign, ingest_harvest, ingest_uk + + path = tmp_path_factory.mktemp("campaign") / "scorecard.db" + ingest_harvest.ingest(path) + ingest_uk.ingest(path) + stats = ingest_campaign.ingest(path) + db = ScorecardDB(path) + yield db, stats + db.close() + + +class TestJoinCounts: + def test_every_family_lands(self, campaign_db): + _, stats = campaign_db + assert stats["results"] == { + "uk_reckoner": 23, + "uk_free_joins": 25, + "uk_obr_measures": 10, + "uk_uprating": 6, + "tpc": 14, + "pwbm": 2, + "cpsp": 8, + "jct_obbba": 1, + "cbo_free_joins": 88, + "total": 177, + } + assert stats["exhibits"] == 11 + assert stats["diagnoses"] == 8 + + def test_only_the_two_honest_skips(self, campaign_db): + _, stats = campaign_db + assert len(stats["skipped"]) == 2 + assert any("LCWRA" in s for s in stats["skipped"]) + assert any("LHA" in s for s in stats["skipped"]) + + def test_idempotent_reingest(self, campaign_db, tmp_path): + db, _ = campaign_db + from scorecard_db import ingest_campaign + + before = db.conn.execute( + "SELECT COUNT(*) FROM pe_results" + ).fetchone()[0] + ingest_campaign.ingest(db.path) + after = db.conn.execute( + "SELECT COUNT(*) FROM pe_results" + ).fetchone()[0] + assert before == after + + +class TestReckonerJoins: + def test_basic_rate_magnitude_and_provenance(self, campaign_db): + db, _ = campaign_db + row = db.conn.execute( + "SELECT c.pe_value, c.value, c.pe_status, c.pe_baseline_key," + " c.data_bundle" + " FROM comparisons c WHERE c.source='hmrc' AND c.period=2026" + " AND json_extract(c.conditions,'$.measure')=" + "'Change basic rate by 1p'" + ).fetchone() + assert row["pe_status"] == "constructed" + assert abs(row["pe_value"] - 7.278e9) < 5e6 # |PE delta| + assert row["value"] == pytest.approx(6.9e9) # HMRC magnitude + assert row["pe_baseline_key"] == baseline_key( + {"policy": "current_law"} + ) + assert row["data_bundle"].startswith("populace-uk-2023") + + def test_all_23_runs_joined(self, campaign_db): + db, _ = campaign_db + n = db.conn.execute( + "SELECT COUNT(*) FROM pe_results WHERE run_id=" + "'uk-reckoner-2026'" + ).fetchone()[0] + assert n == 23 + + +class TestFreeJoins: + def test_dwp_vintage_caveat_surfaces(self, campaign_db): + """The campaign runner selected BECL rows by the staged end-year + ints, so its nominal-2026 state_pension value is the FY2025-26 + cell — the result attaches to the claim the value identifies and + says so.""" + db, _ = campaign_db + row = db.conn.execute( + "SELECT r.annotations, s.period FROM pe_results r" + " JOIN external_scores s USING (claim_id)" + " WHERE r.run_id='uk-free-joins-2026' AND s.source='dwp'" + " AND json_extract(s.conditions,'$.program')='state_pension'" + ).fetchone() + assert row["period"] == 2025 + assert "end-year" in row["annotations"] + + def test_skipped_rows_are_not_computed_with_reasons(self, campaign_db): + db, _ = campaign_db + rows = db.conn.execute( + "SELECT r.status, r.annotations FROM pe_results r" + " JOIN external_scores s USING (claim_id)" + " WHERE r.run_id='uk-free-joins-2026'" + " AND json_extract(s.conditions,'$.line_item')=" + "'Pay as you earn'" + ).fetchall() + assert len(rows) == 2 # 3.4 accrued + 3.8 cash claims + for r in rows: + assert r["status"] == "not_computed" + assert "collection channel" in r["annotations"] + + +class TestOBRMeasureJoins: + def test_anchor_carries_component_sum(self, campaign_db): + db, _ = campaign_db + rows = db.conn.execute( + "SELECT annotations FROM pe_results" + " WHERE run_id='uk-obr-measure-reversals-2026'" + ).fetchall() + assert len(rows) == 10 + for r in rows: + assert "external anchor = sum of the measure's" in ( + r["annotations"] + ) + + +class TestUpratingChecks: + def test_parameter_checks_are_comparable_and_close(self, campaign_db): + db, _ = campaign_db + rows = db.conn.execute( + "SELECT c.value, c.pe_value, c.pe_status_effective," + " json_extract(c.conditions,'$.program') AS program" + " FROM comparisons c" + " WHERE c.source='resolution_foundation'" + " AND c.metric='benefit_uprating' AND c.pe_value IS NOT NULL" + ).fetchall() + assert len(rows) == 4 + for r in rows: + assert r["pe_status_effective"] == "comparable" + # RF states rounded percentages; the tree gives exact ones. + assert abs(r["pe_value"] - r["value"]) < 5e-4, r["program"] + + +class TestTPCJoins: + def test_afa_floor_bound_is_two_results_on_one_claim(self, campaign_db): + db, _ = campaign_db + rows = db.conn.execute( + "SELECT r.computed_value FROM pe_results r" + " JOIN external_scores s USING (claim_id)" + " WHERE s.source='tpc'" + " AND json_extract(s.conditions,'$.provision')=" + "'American Family Act' AND r.run_id LIKE 'tpc-t26-0029%'" + ).fetchall() + assert len(rows) == 2 + values = sorted(r["computed_value"] for r in rows) + assert values[0] == pytest.approx(-132.5e9, rel=0.01) + assert values[1] == pytest.approx(-130.7e9, rel=0.01) + + def test_view_guard_names_the_baseline_mismatch(self, campaign_db): + """TPC's CTC options claims are scored vs current law + Senate + Title VII; the PE runs executed enacted current law — both + labels visible, effective status never plain agreement.""" + db, _ = campaign_db + row = db.conn.execute( + "SELECT claim_baseline_label, pe_baseline_label," + " pe_status_effective FROM comparisons" + " WHERE source='tpc' AND period=2026" + " AND json_extract(conditions,'$.option')='Option 2'" + " AND json_extract(conditions,'$.provision') LIKE" + " 'Increase CTC amount%' AND pe_value IS NOT NULL" + ).fetchone() + assert ( + row["claim_baseline_label"] + == "current_law_plus_senate_obbba_title_vii" + ) + assert row["pe_baseline_label"] == "current_law" + assert row["pe_status_effective"] == "constructed" + + +class TestCPSPJoins: + def test_levels_join_with_descriptive_diagnoses(self, campaign_db): + db, _ = campaign_db + rows = db.conn.execute( + "SELECT c.pe_value, c.value, c.diagnosis_class, c.action_link" + " FROM comparisons c" + " WHERE c.source='cpsp' AND c.period=2024" + " AND c.pe_value IS NOT NULL AND c.metric='poverty_rate'" + ).fetchall() + assert len(rows) == 8 + for r in rows: + assert r["diagnosis_class"] == "methodological_difference" + assert "populace/issues/593" in r["action_link"] + # The documented level gap: PE above CPSP, bounded. + assert 0 < r["pe_value"] - r["value"] < 0.06 + + +class TestJCTAndPWBM: + def test_ctc_extension_direction_and_scale(self, campaign_db): + db, _ = campaign_db + row = db.conn.execute( + "SELECT r.computed_value, s.value FROM pe_results r" + " JOIN external_scores s USING (claim_id)" + " WHERE r.run_id='obbba-family-ctc-ext-2026'" + ).fetchone() + assert row["value"] == pytest.approx(-48.769e9) + # PE marginal-vs-current-law runs larger than JCT's sequential + # stack leg (named convention delta); direction must match. + assert -120e9 < row["computed_value"] < -40e9 + + def test_pwbm_ss_years(self, campaign_db): + db, _ = campaign_db + rows = db.conn.execute( + "SELECT r.computed_value, s.period FROM pe_results r" + " JOIN external_scores s USING (claim_id)" + " WHERE r.run_id LIKE 'pwbm-ss-notax-%' ORDER BY s.period" + ).fetchall() + assert [r["period"] for r in rows] == [2025, 2026] + assert rows[0]["computed_value"] == pytest.approx( + -102.1e9, rel=0.01 + ) + + +class TestTwoChildExhibits: + def test_exhibits_record_the_executed_baseline(self, campaign_db): + db, _ = campaign_db + rows = db.conn.execute( + "SELECT * FROM pe_exhibits WHERE exhibit='uk-two-child-limit'" + ).fetchall() + assert len(rows) == 11 + pre = baseline_key({"policy": "pre_ab2025"}) + for r in rows: + assert r["baseline_key"] == pre + reform = json.loads(r["reform_json"]) + assert reform["reform"]["policy"] == "two_child_limit_removal" + assert reform["baseline"]["policy"] == "pre_ab2025" + + def test_headline_removal_effects(self, campaign_db): + db, _ = campaign_db + + def delta(takeup, group): + return db.conn.execute( + "SELECT delta FROM pe_exhibits" + " WHERE exhibit='uk-two-child-limit'" + " AND metric='poverty_count_change'" + " AND json_extract(conditions,'$.takeup')=?" + " AND json_extract(conditions,'$.child_definition')=?", + (takeup, group), + ).fetchone()["delta"] + + assert delta("calibrated", "hbai_dep") == pytest.approx( + -243108, abs=5 + ) + assert delta("entitlements_basis", "hbai_dep") == pytest.approx( + -277287, abs=5 + ) + + def test_registry_covers_every_baseline_in_use(self, campaign_db): + db, _ = campaign_db + assert db.unregistered_baselines() == [] diff --git a/tests/test_uk_ingest.py b/tests/test_uk_ingest.py index 4c853ca..64b168e 100644 --- a/tests/test_uk_ingest.py +++ b/tests/test_uk_ingest.py @@ -354,7 +354,10 @@ def test_ready_reckoner_join_surface(self, hmrc): scores, _ = hmrc rr = [s for s in scores if s.source_model == "hmrc"] assert len(rr) == 225 - slug = f"uk_hmrc_rr:{slugify('Change basic rate by 1p')}" + slug = ( + "uk_hmrc_rr:income_tax_rates:" + f"{slugify('Change basic rate by 1p')}" + ) basic = [ s for s in rr From 6078e248bd7fbf25f9ea8592da1dfa7cc16bc52c Mon Sep 17 00:00:00 2001 From: Max Ghenis Date: Wed, 12 Aug 2026 07:41:04 -0400 Subject: [PATCH 4/4] Regenerate scorecard.db (full documented order) + README + lane feed MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit data/scorecard.db rebuilt from scratch: urban → platform → solo → diagnoses → harvest → uk → campaign. 74,032 claims across 16 sources, 8,767 PE results, 531 exhibits (solo take-up attribution restored + two-child family), 19 diagnoses, 12 registered baselines, zero unregistered. Ledger staging file: 2,090 UK admin outturn facts. scorecard_db/README.md documents the UK population, the campaign results population, the baselines registry, and the full rebuild order (solo + diagnoses steps now included — they were silently omitted from the previous rebuild, which is why pe_exhibits was empty). Co-Authored-By: Claude Fable 5 --- app/public/data/lanes.json | 70 +++++++++++++++++++++++++++++-------- data/scorecard.db | Bin 40529920 -> 98713600 bytes scorecard_db/README.md | 68 ++++++++++++++++++++++++++++++++++- 3 files changed, 122 insertions(+), 16 deletions(-) diff --git a/app/public/data/lanes.json b/app/public/data/lanes.json index 7f30f16..a938a9c 100644 --- a/app/public/data/lanes.json +++ b/app/public/data/lanes.json @@ -140,50 +140,50 @@ "source": "DWP", "area": "UK income-related benefits take-up", "mode": 1, - "stage": "registered", + "stage": "ingested", "running": false, - "updated": "2026-08-01", - "note": "Canonical UK take-up publication (#3)" + "updated": "2026-08-02", + "note": "805 take-up claims with bounds (609 PC rows seed_source \u2014 pe-uk takeup.yaml cites this series; HB rows held_out vs PE takeup=1, policyengine-uk#1813); 102 BECL forecast rows (30 expenditure lines consumed_as_target via OBR 4.9); 102 BECL outturn rows routed to Ledger staging" }, { "id": "hbai-poverty", "source": "DWP HBAI", "area": "UK poverty rates", "mode": 1, - "stage": "registered", + "stage": "ingested", "running": false, - "updated": "2026-08-01", - "note": "#3" + "updated": "2026-08-02", + "note": "1040 HBAI claims (FYE 1995-2025, relative+absolute \u00d7 BHC+AHC, rates+counts; FYE-2025 + admin-linked FYE-2024 edition pair staged \u2014 the ~2pp methodology-gap diagnosis seed); permanent poverty holdout" }, { "id": "hmrc-personal-tax", "source": "HMRC", "area": "UK personal tax statistics", "mode": 1, - "stage": "registered", + "stage": "ingested", "running": false, - "updated": "2026-08-01", - "note": "#3" + "updated": "2026-08-02", + "note": "225 ready-reckoner claims (policy worlds per line, FY2026-27+, behavioural per HMRC notes \u2014 the campaign reckoner join surface) + 762 SPI-based projections (726 seed_source via the shared SPI 2023-24 base, 36 whole-population liability totals consumed-class); 1855 outturn/provisional admin rows routed to Ledger staging" }, { "id": "obr-welfare", "source": "OBR", "area": "welfare trends / EFO baselines", "mode": 1, - "stage": "registered", + "stage": "ingested", "running": false, - "updated": "2026-08-01", - "note": "#3" + "updated": "2026-08-02", + "note": "1121 EFO Mar-2026 claims (receipts 3.4/3.8, welfare 4.9/4.11, threshold analysis 3.17-3.19); 150 consumed_as_target (exact pe-uk-data target lines, targets/sources/obr.py); 133 outturn rows routed to Ledger staging" }, { "id": "ukmod-stats", "source": "UKMOD", "area": "published statistics", "mode": 1, - "stage": "registered", + "stage": "ingested", "running": false, - "updated": "2026-08-01", - "note": "#3" + "updated": "2026-08-02", + "note": "1392 UKMOD claims \u2014 Country Report 2023-2030 validation block (simulated/official/input-data/HBAI series side by side; take-up priors frozen since 2021 per their own \u00a74.3 warning) + CeMPA 3/26 AB2025 package assessment (209 reform-keyed rows); 300 JRF claims (unrounded AHC headline series, persistent poverty, MIS-adjacent thresholds); 88 MIS weekly-budget cells deliberately dropped (focus-group budget standards, not model-checkable \u2014 recoverable in vendored staging)" }, { "id": "jct-reform-scores", @@ -294,6 +294,46 @@ "running": false, "updated": "2026-08-02", "note": "1033 claims: monthly SPM 2024-01\u21922025-12 (final series \u2014 project ended Dec 2025), CTC counterfactuals 2023/2024 at 100% take-up, state refundable-CTC designs, SNAP TFP-revocation state tables (TRIM3 2015-19 base); annual-SPM\u2248Census reviewed \u2192 held_out (no poverty targets in pe-us calibration); 16.6-vs-11.4 erratum diagnosed external_issue" + }, + { + "id": "obr-measures", + "source": "OBR", + "area": "policy measures database (1970\u2192)", + "mode": 2, + "stage": "ingested", + "running": false, + "updated": "2026-08-02", + "note": "24304 policy-measures-database claims (84 fiscal events since 1970, reform-keyed per measure title, positive_gain_to_exchequer verbatim)" + }, + { + "id": "hmt-costings", + "source": "HM Treasury", + "area": "fiscal-event scorecards + DA", + "mode": 2, + "stage": "ingested", + "running": false, + "updated": "2026-08-02", + "note": "1218 OBR-certified scorecard costings (AB2024 5.1 / B2025 4.1 / SS2025 3.1; exchequer_impact \u2014 Tax/Spend heads mix by design; 31 suppressed cells verbatim) + 150 IGOTM decile medians (annex 2.C); B2025 two-child measure title embeds the government's 450k-children poverty claim \u2014 pentagon leg" + }, + { + "id": "ifs-taxben", + "source": "IFS TAXBEN", + "area": "poverty + benefit options", + "mode": 2, + "stage": "ingested", + "running": false, + "updated": "2026-08-02", + "note": "268 TAXBEN claims: absolute-AHC child-poverty series, Green-Budget-2025 options block (164 reform-keyed rows incl. the \u2212540k steady-state two-child-limit leg of the pentagon), threshold-freeze revenue rows; options baseline = registered ifs_2cl_fp_removal_rolled_out world; TAXBEN is entitlements-basis (full take-up) \u2014 registry axis on every poverty comparison" + }, + { + "id": "rf-outlook", + "source": "Resolution Foundation", + "area": "living standards outlook + Budget analysis", + "mode": 2, + "stage": "ingested", + "running": false, + "updated": "2026-08-02", + "note": "70 Resolution Foundation claims (IPPR Tax Benefit Model on FRS/HBAI 2023-24): LSO 2026 poverty projections incl. the \u2212420k two-child pentagon leg, Budget-2025 decile block, April-2026 uprating set (11 parameter-check rows \u2014 campaign uprating_check joins here); 26 reform-keyed rows; 1 price-index-only row dropped (out of tax/benefit scope, tallied)" } ] } diff --git a/data/scorecard.db b/data/scorecard.db index 9873e9e05d409846ad89505a0447c096c6f2ddfc..81583989f8fb2b03cf35a8cf5876f6f28079eb3b 100644 GIT binary patch literal 98713600 zcmeFa33wF6)<4{nS$kG?1VknvLWD_XUqHkV0vk1)MMcGZx$X<@ieA6p>7EYB2)_6K{NLw$zI(sq;rTJ=RCia^sZ*z_ zt52PpF>PX`f;Wdt%Zs@RvxDix$Yjh_W;4Su#~5bLrTAa^^WcX5SJjSFp 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