From 51b48891750c3e6596adc657280e2d8ab8bbb214 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 13:43:27 +0100 Subject: [PATCH 01/21] Measure stored UK value columns at their binding's period (#1324) A plain-column binding's value variable is read at its measurement period: the binding's measurement_period, else the calibration period. When the frame stores the variable at its own period (2024), the measure resolver's probes report it missing, so the provider computes it at 2025, as it does every engine-computed variable. Engine values for stored names are injected under a reserved engine_period__ name, so filters, conditions and bands keep their stored reads and the stored columns are never overwritten. A declared period other than the calibration or the frame's period refuses. The profit after loss relief reads the frame only at the frame's period. Co-Authored-By: Claude Opus 5.5 --- ...-uk-stored-values-at-their-period.fixed.md | 1 + .../microcosm/build/target_materialization.py | 161 +++++++- .../build/uk_runtime/ledger_targets.py | 41 ++ .../build/uk_runtime/measure_simulation.py | 28 +- .../build/uk_runtime/national_calibration.py | 16 +- ...st_uk_self_employment_after_loss_relief.py | 25 +- .../uk/test_uk_measurement_period.py | 374 ++++++++++++++++++ 7 files changed, 621 insertions(+), 25 deletions(-) create mode 100644 changelog.d/1324-uk-stored-values-at-their-period.fixed.md create mode 100644 packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period.py diff --git a/changelog.d/1324-uk-stored-values-at-their-period.fixed.md b/changelog.d/1324-uk-stored-values-at-their-period.fixed.md new file mode 100644 index 000000000..600ab33d1 --- /dev/null +++ b/changelog.d/1324-uk-stored-values-at-their-period.fixed.md @@ -0,0 +1 @@ +UK calibration now measures a plain-column target's value at the binding's period (microcosm#1324). A value variable the frame stores holds the frame's own year (2024), so at the 2025 calibration period the measure resolver computes it through the engine, as it already did for every engine-computed variable; before, the stored column was read as it is and 76 £ rows compared 2024 values with 2025 targets. The engine values for stored names are injected under a reserved `engine_period__` name, so the stored columns that filters, conditions and bands read are never overwritten; those keep their stored reads, and a test lists the variables they read for review. A binding may declare the frame's period to read the stored column on purpose (ONS road fuel at calendar 2024 and the seven bus and rail outturn rows held without an index), and any other declared period refuses. The self-employment profit after loss relief reads the stored columns only at the frame's period. diff --git a/packages/microcosm-build/src/microcosm/build/target_materialization.py b/packages/microcosm-build/src/microcosm/build/target_materialization.py index b58528dfb..40a2dff4a 100644 --- a/packages/microcosm-build/src/microcosm/build/target_materialization.py +++ b/packages/microcosm-build/src/microcosm/build/target_materialization.py @@ -103,6 +103,51 @@ def counterfactual_column(binding: Mapping[str, Any]) -> str: return COUNTERFACTUAL_DELTA_COLUMN_PREFIX + re.sub(r"[^0-9A-Za-z_]", "_", metric) +#: Prefix of the measure-input column a resolved value lands in when the frame +#: already stores the variable (microcosm#1324). A stored column holds the +#: frame's own period; the provider computes the value at the binding's +#: measurement period, and writing it under the bare name would overwrite the +#: stored column that filters, conditions and later stages still read. +ENGINE_PERIOD_COLUMN_PREFIX = "engine_period__" + + +def measure_input_column(adapter: Any, entity: str, variable: str) -> str: + """The column a resolved measure input is injected under. + + A variable the adapter's frame stores goes under the reserved + ``engine_period__`` name; any other variable keeps its own name, as + before. An adapter that declares no ``stored_columns`` keeps every + variable's own name. + """ + + stored = getattr(adapter, "stored_columns", None) + if stored is not None and variable in stored.get(entity, ()): + return ENGINE_PERIOD_COLUMN_PREFIX + variable + return variable + + +def inject_measure_inputs( + adapter: Any, measure_inputs: Mapping[tuple[str, str], np.ndarray] +) -> None: + """Write resolved measure inputs into an adapter's table copies.""" + + for (entity, variable), values in measure_inputs.items(): + adapter.tables[entity][measure_input_column(adapter, entity, variable)] = values + + +def drop_injected_measure_inputs( + adapter: Any, + measure_inputs: Mapping[tuple[str, str], np.ndarray], + original_columns: Mapping[str, set[str]], +) -> None: + """Drop the columns :func:`inject_measure_inputs` added to an adapter.""" + + for entity, variable in measure_inputs: + column = measure_input_column(adapter, entity, variable) + if column not in original_columns[entity]: + adapter.tables[entity].drop(columns=[column], inplace=True) + + @dataclass(frozen=True) class MaterializationSkip: """One target measure the interpreter could not prepare.""" @@ -217,12 +262,15 @@ def resolve_target_measures( for round_index in range(max_rounds): probe = adapter_factory() _inject_measure_inputs(probe, measure_inputs) + # With a provider at hand, a stored value column read at a period the + # frame does not hold is routed to the provider (microcosm#1324). result = materialize_target_bindings( probe, registry, contract, period=period, band_edge_registry=band_edge_registry, + route_stored_values=True, ) skipped = tuple(result.skipped) round_receipt = { @@ -412,8 +460,7 @@ def _provider_entity_for(provider: MeasureProvider, variable: str) -> str | None def _inject_measure_inputs( adapter: Any, measure_inputs: Mapping[tuple[str, str], np.ndarray] ) -> None: - for (entity, variable), values in measure_inputs.items(): - adapter.tables[entity][variable] = values + inject_measure_inputs(adapter, measure_inputs) def _raise_measure_resolution( @@ -651,8 +698,19 @@ def materialize_target_bindings( period: int | str, providers: Mapping[str, Provider] | None = None, band_edge_registry: TargetRegistry | None = None, + route_stored_values: bool = False, ) -> TargetMaterializationResult: - """Prepare measure columns declared by compiled Ledger target specs.""" + """Prepare measure columns declared by compiled Ledger target specs. + + A plain-column binding's value is read at its measurement period: the + binding's ``measurement_period``, else ``period`` (microcosm#1324). An + adapter with ``column_at`` reads an injected engine-period value first; + with ``route_stored_values`` (the measure resolver's probes) a stored + column that holds another period is reported missing, so the resolver + computes it at the measurement period. Without it (frame-only routes, no + provider) the stored column is read as it is. Filters, conditions and + bands keep their stored reads: who a row counts is fixed at the frame. + """ provider_registry = {**default_provider_registry(), **(providers or {})} band_edges = _band_edges_by_group( @@ -714,8 +772,14 @@ def materialize_target_bindings( 0.0, ) else: + _refuse_ignored_measurement_period(spec, binding, adapter, period) values = _prepared_column_values( - adapter, spec.entity, binding, band=band + adapter, + spec.entity, + binding, + band=band, + period=measurement_period, + route_stored=route_stored_values, ) adapter.set_column(spec.entity, spec.measure, values) except (KeyError, TypeError, ValueError) as error: @@ -870,17 +934,67 @@ def _prepared_column_values( binding: Mapping[str, Any], *, band: tuple[float, float] | None = None, + period: int | str | None = None, + route_stored: bool = False, ) -> np.ndarray: entity = str(binding.get("from_entity") or entity) if "value_expression" in binding: - values = _expression(adapter, entity, str(binding["value_expression"])) + values = _expression( + adapter, + entity, + str(binding["value_expression"]), + period=period, + route_stored=route_stored, + ) else: - values = _column(adapter, entity, binding["value_variable"]) + values = _value_column( + adapter, + entity, + binding["value_variable"], + period=period, + route_stored=route_stored, + ) return np.where( _binding_mask(adapter, entity, binding, values, band=band), values, 0.0 ) +class MeasurementPeriodError(RuntimeError): + """A binding declares a measurement period its read route cannot honour. + + Deliberately not a :class:`ValueError`, which the per-spec loop turns into + a skip: a declared period that is quietly ignored would measure the row + at another year, so the whole run refuses (microcosm#1324). + """ + + +def _refuse_ignored_measurement_period( + spec: Any, + binding: Mapping[str, Any], + adapter: Any, + period: int | str, +) -> None: + """Refuse a plain-column period the route would not honour. + + A plain-column value is read at the calibration period (through the + provider, for a stored column) or, by declaration, at the frame's own + period (the stored column as it is). Any other declared period would be + read at one of those two and is refused. + """ + + declared = binding.get("measurement_period") + frame_period = getattr(adapter, "frame_period", None) + if declared is None or frame_period is None: + return + if str(declared) in {str(period), str(frame_period)}: + return + raise MeasurementPeriodError( + f"target {getattr(spec, 'name', '?')!r} declares measurement period " + f"{declared!r}; a plain-column read honours only the calibration " + f"period {period!r} or the frame's period {frame_period!r}" + ) + + def _binding_mask( adapter: Any, entity: str, @@ -985,19 +1099,50 @@ def _compare(values: np.ndarray, operator: str, expected: object) -> np.ndarray: raise ValueError(f"unsupported predicate operator {operator!r}") -def _expression(adapter: Any, entity: str, expression: str) -> np.ndarray: +def _expression( + adapter: Any, + entity: str, + expression: str, + *, + period: int | str | None = None, + route_stored: bool = False, +) -> np.ndarray: parts = [part.strip() for part in expression.split("+")] if not parts or any(not part for part in parts): raise ValueError(f"unsupported value_expression {expression!r}") total: np.ndarray | None = None for part in parts: - values = _column(adapter, entity, part) + values = _value_column( + adapter, entity, part, period=period, route_stored=route_stored + ) total = values.copy() if total is None else total + values if total is None: raise ValueError(f"unsupported value_expression {expression!r}") return total +def _value_column( + adapter: Any, + entity: str, + variable: object, + *, + period: int | str | None, + route_stored: bool, +) -> np.ndarray: + """A binding's value variable at its measurement period (microcosm#1324). + + An adapter with ``column_at`` knows its frame's period and which columns + the frame stores; any other adapter reads the column as it is. + """ + + column_at = getattr(adapter, "column_at", None) + if callable(column_at) and period is not None: + return np.asarray( + column_at(entity, str(variable), period=period, route_stored=route_stored) + ) + return _column(adapter, entity, variable) + + def _column(adapter: Any, entity: str, variable: object) -> np.ndarray: if hasattr(adapter, "column"): return np.asarray(adapter.column(entity, str(variable))) diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/ledger_targets.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/ledger_targets.py index a4597fbb1..879153ced 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/ledger_targets.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/ledger_targets.py @@ -30,6 +30,7 @@ reference_fact_selectors, ) from microcosm.build.target_materialization import ( + ENGINE_PERIOD_COLUMN_PREFIX, TargetMaterializationResult, materialize_target_bindings, ) @@ -55,6 +56,7 @@ load_uk_local_geography_contract, metric_names, ) +from microcosm.build.uk_runtime.national_frame import UK_TIME_PERIOD_METADATA_KEY from microcosm.build.uk_runtime.off_surface_cells import ( uk_membership_bound_areas, uk_off_surface_frame_rows, @@ -1614,10 +1616,49 @@ def __init__(self, frame: Frame): self.frame = frame self.tables = {entity: frame.table(entity).copy() for entity in frame.entities} self.link_tables = {name: frame.link(name).copy() for name in frame.links} + # The columns the frame itself stores, and the period they hold + # (microcosm#1324): a stored column is the frame's own year, so a + # value read at another period goes to the measure provider. + self.stored_columns = { + entity: frozenset(table.columns) for entity, table in self.tables.items() + } + period = frame.metadata.get(UK_TIME_PERIOD_METADATA_KEY) + self.frame_period = ( + str(period) if isinstance(period, str) and period.strip() else None + ) def has_column(self, entity: str, variable: str) -> bool: return variable in self.tables[entity] + def column_at( + self, + entity: str, + variable: str, + *, + period: int | str, + route_stored: bool, + ) -> np.ndarray: + """A value variable at ``period`` (microcosm#1324). + + The frame's own period reads the stored column. At any other period + a stored column's injected engine-period value is read; before it is + injected, ``route_stored`` reports the column missing, so the + measure resolver computes it at that period. Without a provider + (``route_stored`` false and nothing injected) the stored column is + read as it is. + """ + + stored = variable in self.stored_columns.get(entity, ()) + if not stored or self.frame_period is None or str(period) == self.frame_period: + return self.column(entity, variable) + table = self.tables[entity] + engine_period = ENGINE_PERIOD_COLUMN_PREFIX + variable + if engine_period in table: + return np.asarray(table[engine_period]) + if route_stored: + raise KeyError(f"{entity}.{variable}") + return self.column(entity, variable) + def column(self, entity: str, variable: str) -> np.ndarray: table = self.tables[entity] count_variables = { diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/measure_simulation.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/measure_simulation.py index 6acbafce0..22f99903e 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/measure_simulation.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/measure_simulation.py @@ -37,6 +37,7 @@ from microcosm.build.uk_runtime.national_frame import ( UK_BUILD_IDENTIFIER_COLUMNS, UK_RELEASE_EXPORT_DROPPED_COLUMNS, + UK_TIME_PERIOD_METADATA_KEY, load_uk_national_frame, uk_release_identifier_tables, write_uk_national_frame, @@ -313,6 +314,20 @@ def _uc_calibration_composition( return family_type, child_count.astype(float) +def _measured_at_frame_period(frame: Any, year: int | str) -> bool: + """Whether ``year`` is the period the frame's stored columns hold. + + A frame with no period label is treated as holding the requested year, + which keeps the frame route of hermetic frames that carry no metadata. + """ + + metadata = getattr(frame, "metadata", None) or {} + period = metadata.get(UK_TIME_PERIOD_METADATA_KEY) + if not isinstance(period, str) or not period.strip(): + return True + return period == str(year) + + def compute_uk_measure_input( frame: Any, simulation: Any, entity: str, variable: str, year: int ) -> tuple[np.ndarray, str]: @@ -360,12 +375,15 @@ def compute_uk_measure_input( if entity != "person": raise KeyError(f"{variable} is person-only: {entity}") person = frame.table("person") - if variable == UK_SELF_EMPLOYMENT_INCOME_AFTER_LOSS_RELIEF and ( - "self_employment_income" in person + if ( + variable == UK_SELF_EMPLOYMENT_INCOME_AFTER_LOSS_RELIEF + and "self_employment_income" in person + and _measured_at_frame_period(frame, year) ): - # A binding on a stored column reads the frame's own value, as the - # rows read self_employment_income before the move; the profit - # after the relief is read the same way (microcosm#1095). + # At the frame's own period the stored columns are the values: + # the profit after the relief is read from them (microcosm#1095). + # At any other period the engine computes both components there, + # as it does every other stored value (microcosm#1324). stored_relief = ( person[LOSS_RELIEF_COLUMN].to_numpy(dtype=float) if LOSS_RELIEF_COLUMN in person diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/national_calibration.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/national_calibration.py index 67f08dd59..c6b33dc71 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/national_calibration.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/national_calibration.py @@ -16,6 +16,12 @@ import numpy as np +from microcosm.build.target_materialization import ( + drop_injected_measure_inputs as shared_drop_injected_measure_inputs, +) +from microcosm.build.target_materialization import ( + inject_measure_inputs as shared_inject_measure_inputs, +) from microcosm.build.target_materialization import ( resolve_target_measures, ) @@ -53,8 +59,10 @@ def inject_measure_inputs( adapter: UKFrameTargetAdapter, measure_inputs: Mapping[tuple[str, str], np.ndarray], ) -> None: - for (entity, variable), values in measure_inputs.items(): - adapter.tables[entity][variable] = values + """Inject resolved inputs; a stored variable's value goes under its + reserved engine-period name (microcosm#1324), as the resolver's probes do.""" + + shared_inject_measure_inputs(adapter, measure_inputs) def drop_injected_measure_inputs( @@ -62,9 +70,7 @@ def drop_injected_measure_inputs( measure_inputs: Mapping[tuple[str, str], np.ndarray], original_columns: Mapping[str, set[str]], ) -> None: - for entity, variable in measure_inputs: - if variable not in original_columns[entity]: - adapter.tables[entity].drop(columns=[variable], inplace=True) + shared_drop_injected_measure_inputs(adapter, measure_inputs, original_columns) class CalibrationFrameAdapter(UKFrameTargetAdapter): diff --git a/packages/microcosm-build/tests/engine/uk/test_uk_self_employment_after_loss_relief.py b/packages/microcosm-build/tests/engine/uk/test_uk_self_employment_after_loss_relief.py index 829db920a..c7ab9f796 100644 --- a/packages/microcosm-build/tests/engine/uk/test_uk_self_employment_after_loss_relief.py +++ b/packages/microcosm-build/tests/engine/uk/test_uk_self_employment_after_loss_relief.py @@ -65,21 +65,32 @@ def test_the_hmrc_measures_read_the_profit_after_loss_relief(tmp_path) -> None: assert not resolver.knows("household", name) assert resolver.entity_for(name) == "person" - after, _ = resolver.compute("person", UK_SELF_EMPLOYMENT_INCOME_AFTER_LOSS_RELIEF) + after, route = resolver.compute( + "person", UK_SELF_EMPLOYMENT_INCOME_AFTER_LOSS_RELIEF + ) banded, _ = resolver.compute("person", UK_TOTAL_INCOME_AFTER_LOSS_RELIEF) profit, _ = resolver.compute("person", "self_employment_income") total, _ = resolver.compute("person", "total_income") + # At the frame's own period the profit after the relief is read from the + # stored columns (microcosm#1095). np.testing.assert_allclose(after, [7_000.0, 0.0, 5_000.0]) - # The rows read self_employment_income from the frame's stored column, so - # the profit after the relief is read from the stored columns too, at any - # measurement year (microcosm#1095). + assert route.startswith("frame_columns:") + # At any other period the engine computes both components there, as it + # does every stored value (microcosm#1324). later = UKMeasureResolver( simulation_source=None, frame=_frame(), scratch_dir=tmp_path, year=2026 ) - stored, route = later.compute("person", UK_SELF_EMPLOYMENT_INCOME_AFTER_LOSS_RELIEF) - np.testing.assert_allclose(stored, [7_000.0, 0.0, 5_000.0]) - assert route.startswith("frame_columns:") + projected, route = later.compute( + "person", UK_SELF_EMPLOYMENT_INCOME_AFTER_LOSS_RELIEF + ) + assert route.startswith("engine_components:") + later_profit, _ = later.compute("person", "self_employment_income") + later_relief, _ = later.compute("person", "loss_relief") + np.testing.assert_allclose( + projected, + np.maximum(np.asarray(later_profit) - np.asarray(later_relief), 0.0), + ) # The band reads total income with the profit after the relief in place of # the profit before it. np.testing.assert_allclose(banded, np.asarray(total) - np.asarray(profit) + after) diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period.py new file mode 100644 index 000000000..3c953b35f --- /dev/null +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period.py @@ -0,0 +1,374 @@ +"""Plain-column values are measured at their binding's period (microcosm#1324). + +The frame stores its inputs at its own period (2024); the calibration solves +at 2025. A binding's value variable that the frame stores is computed by the +measure provider at the measurement period, like every engine-computed +variable, unless the binding declares the frame's own period. Filters, +conditions and bands keep their stored reads. +""" + +from __future__ import annotations + +import json +import sys +from importlib import resources as importlib_resources +from types import SimpleNamespace + +import numpy as np +import pandas as pd +import pytest + +from microcosm.build.target_materialization import ( + ENGINE_PERIOD_COLUMN_PREFIX, + MeasurementPeriodError, + drop_injected_measure_inputs, + inject_measure_inputs, + materialize_target_bindings, + measure_input_column, + resolve_target_measures, +) +from microcosm.build.uk_runtime import measure_simulation +from microcosm.build.uk_runtime.hmrc_income import ( + LOSS_RELIEF_COLUMN, + self_employment_income_after_loss_relief, +) +from microcosm.build.uk_runtime.ledger_targets import UKFrameTargetAdapter +from microcosm.build.uk_runtime.measure_simulation import ( + UK_SELF_EMPLOYMENT_INCOME_AFTER_LOSS_RELIEF, + UKMeasureResolver, + compute_uk_measure_input, +) +from microcosm.calibrate import TargetRegistry, TargetSpec + +STORED = np.array([1_000.0, 0.0, 500.0]) +#: The engine's 2025 values. The middle person has none stored but a positive +#: engine value, so a filter that read the engine would let them in. +ENGINE_2025 = np.array([1_053.0, 7.0, 526.5]) + + +class PeriodFrameStub: + """A frame stub with the period label and the surface the adapter reads.""" + + entities = ("person", "benunit", "household") + links = () + + def __init__(self, time_period: str = "2024"): + self.metadata = {"time_period": time_period} + self._tables = { + "person": pd.DataFrame( + { + "person_id": [1, 2, 3], + "person_benunit_id": [10, 10, 20], + "person_household_id": [100, 100, 200], + "employment_income": STORED.copy(), + "self_employment_income": [10_000.0, 2_000.0, 5_000.0], + LOSS_RELIEF_COLUMN: [3_000.0, 5_000.0, 0.0], + } + ), + "benunit": pd.DataFrame({"benunit_id": [10, 20]}), + "household": pd.DataFrame({"household_id": [100, 200]}), + } + + def table(self, entity): + return self._tables[entity] + + def link(self, name): + raise KeyError(name) + + +class SimulationStub: + def __init__(self, values): + self.values = values + self.tax_benefit_system = SimpleNamespace( + variables={ + name: SimpleNamespace( + entity=SimpleNamespace(key=entity), value_type=float + ) + for name, (entity, _) in values.items() + } + ) + self.calls = [] + + def calculate(self, variable, year, map_to=None): + self.calls.append((variable, year)) + return self.values[variable][1] + + +def _resolver(monkeypatch, tmp_path, frame, sim, year=2025): + monkeypatch.setitem( + sys.modules, + "policyengine_uk", + SimpleNamespace(__version__="2.134.4", Microsimulation=lambda **kw: sim), + ) + return UKMeasureResolver( + simulation_source=tmp_path / "input.h5", + scratch_dir=tmp_path, + year=year, + frame=frame, + ) + + +def _registry(bindings): + return ( + TargetRegistry( + [ + TargetSpec( + name=name, + entity="person", + measure=f"test_{name}", + value=1, + source="test", + metadata={"contract_target_id": name}, + ) + for name in bindings + ], + country="uk", + ), + {name: {"bindings": {"policyengine": b}} for name, b in bindings.items()}, + ) + + +def _resolve_and_materialize(monkeypatch, tmp_path, bindings, *, period=2025): + frame = PeriodFrameStub() + sim = SimulationStub({"employment_income": ("person", ENGINE_2025)}) + resolver = _resolver(monkeypatch, tmp_path, frame, sim) + registry, contract = _registry(bindings) + resolver.contract_targets = contract + resolution = resolve_target_measures( + lambda: UKFrameTargetAdapter(frame), registry, resolver, period=period + ) + adapter = UKFrameTargetAdapter(frame) + original_columns = {name: set(t.columns) for name, t in adapter.tables.items()} + inject_measure_inputs(adapter, resolution.measure_inputs) + materialized = materialize_target_bindings( + adapter, registry, contract, period=period + ) + return frame, sim, adapter, materialized, resolution, original_columns + + +def test_a_stored_value_is_measured_at_the_calibration_period(monkeypatch, tmp_path): + positive = [{"variable": "employment_income", "operator": ">", "value": 0}] + frame, sim, adapter, materialized, resolution, original = _resolve_and_materialize( + monkeypatch, + tmp_path, + { + "at_calibration": { + "value_variable": "employment_income", + "filters": positive, + }, + "at_frame": { + "value_variable": "employment_income", + "measurement_period": 2024, + }, + }, + ) + + assert not materialized.skipped + person = adapter.tables["person"] + # The value is the engine's 2025 value; who is counted is the stored filter. + np.testing.assert_allclose(person["test_at_calibration"], [1_053.0, 0.0, 526.5]) + # A binding that declares the frame's period reads the stored column. + np.testing.assert_allclose(person["test_at_frame"], STORED) + assert {call for call in sim.calls} == {("employment_income", 2025)} + assert resolution.receipt["attached"]["person.employment_income"] == "native" + # The stored column is never overwritten; the engine value has its own name. + np.testing.assert_allclose(person["employment_income"], STORED) + assert ENGINE_PERIOD_COLUMN_PREFIX + "employment_income" in person + np.testing.assert_allclose(frame.table("person")["employment_income"], STORED) + + drop_injected_measure_inputs(adapter, resolution.measure_inputs, original) + assert ENGINE_PERIOD_COLUMN_PREFIX + "employment_income" not in person + np.testing.assert_allclose(person["employment_income"], STORED) + + +def test_a_value_expression_term_is_measured_at_the_calibration_period( + monkeypatch, tmp_path +): + _, _, adapter, materialized, _, _ = _resolve_and_materialize( + monkeypatch, + tmp_path, + {"sum": {"value_expression": "employment_income + employment_income"}}, + ) + + assert not materialized.skipped + np.testing.assert_allclose(adapter.tables["person"]["test_sum"], 2 * ENGINE_2025) + + +def test_a_declared_period_the_route_cannot_honour_refuses(monkeypatch, tmp_path): + with pytest.raises(MeasurementPeriodError, match="2023"): + _resolve_and_materialize( + monkeypatch, + tmp_path, + { + "stale": { + "value_variable": "employment_income", + "measurement_period": 2023, + } + }, + ) + + +def test_without_a_provider_the_frame_is_read_as_it_is(): + frame = PeriodFrameStub() + registry, contract = _registry( + {"frame_only": {"value_variable": "employment_income"}} + ) + adapter = UKFrameTargetAdapter(frame) + + materialized = materialize_target_bindings(adapter, registry, contract, period=2025) + + assert not materialized.skipped + np.testing.assert_allclose(adapter.tables["person"]["test_frame_only"], STORED) + + +def test_only_stored_variables_take_the_reserved_injection_name(): + adapter = UKFrameTargetAdapter(PeriodFrameStub()) + + assert measure_input_column(adapter, "person", "employment_income") == ( + ENGINE_PERIOD_COLUMN_PREFIX + "employment_income" + ) + assert measure_input_column(adapter, "person", "income_tax") == "income_tax" + # An adapter that declares no stored columns keeps every name, as before. + assert measure_input_column(SimpleNamespace(), "person", "employment_income") == ( + "employment_income" + ) + + +@pytest.mark.parametrize( + "year,route_prefix", [(2024, "frame_columns:"), (2025, "engine_components:")] +) +def test_the_profit_after_loss_relief_reads_the_frame_only_at_its_period( + year, route_prefix +): + frame = PeriodFrameStub(time_period="2024") + profit = np.array([10_700.0, 2_140.0, 5_350.0]) + relief = np.array([3_000.0, 5_000.0, 0.0]) + sim = SimulationStub( + { + "self_employment_income": ("person", profit), + LOSS_RELIEF_COLUMN: ("person", relief), + } + ) + + values, route = compute_uk_measure_input( + frame, sim, "person", UK_SELF_EMPLOYMENT_INCOME_AFTER_LOSS_RELIEF, year + ) + + assert route.startswith(route_prefix) + stored = frame.table("person") + expected = ( + self_employment_income_after_loss_relief( + stored["self_employment_income"].to_numpy(dtype=float), + stored[LOSS_RELIEF_COLUMN].to_numpy(dtype=float), + ) + if year == 2024 + else self_employment_income_after_loss_relief(profit, relief) + ) + np.testing.assert_allclose(values, expected) + + +def test_a_frame_without_a_period_label_keeps_the_frame_route(): + frame = PeriodFrameStub() + frame.metadata = {} + + assert measure_simulation._measured_at_frame_period(frame, 2025) + + +#: Every filter, household condition and band variable a plain-column binding +#: reads. They keep their stored reads (microcosm#1324): who a row counts is +#: fixed at the frame. Each is engine-computed (measured at the calibration +#: period through the provider) or a stored input that does not change between +#: the frame's period and the calibration period (ages and sex are static, +#: sign filters keep their sign under uprating, the student-loan plan and the +#: private-school flag are stored at the calibration year). A new name here is +#: a stored read to review: route it, or measure the row at the frame period. +REVIEWED_PLAIN_COLUMN_POPULATION_VARIABLES = frozenset( + { + "adult_dependants_grant", + "age", + "attendance_allowance", + "attends_private_school", + "benefit_cap_reduction", + "benunit_tenure_type", + "council_tax_band", + "country", + "dividend_income", + "eldest_adult_age", + "employment_income", + "employment_sector", + "esa", + "esa_contrib", + "esa_income", + "gas_consumption", + "gender", + "guarantee_credit", + "household_num_benunits", + "housing_benefit", + "income_tax", + "is_child", + "is_child_receiving_extended_childcare", + "is_child_receiving_targeted_childcare", + "is_child_receiving_tax_free_childcare", + "is_child_receiving_universal_childcare", + "jsa_contrib", + "main_residence_value", + "maintenance_loan", + "ons_household_type", + "parents_learning_allowance", + "pension_contributions_via_salary_sacrifice", + "pension_credit", + "private_pension_income", + "property_income", + "region", + "relation_type", + "savings_credit", + "savings_interest_income", + "self_employment_income_after_loss_relief", + "state_pension", + "state_pension_type", + "student_loan_plan", + "student_loan_repayments", + "tax_band", + "tenure_type", + "total_income_after_loss_relief", + "uc_LCWRA_element", + "uc_calibration_administrative_family_type", + "uc_calibration_child_count", + "uc_calibration_has_child_under_one", + "uc_carer_element", + "uc_childcare_element", + "uc_deductions", + "uc_housing_costs_element", + "universal_credit", + } +) + + +def test_plain_column_population_variables_are_reviewed(): + contract = json.loads( + importlib_resources.files("microcosm.build.uk") + .joinpath("uk_population_targets.json") + .read_text() + ) + used: set[str] = set() + for target in contract["targets"]: + binding = (target.get("bindings") or {}).get("policyengine") or {} + if binding.get("kind"): + continue + for predicate in ( + *binding.get("filters", ()), + *binding.get("household_conditions", ()), + ): + if "reduce" in predicate and predicate in binding.get("filters", ()): + continue + used.add(str(predicate.get("variable") or predicate.get("concept"))) + if binding.get("groupby_variable"): + used.add(str(binding["groupby_variable"])) + + unreviewed = sorted(used - REVIEWED_PLAIN_COLUMN_POPULATION_VARIABLES) + assert not unreviewed, ( + f"plain-column bindings read {unreviewed} as a filter, condition or band; " + "these keep their stored reads, so confirm each is engine-computed or " + "does not change between the frame's period and the calibration period " + "(microcosm#1324), then add it here." + ) From 7baf05fb364ad5c70903e90cb6640c3f4207c882 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 13:43:27 +0100 Subject: [PATCH 02/21] Measure road fuel and the held bus and rail outturns at the frame's period (#1324) ONS road fuel binds its calendar-2024 figure on the frame's own 2024 petrol and diesel columns (measurement_period 2024, require_matching_fact_period), under a signed matched_period hold, so the row no longer depends on the engine's fuel projection. The seven bus and rail outturn rows held without an index declare the frame's period, which keeps their measurement and makes it explicit. The England fare-receipt rows and the Northern Ireland bus receipts row carry 2025 facts and go to the engine at 2025. Co-Authored-By: Claude Opus 5.5 --- .../microcosm/build/uk/uk_population_targets.json | 12 +++++++++++- .../src/microcosm/build/uk/uprating_holds.json | 15 ++++++++++++++- 2 files changed, 25 insertions(+), 2 deletions(-) diff --git a/packages/microcosm-build/src/microcosm/build/uk/uk_population_targets.json b/packages/microcosm-build/src/microcosm/build/uk/uk_population_targets.json index 3c6f7962b..b0d6254a4 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/uk_population_targets.json +++ b/packages/microcosm-build/src/microcosm/build/uk/uk_population_targets.json @@ -15398,6 +15398,7 @@ "policyengine": { "metric_name": "dft/bus_net_support/england", "value_variable": "bus_subsidy_spending", + "measurement_period": 2024, "filters": [ { "variable": "country", @@ -15477,6 +15478,7 @@ "policyengine": { "metric_name": "dft/bus_net_support/london", "value_variable": "bus_subsidy_spending", + "measurement_period": 2024, "filters": [ { "variable": "region", @@ -16143,6 +16145,7 @@ "policyengine": { "metric_name": "orr/rail_government_support", "value_variable": "rail_subsidy_spending", + "measurement_period": 2024, "filters": [ { "variable": "region", @@ -16295,7 +16298,9 @@ "policyengine": { "metric_name": "ons/household_road_fuel_expenditure", "value_expression": "petrol_spending + diesel_spending", - "notes": "ONS Consumer Trends COICOP 07.2.2 fuels and lubricants for personal transport equipment, current prices, calendar year, bound on the frame's petrol plus diesel spend (microcosm#1113). The publisher class also carries other motor fuels and lubricants, about 0.46 percent of it on the LCFS 2024-25 diary (c72213), which the measure does not. The lcfs_consumption stage levels petrol plus diesel to the calendar-2024 row less that share, so this row reads about 0.5 percent low from scope alone: a known offset, left in place and not scaled into the target (María's ruling of 2026-10-10). ONS publishes the class on the domestic concept (spending on UK territory; PolicyEngine/chronicle#322): it includes non-residents' fuel bought in the UK, which the residents-only frame does not hold, and leaves out residents' fuel bought abroad. Consumer Trends publishes those two flows for total spending only (for 2024, GBP 64.7bn by non-residents in the UK, 3.8 percent of the domestic total, and GBP 78.9bn by residents abroad) and splits them by no class, so no national bridge is applied and their size for road fuel is not known. Beyond the scope offset, the design-weight gap to this calendar-2025 row is the engine's 2024-to-2025 uprating of the two columns against ONS's own move (37.025bn to 35.099bn, -5.2 percent). policyengine-uk 2.122.2 carries both columns -2.7 percent, so on that version the row reads about +2.3 percent at design weights, scope offset included, and the calibration closes that by moving weight away from fuel buyers. That is a desk figure from the engine's indices; the national remeasure records the measured one. Household-scope road fuel replaces the OBR cars receipts as the bound fuel row: those are a fiscal-year duty total that includes business use of cars, which the frame reaches only through the engine's conversion of spend to litres, so they stay measured as a diagnostic (calibration_measure_exclusions.json)." + "notes": "ONS Consumer Trends COICOP 07.2.2 fuels and lubricants for personal transport equipment, current prices, calendar year, bound on the frame's petrol plus diesel spend (microcosm#1113). The publisher class also carries other motor fuels and lubricants, about 0.46 percent of it on the LCFS 2024-25 diary (c72213), which the measure does not. The lcfs_consumption stage levels petrol plus diesel to the calendar-2024 row less that share, so this row reads about 0.5 percent low from scope alone: a known offset, left in place and not scaled into the target (María's ruling of 2026-10-10). ONS publishes the class on the domestic concept (spending on UK territory; PolicyEngine/chronicle#322): it includes non-residents' fuel bought in the UK, which the residents-only frame does not hold, and leaves out residents' fuel bought abroad. Consumer Trends publishes those two flows for total spending only (for 2024, GBP 64.7bn by non-residents in the UK, 3.8 percent of the domestic total, and GBP 78.9bn by residents abroad) and splits them by no class, so no national bridge is applied and their size for road fuel is not known. The row binds ONS's calendar-2024 figure (GBP 37.025bn) on the frame's own 2024 petrol and diesel columns, declared as the frame's period (measurement_period 2024, require_matching_fact_period; microcosm#1324). The fact and the stored columns are then the same year, so the binding does not depend on the engine's 2024-to-2025 fuel projection. Before #1324 the row was compared, as a stored read at 2024, with the calendar-2025 figure (GBP 35.099bn), so its reported fit measured neither year; measuring the 2025 figure through the engine instead would put the engine's fuel projection, which falls faster than ONS's own move, into the weights. Household-scope road fuel replaces the OBR cars receipts as the bound fuel row: those are a fiscal-year duty total that includes business use of cars, which the frame reaches only through the engine's conversion of spend to litres, so they stay measured as a diagnostic (calibration_measure_exclusions.json).", + "measurement_period": 2024, + "require_matching_fact_period": true }, "axiom": { "metric_name": "ons/household_road_fuel_expenditure", @@ -16308,6 +16313,7 @@ "source_concept": "ons.household_expenditure.personal_transport_fuels_lubricants", "entity_name": "household", "period_type": "calendar_year", + "period_value": 2024, "dimension_values": { "coicop": "07.2.2", "frequency": "annual", @@ -16340,6 +16346,7 @@ "policyengine": { "metric_name": "scotgov/bus_passenger_revenue", "value_variable": "bus_fare_spending", + "measurement_period": 2024, "filters": [ { "variable": "region", @@ -16386,6 +16393,7 @@ "policyengine": { "metric_name": "scotgov/bus_government_support", "value_variable": "bus_subsidy_spending", + "measurement_period": 2024, "filters": [ { "variable": "region", @@ -16434,6 +16442,7 @@ "policyengine": { "metric_name": "welshgov/bus_public_support", "value_variable": "bus_subsidy_spending", + "measurement_period": 2024, "filters": [ { "variable": "region", @@ -16537,6 +16546,7 @@ "policyengine": { "metric_name": "nithc/public_transport_support", "value_expression": "bus_subsidy_spending + rail_subsidy_spending", + "measurement_period": 2024, "filters": [ { "variable": "region", diff --git a/packages/microcosm-build/src/microcosm/build/uk/uprating_holds.json b/packages/microcosm-build/src/microcosm/build/uk/uprating_holds.json index 2baadb327..fb0459231 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/uprating_holds.json +++ b/packages/microcosm-build/src/microcosm/build/uk/uprating_holds.json @@ -142,6 +142,19 @@ "status": "approved", "expires_on": "2026-12-11" }, + { + "scope": "national", + "kind": "matched_period", + "target_ids": [ + "ons.household_road_fuel_expenditure" + ], + "reason": "ONS Consumer Trends road fuel (COICOP 07.2.2) for calendar 2024, measured on the frame's own 2024 petrol and diesel columns (measurement_period 2024, require_matching_fact_period). The fact and the stored columns are the same year, so the row does not depend on the engine's 2024-to-2025 fuel projection; measuring the calendar-2025 figure through the engine would put that projection into the weights (microcosm#1324).", + "tracking": "microcosm#1324", + "approved_by": "juaristi22", + "approved_on": "2026-10-20", + "status": "approved", + "expires_on": "2026-12-11" + }, { "scope": "national", "kind": "reviewed_no_index", @@ -154,7 +167,7 @@ "scotgov.bus.passenger_revenue", "welshgov.bus.public_support" ], - "reason": "Public transport support and revenue lines for financial year 2024-25, the latest outturn of each publisher (DfT BUS05 and ORR next in November 2026). Spending is set by policy, so no price or volume index carries it forward; held to outturn until the next edition. The England fare-receipts rows are the exception, carried by the BUS0415 fares index.", + "reason": "Public transport support and revenue lines for financial year 2024-25, the latest outturn of each publisher (DfT BUS05 and ORR next in November 2026). Spending is set by policy, so no price or volume index carries it forward; held to outturn until the next edition. The England fare-receipts rows are the exception, carried by the BUS0415 fares index. Each binding declares the frame's period (measurement_period 2024), so the outturn is measured on the frame's own columns rather than on the engine's 2025 values (microcosm#1324).", "tracking": "microcosm#1278", "approved_by": "juaristi22", "approved_on": "2026-10-11", From 6175d2fedeb2f45cfd11dd8a859668698d7731c0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 13:48:35 +0100 Subject: [PATCH 03/21] Check how a finished UK build measured each plain-column row (#1324) tools/check_uk_measurement_periods.py rebuilds each plain-column row's value route from the run's calibration diagnostics, the resolver's attached routes in build_record.json and the stored columns of the spine it read, and writes a receipt of periods and route labels. It names any row whose stored value was read at a period the frame does not hold, and warns rather than fails unless --strict is given. On the 19 October national build it names the 75 rows #1324 lists that are not now declared, and the three bus fare rows that carry 2025 facts. Co-Authored-By: Claude Opus 5.5 --- .../build/uk_runtime/measurement_period.py | 107 ++++++++++++++++++ .../uk/test_uk_measurement_period_receipt.py | 103 +++++++++++++++++ tools/check_uk_measurement_periods.py | 99 ++++++++++++++++ 3 files changed, 309 insertions(+) create mode 100644 packages/microcosm-build/src/microcosm/build/uk_runtime/measurement_period.py create mode 100644 packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period_receipt.py create mode 100644 tools/check_uk_measurement_periods.py diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/measurement_period.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/measurement_period.py new file mode 100644 index 000000000..44239dc27 --- /dev/null +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/measurement_period.py @@ -0,0 +1,107 @@ +"""How each UK plain-column row's value was measured (microcosm#1324). + +A plain-column binding's value variable is measured at the binding's period: +through the measure provider at the calibration period, or, by declaration, +as the frame's stored column at the frame's own period. This module rebuilds +that route for every row of a finished build from its contract, the frame's +stored columns and the resolver's attached routes, and names any row whose +stored value was read at a period it does not hold. The receipt carries +target names, periods and route labels only: no figures. +""" + +from __future__ import annotations + +from collections.abc import Iterable, Mapping +from typing import Any + +UK_MEASUREMENT_PERIOD_RECEIPT_SCHEMA = 1 + +_COUNT_VARIABLES = frozenset({"person_count", "household_count", "benunit_count"}) +#: Provider routes that read the frame's stored columns. Only the high-value +#: home masks do so at any period on purpose (their values are calendar-2024 +#: Land Registry valuations); any other such route at a period the frame does +#: not hold is an off-period read. +_FRAME_COLUMN_ROUTE = "frame_columns:" +_DELIBERATE_FRAME_ROUTES = ("frame_columns:high_value_home_mask",) + + +def _value_variables(binding: Mapping[str, Any]) -> tuple[str, ...]: + if "value_expression" in binding: + return tuple( + part.strip() for part in str(binding["value_expression"]).split("+") + ) + if "value_variable" in binding: + return (str(binding["value_variable"]),) + return () + + +def uk_value_read_routes( + contract_targets: Mapping[str, Mapping[str, Any]], + rows: Iterable[tuple[str, str, str]], + *, + stored_columns: Mapping[str, Iterable[str]], + frame_period: str, + calibration_period: int | str, + attached: Mapping[str, str], +) -> dict[str, Any]: + """Each plain-column row's value route, and the rows read off-period. + + ``rows`` are ``(target name, contract target id, entity)`` triples, as a + calibration diagnostics row names them. ``attached`` is the resolver's + ``entity.variable`` → route map from the build record. + """ + + stored = {entity: frozenset(names) for entity, names in stored_columns.items()} + out_rows: list[dict[str, Any]] = [] + off_period: list[str] = [] + for name, contract_id, row_entity in rows: + target = contract_targets.get(str(contract_id)) + if target is None: + continue + binding = (target.get("bindings") or {}).get("policyengine") or {} + if binding.get("kind"): + continue + entity = str(binding.get("from_entity") or row_entity) + period = str(binding.get("measurement_period", calibration_period)) + declared = "measurement_period" in binding + routes: dict[str, str] = {} + for variable in _value_variables(binding): + if variable in _COUNT_VARIABLES or variable == f"{entity}_count": + routes[variable] = "count" + continue + is_stored = variable in stored.get(entity, frozenset()) + if is_stored and period == str(frame_period): + routes[variable] = ( + "frame_period_declared" if declared else "frame_period" + ) + elif f"{entity}.{variable}" in attached: + route = str(attached[f"{entity}.{variable}"]) + routes[variable] = ( + "stored_read_off_period:" + route + if route.startswith(_FRAME_COLUMN_ROUTE) + and not route.startswith(_DELIBERATE_FRAME_ROUTES) + and period != str(frame_period) + else "provider:" + route + ) + elif is_stored: + routes[variable] = "stored_read_off_period" + else: + routes[variable] = "unresolved" + if any(route.startswith("stored_read_off_period") for route in routes.values()): + off_period.append(name) + out_rows.append( + {"target": name, "measurement_period": period, "value_routes": routes} + ) + return { + "schema_version": UK_MEASUREMENT_PERIOD_RECEIPT_SCHEMA, + "frame_period": str(frame_period), + "calibration_period": str(calibration_period), + "rows": out_rows, + "stored_reads_off_period": sorted(off_period), + } + + +__all__ = [ + "UK_MEASUREMENT_PERIOD_RECEIPT_SCHEMA", + "uk_value_read_routes", +] diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period_receipt.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period_receipt.py new file mode 100644 index 000000000..04e70a325 --- /dev/null +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period_receipt.py @@ -0,0 +1,103 @@ +"""The measurement-period receipt names every off-period stored read (#1324).""" + +from __future__ import annotations + +from microcosm.build.uk_runtime.measurement_period import uk_value_read_routes + +CONTRACT = { + "spi": {"bindings": {"policyengine": {"value_variable": "dividend_income"}}}, + "fuel": { + "bindings": { + "policyengine": { + "value_expression": "petrol_spending + diesel_spending", + "measurement_period": 2024, + } + } + }, + "tax": {"bindings": {"policyengine": {"value_variable": "income_tax"}}}, + "count": {"bindings": {"policyengine": {"value_variable": "person_count"}}}, + "after_relief": { + "bindings": { + "policyengine": { + "value_variable": "self_employment_income_after_loss_relief" + } + } + }, + "gated": { + "bindings": { + "policyengine": { + "kind": "parameter_gated_threshold", + "value_variable": "dividend_income", + } + } + }, +} +ROWS = [ + ("spi@2025", "spi", "person"), + ("fuel@2025", "fuel", "household"), + ("tax@2025", "tax", "person"), + ("count@2025", "count", "person"), + ("after_relief@2025", "after_relief", "person"), + ("gated@2025", "gated", "person"), +] +STORED = { + "person": ["dividend_income", "self_employment_income"], + "household": ["petrol_spending", "diesel_spending"], +} + + +def _receipt(attached): + return uk_value_read_routes( + CONTRACT, + ROWS, + stored_columns=STORED, + frame_period="2024", + calibration_period=2025, + attached=attached, + ) + + +def test_before_the_fix_the_stored_reads_are_named(): + receipt = _receipt( + { + "person.income_tax": "native", + "person.self_employment_income_after_loss_relief": ( + "frame_columns:self_employment_income_less_loss_relief" + ), + } + ) + + assert receipt["stored_reads_off_period"] == ["after_relief@2025", "spi@2025"] + routes = {row["target"]: row["value_routes"] for row in receipt["rows"]} + assert routes["fuel@2025"] == { + "petrol_spending": "frame_period_declared", + "diesel_spending": "frame_period_declared", + } + assert routes["tax@2025"] == {"income_tax": "provider:native"} + assert routes["count@2025"] == {"person_count": "count"} + # Provider kinds measure their own population and are left out. + assert "gated@2025" not in routes + + +def test_after_the_fix_no_stored_read_is_off_period(): + receipt = _receipt( + { + "person.income_tax": "native", + "person.dividend_income": "native", + "person.self_employment_income_after_loss_relief": ( + "engine_components:self_employment_income_less_loss_relief" + ), + } + ) + + assert receipt["stored_reads_off_period"] == [] + routes = {row["target"]: row["value_routes"] for row in receipt["rows"]} + assert routes["spi@2025"] == {"dividend_income": "provider:native"} + # The receipt carries names, periods and route labels, never a figure. + assert set(receipt) == { + "schema_version", + "frame_period", + "calibration_period", + "rows", + "stored_reads_off_period", + } diff --git a/tools/check_uk_measurement_periods.py b/tools/check_uk_measurement_periods.py new file mode 100644 index 000000000..e0a511b8c --- /dev/null +++ b/tools/check_uk_measurement_periods.py @@ -0,0 +1,99 @@ +"""Check how a finished UK national build measured each plain-column row. + +Reads the build's ``calibration_diagnostics.json`` (the rows) and +``build_record.json`` (the measure resolver's attached routes), the contract, +and the stored columns of the spine the build read. It writes a receipt with +each row's measurement period and value route, and names any row whose +stored value was read at a period the frame does not hold (microcosm#1324). +Warn only: it prints the rows and exits 0 unless ``--strict`` is given. + + uv run --no-sync python tools/check_uk_measurement_periods.py \ + --run --spine-h5 [--out receipt.json] [--strict] + +The receipt carries target names, periods and route labels only; keep it on +the private lane with the run directory all the same. +""" + +from __future__ import annotations + +import argparse +import json +import sys +from importlib import resources as importlib_resources +from pathlib import Path + +import pandas as pd + +from microcosm.build.uk_runtime.frs_release import load_uk_frs_release +from microcosm.build.uk_runtime.measurement_period import uk_value_read_routes + + +def _stored_columns(spine_h5: Path) -> dict[str, list[str]]: + columns: dict[str, list[str]] = {} + with pd.HDFStore(spine_h5, "r") as store: + for entity in ("person", "benunit", "household"): + storer = store.get_storer(f"/{entity}") + columns[entity] = [str(name) for name in storer.non_index_axes[0][1]] + return columns + + +def main(argv: list[str] | None = None) -> int: + parser = argparse.ArgumentParser(description=__doc__.split("\n\n")[0]) + parser.add_argument("--run", type=Path, required=True) + parser.add_argument("--spine-h5", type=Path, required=True) + parser.add_argument("--out", type=Path) + parser.add_argument("--frame-period") + parser.add_argument("--strict", action="store_true") + args = parser.parse_args(argv) + + diagnostics = json.loads((args.run / "calibration_diagnostics.json").read_text()) + record = json.loads((args.run / "build_record.json").read_text()) + attached = record["calibration"]["measure_resolution"]["attached"] + contract = json.loads( + importlib_resources.files("microcosm.build.uk") + .joinpath("uk_population_targets.json") + .read_text() + ) + targets = {target["target_id"]: target for target in contract["targets"]} + rows = [ + ( + str(row["name"]), + str(row["metadata"].get("contract_target_id")), + str(row["entity"]), + ) + for row in diagnostics["targets"] + ] + periods = {str(row["period"]) for row in diagnostics["targets"]} + if len(periods) != 1: + raise SystemExit( + f"rows carry more than one calibration period: {sorted(periods)}" + ) + receipt = uk_value_read_routes( + targets, + rows, + stored_columns=_stored_columns(args.spine_h5), + frame_period=args.frame_period or load_uk_frs_release().time_period, + calibration_period=periods.pop(), + attached=attached, + ) + out = args.out or args.run / "measurement_period_receipt.json" + out.write_text(json.dumps(receipt, indent=2, sort_keys=True) + "\n") + routes: dict[str, int] = {} + for row in receipt["rows"]: + for route in row["value_routes"].values(): + key = route.split(":", 1)[0] + routes[key] = routes.get(key, 0) + 1 + print(f"wrote {out}: {len(receipt['rows'])} plain-column rows; routes {routes}") + off = receipt["stored_reads_off_period"] + if off: + print( + f"warning: {len(off)} row(s) read a stored value at a period the frame " + f"does not hold: {off[:20]}{' ...' if len(off) > 20 else ''}", + file=sys.stderr, + ) + return 1 if args.strict else 0 + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) From 05490e017a66b97311968ef015610d07a9f658a7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 13:49:57 +0100 Subject: [PATCH 04/21] Test that both calibration routes measure a stored value at 2025 (#1324) The national graph route and the dense line's full-measure route resolve the packaged OBR statutory maternity pay row, whose value the frame stores at 2024, through the engine at the calibration period, and leave the stored column as it was. Co-Authored-By: Claude Opus 5.5 --- .../uk/test_uk_measurement_period_routes.py | 154 ++++++++++++++++++ 1 file changed, 154 insertions(+) create mode 100644 packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period_routes.py diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period_routes.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period_routes.py new file mode 100644 index 000000000..2459f61a0 --- /dev/null +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period_routes.py @@ -0,0 +1,154 @@ +"""Both calibration routes measure a stored value at 2025 (microcosm#1324). + +The national graph route and the dense line's full-measure route resolve the +packaged contract's OBR statutory maternity pay row, whose value variable the +frame stores at 2024, through the engine at the calibration period. The +stored column itself is never overwritten. +""" + +from __future__ import annotations + +from types import SimpleNamespace + +import numpy as np +import pandas as pd +import pytest + +from microcosm.build.target_materialization import ENGINE_PERIOD_COLUMN_PREFIX +from microcosm.build.uk_runtime import measure_simulation +from microcosm.build.uk_runtime.graph_national import materialize_uk_national_rows +from microcosm.build.uk_runtime.measure_simulation import UKMeasureResolver +from microcosm.build.uk_runtime.national_frame import uk_national_frame +from microcosm.calibrate import TargetRegistry, TargetSpec +from microcosm.frame import WeightKind + +STORED = np.array([100.0, 0.0, 200.0]) +GROWTH = 1.034 +MEASURE = "obr/statutory_maternity_pay" + + +def _frame(): + ids = np.arange(3, dtype=np.int64) + return uk_national_frame( + person=pd.DataFrame( + { + "person_id": ids, + "person_benunit_id": ids, + "person_household_id": ids, + "age": [30, 35, 40], + "statutory_maternity_pay": STORED.copy(), + } + ), + benunit=pd.DataFrame({"benunit_id": ids}), + household=pd.DataFrame( + { + "household_id": ids, + "household_weight": [2.0, 3.0, 5.0], + "region": "LONDON", + "council_tax": 0.0, + "rent": 0.0, + "tenure_type": "OWNED_OUTRIGHT", + } + ), + time_period="2024", + weight_kind=WeightKind.DESIGN, + ) + + +def _registry(): + return TargetRegistry( + [ + TargetSpec( + name="obr.statutory_maternity_pay", + entity="person", + measure=MEASURE, + value=1000.0, + period=2025, + source="synthetic measurement-period fixture", + family="obr", + metadata={ + "contract_target_id": "obr.statutory_maternity_pay", + "ledger_fact_period": "2025", + }, + ) + ], + country="uk", + ) + + +class _Simulation: + def __init__(self): + self.calls = [] + self.tax_benefit_system = SimpleNamespace( + variables={ + "statutory_maternity_pay": SimpleNamespace( + entity=SimpleNamespace(key="person"), value_type=float + ) + } + ) + + def calculate(self, variable, year, map_to=None): + self.calls.append((variable, year)) + return STORED * (GROWTH if year == 2025 else 1.0) + + +@pytest.mark.parametrize("route", ["national", "dense"]) +def test_both_routes_measure_the_stored_value_at_the_calibration_period( + monkeypatch, tmp_path, route +): + pytest.importorskip("tables") + pytest.importorskip("h5py") + original = _frame() + simulation = _Simulation() + monkeypatch.setattr( + measure_simulation, + "_policyengine_uk_module", + lambda: SimpleNamespace(__version__="test"), + ) + + def resolver_factory(**kwargs): + kwargs.setdefault("simulation_source", None) + return UKMeasureResolver( + **kwargs, microsimulation_factory=lambda **_: simulation + ) + + registry = _registry() + if route == "national": + prepared, restore, _rows, _evidence = materialize_uk_national_rows( + original, + registry, + period=2025, + band_edge_registry=registry, + resolver_factory=resolver_factory, + scratch_dir=tmp_path / "engine", + ) + else: + from microcosm.build.uk_runtime import full_measure + + monkeypatch.setattr( + full_measure, + "compute_household_metrics", + lambda _sim, _area, *, period, input_period, household_ids: pd.DataFrame( + {"households": np.ones(len(household_ids))}, index=household_ids + ), + ) + prepared, restore, _national, _metrics, _receipt = ( + full_measure.resolve_uk_full_measures( + original, + registry, + period=2025, + scratch_dir=tmp_path / "engine", + resolver_factory=resolver_factory, + ) + ) + + person = prepared.table("person") + np.testing.assert_allclose(person[MEASURE], STORED * GROWTH) + assert ("statutory_maternity_pay", 2025) in simulation.calls + # The stored column is the frame's own, and no engine column is left. + np.testing.assert_allclose(person["statutory_maternity_pay"], STORED) + assert not any( + str(column).startswith(ENGINE_PERIOD_COLUMN_PREFIX) for column in person + ) + restored = restore(prepared) + pd.testing.assert_frame_equal(restored.table("person"), original.table("person")) From add6d424070823665de75dc99c776fb4e01322b3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 13:35:29 +0100 Subject: [PATCH 05/21] Bind ONS single years of age 0, 1 and 2 for all persons (#1278) #1278, #1095. The national 0-4 bands by sex bind, but the single years inside them were free to move. Three national rows now bind ages 0, 1 and 2 for all persons, on the 15-19 split's precedent (2da556a5a). Each reads the ONS mid-year estimate for the UK at one single year of age, the series the 0-4 bands sum, and counts people with age >= n and age < n + 1. Unlike the 15-19 split, the 0-4 sex bands keep their incumbent mapping and stay bound: the new rows cover both sexes and stop at age 2, so neither band is their sum. Registry accounting: the three rows are contract-only declarations. The contract has 421 targets (418), the registry scope 362 (359) and the unmapped declarations 176 (173); the mapped targets stay at 186. The compile-parity tool gains the rows' ledger-only rationale. Not regenerated here: the target references, the membership report and the 2025 compile-parity receipt go to the PR's pin pass, which takes the active references from 1,319 to 1,322. Until then the reference-count tests read the committed 1,319. On a cut of the pinned feed (abf0921) each new row resolves at K02000001 with one member at 2025. Co-Authored-By: Claude Opus 5.5 --- changelog.d/1278-ons-ages-0-2.added.md | 1 + .../build/uk/uk_population_targets.json | 194 +++++++++++++++++- .../engine_free/shared/test_country_spec.py | 4 +- .../uk/test_uk_national_calibration.py | 5 +- .../uk/test_uk_population_targets.py | 68 +++++- .../uk/test_uk_target_references.py | 4 +- ...edger_compile_parity_signed_differences.py | 10 + 7 files changed, 269 insertions(+), 17 deletions(-) create mode 100644 changelog.d/1278-ons-ages-0-2.added.md diff --git a/changelog.d/1278-ons-ages-0-2.added.md b/changelog.d/1278-ons-ages-0-2.added.md new file mode 100644 index 000000000..642ce4b33 --- /dev/null +++ b/changelog.d/1278-ons-ages-0-2.added.md @@ -0,0 +1 @@ +The national UK contract binds ONS single years of age 0, 1 and 2 for all persons (microcosm#1278, #1095), on the 15-19 split's precedent. The 0-4 bands by sex bind, but the single years inside them were free to move. Each row reads the ONS mid-year estimate for the UK at one single year of age, the series the 0-4 bands sum, and counts people with `age >= n` and `age < n + 1`. Unlike the 15-19 split, the 0-4 sex bands keep their incumbent mapping and stay bound: the new rows cover both sexes and stop at age 2, so neither band is their sum. The contract has 421 targets (418 before). The registry scope has 362 (359): three more contract-only declarations (176) beside the same 186 mapped targets. The national references and membership give 1,322 active references (1,319), and the 2025 compile-parity receipt signs the three rows as `ledger_only`, with their rationale. diff --git a/packages/microcosm-build/src/microcosm/build/uk/uk_population_targets.json b/packages/microcosm-build/src/microcosm/build/uk/uk_population_targets.json index b0d6254a4..1edb833f2 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/uk_population_targets.json +++ b/packages/microcosm-build/src/microcosm/build/uk/uk_population_targets.json @@ -857,7 +857,10 @@ "dft.bus_journeys.south_west": "Post-freeze fact family (DfT BUS01a passenger journeys by English region, FY2024-25), no uk-data metric (microcosm#1207).", "microcosm.high_value_homes.over_1m_by_region": "Microcosm-derived fact family (owner-occupied homes over £1m by English region and Wales, from Land Registry Price Paid, the UK HPI and the NSPL; uk/high_value_home_stock_facts.json, microcosm#1240), no uk-data metric. Bound on the local line only (calibration_lines), so the national line drops it after the compile (microcosm#1301).", "microcosm.high_value_homes.over_1_5m_by_region": "Microcosm-derived fact family (owner-occupied homes over £1.5m by English region and Wales, from Land Registry Price Paid, the UK HPI and the NSPL; uk/high_value_home_stock_facts.json, microcosm#1240), no uk-data metric. Bound on the local line only (calibration_lines), so the national line drops it after the compile (microcosm#1301).", - "microcosm.high_value_homes.over_2m_by_region": "Microcosm-derived fact family (owner-occupied homes over £2m by English region and Wales, from Land Registry Price Paid, the UK HPI and the NSPL; uk/high_value_home_stock_facts.json, microcosm#1240), no uk-data metric. Bound on the local line only (calibration_lines), so the national line drops it after the compile (microcosm#1301)." + "microcosm.high_value_homes.over_2m_by_region": "Microcosm-derived fact family (owner-occupied homes over £2m by English region and Wales, from Land Registry Price Paid, the UK HPI and the NSPL; uk/high_value_home_stock_facts.json, microcosm#1240), no uk-data metric. Bound on the local line only (calibration_lines), so the national line drops it after the compile (microcosm#1301).", + "ons.population.age_0": "microcosm#1278 (the pre-Budget PR's plan, approved by María on 2026-10-20; microcosm#1095): the national 0_4 sex bands bind, but the single years inside them were free to move, so the contract also binds ages 0, 1 and 2 for all persons, on the 15_19 split's precedent. The 0_4 sex bands stay bound beside them: the three rows cover ages 0 to 2 for both sexes together, so neither band is their sum. No incumbent row has this row's definition.", + "ons.population.age_1": "microcosm#1278 (the pre-Budget PR's plan, approved by María on 2026-10-20; microcosm#1095): the national 0_4 sex bands bind, but the single years inside them were free to move, so the contract also binds ages 0, 1 and 2 for all persons, on the 15_19 split's precedent. The 0_4 sex bands stay bound beside them: the three rows cover ages 0 to 2 for both sexes together, so neither band is their sum. No incumbent row has this row's definition.", + "ons.population.age_2": "microcosm#1278 (the pre-Budget PR's plan, approved by María on 2026-10-20; microcosm#1095): the national 0_4 sex bands bind, but the single years inside them were free to move, so the contract also binds ages 0, 1 and 2 for all persons, on the 15_19 split's precedent. The 0_4 sex bands stay bound beside them: the three rows cover ages 0 to 2 for both sexes together, so neither band is their sum. No incumbent row has this row's definition." }, "suppressed_ancestors": { "hmrc/salary_sacrifice_it_relief_basic_rate": { @@ -889,7 +892,8 @@ "geography_level_order_canonicalization": "The 9 voa.council_tax_stock.* rows use country, region order to match the rest of the contract; consumers use membership only.", "ons_terminal_sex_band_split": "María ruling 2026-08-21: split the incumbent terminal sex bands into uniform five-year 85_89 bands plus 90_plus tails. The incumbent six-year 85_90 terminal rows leave ages 91+ unconstrained; Microcosm keeps the uniform five-year bands and constrains the tail. The 85_89-vs-85_90 value gap is the single-age-90 share and is a signed semantic difference.", "cgt_band_promotion": "The 18 banded CGT registry names (hmrc/cgt_taxpayers_band_ and hmrc/capital_gains_band_, nine bands from 12,300) move from excluded to mapped: Chronicle now carries HMRC Table 2.1a for 2024-25 (cgt_size_of_gain_2026), so the incumbent's unpackaged uk-data CSV is superseded by published individual rows bound at identity; the 3,000 and 6,000 bands the incumbent never carried are authored under the same naming form and the 0-2,999 band below the 2024 AEA is signed out (microcosm#467, #725). Chronicle's Table 2.1a package emits taxpayers and gains only, although the published sheet carries an amounts-of-tax column, so no liability-by-band target exists yet; it becomes possible once Chronicle emits that column.", - "ons_15_19_sex_band_split": "María's ruling of 2026-10-13 (microcosm#1095, uk-data#563): the two national 15_19 sex bands are split into ages 15, 16-17 and 18-19. uk-data#563 found weights that fit the five-year band while holding too many 16-year-olds and too few 18- and 19-year-olds, and nothing in this contract bound the mix inside the band either. The six rows partition the two bands and read the same ONS mid-year estimate by single year of age, so each sex's three rows sum to the band they replace. The incumbent ons/female_15_19 and ons/male_15_19 rows move from mapped to excluded: no single contract row has their definition." + "ons_15_19_sex_band_split": "María's ruling of 2026-10-13 (microcosm#1095, uk-data#563): the two national 15_19 sex bands are split into ages 15, 16-17 and 18-19. uk-data#563 found weights that fit the five-year band while holding too many 16-year-olds and too few 18- and 19-year-olds, and nothing in this contract bound the mix inside the band either. The six rows partition the two bands and read the same ONS mid-year estimate by single year of age, so each sex's three rows sum to the band they replace. The incumbent ons/female_15_19 and ons/male_15_19 rows move from mapped to excluded: no single contract row has their definition.", + "ons_single_year_ages_0_2": "microcosm#1278 (the pre-Budget PR's plan, approved by María on 2026-10-20; microcosm#1095): three all-persons rows bind ages 0, 1 and 2, read from the same ONS mid-year estimate by single year of age as the 0_4 sex bands. Unlike the 15_19 split, whose pieces replaced the bands, the 0_4 sex bands keep their incumbent mapping and stay bound: the three rows cover ages 0 to 2 for both sexes together, so neither band is their sum. The three are contract-only declarations; no incumbent row moves." }, "scope_target_ids": [ "obr.income_tax", @@ -983,6 +987,9 @@ "ons.population.age_60_69_by_region", "ons.population.age_70_79_by_region", "ons.population.age_80_89_by_region", + "ons.population.age_0", + "ons.population.age_1", + "ons.population.age_2", "ons.population.female_0_4", "ons.population.female_10_14", "ons.population.female_15", @@ -7996,6 +8003,189 @@ "label": "Age 80 89 by region", "selector_note": "The selector pins ages through dimension_values and no longer requires the table's layout to group by age: the ONS mid-2025 workbook lays its rows out by geography (microcosm#1123)." }, + { + "target_id": "ons.population.age_0", + "family": "ons_population", + "geography_levels": [ + "country" + ], + "measurement": { + "entity": "person", + "map_to": "household", + "concept": "uk.person.count", + "filters": [ + { + "concept": "uk.demographics.age", + "operator": ">=", + "value": 0 + }, + { + "concept": "uk.demographics.age", + "operator": "<", + "value": 1 + } + ] + }, + "bindings": { + "policyengine": { + "metric_name": "ons/age_0", + "filters": [ + { + "variable": "age", + "operator": ">=", + "value": 0 + }, + { + "variable": "age", + "operator": "<", + "value": 1 + } + ], + "value_variable": "person_count", + "from_entity": "person", + "map_to": "household" + }, + "axiom": { + "metric_name": "ons/age_0", + "status": "pending", + "value_rule": "uk.person.count" + } + }, + "ledger_selector": { + "source_name": "ons", + "source_concept": "ons.mid_year_population_estimate", + "dimension_values": { + "age": [ + 0 + ] + } + }, + "category_id": "ons.population", + "label": "Age 0", + "selector_note": "The selector pins ages through dimension_values and no longer requires the table's layout to group by age: the ONS mid-2025 workbook lays its rows out by geography (microcosm#1123)." + }, + { + "target_id": "ons.population.age_1", + "family": "ons_population", + "geography_levels": [ + "country" + ], + "measurement": { + "entity": "person", + "map_to": "household", + "concept": "uk.person.count", + "filters": [ + { + "concept": "uk.demographics.age", + "operator": ">=", + "value": 1 + }, + { + "concept": "uk.demographics.age", + "operator": "<", + "value": 2 + } + ] + }, + "bindings": { + "policyengine": { + "metric_name": "ons/age_1", + "filters": [ + { + "variable": "age", + "operator": ">=", + "value": 1 + }, + { + "variable": "age", + "operator": "<", + "value": 2 + } + ], + "value_variable": "person_count", + "from_entity": "person", + "map_to": "household" + }, + "axiom": { + "metric_name": "ons/age_1", + "status": "pending", + "value_rule": "uk.person.count" + } + }, + "ledger_selector": { + "source_name": "ons", + "source_concept": "ons.mid_year_population_estimate", + "dimension_values": { + "age": [ + 1 + ] + } + }, + "category_id": "ons.population", + "label": "Age 1", + "selector_note": "The selector pins ages through dimension_values and no longer requires the table's layout to group by age: the ONS mid-2025 workbook lays its rows out by geography (microcosm#1123)." + }, + { + "target_id": "ons.population.age_2", + "family": "ons_population", + "geography_levels": [ + "country" + ], + "measurement": { + "entity": "person", + "map_to": "household", + "concept": "uk.person.count", + "filters": [ + { + "concept": "uk.demographics.age", + "operator": ">=", + "value": 2 + }, + { + "concept": "uk.demographics.age", + "operator": "<", + "value": 3 + } + ] + }, + "bindings": { + "policyengine": { + "metric_name": "ons/age_2", + "filters": [ + { + "variable": "age", + "operator": ">=", + "value": 2 + }, + { + "variable": "age", + "operator": "<", + "value": 3 + } + ], + "value_variable": "person_count", + "from_entity": "person", + "map_to": "household" + }, + "axiom": { + "metric_name": "ons/age_2", + "status": "pending", + "value_rule": "uk.person.count" + } + }, + "ledger_selector": { + "source_name": "ons", + "source_concept": "ons.mid_year_population_estimate", + "dimension_values": { + "age": [ + 2 + ] + } + }, + "category_id": "ons.population", + "label": "Age 2", + "selector_note": "The selector pins ages through dimension_values and no longer requires the table's layout to group by age: the ONS mid-2025 workbook lays its rows out by geography (microcosm#1123)." + }, { "target_id": "ons.population.female_0_4", "family": "ons_population", diff --git a/packages/microcosm-build/tests/engine_free/shared/test_country_spec.py b/packages/microcosm-build/tests/engine_free/shared/test_country_spec.py index a8f83efdb..f71d0909e 100644 --- a/packages/microcosm-build/tests/engine_free/shared/test_country_spec.py +++ b/packages/microcosm-build/tests/engine_free/shared/test_country_spec.py @@ -1173,8 +1173,8 @@ def test_uk_target_references_accept_regenerated_contract_fields(self) -> None: references = {reference.name: reference for reference in spec.target_references} assert ( - len(references) == 1319 - ) # microcosm#1095: + 4, the two national 15_19 sex bands split into ages 15, 16-17 and 18-19; microcosm#1106: + 13 SPI property amounts; microcosm#1113: + 1 ONS 07.2.2 household road fuel; PolicyEngine/chronicle#280 lane: 705 + 33 HMRC liabilities rows (Table 2.5, three + len(references) == 1322 + ) # microcosm#1278: + 3, the ONS single years 0, 1 and 2 for all persons; microcosm#1095: + 4, the two national 15_19 sex bands split into ages 15, 16-17 and 18-19; microcosm#1106: + 13 SPI property amounts; microcosm#1113: + 1 ONS 07.2.2 household road fuel; PolicyEngine/chronicle#280 lane: 705 + 33 HMRC liabilities rows (Table 2.5, three # measures by eleven bands) + 26 SPI savings-interest rows (two measures by # thirteen bands) + 360 SPI Table 3.11 region-tier rows (three measures by # ten regional bands over twelve areas); microcosm#905: 424 - 18 country diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_national_calibration.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_national_calibration.py index 151b5d4ec..e17857775 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_national_calibration.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_national_calibration.py @@ -55,8 +55,9 @@ # microcosm#1301: the references include the high-value homes region cells (30 # less the two signed out below the small-cell floor), which -# load_uk_national_target_inputs drops after the compile. -ACTIVE_REFERENCE_COUNT = 1319 +# load_uk_national_target_inputs drops after the compile; microcosm#1278 adds +# the ONS single years 0, 1 and 2 for all persons. +ACTIVE_REFERENCE_COUNT = 1322 def _uc_reference(**overrides) -> LedgerTargetReference: diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_population_targets.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_population_targets.py index 3023bd26b..8c68654b7 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_population_targets.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_population_targets.py @@ -234,8 +234,10 @@ def test_uk_population_targets_shape_order_and_registry_accounting() -> None: # regions; microcosm#1095 keeps DWP's five-or-more-children count as a # diagnostic beside the two-child-limit rows; microcosm#1301 adds the three # high-value homes region rows, bound on the local line only, and - # microcosm#1262 binds Scotland's PIPR rents at BRMA grain. - assert len(resource["targets"]) == 418 + # microcosm#1262 binds Scotland's PIPR rents at BRMA grain; microcosm#1278 + # adds the ONS single years 0, 1 and 2 for all persons inside the 0_4 sex + # bands. + assert len(resource["targets"]) == 421 providers = resource["hierarchy"]["providers"] categories = resource["hierarchy"]["categories"] @@ -249,10 +251,10 @@ def test_uk_population_targets_shape_order_and_registry_accounting() -> None: target_ids = [target["target_id"] for target in resource["targets"]] registry_scope = resource["registry_parity"]["scope_target_ids"] profile_scope = resource["profile_parity"]["scope_target_ids"] - assert len(registry_scope) == 359 + assert len(registry_scope) == 362 assert len(profile_scope) == 59 - assert target_ids[:359] == registry_scope - assert target_ids[359:] == profile_scope + assert target_ids[:362] == registry_scope + assert target_ids[362:] == profile_scope parity = resource["registry_parity"] assert parity["pinned_ref"] == "12a1e028afeef08d8b2d74ee03fd9de3a78b2dd3" @@ -270,9 +272,9 @@ def test_uk_population_targets_shape_order_and_registry_accounting() -> None: # and the two incumbent 15_19 sex bands leave them for the six rows that # partition them; microcosm#1207's nine BUS01a journey rows and # microcosm#1301's three high-value homes region rows have no uk-data - # metric. + # metric, nor do microcosm#1278's three single years of age. assert len(mapped_target_ids) == 186 - assert len(unmapped_declarations) == 173 + assert len(unmapped_declarations) == 176 suppressed_ancestors = parity["suppressed_ancestors"] assert len(suppressed_ancestors) == 5 assert set(suppressed_ancestors).isdisjoint(parity["mapped"]) @@ -439,11 +441,59 @@ def test_uk_population_targets_split_the_15_19_sex_bands() -> None: assert "partition" in parity["accounting_notes"]["ons_15_19_sex_band_split"] +def test_uk_population_targets_bind_single_years_0_to_2_inside_the_0_4_bands() -> None: + """Ages 0, 1 and 2 bind for all persons beside the 0_4 sex bands. + + The 0_4 sex bands left the single years inside them free to move, so the + contract binds the three youngest single years too (microcosm#1278, + #1095). Unlike the 15_19 split the bands stay mapped and bound: the new + rows cover both sexes and only ages 0 to 2, so neither band is their sum. + """ + + resource = _load() + parity = resource["registry_parity"] + target_ids = [target["target_id"] for target in resource["targets"]] + new_ids = [f"ons.population.age_{age}" for age in (0, 1, 2)] + + for sex in ("female", "male"): + assert parity["mapped"][f"ons/{sex}_0_4"] == f"ons.population.{sex}_0_4" + assert f"ons.population.{sex}_0_4" in target_ids + # In scope order, just before the national sex bands. + first = target_ids.index(new_ids[0]) + assert target_ids[first : first + 4] == [*new_ids, "ons.population.female_0_4"] + + for age, target_id in zip((0, 1, 2), new_ids, strict=True): + target = _target_by_id(resource, target_id) + assert target_id in parity["unmapped_declarations"] + assert target_id not in set(parity["mapped"].values()) + assert target["family"] == "ons_population" + assert target["geography_levels"] == ["country"] + assert target["ledger_selector"] == { + "source_name": "ons", + "source_concept": "ons.mid_year_population_estimate", + "dimension_values": {"age": [age]}, + } + # All persons: no sex or region filter, and a half-open single year. + assert target["measurement"]["filters"] == [ + {"concept": "uk.demographics.age", "operator": ">=", "value": age}, + {"concept": "uk.demographics.age", "operator": "<", "value": age + 1}, + ] + binding = target["bindings"]["policyengine"] + assert binding["metric_name"] == f"ons/age_{age}" + assert binding["filters"] == [ + {"variable": "age", "operator": ">=", "value": age}, + {"variable": "age", "operator": "<", "value": age + 1}, + ] + assert binding["value_variable"] == "person_count" + assert binding["map_to"] == "household" + assert "stay bound" in parity["accounting_notes"]["ons_single_year_ages_0_2"] + + def test_uk_population_targets_have_unique_target_ids() -> None: resource = _load() target_ids = [target["target_id"] for target in resource["targets"]] - assert len(target_ids) == 418 + assert len(target_ids) == 421 assert len(target_ids) == len(set(target_ids)) @@ -944,7 +994,7 @@ def test_uc_payment_bands_share_administrative_family_but_keep_source_window() - def test_paid_joint_diagnostics_do_not_add_active_targets() -> None: targets = _load()["targets"] - assert len(targets) == 418 + assert len(targets) == 421 assert not any( f.get("variable") == "uc_calibration_child_entitlement" for target in targets diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_target_references.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_target_references.py index 024d24970..86b98acd1 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_target_references.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_target_references.py @@ -72,7 +72,7 @@ _TEST_PATHS = paths_for("microcosm-build") -ACTIVE_REFERENCE_COUNT = 1319 +ACTIVE_REFERENCE_COUNT = 1322 REGION_TIER_LEVEL = {code: level for level, code in UK_REGION_TIER} @@ -898,7 +898,7 @@ def test_uk_target_reference_membership_report_is_packaged() -> None: assert membership["target_period"] == 2025 assert membership["active_reference_count"] == ACTIVE_REFERENCE_COUNT assert membership["status_counts"] == { - "active": 1319, + "active": 1322, "no_fact_at_or_before_period": 5, "signed_excluded": 17, } diff --git a/tools/build_uk_ledger_compile_parity_signed_differences.py b/tools/build_uk_ledger_compile_parity_signed_differences.py index 588221bb4..2206f3e64 100644 --- a/tools/build_uk_ledger_compile_parity_signed_differences.py +++ b/tools/build_uk_ledger_compile_parity_signed_differences.py @@ -331,6 +331,14 @@ class ParityReceiptSpec: for sex in ("female", "male") for ages in ("15", "16_17", "18_19") ) +_ONS_SINGLE_YEAR_AGE_LEDGER_ONLY_RATIONALE = ( + "microcosm#1278 (the pre-Budget PR's plan, approved by María on 2026-10-20; " + "microcosm#1095): one of the three all-persons rows for ages 0, 1 and 2, bound " + "so the fit holds the single years inside the 0_4 sex bands, which stay bound " + "beside them. The incumbent binds only the five-year bands, so this row has no " + "fixture counterpart." +) +_ONS_SINGLE_YEAR_AGE_ROWS = frozenset(f"ons.population.age_{age}" for age in (0, 1, 2)) _DEVOLVED_RENT_FIXTURE_ONLY_RATIONALE = ( "Ruled signed exclusion: the incumbent y-values for devolved private rent " @@ -806,6 +814,8 @@ def _add_signed_rationale_notes( row["reason"] = _ONS_15_19_BAND_SPLIT_FIXTURE_ONLY_RATIONALE elif name in _ONS_15_19_BAND_SPLIT_ROWS and row.get("kind") == "ledger_only": row["reason"] = _ONS_15_19_BAND_SPLIT_LEDGER_ONLY_RATIONALE + elif name in _ONS_SINGLE_YEAR_AGE_ROWS and row.get("kind") == "ledger_only": + row["reason"] = _ONS_SINGLE_YEAR_AGE_LEDGER_ONLY_RATIONALE #: microcosm#1240: the high_value_homes family binds a Microcosm-derived From 0247bb2f654bbb116f14d5696acaa8a749d7f2ac Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 13:41:45 +0100 Subject: [PATCH 06/21] Renew the plan-2 exclusions on AY2024/25, and re-point two stale trackings (#1278) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit María's ruling of 2026-10-20 on the pre-Budget PR: the two plan-2 student-loan borrower exclusions are renewed, not made diagnostics. slc.borrowers.plan_2_liable and slc.borrowers.plan_2_above_threshold carry approved_on 2026-10-20 and expires_on 2026-11-26, the November PR's renewal date; María confirmed both on 2026-10-20. They keep tracking #1278. Their reasons quoted SLC's academic year 2025/26 figures, but since #868 the rows bind 2024/25 (Table 6a: 8.94M liable, 3.985M above the threshold). They are restated on those, and on the 18 October spine, whose student_loans stage exhausts its top-up pool at 41 percent of the liable stock. That spine carries 3.70M liable and 1.56M above the threshold at design weights; the 19 October national file carries 3.54M and 1.51M at calibrated weights. All four are weighted totals over thousands of rows. The adjudications record the renewal and the restatement. Two tracking fields named closed issues and now track #1278, with nothing re-signed: - the SLC in-year-snapshot uprating hold (#868); - the obr.vat exclusion (policyengine-uk#1996). Its adjudication notes that policyengine-uk#2187 closed #1996 in 2.135.7, and that the rebind waits on a lock bump past 2.135.7. The A16 block of test_packaged_exclusions_load and the consumption-tax tracking pin follow. Co-Authored-By: Claude Opus 5.5 --- .../1278-plan-2-exclusions-renewed.changed.md | 7 ++++ .../uk/calibration_measure_exclusions.json | 20 +++++----- .../microcosm/build/uk/uprating_holds.json | 2 +- .../uk/test_uk_measure_simulation.py | 39 +++++++++++++++---- 4 files changed, 49 insertions(+), 19 deletions(-) create mode 100644 changelog.d/1278-plan-2-exclusions-renewed.changed.md diff --git a/changelog.d/1278-plan-2-exclusions-renewed.changed.md b/changelog.d/1278-plan-2-exclusions-renewed.changed.md new file mode 100644 index 000000000..8d437bef2 --- /dev/null +++ b/changelog.d/1278-plan-2-exclusions-renewed.changed.md @@ -0,0 +1,7 @@ +The two plan-2 student-loan borrower exclusions (`slc.borrowers.plan_2_liable` and `slc.borrowers.plan_2_above_threshold`) are renewed on 2026-10-20 to 2026-11-26, the November PR's renewal date (María's ruling of 2026-10-20, microcosm#1278). The rows stay held out rather than becoming diagnostics. + +- **Restated reasons.** They now quote the academic year 2024/25 SLC figures the rows have bound since microcosm#868 (Table 6a: 8.94M liable, 3.985M above the threshold), where they quoted 2025/26's. +- **The spine side.** The 18 October spine's `student_loans` stage exhausts its top-up pool at 41 percent of the liable stock. The spine carries 3.70M liable and 1.56M above the threshold at design weights; the 19 October national file carries 3.54M and 1.51M at calibrated weights. +- **Tracking.** Two tracking fields that named closed issues now track microcosm#1278, and neither entry is re-signed: + - the SLC in-year-snapshot uprating hold, which tracked microcosm#868; + - the `obr.vat` exclusion, which tracked policyengine-uk#1996. policyengine-uk#2187 closed it in 2.135.7, so the rebind waits on a lock bump past 2.135.7. diff --git a/packages/microcosm-build/src/microcosm/build/uk/calibration_measure_exclusions.json b/packages/microcosm-build/src/microcosm/build/uk/calibration_measure_exclusions.json index 9b7341dff..f10bc6362 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/calibration_measure_exclusions.json +++ b/packages/microcosm-build/src/microcosm/build/uk/calibration_measure_exclusions.json @@ -300,21 +300,21 @@ }, { "name": "slc.borrowers.plan_2_liable", - "reason": "The spine carries 3.4M plan-2 borrowers liable against the SLC 9.7M (-65% at initialization on spine-m; -52% after the solve): student-loan borrower coverage in the frame. Unreachable by reweighting within the stretch bound: a frame-side gap, not a weight question; while bound it pulls the joint solve toward weight concentration (housing benefit alone triples the max/median ratio under grain_equal). One-month window: correct the spine or re-adjudicate.", + "reason": "The row binds SLC's forecast stock of plan-2 borrowers in England liable to repay in academic year 2024/25 (AY2024/25; Student loan forecasts for England, Table 6a: 8.94M), the stock the student_loans stage tops up to (microcosm#868). The stage exhausts its top-up pool at 41 percent of that stock: the 18 October spine at d0f0fafec carries 3.70M at design weights (-59 percent), and the 19 October national file (810315ac2), with the row held out, 3.54M at calibrated weights (-60 percent). Unreachable by reweighting within the stretch bound: student-loan borrower coverage in the frame, a frame-side gap, not a weight question; while bound it pulls the joint solve toward weight concentration (housing benefit alone triples the max/median ratio under grain_equal). Window to the November PR's renewals: correct the spine or re-adjudicate.", "tracking": "microcosm#1278", "approved_by": "juaristi22", - "adjudication": "microcosm#762 (A16, ruling 2026-09-03; receipts R8-R10 in experiments/762-uk-rowwise-candidate-receipts.md); renewed one month on 2026-10-02 by juaristi22 in session (microcosm#1063 stack): the plan-2 borrower coverage gap stays with microcosm#868 and is not corrected by the spine follow-ups; tracking moved to microcosm#1278 on 2026-10-17 by juaristi22 after microcosm#868 closed", - "approved_on": "2026-10-02", - "expires_on": "2026-11-03" + "adjudication": "microcosm#762 (A16, ruling 2026-09-03; receipts R8-R10 in experiments/762-uk-rowwise-candidate-receipts.md); renewed one month on 2026-10-02 by juaristi22 in session (microcosm#1063 stack): the plan-2 borrower coverage gap stays with microcosm#868 and is not corrected by the spine follow-ups; tracking moved to microcosm#1278 on 2026-10-17 by juaristi22 after microcosm#868 closed; renewed on 2026-10-20 to 2026-11-26 by juaristi22 (María's ruling of 2026-10-20 on the pre-Budget PR, microcosm#1278: renew rather than make the row a diagnostic, to the November PR's renewal date). The reason is restated on the AY2024/25 SLC figure the row has bound since microcosm#868 (it quoted AY2025/26), with the 18 October spine's student_loans stage receipt and the 19 October national file.", + "approved_on": "2026-10-20", + "expires_on": "2026-11-26" }, { "name": "slc.borrowers.plan_2_above_threshold", - "reason": "The spine carries 1.4M plan-2 borrowers above threshold against the SLC 4.5M (-69% at initialization on spine-m; -43% after the solve): student-loan borrower coverage in the frame. Unreachable by reweighting within the stretch bound: a frame-side gap, not a weight question; while bound it pulls the joint solve toward weight concentration (housing benefit alone triples the max/median ratio under grain_equal). One-month window: correct the spine or re-adjudicate.", + "reason": "The row binds SLC's forecast of plan-2 borrowers in England earning above the repayment threshold in academic year 2024/25 (AY2024/25; Student loan forecasts for England, Table 6a: 3.985M), counted as England plan-2 borrowers with positive repayments. The 18 October spine at d0f0fafec carries 1.56M at design weights (-61 percent), and the 19 October national file (810315ac2), with the row held out, 1.51M at calibrated weights (-62 percent). Unreachable by reweighting within the stretch bound: student-loan borrower coverage in the frame, a frame-side gap, not a weight question; while bound it pulls the joint solve toward weight concentration (housing benefit alone triples the max/median ratio under grain_equal). Window to the November PR's renewals: correct the spine or re-adjudicate.", "tracking": "microcosm#1278", "approved_by": "juaristi22", - "adjudication": "microcosm#762 (A16, ruling 2026-09-03; receipts R8-R10 in experiments/762-uk-rowwise-candidate-receipts.md); renewed one month on 2026-10-02 by juaristi22 in session (microcosm#1063 stack): the plan-2 borrower coverage gap stays with microcosm#868 and is not corrected by the spine follow-ups; tracking moved to microcosm#1278 on 2026-10-17 by juaristi22 after microcosm#868 closed", - "approved_on": "2026-10-02", - "expires_on": "2026-11-03" + "adjudication": "microcosm#762 (A16, ruling 2026-09-03; receipts R8-R10 in experiments/762-uk-rowwise-candidate-receipts.md); renewed one month on 2026-10-02 by juaristi22 in session (microcosm#1063 stack): the plan-2 borrower coverage gap stays with microcosm#868 and is not corrected by the spine follow-ups; tracking moved to microcosm#1278 on 2026-10-17 by juaristi22 after microcosm#868 closed; renewed on 2026-10-20 to 2026-11-26 by juaristi22 (María's ruling of 2026-10-20 on the pre-Budget PR, microcosm#1278: renew rather than make the row a diagnostic, to the November PR's renewal date). The reason is restated on the AY2024/25 SLC figure the row has bound since microcosm#868 (it quoted AY2025/26), with the 18 October spine's student_loans stage receipt and the 19 October national file.", + "approved_on": "2026-10-20", + "expires_on": "2026-11-26" }, { "name": "dwp.jsa_claimants", @@ -490,9 +490,9 @@ { "name": "obr.vat", "reason": "Level set by an engine factor, not the weights: policyengine-uk's vat divides household VAT by gov.simulation.microdata_vat_coverage (0.38, a constant since January 2023 with no recorded derivation; policyengine-uk#1996), which folds the household share of VAT receipts (about 70 percent per OBR and the HMRC VAT gap estimates) together with the survey's capture of household spending. The frame's raw household VAT is about 46 percent of the OBR receipts, so the row reads +24.7 percent at design weights and +24.1 percent calibrated on microcosm#1121's head calibration (policyengine-uk 2.122.2), against the 25 percent bound. On the 2026-09-30 national problem (1,090 rows, before this stage set any level) the calibration with the four consumption-tax rows bound left total consumption GBP 55bn (5 percent) below a re-solve with the four consumption-tax rows masked together (GBP 982bn against GBP 1,037bn). In that re-solve the other 1,086 rows fitted no worse (98.5 against 98.4 percent within 10 percent, none past 25 percent against one). Measured on every evaluation with tools/diagnose_uk_consumption_taxes.py; rebind when a locked policyengine-uk splits the factor into the published household share and a declared survey capture and the row fits.", - "tracking": "policyengine-uk#1996", + "tracking": "microcosm#1278", "approved_by": "juaristi22", - "adjudication": "María's ruling of 2026-10-08 on the VAT, road fuel and domestic energy plan (microcosm#1113, microcosm#1123 item 3), decision D3: hold the row out until the engine factor is split. The reason's figures were restated on 2026-10-11 after her review of PolicyEngine/microcosm#1167, which found bases mixed. Receipts: experiments/1113-consumption-tax-levels-receipts.md (the masked re-solve of the 2026-09-30 problem and microcosm#1121's head calibration).", + "adjudication": "María's ruling of 2026-10-08 on the VAT, road fuel and domestic energy plan (microcosm#1113, microcosm#1123 item 3), decision D3: hold the row out until the engine factor is split. The reason's figures were restated on 2026-10-11 after her review of PolicyEngine/microcosm#1167, which found bases mixed. Receipts: experiments/1113-consumption-tax-levels-receipts.md (the masked re-solve of the 2026-09-30 problem and microcosm#1121's head calibration). Tracking moved from policyengine-uk#1996 to microcosm#1278 on 2026-10-20: policyengine-uk#2187, released in 2.135.7, closed #1996, and main locks 2.134.4, so the rebind waits on a lock bump past 2.135.7, after the Budget.", "approved_on": "2026-10-08", "expires_on": "2027-01-08" }, diff --git a/packages/microcosm-build/src/microcosm/build/uk/uprating_holds.json b/packages/microcosm-build/src/microcosm/build/uk/uprating_holds.json index fb0459231..8930ece4a 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/uprating_holds.json +++ b/packages/microcosm-build/src/microcosm/build/uk/uprating_holds.json @@ -381,7 +381,7 @@ "slc.borrowers.plan_5_liable" ], "reason": "SLC Student loan forecasts for England, Table 6a: borrowers liable to repay and earning above the repayment threshold in academic year 2024/25, the stock whose reference date falls inside the calibration year 2025, which Chronicle stores under the academic year's opening year 2024. A stock at a date inside the calibration year, not a lagged period; the student_loans stage tops up to the same stock.", - "tracking": "microcosm#868", + "tracking": "microcosm#1278", "approved_by": "juaristi22", "approved_on": "2026-10-16", "status": "approved", diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_measure_simulation.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_measure_simulation.py index c1a502846..53ef91db1 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_measure_simulation.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_measure_simulation.py @@ -731,9 +731,10 @@ def test_packaged_exclusions_load(): # mechanism receipts (#882) and moved to the 2026-12-08 clock; the # savings-interest row moved to the 2026-09-22 concept clock; the two # plan-2 borrower rows were renewed one month on 2026-10-02 (microcosm#1063 - # stack), so nothing remains on the 2026-09-03 clock. The plan-2 rows - # track microcosm#1278 since microcosm#868 closed (María's ruling of - # 2026-10-17). + # stack) and again on 2026-10-20, to the November PR's renewals (María's + # ruling on the pre-Budget PR, microcosm#1278), so nothing remains on the + # 2026-09-03 clock. The plan-2 rows track microcosm#1278 since + # microcosm#868 closed (María's ruling of 2026-10-17). a16_issues = { "ons.savings_interest_income": "microcosm#866", "obr.housing_benefit": "microcosm#867", @@ -742,9 +743,11 @@ def test_packaged_exclusions_load(): "dwp.jsa_claimants": "microcosm#869", } assert [e for e in exclusions if e["approved_on"] == "2026-09-03"] == [] - renewed = [e for e in exclusions if e["approved_on"] == "2026-10-02"] # The two thin UC payment cells that joined the uk-data#452 class on the - # #1063 stack arm retired 2026-10-16: the support floor drops them. + # #1063 stack arm retired 2026-10-16 (the support floor drops them), and + # the plan-2 rows left the 2026-10-02 clock on their 2026-10-20 renewal. + assert [e for e in exclusions if e["approved_on"] == "2026-10-02"] == [] + renewed = [e for e in exclusions if e["approved_on"] == "2026-10-20"] assert sorted(e["name"] for e in renewed) == sorted(_A16_UNREACHABLE_ROWS[:2]) # So did the two bands the engine bump of microcosm#1095 (policyengine-uk # 2.122.2) emptied, the 2026-10-07 entries. @@ -758,7 +761,9 @@ def test_packaged_exclusions_load(): # worse, so they are held out of the objective and measured by the # diagnose tool. The PR that added them closes microcosm#1113, so the # three that tracked it tracked its follow-up issue, microcosm#1207, and - # since that closed into it, microcosm#1278. + # since that closed into it, microcosm#1278. obr.vat tracked + # policyengine-uk#1996 until policyengine-uk#2187 (released in 2.135.7) + # closed it; it tracks microcosm#1278 until a lock bump lets it rebind. consumption_taxes = [e for e in exclusions if e["approved_on"] == "2026-10-08"] assert sorted(e["name"] for e in consumption_taxes) == [ "obr.fuel_duties_cars", @@ -777,11 +782,14 @@ def test_packaged_exclusions_load(): ), entry["name"] trackings = {e["name"]: e["tracking"] for e in consumption_taxes} assert trackings == { - "obr.vat": "policyengine-uk#1996", + "obr.vat": "microcosm#1278", "obr.fuel_duties_cars": "microcosm#1278", "ons.household_electricity_expenditure": "microcosm#1278", "ons.household_gas_expenditure": "microcosm#1278", } + vat = next(e for e in consumption_taxes if e["name"] == "obr.vat") + assert "policyengine-uk#2187" in vat["adjudication"] + assert "lock bump" in vat["adjudication"] # microcosm#1095: the five-or-more children row held out on 2026-10-14 # (María's ruling on microcosm#1271) is no target since 2026-10-16, but a # diagnostic beside the two-child-limit rows, so no exclusion names it and @@ -794,12 +802,27 @@ def test_packaged_exclusions_load(): e["name"] for e in exclusions if e["approved_on"] == "2026-10-14" ) == sorted(_UC_ELEMENT_REGISTER_ROWS) assert "dwp.uc.households_children_5_or_more" not in names + # María's ruling of 2026-10-20 (microcosm#1278): renewed rather than made + # diagnostics, and restated on the academic year 2024/25 stock the rows + # bind since microcosm#868, not the 2025/26 one the reasons quoted. + plan_2_stocks = { + "slc.borrowers.plan_2_liable": "8.94M", + "slc.borrowers.plan_2_above_threshold": "3.985M", + } for entry in renewed: - assert entry["expires_on"] == "2026-11-03", entry["name"] + assert entry["approved_by"] == "juaristi22", entry["name"] + assert entry["expires_on"] == "2026-11-26", entry["name"] assert entry["tracking"] == a16_issues[entry["name"]], entry["name"] assert "A16" in entry["adjudication"], entry["name"] assert "renewed one month on 2026-10-02" in entry["adjudication"], entry["name"] assert "microcosm#1063" in entry["adjudication"], entry["name"] + assert "renewed on 2026-10-20 to 2026-11-26" in entry["adjudication"], entry[ + "name" + ] + assert "AY2024/25" in entry["reason"], entry["name"] + assert "Table 6a" in entry["reason"], entry["name"] + assert plan_2_stocks[entry["name"]] in entry["reason"], entry["name"] + assert "frame-side gap" in entry["reason"], entry["name"] for name in _A16_READJUDICATED_ROWS: entry = next(e for e in exclusions if e["name"] == name) assert entry["approved_on"] == "2026-09-16", name From 6166ea84a09f5dbe93b6eedae611d93c258b1b66 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 13:44:29 +0100 Subject: [PATCH 07/21] Name the per-band council-tax amounts in the Band D parity exclusion (#1278) uk-data#482 (open) adds eight columns, band_A_amount to band_H_amount, to storage/la_council_tax.csv: each English authority's 2026-27 amount for one band from MHCLG Table 9, its Band D amount times the band's statutory ratio. Like Band D they are rates, not additive household controls. local_council_tax_band_d_rate's reason now names them, so the next re-pin does not port them as targets. The register is regenerated with tools/census_uk_data_target_parity.py and its --check passes; this is the one generated file this commit carries. test_uk_data_target_parity pins the named columns. Co-Authored-By: Claude Opus 5.5 --- changelog.d/1278-parity-band-d-per-band-amounts.changed.md | 1 + .../src/microcosm/build/uk/uk_data_target_parity.json | 2 +- .../src/microcosm/build/uk_runtime/data_target_parity.py | 2 +- .../tests/engine_free/uk/test_uk_data_target_parity.py | 5 +++++ 4 files changed, 8 insertions(+), 2 deletions(-) create mode 100644 changelog.d/1278-parity-band-d-per-band-amounts.changed.md diff --git a/changelog.d/1278-parity-band-d-per-band-amounts.changed.md b/changelog.d/1278-parity-band-d-per-band-amounts.changed.md new file mode 100644 index 000000000..95d477d55 --- /dev/null +++ b/changelog.d/1278-parity-band-d-per-band-amounts.changed.md @@ -0,0 +1 @@ +The UK data-target parity register's `local_council_tax_band_d_rate` exclusion now also names the eight per-band amounts, `band_A_amount` to `band_H_amount`, that uk-data#482 adds to `storage/la_council_tax.csv` (microcosm#1278). Each is an English authority's 2026-27 amount for one band (MHCLG Table 9), its Band D amount times the band's statutory ratio. Like Band D, each is a rate, not an additive household control, so none is to be ported as a target. uk-data#482 is open, so the a43e8c5 inventory does not carry it yet; the register is regenerated and a test pins the named columns. diff --git a/packages/microcosm-build/src/microcosm/build/uk/uk_data_target_parity.json b/packages/microcosm-build/src/microcosm/build/uk/uk_data_target_parity.json index a0fabe928..620998eae 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/uk_data_target_parity.json +++ b/packages/microcosm-build/src/microcosm/build/uk/uk_data_target_parity.json @@ -882,7 +882,7 @@ "purpose": "Avoid treating a rate as an additive target.", "verdict_basis": "Keep excluded until a rate-aware non-linear objective exists." }, - "reason": "Band D currency amounts are per-rate, not additive household controls.", + "reason": "Band D currency amounts are per-rate, not additive household controls. So are the eight per-band amounts, band_A_amount to band_H_amount, that uk-data#482 (open, so not in the a43e8c5 inventory) adds to storage/la_council_tax.csv: each English authority's 2026-27 amount for one band (MHCLG Table 9, England only), its Band D amount times the band's statutory ratio. None of the eight is to be ported as a target either.", "status": "reviewed_exclusion" }, { diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/data_target_parity.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/data_target_parity.py index 7dd15d47d..57724d74e 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/data_target_parity.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/data_target_parity.py @@ -443,7 +443,7 @@ def _fence(origin: str, purpose: str, verdict_basis: str) -> dict[str, str]: "concern_id": "local_council_tax_band_d_rate", "status": "reviewed_exclusion", "classification": "non_linear", - "reason": "Band D currency amounts are per-rate, not additive household controls.", + "reason": "Band D currency amounts are per-rate, not additive household controls. So are the eight per-band amounts, band_A_amount to band_H_amount, that uk-data#482 (open, so not in the a43e8c5 inventory) adds to storage/la_council_tax.csv: each English authority's 2026-27 amount for one band (MHCLG Table 9, England only), its Band D amount times the band's statutory ratio. None of the eight is to be ported as a target either.", "evidence": "uk-data targets/sources/la_council_tax.py module doctrine; no Microcosm contract row.", "fence": _fence( "uk-data emitted each authority's Band D amount as a registry target but never as a column of the additive LA loss; Band D entered that loss only as the multiplier in England's housing/council_tax_net proxy (MHCLG taxbase after support times Band D).", diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_data_target_parity.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_data_target_parity.py index d309e2afc..cd77d8c91 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_data_target_parity.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_data_target_parity.py @@ -95,6 +95,11 @@ def covers(concern_id: str) -> list[str]: assert covers("national_ons_lfs_employment") == ["ons_labour_market"] band_d = rows["local_council_tax_band_d_rate"]["fence"]["origin"] assert "housing/council_tax_net" in band_d + # uk-data#482 adds the eight per-band amounts beside Band D; the reason + # names them, so none is ported as a target (microcosm#1278). + band_d_reason = rows["local_council_tax_band_d_rate"]["reason"] + assert "uk-data#482" in band_d_reason + assert "band_A_amount" in band_d_reason and "band_H_amount" in band_d_reason outliers = rows["credibility_local_council_tax_outliers"] assert (outliers["status"], outliers["classification"]) == ( "ported_local_declared", From 24e9e869e4e715bc8ae0fdb4ffab450b80c8d0ba Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 13:40:26 +0100 Subject: [PATCH 08/21] Annualise the State Pension at 52 weeks on the UK spine (#1278, #1095) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit policyengine-uk reads state_pension_reported back to a weekly amount at 52 weeks a year before comparing it with the full rate, so the spine's 365.25/7 put every full-rate pensioner 0.34% above the full rate and made the excess a protected payment. In 2026-27 the full new State Pension is £12,547.60 a year at 52 weeks, below the £12,570 personal allowance, but it read above the allowance. The State Pension alone now annualises at STATE_PENSION_WEEKS_IN_YEAR (52), María's ruling of 2026-10-20 and an exception to #1095's weekly amounts. WEEKS_IN_YEAR and the HMRC replay's SRP leaf keep 365.25/7. The frs_spine stage declares the exception in a new weeks_in_year_exceptions field of its annualize_periodic_amounts operation, in sources.yaml, its source_stages.json projection and the sources schema. Co-Authored-By: Claude Opus 5.5 --- .../1095-state-pension-weeks.changed.md | 1 + .../spec_engine/schema/sources.schema.json | 20 ++++++ .../src/microcosm/build/uk/source_stages.json | 8 ++- .../src/microcosm/build/uk/spec/sources.yaml | 4 ++ .../microcosm/build/uk_runtime/frs_spine.py | 17 +++++ .../tests/engine_free/uk/test_uk_frs_spine.py | 66 +++++++++++++++++++ 6 files changed, 115 insertions(+), 1 deletion(-) create mode 100644 changelog.d/1095-state-pension-weeks.changed.md diff --git a/changelog.d/1095-state-pension-weeks.changed.md b/changelog.d/1095-state-pension-weeks.changed.md new file mode 100644 index 000000000..2ec00bf2f --- /dev/null +++ b/changelog.d/1095-state-pension-weeks.changed.md @@ -0,0 +1 @@ +The UK spine annualises the State Pension at 52 weeks a year, while every other weekly FRS amount keeps 365.25 / 7 (microcosm#1278; María's ruling of 2026-10-20, an exception for the State Pension alone to microcosm#1095's weekly amounts). The State Pension is paid at weekly rates, and policyengine-uk reads `state_pension_reported` back to a weekly amount at 52 weeks before comparing it with the full rate, so at 365.25 / 7 every full-rate pensioner read 0.34% above the full rate and the excess became a spurious protected payment in `additional_state_pension`; in 2026-27 the full new State Pension is £12,547.60 a year at 52 weeks, below the £12,570 personal allowance, but it read above the allowance. `frs_spine.STATE_PENSION_WEEKS_IN_YEAR` (52) sits beside `WEEKS_IN_YEAR`, which is unchanged, and the `frs_spine` stage's `annualize_periodic_amounts` declaration names the exception in `weeks_in_year_exceptions`, a new field of the sources schema. The HMRC replay's State Pension leaf (`srp_regular_code5`) keeps 365.25 / 7. The release input coverage manifest and the H2 spine fixture are regenerated. diff --git a/packages/microcosm-build/src/microcosm/build/spec_engine/schema/sources.schema.json b/packages/microcosm-build/src/microcosm/build/spec_engine/schema/sources.schema.json index afa15376b..5271d6972 100644 --- a/packages/microcosm-build/src/microcosm/build/spec_engine/schema/sources.schema.json +++ b/packages/microcosm-build/src/microcosm/build/spec_engine/schema/sources.schema.json @@ -6208,6 +6208,26 @@ }, "weeks_in_year": { "type": "number" + }, + "weeks_in_year_exceptions": { + "type": "object", + "minProperties": 1, + "additionalProperties": { + "type": "object", + "additionalProperties": false, + "required": [ + "weeks_in_year", + "reason" + ], + "properties": { + "weeks_in_year": { + "type": "number" + }, + "reason": { + "type": "string" + } + } + } } } }, diff --git a/packages/microcosm-build/src/microcosm/build/uk/source_stages.json b/packages/microcosm-build/src/microcosm/build/uk/source_stages.json index 91dfc6bfa..8a2ce6c5f 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/source_stages.json +++ b/packages/microcosm-build/src/microcosm/build/uk/source_stages.json @@ -237,7 +237,13 @@ }, { "kind": "annualize_periodic_amounts", - "weeks_in_year": 52.17857142857143 + "weeks_in_year": 52.17857142857143, + "weeks_in_year_exceptions": { + "state_pension_reported": { + "weeks_in_year": 52, + "reason": "The State Pension is paid at weekly rates, and policyengine-uk reads state_pension_reported back to a weekly amount at 52 weeks a year before comparing it with the full rate, so at 365.25 / 7 a full-rate pensioner would read 0.34% above the full rate and the excess would become a protected payment. An exception for the State Pension alone to microcosm#1095's weekly amounts (María's ruling of 2026-10-20, microcosm#1278)." + } + } }, { "kind": "assign_binary_from_rate", diff --git a/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml b/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml index 9e87edbb4..f62ed4b27 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml +++ b/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml @@ -373,6 +373,10 @@ stages: scope: region, tenure, accommodation, council tax band, benefit-code amount mappings (Scotland's Adult and Child Disability Payment codes 117/118 and 121/122 into the PIP and DLA columns they replace; benefit recovery codes 69 and 70 unmapped); adult HOURTOT care-hours band code to weekly care_hours at the band's lower edge (codes 5, 6, 7 and 10 reach the 35-hour Carer's Allowance line); would_claim_carers_allowance from positive reported Carer's Allowance - kind: annualize_periodic_amounts weeks_in_year: 52.17857142857143 + weeks_in_year_exceptions: + state_pension_reported: + weeks_in_year: 52 + reason: 'The State Pension is paid at weekly rates, and policyengine-uk reads state_pension_reported back to a weekly amount at 52 weeks a year before comparing it with the full rate, so at 365.25 / 7 a full-rate pensioner would read 0.34% above the full rate and the excess would become a protected payment. An exception for the State Pension alone to microcosm#1095''s weekly amounts (María''s ruling of 2026-10-20, microcosm#1278).' - kind: assign_binary_from_rate output: uc_is_in_startup_period draw: uc_is_in_startup_period diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_spine.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_spine.py index 022fc09c3..d4b63d13e 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_spine.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_spine.py @@ -31,6 +31,7 @@ "FRS_SPINE_TABLES", "OUTPUT_COLUMNS", "REGION_MAP", + "STATE_PENSION_WEEKS_IN_YEAR", "TIME_PERIOD", "UC_CAPITAL_UNAVAILABLE", "WEEKS_IN_YEAR", @@ -66,6 +67,13 @@ ) WEEKS_IN_YEAR = 365.25 / 7 +#: The State Pension alone annualises at 52 weeks (María's ruling of 2026-10-20, +#: an exception to microcosm#1095's weekly amounts). It is paid at weekly rates, +#: and policyengine-uk reads ``state_pension_reported`` back to a weekly amount +#: at 52 weeks a year before comparing it with the full rate, so at 365.25 / 7 a +#: full-rate pensioner would read 0.34% above the full rate and the excess +#: would become a protected payment. +STATE_PENSION_WEEKS_IN_YEAR = 52 TIME_PERIOD = "2024" # Raw TOTCAPB4 blanks, nonnumeric values, and negative codes mean that the @@ -981,6 +989,15 @@ def _add_benefits( pe_person["winter_fuel_allowance_reported"] = ( pe_person["winter_fuel_allowance_reported"] / WEEKS_IN_YEAR ) + # The State Pension's weekly amounts, re-summed at its own 52 weeks. + pe_person["state_pension_reported"] = ( + _sum_to_entity( + amount * benefit.isin(BENEFIT_CODES["state_pension"]), + person_id, + person["person_id"], + ) + * STATE_PENSION_WEEKS_IN_YEAR + ) def _add_person_expenses( diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_spine.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_spine.py index dfcf134f6..2d577e145 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_spine.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_spine.py @@ -45,6 +45,7 @@ OWNER_MANAGER_COLUMNS, REGION_MAP, SCOTTISH_WATER_CHARGES_REDUCTION_RECIPIENT_SHARE, + STATE_PENSION_WEEKS_IN_YEAR, UC_CAPITAL_UNAVAILABLE, WEEKS_IN_YEAR, UKFRSSpineStageTransform, @@ -1741,6 +1742,71 @@ def test_scottish_disability_payments_land_in_the_pip_and_dla_columns() -> None: ) +def test_state_pension_alone_annualises_at_52_weeks() -> None: + """policyengine-uk reads the State Pension back at 52 weeks a year. + + At 365.25 / 7 a full-rate pensioner would read above the full rate and the + excess would become a protected payment (María's ruling of 2026-10-20, an + exception to microcosm#1095's weekly amounts). Every other weekly benefit + keeps 365.25 / 7, and the Winter Fuel Payment, already annual, keeps its + amount. + """ + + person = pd.DataFrame({"person_id": [1001, 1002, 1003]}) + pe_person = pd.DataFrame(index=person.index) + benefits = pd.DataFrame( + { + "person_id": [1001, 1002, 1002, 1002, 1003, 1003], + # The 2024-25 full new and basic State Pensions, a second State + # Pension row, Carer's Allowance and the Winter Fuel Payment. + "benefit": [5, 5, 5, 13, 13, 62], + "var2": [0] * 6, + "var3": [0] * 6, + "benamt": [221.20, 169.50, 10.0, 81.90, 81.90, 300.0], + } + ) + + _add_benefits(pe_person, person, benefits) + + assert STATE_PENSION_WEEKS_IN_YEAR == 52 + state_pension = pe_person["state_pension_reported"] + assert state_pension.tolist() == pytest.approx([221.20 * 52, 179.50 * 52, 0.0]) + # Read back at the engine's 52 weeks, the full rate is the full rate. + assert (state_pension / 52).tolist() == pytest.approx([221.20, 179.50, 0.0]) + assert pe_person["carers_allowance_reported"].tolist() == pytest.approx( + [0.0, 81.90 * WEEKS_IN_YEAR, 81.90 * WEEKS_IN_YEAR] + ) + assert pe_person["winter_fuel_allowance_reported"].tolist() == pytest.approx( + [0.0, 0.0, 300.0] + ) + # The 52-week State Pension stays out of the 365.25 / 7 sum. + reported = pe_person.drop( + columns=[ + "state_pension_reported", + "winter_fuel_allowance_reported", + "esa_includes_support_component", + ] + ) + assert reported.to_numpy().sum() == pytest.approx(2 * 81.90 * WEEKS_IN_YEAR) + + +def test_manifest_declares_the_state_pension_weeks_in_year() -> None: + operation = next( + operation + for operation in _manifest_stage().operations + if operation.kind == "annualize_periodic_amounts" + ) + parameters = dict(operation.parameters) + + assert parameters["weeks_in_year"] == WEEKS_IN_YEAR + exceptions = parameters["weeks_in_year_exceptions"] + assert set(exceptions) == {"state_pension_reported"} + assert ( + exceptions["state_pension_reported"]["weeks_in_year"] + == STATE_PENSION_WEEKS_IN_YEAR + ) + + def test_northern_ireland_households_take_the_placeholder_band() -> None: # Northern Ireland pays domestic rates, so a ctband code there is ignored; # elsewhere codes 1-9 are bands A-I and any other code is the placeholder. From 360a2b2205a0210584b4c3e48a6089f91a537116 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 13:44:36 +0100 Subject: [PATCH 09/21] Impute paying households' zero council-tax bills from the cell mean (#1278) From 2024-25 the FRS no longer asks how much council tax a household pays; DWP derives CTANNUAL from the band. Some households that answer yes to CTPaid ("Does anyone living here pay Council Tax?") and report no reduction still carry a zero CTANNUAL, and frs_council_tax kept the zero, leaving England's share of zero bills well above Wales's and Scotland's. Such a household (CTPAID 1, CTREB not 1, CTANNUAL 0) now takes its region, band and single-adult cell mean, as a missing bill does. A non-recipient's zero bill otherwise stays zero: CTPAID 3 (the household does not have to pay) or CTPAID 2 (the council pays, with no reduction reported). frs_council_tax reads CTPAID and refuses a tab without it, and the impute_cell_means declaration's missing rule changes in sources.yaml and source_stages.json together. The spine test fixture and the H2 fixture tool carry CTPAID, and the tool adds one paying household with a zero bill. The bill level waits until after the Budget. Co-Authored-By: Claude Opus 5.5 --- .../1278-council-tax-paying-zeros.fixed.md | 1 + .../src/microcosm/build/uk/source_stages.json | 4 +-- .../src/microcosm/build/uk/spec/sources.yaml | 4 +-- .../build/uk_runtime/frs_council_tax.py | 31 +++++++++++++---- .../engine_free/uk/test_uk_frs_council_tax.py | 34 +++++++++++++++++-- .../tests/engine_free/uk/test_uk_frs_spine.py | 2 ++ tools/graph_uk_spine_fixture.py | 6 +++- 7 files changed, 67 insertions(+), 15 deletions(-) create mode 100644 changelog.d/1278-council-tax-paying-zeros.fixed.md diff --git a/changelog.d/1278-council-tax-paying-zeros.fixed.md b/changelog.d/1278-council-tax-paying-zeros.fixed.md new file mode 100644 index 000000000..5df5f9e83 --- /dev/null +++ b/changelog.d/1278-council-tax-paying-zeros.fixed.md @@ -0,0 +1 @@ +A UK household where someone pays council tax but whose derived bill is zero now takes its cell's mean bill (microcosm#1278). From 2024-25 the FRS no longer asks how much council tax a household pays, and DWP derives `CTANNUAL` from the band, yet some households that answer yes to CTPaid ("Does anyone living here pay Council Tax?") and report no council tax reduction carry a zero `CTANNUAL`, which `frs_council_tax` kept, leaving England's share of zero bills well above Wales's and Scotland's. A household with `CTPAID` 1, `CTREB` not 1 and a zero `CTANNUAL` is now imputed as a missing bill is, from the mean of the positive non-recipient bills in its region, band and single-adult cell. A non-recipient's zero bill otherwise stays zero: the household does not have to pay (`CTPAID` 3), or says the council pays (`CTPAID` 2) without reporting a reduction. Reduction recipients keep their rules, and the bill level, low against published Band D averages, waits until after the Budget. The stage's `impute_cell_means` declaration names the new missing rule and the stage refuses a raw tab without `CTPAID`. The release input coverage manifest and the H2 spine fixture are regenerated. diff --git a/packages/microcosm-build/src/microcosm/build/uk/source_stages.json b/packages/microcosm-build/src/microcosm/build/uk/source_stages.json index 8a2ce6c5f..1b7adef6c 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/source_stages.json +++ b/packages/microcosm-build/src/microcosm/build/uk/source_stages.json @@ -766,7 +766,7 @@ "adulth == 1" ], "donor_filter": "raw ctreb != 1 and ctannual > 0", - "missing": "raw ctannual < 0 or NaN", + "missing": "raw ctannual < 0 or NaN, or ctannual == 0 with ctpaid == 1 and ctreb != 1", "value": "council tax before council tax reduction: CTANNUAL net of the Scottish water and sewerage charges ((CWATAMT1 + CSEWAMT1) x 365.25/7, at 0.65 where CTREB is 1; CWATAMTD where CWATAMT1 is not positive), plus CTREBAMT x 365.25/7 where CTREB is 1 and CTREBAMT > 0; a CTREB 1 household without a positive CTREBAMT takes the larger of its netted CTANNUAL and its cell mean" } ], @@ -776,7 +776,7 @@ "nonnegative_outputs": [ "council_tax" ], - "notes": "Re-reads raw househol.tab because spine council_tax_reported clips missing values. FRS 2024-25 CTANNUAL is the bill after discounts and council tax reduction, and the engine reads council_tax before the reduction, so a household reporting a reduction gets its CTREBAMT added back and the cells pool non-recipients only (uk-data#496/#499, microcosm#1095). Scottish water and sewerage charges are netted before cell means at the shares DWP's CTANNUAL carries (the gross charges in full for non-recipients, 65% for reduction recipients); no-donor cells impute zero. The dead ct_mean.replace(-1, ...) branch is intentionally dropped." + "notes": "Re-reads raw househol.tab because spine council_tax_reported clips missing values. FRS 2024-25 CTANNUAL is the bill after discounts and council tax reduction, and the engine reads council_tax before the reduction, so a household reporting a reduction gets its CTREBAMT added back and the cells pool non-recipients only (uk-data#496/#499, microcosm#1095). Scottish water and sewerage charges are netted before cell means at the shares DWP's CTANNUAL carries (the gross charges in full for non-recipients, 65% for reduction recipients); no-donor cells impute zero. A household where someone pays council tax (CTPAID 1) with no reported reduction and a zero CTANNUAL owes a bill, so it takes its cell mean as a missing bill does (microcosm#1278). The dead ct_mean.replace(-1, ...) branch is intentionally dropped." }, { "stage": "frs_disability", diff --git a/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml b/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml index f62ed4b27..1788e81ac 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml +++ b/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml @@ -761,13 +761,13 @@ stages: - ctband - adulth == 1 donor_filter: raw ctreb != 1 and ctannual > 0 - missing: raw ctannual < 0 or NaN + missing: raw ctannual < 0 or NaN, or ctannual == 0 with ctpaid == 1 and ctreb != 1 value: 'council tax before council tax reduction: CTANNUAL net of the Scottish water and sewerage charges ((CWATAMT1 + CSEWAMT1) x 365.25/7, at 0.65 where CTREB is 1; CWATAMTD where CWATAMT1 is not positive), plus CTREBAMT x 365.25/7 where CTREB is 1 and CTREBAMT > 0; a CTREB 1 household without a positive CTREBAMT takes the larger of its netted CTANNUAL and its cell mean' outputs: - council_tax nonnegative_outputs: - council_tax - notes: Re-reads raw househol.tab because spine council_tax_reported clips missing values. FRS 2024-25 CTANNUAL is the bill after discounts and council tax reduction, and the engine reads council_tax before the reduction, so a household reporting a reduction gets its CTREBAMT added back and the cells pool non-recipients only (uk-data#496/#499, microcosm#1095). Scottish water and sewerage charges are netted before cell means at the shares DWP's CTANNUAL carries (the gross charges in full for non-recipients, 65% for reduction recipients); no-donor cells impute zero. The dead ct_mean.replace(-1, ...) branch is intentionally dropped. + notes: Re-reads raw househol.tab because spine council_tax_reported clips missing values. FRS 2024-25 CTANNUAL is the bill after discounts and council tax reduction, and the engine reads council_tax before the reduction, so a household reporting a reduction gets its CTREBAMT added back and the cells pool non-recipients only (uk-data#496/#499, microcosm#1095). Scottish water and sewerage charges are netted before cell means at the shares DWP's CTANNUAL carries (the gross charges in full for non-recipients, 65% for reduction recipients); no-donor cells impute zero. A household where someone pays council tax (CTPAID 1) with no reported reduction and a zero CTANNUAL owes a bill, so it takes its cell mean as a missing bill does (microcosm#1278). The dead ct_mean.replace(-1, ...) branch is intentionally dropped. - stage: frs_disability survey: Family Resources Survey 2024-25 source: Department for Work and Pensions Family Resources Survey 2024-25, UK Data Service SN 9563, DOI 10.5255/UKDA-SN-9563-1; local licensed 2024_25 tabs. plus policyengine-uk DWP parameters. diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_council_tax.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_council_tax.py index aa74ae1bf..e867e8791 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_council_tax.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_council_tax.py @@ -29,6 +29,7 @@ #: Raw household cells the derivation reads; the pinned tab carries them all. FRS_COUNCIL_TAX_RAW_COLUMNS = ( "ctannual", + "ctpaid", "ctreb", "ctrebamt", "gvtregno", @@ -38,6 +39,10 @@ "csewamt1", "cwatamtd", ) +#: FRS 2024-25 question CTPaid, "Does anyone living here pay Council Tax?": +#: 1 yes, 2 no because the council pays (a rebate), 3 no because the household +#: does not have to. Northern Ireland, which pays domestic rates, is not asked. +FRS_CTPAID_PAYS = 1 #: Share of the gross Scottish water and sewerage charges that DWP's CTANNUAL #: carries for a council tax reduction recipient. Netting 65% of the gross #: charges brings Scottish recipients' bills to the non-recipient cells (ratio @@ -57,7 +62,9 @@ def frs_council_tax_operation_parameters() -> dict[str, Any]: "kind": FRS_COUNCIL_TAX_IMPUTATION_KIND, "cells": ["gvtregno", "ctband", "adulth == 1"], "donor_filter": "raw ctreb != 1 and ctannual > 0", - "missing": "raw ctannual < 0 or NaN", + "missing": ( + "raw ctannual < 0 or NaN, or ctannual == 0 with ctpaid == 1 and ctreb != 1" + ), "value": ( "council tax before council tax reduction: CTANNUAL net of the " "Scottish water and sewerage charges ((CWATAMT1 + CSEWAMT1) x " @@ -161,8 +168,14 @@ def derive_council_tax( cell (ratio 0.99 in England, 1.01 in Wales; uk-data#496/#499, microcosm#1095). A recipient with no positive amount has an unknown reduction and takes the larger of its bill and its cell's mean. Missing - or negative bills take the cell mean. The cells pool non-recipients with - a positive bill only, since recipients' ``CTANNUAL`` is net of their + or negative bills take the cell mean. So does a zero bill where someone + pays council tax (``CTPAID`` 1) and no reduction is reported, since such + a household owes a bill (microcosm#1278); from 2024-25 the FRS no longer + asks the amount, and DWP derives ``CTANNUAL`` from the band. A + non-recipient's zero bill otherwise stays zero: the household does not + have to pay (``CTPAID`` 3), or says the council pays (``CTPAID`` 2) + without reporting a reduction. The cells pool non-recipients with a + positive bill only, since recipients' ``CTANNUAL`` is net of their reduction. Scottish bills carry the water and sewerage charges, which council tax @@ -204,14 +217,18 @@ def positive(column: str) -> pd.Series: tax_only = pd.Series(np.maximum(ctannual - netted, 0), index=aligned.index) donors = ~recipient & (ctannual > 0) - cell_mean = tax_only[donors].groupby( - [gvtregno[donors], ctband[donors], single_adult[donors]], dropna=False - ).mean() + cell_mean = ( + tax_only[donors] + .groupby([gvtregno[donors], ctband[donors], single_adult[donors]], dropna=False) + .mean() + ) keys = pd.MultiIndex.from_arrays([gvtregno, ctband, single_adult]) imputed = pd.Series(keys.map(cell_mean).to_numpy(dtype=float), index=aligned.index) imputed = imputed.fillna(0.0).clip(lower=0) - missing = (ctannual < 0) | ctannual.isna() + pays = number("ctpaid") == FRS_CTPAID_PAYS + paying_zero = (ctannual == 0) & pays & ~recipient + missing = (ctannual < 0) | ctannual.isna() | paying_zero gross = np.where( missing, imputed, diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_council_tax.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_council_tax.py index 4e5ac7e66..517d141b6 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_council_tax.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_council_tax.py @@ -25,6 +25,8 @@ def _raw(**columns) -> pd.DataFrame: rows = len(columns["ctannual"]) defaults = { "household_id": list(range(1, rows + 1)), + # CTPAID 3, the household does not have to pay: a zero bill stays zero. + "ctpaid": [3] * rows, "ctreb": [2] * rows, "ctrebamt": [0.0] * rows, "gvtregno": [1] * rows, @@ -66,6 +68,30 @@ def test_council_tax_imputes_raw_missing_from_raw_cells() -> None: assert result.loc[6] == 0.0 +def test_paying_household_with_a_zero_bill_takes_the_cell_mean() -> None: + raw = _raw( + gvtregno=[1, 1, 1, 1, 1, 1, 1, 13, 2], + ctannual=[1200.0, 1400.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + ctpaid=[1, 1, 1, 1, 2, 3, np.nan, np.nan, 1], + ctreb=[2, 2, 2, 1, 2, 2, 2, 2, 2], + ctrebamt=[0.0, 0.0, 0.0, 20.0, 0.0, 0.0, 0.0, 0.0, 0.0], + ) + + result = _derive(raw) + + # Someone pays and no reduction is reported, so the household owes a bill. + assert result.loc[3] == pytest.approx(1300.0) + # A reported reduction is added back, as for any recipient. + assert result.loc[4] == pytest.approx(20.0 * WEEKS_IN_YEAR) + # Council-paid, exempt, blank and unasked (Northern Ireland) zeros stay zero. + assert result.loc[5] == 0.0 + assert result.loc[6] == 0.0 + assert result.loc[7] == 0.0 + assert result.loc[8] == 0.0 + # No positive non-recipient bill in the cell: nothing to impute from. + assert result.loc[9] == 0.0 + + def test_reported_reduction_is_added_back_to_the_bill() -> None: raw = _raw( ctannual=[0.0, 500.0, 1300.0], @@ -162,10 +188,11 @@ def test_bills_outside_scotland_keep_ctannual_or_add_the_reduction() -> None: assert (result[recipient] >= ctannual[recipient] - 1e-9).all() -def test_missing_raw_cells_refuse() -> None: - raw = _raw(ctannual=[100.0]).drop(columns="ctreb") +@pytest.mark.parametrize("column", ["ctreb", "ctpaid"]) +def test_missing_raw_cells_refuse(column) -> None: + raw = _raw(ctannual=[100.0]).drop(columns=column) - with pytest.raises(KeyError, match="ctreb"): + with pytest.raises(KeyError, match=column): _derive(raw) @@ -184,6 +211,7 @@ def test_committed_manifest_declares_the_implemented_rule() -> None: ("parameter", "value"), [ ("donor_filter", "raw ctannual > 0"), + ("missing", "raw ctannual < 0 or NaN"), ("value", "Scottish-water-netted CTANNUAL"), ("cells", ["gvtregno", "ctband"]), ], diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_spine.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_spine.py index 2d577e145..b272b34ef 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_spine.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_spine.py @@ -193,6 +193,8 @@ def _fixture_tables() -> dict[str, list[dict[str, object]]]: "TYPEACC": 1, "BEDROOM6": 3, "CTANNUAL": 1000.0, + # Someone in the household pays council tax (CTPAID 1). + "CTPAID": 1, "CTBAND": 4, "CTDISC": 2, "CT25D50D": "", diff --git a/tools/graph_uk_spine_fixture.py b/tools/graph_uk_spine_fixture.py index ebf3cf29b..00fe2a760 100644 --- a/tools/graph_uk_spine_fixture.py +++ b/tools/graph_uk_spine_fixture.py @@ -373,7 +373,11 @@ def _frs_tables() -> dict[str, pd.DataFrame]: "PTENTYP2": 5 + household_id % 2, "TYPEACC": 1 + household_id % 4, "BEDROOM6": 1 + household_id % 4, - "CTANNUAL": 900.0 + household_id * 10.0, + # Household 12 pays council tax (CTPAID 1) and reports no + # reduction, but its derived bill is zero, so it takes its + # cell's mean (microcosm#1278). + "CTANNUAL": 0.0 if household_id == 12 else 900.0 + household_id * 10.0, + "CTPAID": 1, "CTBAND": 1 + household_id % 7, "CTDISC": 1 if household_id % 3 == 0 else 2, "CT25D50D": ( From 16107a839b6830e5e8d9f7aef68b85f8216980b0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 13:56:52 +0100 Subject: [PATCH 10/21] Count ALLPAY2 once, as miscellaneous income (#1320, uk-data#627) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit ALLPAY2, the FRS 2024-25 "Amount of allowance: organisation", is one amount, but the spine summed it into both miscellaneous_income and private_transfer_income, so every total adding the two counted it twice. It stays in miscellaneous_income only (María's ruling of 2026-10-20); private_transfer_income sums APAMT, APDAMT, PAREAMT, ALLPAY3 and ALLPAY4. A new test copies a fixture household once per field of its adult, child, household, odd-job and pension rows, raises that field in its copy, and refuses any field that moves more than one person income column; on the old lists it names ALLPAY2. The spousal-maintenance split in #1320 waits on uk-data#627. Co-Authored-By: Claude Opus 5.5 --- changelog.d/1320-allpay2-once.fixed.md | 1 + .../microcosm/build/uk_runtime/frs_spine.py | 5 +- .../tests/engine_free/uk/test_uk_frs_spine.py | 96 ++++++++++++++++++- 3 files changed, 100 insertions(+), 2 deletions(-) create mode 100644 changelog.d/1320-allpay2-once.fixed.md diff --git a/changelog.d/1320-allpay2-once.fixed.md b/changelog.d/1320-allpay2-once.fixed.md new file mode 100644 index 000000000..35074294c --- /dev/null +++ b/changelog.d/1320-allpay2-once.fixed.md @@ -0,0 +1 @@ +`ALLPAY2`, the FRS 2024-25 "Amount of allowance: organisation", now counts once on the UK spine, in `miscellaneous_income` (microcosm#1320, uk-data#627; María's ruling of 2026-10-20). It was summed into both `miscellaneous_income` and `private_transfer_income`, so every total that adds the two counted an organisation's allowance twice; `private_transfer_income` now sums `APAMT`, `APDAMT`, `PAREAMT`, `ALLPAY3` and `ALLPAY4`. A new test raises each field of an FRS household's adult, child, household, odd-job and pension rows in turn and refuses any field that moves more than one person income column. The spousal-maintenance split #1320 also raises waits on uk-data#627. The H2 spine fixture is regenerated. diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_spine.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_spine.py index d4b63d13e..b7100e275 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_spine.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_spine.py @@ -792,6 +792,9 @@ def _add_person_income( pe_person["maintenance_income"] = ( maintenance_to_self + _positive(person, "mntamt2").to_numpy() ) * WEEKS_IN_YEAR + # ALLPAY2, "Amount of allowance: organisation", is one amount, so it is + # miscellaneous income alone and not also a private transfer + # (microcosm#1320, uk-data#627; María's ruling of 2026-10-20). pe_person["miscellaneous_income"] = ( _odd_job_income(person, oddjob) + _sum_positive_fields( @@ -800,7 +803,7 @@ def _add_person_income( ) * WEEKS_IN_YEAR pe_person["private_transfer_income"] = ( _sum_positive_fields( - person, ("apamt", "apdamt", "pareamt", "allpay2", "allpay3", "allpay4") + person, ("apamt", "apdamt", "pareamt", "allpay3", "allpay4") ) * WEEKS_IN_YEAR ) diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_spine.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_spine.py index b272b34ef..e017b349e 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_spine.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_frs_spine.py @@ -41,6 +41,7 @@ frs_relationships_operation_parameters, ) from microcosm.build.uk_runtime.frs_spine import ( + BENEFIT_CODES, FRS_SPINE_TABLES, OWNER_MANAGER_COLUMNS, REGION_MAP, @@ -1178,8 +1179,11 @@ def test_direct_person_mapping_values_are_ported(tmp_path: Path) -> None: assert adult["rent_paid_as_lodger"] == pytest.approx(WEEKS_IN_YEAR) assert adult["rent_paid_as_boarder"] == 0 assert adult["maintenance_income"] == pytest.approx(3 * WEEKS_IN_YEAR) + # Odd jobs 4, ALLPAY2 6, ROYYR2-4 3 + 4 + 5, CHAMTERN 9 and CHAMTTST 10. assert adult["miscellaneous_income"] == pytest.approx(41 * WEEKS_IN_YEAR) - assert adult["private_transfer_income"] == pytest.approx(57 * WEEKS_IN_YEAR) + # APAMT 11, APDAMT 12, PAREAMT 13, ALLPAY3 7 and ALLPAY4 8: ALLPAY2 is + # miscellaneous income alone (#1320). + assert adult["private_transfer_income"] == pytest.approx(51 * WEEKS_IN_YEAR) assert adult["lump_sum_income"] == pytest.approx(100) assert adult["student_loan_repayments"] == pytest.approx(2 * WEEKS_IN_YEAR) assert adult["statutory_sick_pay"] == pytest.approx(WEEKS_IN_YEAR) @@ -1204,6 +1208,96 @@ def test_direct_person_mapping_values_are_ported(tmp_path: Path) -> None: assert adult["salary_sacrifice_asked"] == 1 +#: The spine's person income columns (#1320, uk-data#627). +#: tax_free_savings_income is not one: it is the ISA part of +#: savings_interest_income. +_PERSON_INCOME_COLUMNS = ( + "employment_income", + "self_employment_income", + "private_pension_income", + "savings_interest_income", + "dividend_income", + "property_income", + "maintenance_income", + "miscellaneous_income", + "private_transfer_income", + "lump_sum_income", + "statutory_sick_pay", + "statutory_maternity_pay", + "statutory_paternity_pay", + "student_loans", + "access_fund", + "education_grants", + "healthy_start_vouchers", + "free_school_breakfasts", + "free_school_fruit_veg", + "free_school_meals", + "council_tax_benefit_reported", + *(f"{name}_reported" for name in BENEFIT_CODES), + "jsa_contrib_reported", + "jsa_income_reported", + "esa_contrib_reported", + "esa_income_reported", + "bsp_reported", +) + + +def test_no_frs_field_feeds_two_income_columns(tmp_path: Path) -> None: + """Each FRS field adds to one person income column at most (#1320). + + ALLPAY2, "Amount of allowance: organisation", was counted in both + miscellaneous_income and private_transfer_income (uk-data#627). Household + 1 is copied once for each field of its adult, child, household, odd-job + and pension rows, with that field raised by one in its copy, and each + copy's people are compared with an unchanged copy's. The benefits and + accounts tabs route one amount column by a row code, and the other tabs + carry no person income, so they are not varied. + """ + + tables = _fixture_tables() + fields = [ + (table, field) + for table in ("adult", "child", "househol", "oddjob", "pension") + for field in dict.fromkeys( + field for row in tables[table] if row["SERNUM"] == 1 for field in row + ) + if field not in {"SERNUM", "BENUNIT", "PERSON"} + ] + copies: dict[str, list[dict[str, object]]] = {table: [] for table in tables} + for household, varied in enumerate([None, *fields], start=1): + for table, rows in tables.items(): + for row in rows: + if row["SERNUM"] != 1: + continue + copy = {**row, "SERNUM": household} + if varied is not None and varied[0] == table: + value = pd.to_numeric(copy[varied[1]], errors="coerce") + copy[varied[1]] = float(np.nan_to_num(value)) + 1.0 + copies[table].append(copy) + stage = _write_fixture(tmp_path, copies) + + person = build_uk_frs_spine_frame(tmp_path, stage=stage).table("person") + incomes = person.set_index("person_id")[list(_PERSON_INCOME_COLUMNS)] + moved: dict[tuple[str, str], set[str]] = {} + for household, varied in enumerate(fields, start=2): + for number in (1, 2): + changed = ~np.isclose( + incomes.loc[household * 1000 + number], incomes.loc[1000 + number] + ) + moved.setdefault(varied, set()).update(incomes.columns[changed]) + + assert { + field: columns for field, columns in moved.items() if len(columns) > 1 + } == {} + # The comparison sees a field's own column. + assert moved[("adult", "ALLPAY2")] == {"miscellaneous_income"} + assert moved[("adult", "APAMT")] == {"private_transfer_income"} + assert moved[("adult", "INEARNS")] == {"employment_income"} + assert moved[("househol", "CTREBAMT")] == {"council_tax_benefit_reported"} + assert moved[("oddjob", "OJAMT")] == {"miscellaneous_income"} + assert moved[("pension", "PENPAY")] == {"private_pension_income"} + + @pytest.mark.parametrize("seed", range(8)) def test_property_income_matches_a_merge_of_the_raw_tabs( tmp_path: Path, seed: int From 4f361e5ada191d23088fbee6036d501fc0f80a54 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 14:00:08 +0100 Subject: [PATCH 11/21] Draw Carer's Allowance claims for carers over the earnings limit (#1319) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit would_claim_carers_allowance followed reported receipt (#882), and a carer above the earnings limit cannot report the allowance, so no reform that widens it reached a new claimant. That includes the April 2025 rise of the limit from £151 to £196 a week, which the Independent Review of Carer's Allowance Overpayments (July 2025, chapter 7) estimates brought about 61,000 more people into eligibility. A new ungated spine stage, carers_allowance_take_up, runs after child_benefit_take_up and before uc_deduction_attributes. It keeps reported receipt as the anchor (frs_spine sets it, the SPI income chain refreshes it on the rows it redraws) and refuses a frame whose flag no longer follows it. One consumed-only engine materialization at the survey year reads is_gainfully_employed_for_carers_allowance on the frame's own values, at the 2024-25 limit of £151 (the engine reads a year's parameters at 30 April); a frame at any other period is refused. A person outside Scotland whose care_hours reach the engine's gov.dwp.carers_allowance.min_hours, who reports no allowance and whom that test holds gainfully employed claims at the take-up contract's new carers_allowance_newly_entitled rate, on a uniform keyed on person_id (seed 0, salt would_claim_carers_allowance): would_claim = reported OR (eligible AND u < rate). Reporters stay true, carers under the limit who report no allowance stay false, and Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test. The stage uses the existing assign_binary_from_rate operation, so the schema and the operation vocabulary do not move. The earnings test is read before salary_sacrifice moves some contributors' pension amounts out of their pay, which lowers the earnings the engine tests by about half the amount moved. A drawn carer whom that conversion takes under the survey year's limit keeps the flag, although the released file then shows them entitled and not reporting. Reading the converted pay would need the stage after salary_sacrifice, with a lineage-keyed draw for the CGT clones; the module and the notes say so. The rate, 0.6 with a sensitivity of 0.45 to 0.75, is María's ruling of 2026-10-20. No published take-up rate exists for newly entitled carers, so the contract entry is frozen_by_adjudication, with the earnings-limit back-test against the 61,000 as its follow-up. The receipt bands support on distinct household_source_id, gives a weighted total only where ten or more sources carry it, and gives the realised share only where neither side rests on one to nine. The stage has no health gate, and the flag stays out of the terminal take-up signal gate. As for the Pension Credit and Child Benefit redraws, the graph opens an isolation boundary before the rewrite and declares an open input surface. The kernel tables, the spine registration, the stage JSON, the stale notes on the anchor and in the policyengine-uk concept mapping, the roster pins (45 to 46 stages) and the H2 fixture tool move with it. The fixture gains 35-hour carers on both sides of the limit, in Scotland and outside it, and Carer's Allowance rows, so the stage draws there. The coverage manifest and the H2 fixture are left for the pin pass to regenerate. Co-Authored-By: Claude Opus 5.5 --- .../1319-carers-allowance-take-up.added.md | 1 + docs/uk-full-build-graph.md | 4 +- .../src/microcosm/build/uk/source_stages.json | 39 +- .../src/microcosm/build/uk/spec/sources.yaml | 30 +- .../microcosm/build/uk/take_up_contract.json | 21 + .../uk_runtime/carers_allowance_take_up.py | 470 +++++++++++++++ .../src/microcosm/build/uk_runtime/graph.py | 14 +- .../build/uk_runtime/graph_kernels.py | 10 + .../microcosm/build/uk_runtime/spi_income.py | 6 +- .../microcosm/build/uk_runtime/spine_build.py | 11 + .../uk/test_uk_carers_allowance_take_up.py | 203 +++++++ .../engine_free/shared/test_country_spec.py | 5 +- .../uk/test_uk_carers_allowance_take_up.py | 564 ++++++++++++++++++ .../tests/engine_free/uk/test_uk_graph.py | 6 +- .../engine_free/uk/test_uk_source_stages.py | 8 + .../uk/test_uk_spine_acceptance_receipt.py | 4 + .../uk/test_uk_take_up_contract.py | 3 + .../uk/test_uk_uc_capital_coherence.py | 9 +- .../adapters/policyengine_uk_concepts.py | 6 +- tools/graph_uk_spine_fixture.py | 33 +- 20 files changed, 1425 insertions(+), 22 deletions(-) create mode 100644 changelog.d/1319-carers-allowance-take-up.added.md create mode 100644 packages/microcosm-build/src/microcosm/build/uk_runtime/carers_allowance_take_up.py create mode 100644 packages/microcosm-build/tests/engine/uk/test_uk_carers_allowance_take_up.py create mode 100644 packages/microcosm-build/tests/engine_free/uk/test_uk_carers_allowance_take_up.py diff --git a/changelog.d/1319-carers-allowance-take-up.added.md b/changelog.d/1319-carers-allowance-take-up.added.md new file mode 100644 index 000000000..557ca71b7 --- /dev/null +++ b/changelog.d/1319-carers-allowance-take-up.added.md @@ -0,0 +1 @@ +The UK spine now draws `would_claim_carers_allowance` for the carers the Carer's Allowance earnings limit keeps out (microcosm#1319). The flag followed reported receipt (#882), and a carer above the limit cannot report the allowance, so no reform that widens it reached a new claimant; the Independent Review of Carer's Allowance Overpayments (July 2025) estimates that the April 2025 rise of the limit from £151 to £196 a week brought about 61,000 more people into eligibility. A new stage, `carers_allowance_take_up`, runs after `child_benefit_take_up` and keeps reported receipt as its anchor. One engine materialization at the survey year reads `is_gainfully_employed_for_carers_allowance` at the 2024-25 limit, and a person outside Scotland whose `care_hours` reach the engine's hours condition (35 a week), who reports no allowance and whom that test holds gainfully employed claims at the take-up contract's new `carers_allowance_newly_entitled` rate, 0.6 (María's ruling of 2026-10-20, sensitivity 0.45 to 0.75), on an identity-keyed uniform. Reporters stay true, and carers under the limit who report no allowance stay false. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test. The receipt bands support on distinct source households, the stage has no health gate, and the roster moves from 45 to 46 stages. diff --git a/docs/uk-full-build-graph.md b/docs/uk-full-build-graph.md index 2f091203b..ed179cdca 100644 --- a/docs/uk-full-build-graph.md +++ b/docs/uk-full-build-graph.md @@ -66,11 +66,11 @@ For smaller outputs, add `--dataset-households 150000` to use the common informe ## Graph owners and shared contracts -The spine graph is the 45-stage source roster declared by the UK spec, built by `uk_runtime.spine_build` (the spine tool moved into the package; `tools/build_uk_frs_spine.py` is a six-line shim over it). The superseded `frs_hmrc_retained_leaves` and `hmrc_spi_income` stages and the `UK_SPINE_EXCLUSIONS` list that hid them are removed; the active HMRC path is `frs_hmrc_spine_leaves`, `spi_support_channel`, `spi_income_band_donors` and `hmrc_spi_income_spine`, and the FRS HMRC leaf columns come from `uk_runtime.frs_hmrc_source`. The spine's assembled and transferred gate batteries are graph nodes (`uk_runtime.graph_evidence`); stage evidence and fit-weight records are read back from the content store through the shared `stage_evidence` artifact rather than from in-memory collectors; the HMRC replay sidecar is rebuilt from the SPI stage's checkpoint metadata; the spine sidecar records the operation inventory and the graph manifest, and the graph manifest is saved as `spine.graph.json` under the checkpoint root. +The spine graph is the 46-stage source roster declared by the UK spec, built by `uk_runtime.spine_build` (the spine tool moved into the package; `tools/build_uk_frs_spine.py` is a six-line shim over it). The superseded `frs_hmrc_retained_leaves` and `hmrc_spi_income` stages and the `UK_SPINE_EXCLUSIONS` list that hid them are removed; the active HMRC path is `frs_hmrc_spine_leaves`, `spi_support_channel`, `spi_income_band_donors` and `hmrc_spi_income_spine`, and the FRS HMRC leaf columns come from `uk_runtime.frs_hmrc_source`. The spine's assembled and transferred gate batteries are graph nodes (`uk_runtime.graph_evidence`); stage evidence and fit-weight records are read back from the content store through the shared `stage_evidence` artifact rather than from in-memory collectors; the HMRC replay sidecar is rebuilt from the SPI stage's checkpoint metadata; the spine sidecar records the operation inventory and the graph manifest, and the graph manifest is saved as `spine.graph.json` under the checkpoint root. | Operation | Graph owner | | --- | --- | -| Raw FRS and donor preparation, enrichment, support channels | The 45 UK spine stage nodes and their declared composite operations | +| Raw FRS and donor preparation, enrichment, support channels | The 46 UK spine stage nodes and their declared composite operations | | Assembled and transferred spine gates | `spine.gates.assembled`, `spine.gates.transferred` | | Bound checkpoint admission | `uk.full.spine_checkpoint`, when resuming a saved spine | | Pool sample and mass normalization | `uk.full.sample`, `uk.full.normalize` | diff --git a/packages/microcosm-build/src/microcosm/build/uk/source_stages.json b/packages/microcosm-build/src/microcosm/build/uk/source_stages.json index 1b7adef6c..cb4556e02 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/source_stages.json +++ b/packages/microcosm-build/src/microcosm/build/uk/source_stages.json @@ -233,7 +233,7 @@ }, { "kind": "map_coded_amounts", - "scope": "region, tenure, accommodation, council tax band, benefit-code amount mappings (Scotland's Adult and Child Disability Payment codes 117/118 and 121/122 into the PIP and DLA columns they replace; benefit recovery codes 69 and 70 unmapped); adult HOURTOT care-hours band code to weekly care_hours at the band's lower edge (codes 5, 6, 7 and 10 reach the 35-hour Carer's Allowance line); would_claim_carers_allowance from positive reported Carer's Allowance" + "scope": "region, tenure, accommodation, council tax band, benefit-code amount mappings (Scotland's Adult and Child Disability Payment codes 117/118 and 121/122 into the PIP and DLA columns they replace; benefit recovery codes 69 and 70 unmapped); adult HOURTOT care-hours band code to weekly care_hours at the band's lower edge (codes 5, 6, 7 and 10 reach the 35-hour Carer's Allowance line); would_claim_carers_allowance from positive reported Carer's Allowance, the anchor carers_allowance_take_up opens to carers over the earnings limit (microcosm#1319)" }, { "kind": "annualize_periodic_amounts", @@ -401,7 +401,7 @@ "external_child_payments", "care_hours" ], - "notes": "Root E2 spine assembly. It carries direct raw mappings only; education-grant aggregate and council-tax reported fields remain raw carriers for E3. Benefit take-up, BRMA/LHA assignment, stochastic flags, and imputations are intentionally absent from this stage, except two identity-keyed draws. One is the UC start-up claim recency (uk-data#527). The other is each person's months_since_last_birthday, which policyengine-uk reads to place a date of birth (the two-child limit, the State Pension scheme, the Pension Credit qualifying age). Each single year of age and sex is spread evenly over the year at the FRS weights, in an order set by a draw on the person's stable id, as the engine spreads it when the column is unset, and the column is stored so every later engine read, the calibration's and the release's included, takes the same months whatever weights or identifiers the file carries (microcosm#1095). The UC start-up period needs the raw claim, interview and job dates only this stage reads, so a UC record without a linked claim date takes its claim recency from a benefit-unit-keyed draw at the linked share. The 2024-25 househol.tab is not sernum-ordered; the declared household sort guards stable identity. care_hours carries the FRS banded care-hours code as weekly hours (lower band edge) and would_claim_carers_allowance follows reported receipt, so the engine keeps Carer's Allowance on reported claimants while the hours qualify carers for the Universal Credit carer element (#882). SEINCAM2, the self-employment income the respondent gives, splits by its sign (uk-data#528), so profits go to self_employment_income and losses to trading_loss as a positive amount, the two inputs policyengine-uk reads from 2.131.0 (pe-uk#2085). The engine uprates trading_loss into each projected year as it does self_employment_income, so a loss persists like a profit; the engine documents that a one-off loss would be set to zero in later years, which a one-year survey cannot tell apart. Six of policyengine-uk's eleven owned-company inputs (pe-uk#1965) come from the FRS job tab (microcosm#1095). A director (DIRECTOR 1 or NATURE 1) who owns at least half of the company (DIRPERC 1 to 3, the ruling of 2026-10-16) stands as its sole owner or partner and works in it. The company is their main employment when the job is their first (JOBTYPE 1); it carries on a property business when the main job's SIC division is 68 and a trade otherwise, and its income share is the dividends the job records (DIVIDEND, after tax), the part of the company's profit the survey sees. A company held in another job carries on neither, since ADULT.SIC codes the main job only, which leaves the engine's company-owner rules off for it. The stocks and the intermediaries inputs keep the engine's defaults." + "notes": "Root E2 spine assembly. It carries direct raw mappings only; education-grant aggregate and council-tax reported fields remain raw carriers for E3. Benefit take-up, BRMA/LHA assignment, stochastic flags, and imputations are intentionally absent from this stage, except two identity-keyed draws. One is the UC start-up claim recency (uk-data#527). The other is each person's months_since_last_birthday, which policyengine-uk reads to place a date of birth (the two-child limit, the State Pension scheme, the Pension Credit qualifying age). Each single year of age and sex is spread evenly over the year at the FRS weights, in an order set by a draw on the person's stable id, as the engine spreads it when the column is unset, and the column is stored so every later engine read, the calibration's and the release's included, takes the same months whatever weights or identifiers the file carries (microcosm#1095). The UC start-up period needs the raw claim, interview and job dates only this stage reads, so a UC record without a linked claim date takes its claim recency from a benefit-unit-keyed draw at the linked share. The 2024-25 househol.tab is not sernum-ordered; the declared household sort guards stable identity. care_hours carries the FRS banded care-hours code as weekly hours (lower band edge) and would_claim_carers_allowance follows reported receipt, so the engine keeps Carer's Allowance on reported claimants while the hours qualify carers for the Universal Credit carer element (#882); after the SPI income chain, carers_allowance_take_up opens the flag to carers the earnings limit alone keeps from the allowance (microcosm#1319). SEINCAM2, the self-employment income the respondent gives, splits by its sign (uk-data#528), so profits go to self_employment_income and losses to trading_loss as a positive amount, the two inputs policyengine-uk reads from 2.131.0 (pe-uk#2085). The engine uprates trading_loss into each projected year as it does self_employment_income, so a loss persists like a profit; the engine documents that a one-off loss would be set to zero in later years, which a one-year survey cannot tell apart. Six of policyengine-uk's eleven owned-company inputs (pe-uk#1965) come from the FRS job tab (microcosm#1095). A director (DIRECTOR 1 or NATURE 1) who owns at least half of the company (DIRPERC 1 to 3, the ruling of 2026-10-16) stands as its sole owner or partner and works in it. The company is their main employment when the job is their first (JOBTYPE 1); it carries on a property business when the main job's SIC division is 68 and a trade otherwise, and its income share is the dividends the job records (DIVIDEND, after tax), the part of the company's profit the survey sees. A company held in another job carries on neither, since ADULT.SIC codes the main job only, which leaves the engine's company-owner rules off for it. The stocks and the intermediaries inputs keep the engine's defaults." }, { "stage": "age_tail", @@ -5247,7 +5247,7 @@ "receives_benefits_in_own_right", "would_claim_uc" ], - "notes": "Runs on SPI-channel rows after uc_reporter_redraw, the last writer of Universal Credit reports, and before uc_capital_coherence and the Pension Credit and Child Benefit take-up stages (microcosm#1095, uk-data#514). The stage-2 forests of hmrc_spi_income_spine re-impute each SPI adult's benefit reports from age, gender, region and the new incomes, with nothing of the benefit unit's entitlement or claim history. This stage zeroes the SPI rows' contributory and income-based JSA, income-related ESA, Income Support, Working and Child Tax Credit, Severe Disablement Allowance and Sure Start Maternity Grant reports, whose award needs an existing legacy claim, an out-of-work test, or a claim the copied household's new incomes cannot carry (policyengine-uk pays income-related ESA as reported behind a capital test alone); restores Industrial Injuries Disablement Benefit, the Armed Forces Compensation Scheme and bereavement support from the FRS twin (person_source_id), since they follow an injury, service or a death; re-derives the disability flags (the categories, which read only AA, DLA and PIP, are asserted unchanged) and receives_benefits_in_own_right from the final reports; and redraws would_claim_uc for SPI benefit units as frs_take_up draws it for FRS units: a unit with a Universal Credit reporter claims, and the other units in frs_take_up's Universal Credit population (a UC claimant or partner aged 18 to under Pension Credit qualifying age) claim as the residual of the contract's universal_credit rate on draws keyed on the SPI unit's own identity. Contributory ESA, PIP, DLA, AA, Carer's Allowance, State Pension and Winter Fuel Payment keep their draws, and FRS rows are never modified; contributory ESA is open to new claims and not income-tested, and the incapacity it needs follows the person, whose health and disability reports the SPI copy keeps." + "notes": "Runs on SPI-channel rows after uc_reporter_redraw, the last writer of Universal Credit reports, and before uc_capital_coherence and the Pension Credit, Child Benefit and Carer's Allowance take-up stages (microcosm#1095, uk-data#514). The stage-2 forests of hmrc_spi_income_spine re-impute each SPI adult's benefit reports from age, gender, region and the new incomes, with nothing of the benefit unit's entitlement or claim history. This stage zeroes the SPI rows' contributory and income-based JSA, income-related ESA, Income Support, Working and Child Tax Credit, Severe Disablement Allowance and Sure Start Maternity Grant reports, whose award needs an existing legacy claim, an out-of-work test, or a claim the copied household's new incomes cannot carry (policyengine-uk pays income-related ESA as reported behind a capital test alone); restores Industrial Injuries Disablement Benefit, the Armed Forces Compensation Scheme and bereavement support from the FRS twin (person_source_id), since they follow an injury, service or a death; re-derives the disability flags (the categories, which read only AA, DLA and PIP, are asserted unchanged) and receives_benefits_in_own_right from the final reports; and redraws would_claim_uc for SPI benefit units as frs_take_up draws it for FRS units: a unit with a Universal Credit reporter claims, and the other units in frs_take_up's Universal Credit population (a UC claimant or partner aged 18 to under Pension Credit qualifying age) claim as the residual of the contract's universal_credit rate on draws keyed on the SPI unit's own identity. Contributory ESA, PIP, DLA, AA, Carer's Allowance, State Pension and Winter Fuel Payment keep their draws (carers_allowance_take_up later opens the Carer's Allowance claim flag to carers over the earnings limit, microcosm#1319), and FRS rows are never modified; contributory ESA is open to new claims and not income-tested, and the incapacity it needs follows the person, whose health and disability reports the SPI copy keeps." }, { "stage": "uc_capital_coherence", @@ -5516,6 +5516,39 @@ ], "notes": "Runs after the SPI income chain, UC capital coherence and the Pension Credit redraw, before CGT cloning (microcosm#1063). frs_take_up draws would_claim_child_benefit early at one flat rate over every benefit unit with the reporters on top, and child_benefit_opts_out at a flat rate whatever the unit's income; this stage redraws both. One temporary engine materialization gives each person's eligibility as a child or qualifying young person and each person's adjusted net income (consumed only). A family claims for all its children or none, so the draw is by family, keyed on the age of its eldest eligible child: a reporter claims, and the other families claim at rates solved from the eldest age down so that the claimed share of the eligible children of each single year of age is HMRC's published one (Table 15, May 2025, opted-out families included), weighted at the stage's household weights. The published opted-out share of registered families (August 2025) is drawn among claiming non-reporters, fully charged first. Opt-out-aware models restrict both the full-charge and taper pools to a positive charge fraction at least the installed opt_out_charge_share. With the default share of one, only fully charged families can opt out; an insufficient pool is recorded as a shortfall instead of selecting paid taper families. Legacy models retain the original full-charge pool and taper fallback. Models exposing gov.hmrc.child_benefit.opt_out_charge_share (policyengine-uk#2140) receive registered claims, including opted-out families, in would_claim_child_benefit and the separate opt-out in child_benefit_opts_out. Older models receive the legacy claims-and-not-opted-out payment flag because they ignore the opt-out input. Stage evidence records the selected encoding, evaluated opt-out charge share and engine parameter source. The in-payment audit counts claims-and-not-opted-out in the draw, with new candidates aligned to baseline payment suppression; it is not a fresh model run or population calibration evidence. A benefit unit with no eligible child keeps its early draw and is never opted out." }, + { + "stage": "carers_allowance_take_up", + "survey": "Family Resources Survey 2024-25", + "source": "Independent Review of Carer's Allowance Overpayments (July 2025), chapter 7, and DWP benefit statistics, through the UK take-up contract's carers_allowance_newly_entitled rate, applied to PolicyEngine-UK's Carer's Allowance earnings test after the SPI income chain.", + "grain": "person", + "artifacts": [], + "operations": [ + { + "kind": "materialize_rules_engine_predictors", + "predictors": [ + "is_gainfully_employed_for_carers_allowance" + ], + "consumed_only": true, + "year_rule": "survey_year" + }, + { + "kind": "assign_binary_from_rate", + "output": "would_claim_carers_allowance", + "draw": "would_claim_carers_allowance", + "assignment_unit": "person", + "eligibility": "persons outside Scotland whose care_hours reach policyengine-uk's gov.dwp.carers_allowance.min_hours, who report no Carer's Allowance, and whom is_gainfully_employed_for_carers_allowance holds gainfully employed at the survey year: the carers the earnings limit alone keeps from the allowance. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test", + "reported_true_anchor": "carers_allowance_reported > 0", + "rate_key": "carers_allowance_newly_entitled", + "rate_derivation": "the take-up contract's carers_allowance_newly_entitled rate, drawn flat over the eligible persons; would_claim = reported OR (eligible AND u < rate), so a reporter stays true and every other person false", + "seed": 0 + } + ], + "outputs": [], + "rewrites": [ + "would_claim_carers_allowance" + ], + "notes": "Runs after the SPI income chain, UC capital coherence and the Pension Credit and Child Benefit redraws, before CGT cloning, so every clone carries its source's draw (microcosm#1319). frs_spine sets would_claim_carers_allowance from reported receipt and the SPI income chain re-derives it from the refilled receipt on the rows it redraws, so that care_hours qualifies a carer for the Universal Credit carer element without paying the allowance to every carer (#882). A carer above the earnings limit cannot report the allowance, so no reform that widens it reached a carer who would claim once entitled: the April 2025 rise of the limit from £151 to £196 a week brought an estimated 61,000 more people into eligibility (Independent Review of Carer's Allowance Overpayments, July 2025, chapter 7). One temporary engine materialization at the survey year, on the frame's own values, gives each person's is_gainfully_employed_for_carers_allowance (consumed only); the engine reads a year's parameters at 30 April, so the limit is 2024-25's £151. A person outside Scotland whose care_hours reach the engine's gov.dwp.carers_allowance.min_hours (35), who reports no allowance and whom that test holds gainfully employed claims at the take-up contract's carers_allowance_newly_entitled rate (0.6, María's ruling of 2026-10-20, sensitivity 0.45 to 0.75) on the person's identity-keyed uniform (seed 0, salt would_claim_carers_allowance): would_claim = reported OR (eligible AND u < rate). A reporter stays true; a carer under the limit who reports no allowance stays false, as the survey records them entitled and not claiming. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test. The earnings test is read before salary_sacrifice moves some contributors' pension amounts out of their pay, so a drawn carer whom that conversion takes under the survey year's limit keeps the flag although the file then shows them entitled and not reporting. The stage rebuilds the flag from reported receipt and refuses a frame whose flag no longer follows it. Its receipt bands support on distinct source households (household_source_id), and gives a weighted total only where ten or more carry it and the realised share only where neither side rests on one to nine; the stage has no health gate." + }, { "stage": "uc_deduction_attributes", "survey": "DWP Universal Credit deductions statistics, March 2025 to February 2026", diff --git a/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml b/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml index 1788e81ac..a2f1f7208 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml +++ b/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml @@ -370,7 +370,7 @@ stages: - kind: map_columns scope: 'raw-to-column E2 mappings and FRS claimant-role derivation (is_benunit_head OR is_parent OR no dependent children within the benefit unit) to is_uc_claimant; benunit.TOTCAPB4 -> frs_benunit_capital with blank, nonnumeric, or negative raw values -> named -1 unavailable sentinel (mapped-row count reported in stage evidence); Scottish water_and_sewerage_charges is the charge paid, (CWATAMT1 + CSEWAMT1) less the CTDISC/CT25D50D status discount, or where CTREB is 1 less the larger of that discount and the Water Charges Reduction Scheme''s 35% (the full-reduction case), and CWATAMTD where CWATAMT1 is not positive (uk-data#499, microcosm#1095); access_fund is ACCSSAMT annualised, except that a calendar-month award (ACCSSPD 5) that annualises to more than twice the largest annual-coded (ACCSSPD 52) award on the tab is read as the annual award, ACCSSAMT x 52/12 (microcosm#1095), and a tab with calendar-month awards but no annual-coded award refuses, since the threshold comes from that award; the stage evidence records the awards by period code, the threshold and the repaired count; is_blind is SPCREG1 = 1, registered blind or severely sight impaired with the local authority, read on the adult and child tabs alike, while partial-sight registration (SPCREG2) is not read (uk-data#523); esa_includes_support_component is false where a person''s ESA rows (BENEFIT 16) record VAR3 (ESAGROUP) 1 or 3, the work-related activity group or the assessment phase, and none records 2, the support group, and true everywhere else, policyengine-uk''s own default for an award of one''s own, and a benefits tab without VAR3 refuses (microcosm#1095); uc_is_in_startup_period holds for a self-employed person (EMPSTATI 3 or 4, a held self-employed JOB row with ETYPE 2-7 and no SEEND, or nonzero SEINCAM2) whose benefit unit''s UC claim (BENEFIT 95, UCSTART month/day/year) or whose first self-employed job (SEJBLONG, main job first) began less than 12 calendar months before INTDATE, except that a self-employed-job answer under a year from someone self-employed all year (SAMESIT 2 or every SDEMP month 3 or 4) who does not describe a business (JOBBUS 2) is a new engagement and does not date the trade (UC Regs 2013 reg 63, uk-data#527); is_claimant_or_partner is adult-table membership and is_hbai_dependent_child child-table membership (uk-data#524, uk-data#486), the claimant derivation already refusing a benefit unit without one or two adult records; CVPAY, the rent a boarder or lodger pays the householder, is not the payer''s property income but rent_paid_as_boarder where CONVBL is 1 and rent_paid_as_lodger otherwise, and liable_for_share_of_household_rent holds for a later benefit unit of a shared household (HHSTAT 2) with a rent share (SRENTAMT), Housing Benefit (HBOTHAMT) or a linked UC housing element (UCHOUSEL on BENEFIT 95) (pe-uk#2006, uk-data#512); uc_is_in_gainful_self_employment holds for a self-employed main job (EMPSTATI 3 or 4) whatever its profit, and for a side trade whose SEINCAM2 profit is above 0 and above INEARNS pay (UC Regs 2013 reg 64, ADM H4034, uk-data#525); reports_rent_from_other_property is an internal carrier, a positive ROYYR1 whether the letting made a profit or a loss (RENTPROF 2), which property_income counts as zero; the CGT stages read it as the landlord signal and the release drops it' - kind: map_coded_amounts - scope: region, tenure, accommodation, council tax band, benefit-code amount mappings (Scotland's Adult and Child Disability Payment codes 117/118 and 121/122 into the PIP and DLA columns they replace; benefit recovery codes 69 and 70 unmapped); adult HOURTOT care-hours band code to weekly care_hours at the band's lower edge (codes 5, 6, 7 and 10 reach the 35-hour Carer's Allowance line); would_claim_carers_allowance from positive reported Carer's Allowance + scope: region, tenure, accommodation, council tax band, benefit-code amount mappings (Scotland's Adult and Child Disability Payment codes 117/118 and 121/122 into the PIP and DLA columns they replace; benefit recovery codes 69 and 70 unmapped); adult HOURTOT care-hours band code to weekly care_hours at the band's lower edge (codes 5, 6, 7 and 10 reach the 35-hour Carer's Allowance line); would_claim_carers_allowance from positive reported Carer's Allowance, the anchor carers_allowance_take_up opens to carers over the earnings limit (microcosm#1319) - kind: annualize_periodic_amounts weeks_in_year: 52.17857142857143 weeks_in_year_exceptions: @@ -528,7 +528,7 @@ stages: - housing_service_charges - external_child_payments - care_hours - notes: Root E2 spine assembly. It carries direct raw mappings only; education-grant aggregate and council-tax reported fields remain raw carriers for E3. Benefit take-up, BRMA/LHA assignment, stochastic flags, and imputations are intentionally absent from this stage, except two identity-keyed draws. One is the UC start-up claim recency (uk-data#527). The other is each person's months_since_last_birthday, which policyengine-uk reads to place a date of birth (the two-child limit, the State Pension scheme, the Pension Credit qualifying age). Each single year of age and sex is spread evenly over the year at the FRS weights, in an order set by a draw on the person's stable id, as the engine spreads it when the column is unset, and the column is stored so every later engine read, the calibration's and the release's included, takes the same months whatever weights or identifiers the file carries (microcosm#1095). The UC start-up period needs the raw claim, interview and job dates only this stage reads, so a UC record without a linked claim date takes its claim recency from a benefit-unit-keyed draw at the linked share. The 2024-25 househol.tab is not sernum-ordered; the declared household sort guards stable identity. care_hours carries the FRS banded care-hours code as weekly hours (lower band edge) and would_claim_carers_allowance follows reported receipt, so the engine keeps Carer's Allowance on reported claimants while the hours qualify carers for the Universal Credit carer element (#882). SEINCAM2, the self-employment income the respondent gives, splits by its sign (uk-data#528), so profits go to self_employment_income and losses to trading_loss as a positive amount, the two inputs policyengine-uk reads from 2.131.0 (pe-uk#2085). The engine uprates trading_loss into each projected year as it does self_employment_income, so a loss persists like a profit; the engine documents that a one-off loss would be set to zero in later years, which a one-year survey cannot tell apart. Six of policyengine-uk's eleven owned-company inputs (pe-uk#1965) come from the FRS job tab (microcosm#1095). A director (DIRECTOR 1 or NATURE 1) who owns at least half of the company (DIRPERC 1 to 3, the ruling of 2026-10-16) stands as its sole owner or partner and works in it. The company is their main employment when the job is their first (JOBTYPE 1); it carries on a property business when the main job's SIC division is 68 and a trade otherwise, and its income share is the dividends the job records (DIVIDEND, after tax), the part of the company's profit the survey sees. A company held in another job carries on neither, since ADULT.SIC codes the main job only, which leaves the engine's company-owner rules off for it. The stocks and the intermediaries inputs keep the engine's defaults. + notes: Root E2 spine assembly. It carries direct raw mappings only; education-grant aggregate and council-tax reported fields remain raw carriers for E3. Benefit take-up, BRMA/LHA assignment, stochastic flags, and imputations are intentionally absent from this stage, except two identity-keyed draws. One is the UC start-up claim recency (uk-data#527). The other is each person's months_since_last_birthday, which policyengine-uk reads to place a date of birth (the two-child limit, the State Pension scheme, the Pension Credit qualifying age). Each single year of age and sex is spread evenly over the year at the FRS weights, in an order set by a draw on the person's stable id, as the engine spreads it when the column is unset, and the column is stored so every later engine read, the calibration's and the release's included, takes the same months whatever weights or identifiers the file carries (microcosm#1095). The UC start-up period needs the raw claim, interview and job dates only this stage reads, so a UC record without a linked claim date takes its claim recency from a benefit-unit-keyed draw at the linked share. The 2024-25 househol.tab is not sernum-ordered; the declared household sort guards stable identity. care_hours carries the FRS banded care-hours code as weekly hours (lower band edge) and would_claim_carers_allowance follows reported receipt, so the engine keeps Carer's Allowance on reported claimants while the hours qualify carers for the Universal Credit carer element (#882); after the SPI income chain, carers_allowance_take_up opens the flag to carers the earnings limit alone keeps from the allowance (microcosm#1319). SEINCAM2, the self-employment income the respondent gives, splits by its sign (uk-data#528), so profits go to self_employment_income and losses to trading_loss as a positive amount, the two inputs policyengine-uk reads from 2.131.0 (pe-uk#2085). The engine uprates trading_loss into each projected year as it does self_employment_income, so a loss persists like a profit; the engine documents that a one-off loss would be set to zero in later years, which a one-year survey cannot tell apart. Six of policyengine-uk's eleven owned-company inputs (pe-uk#1965) come from the FRS job tab (microcosm#1095). A director (DIRECTOR 1 or NATURE 1) who owns at least half of the company (DIRPERC 1 to 3, the ruling of 2026-10-16) stands as its sole owner or partner and works in it. The company is their main employment when the job is their first (JOBTYPE 1); it carries on a property business when the main job's SIC division is 68 and a trade otherwise, and its income share is the dividends the job records (DIVIDEND, after tax), the part of the company's profit the survey sees. A company held in another job carries on neither, since ADULT.SIC codes the main job only, which leaves the engine's company-owner rules off for it. The stocks and the intermediaries inputs keep the engine's defaults. - stage: age_tail survey: Family Resources Survey 2024-25 and ONS mid-year population estimates source: Office for National Statistics mid-year population estimates for the 80+ age bands by sex, via the chronicle ledger facts the calibration register binds (target family ons_population). @@ -4254,7 +4254,7 @@ stages: - is_severely_disabled_for_benefits - receives_benefits_in_own_right - would_claim_uc - notes: 'Runs on SPI-channel rows after uc_reporter_redraw, the last writer of Universal Credit reports, and before uc_capital_coherence and the Pension Credit and Child Benefit take-up stages (microcosm#1095, uk-data#514). The stage-2 forests of hmrc_spi_income_spine re-impute each SPI adult''s benefit reports from age, gender, region and the new incomes, with nothing of the benefit unit''s entitlement or claim history. This stage zeroes the SPI rows'' contributory and income-based JSA, income-related ESA, Income Support, Working and Child Tax Credit, Severe Disablement Allowance and Sure Start Maternity Grant reports, whose award needs an existing legacy claim, an out-of-work test, or a claim the copied household''s new incomes cannot carry (policyengine-uk pays income-related ESA as reported behind a capital test alone); restores Industrial Injuries Disablement Benefit, the Armed Forces Compensation Scheme and bereavement support from the FRS twin (person_source_id), since they follow an injury, service or a death; re-derives the disability flags (the categories, which read only AA, DLA and PIP, are asserted unchanged) and receives_benefits_in_own_right from the final reports; and redraws would_claim_uc for SPI benefit units as frs_take_up draws it for FRS units: a unit with a Universal Credit reporter claims, and the other units in frs_take_up''s Universal Credit population (a UC claimant or partner aged 18 to under Pension Credit qualifying age) claim as the residual of the contract''s universal_credit rate on draws keyed on the SPI unit''s own identity. Contributory ESA, PIP, DLA, AA, Carer''s Allowance, State Pension and Winter Fuel Payment keep their draws, and FRS rows are never modified; contributory ESA is open to new claims and not income-tested, and the incapacity it needs follows the person, whose health and disability reports the SPI copy keeps.' + notes: 'Runs on SPI-channel rows after uc_reporter_redraw, the last writer of Universal Credit reports, and before uc_capital_coherence and the Pension Credit, Child Benefit and Carer''s Allowance take-up stages (microcosm#1095, uk-data#514). The stage-2 forests of hmrc_spi_income_spine re-impute each SPI adult''s benefit reports from age, gender, region and the new incomes, with nothing of the benefit unit''s entitlement or claim history. This stage zeroes the SPI rows'' contributory and income-based JSA, income-related ESA, Income Support, Working and Child Tax Credit, Severe Disablement Allowance and Sure Start Maternity Grant reports, whose award needs an existing legacy claim, an out-of-work test, or a claim the copied household''s new incomes cannot carry (policyengine-uk pays income-related ESA as reported behind a capital test alone); restores Industrial Injuries Disablement Benefit, the Armed Forces Compensation Scheme and bereavement support from the FRS twin (person_source_id), since they follow an injury, service or a death; re-derives the disability flags (the categories, which read only AA, DLA and PIP, are asserted unchanged) and receives_benefits_in_own_right from the final reports; and redraws would_claim_uc for SPI benefit units as frs_take_up draws it for FRS units: a unit with a Universal Credit reporter claims, and the other units in frs_take_up''s Universal Credit population (a UC claimant or partner aged 18 to under Pension Credit qualifying age) claim as the residual of the contract''s universal_credit rate on draws keyed on the SPI unit''s own identity. Contributory ESA, PIP, DLA, AA, Carer''s Allowance, State Pension and Winter Fuel Payment keep their draws (carers_allowance_take_up later opens the Carer''s Allowance claim flag to carers over the earnings limit, microcosm#1319), and FRS rows are never modified; contributory ESA is open to new claims and not income-tested, and the incapacity it needs follows the person, whose health and disability reports the SPI copy keeps.' - stage: uc_capital_coherence survey: Family Resources Survey 2024-25 source: Family Resources Survey 2024-25 benefit-unit TOTCAPB4 observations carried through the SPI support channel, plus the household's Wealth and Assets Survey property imputation for the unit that holds it. @@ -4453,6 +4453,30 @@ stages: - would_claim_child_benefit - child_benefit_opts_out notes: 'Runs after the SPI income chain, UC capital coherence and the Pension Credit redraw, before CGT cloning (microcosm#1063). frs_take_up draws would_claim_child_benefit early at one flat rate over every benefit unit with the reporters on top, and child_benefit_opts_out at a flat rate whatever the unit''s income; this stage redraws both. One temporary engine materialization gives each person''s eligibility as a child or qualifying young person and each person''s adjusted net income (consumed only). A family claims for all its children or none, so the draw is by family, keyed on the age of its eldest eligible child: a reporter claims, and the other families claim at rates solved from the eldest age down so that the claimed share of the eligible children of each single year of age is HMRC''s published one (Table 15, May 2025, opted-out families included), weighted at the stage''s household weights. The published opted-out share of registered families (August 2025) is drawn among claiming non-reporters, fully charged first. Opt-out-aware models restrict both the full-charge and taper pools to a positive charge fraction at least the installed opt_out_charge_share. With the default share of one, only fully charged families can opt out; an insufficient pool is recorded as a shortfall instead of selecting paid taper families. Legacy models retain the original full-charge pool and taper fallback. Models exposing gov.hmrc.child_benefit.opt_out_charge_share (policyengine-uk#2140) receive registered claims, including opted-out families, in would_claim_child_benefit and the separate opt-out in child_benefit_opts_out. Older models receive the legacy claims-and-not-opted-out payment flag because they ignore the opt-out input. Stage evidence records the selected encoding, evaluated opt-out charge share and engine parameter source. The in-payment audit counts claims-and-not-opted-out in the draw, with new candidates aligned to baseline payment suppression; it is not a fresh model run or population calibration evidence. A benefit unit with no eligible child keeps its early draw and is never opted out.' +- stage: carers_allowance_take_up + survey: Family Resources Survey 2024-25 + source: 'Independent Review of Carer''s Allowance Overpayments (July 2025), chapter 7, and DWP benefit statistics, through the UK take-up contract''s carers_allowance_newly_entitled rate, applied to PolicyEngine-UK''s Carer''s Allowance earnings test after the SPI income chain.' + grain: person + artifacts: [] + operations: + - kind: materialize_rules_engine_predictors + predictors: + - is_gainfully_employed_for_carers_allowance + consumed_only: true + year_rule: survey_year + - kind: assign_binary_from_rate + output: would_claim_carers_allowance + draw: would_claim_carers_allowance + assignment_unit: person + eligibility: 'persons outside Scotland whose care_hours reach policyengine-uk''s gov.dwp.carers_allowance.min_hours, who report no Carer''s Allowance, and whom is_gainfully_employed_for_carers_allowance holds gainfully employed at the survey year: the carers the earnings limit alone keeps from the allowance. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test' + reported_true_anchor: carers_allowance_reported > 0 + rate_key: carers_allowance_newly_entitled + rate_derivation: 'the take-up contract''s carers_allowance_newly_entitled rate, drawn flat over the eligible persons; would_claim = reported OR (eligible AND u < rate), so a reporter stays true and every other person false' + seed: 0 + outputs: [] + rewrites: + - would_claim_carers_allowance + notes: 'Runs after the SPI income chain, UC capital coherence and the Pension Credit and Child Benefit redraws, before CGT cloning, so every clone carries its source''s draw (microcosm#1319). frs_spine sets would_claim_carers_allowance from reported receipt and the SPI income chain re-derives it from the refilled receipt on the rows it redraws, so that care_hours qualifies a carer for the Universal Credit carer element without paying the allowance to every carer (#882). A carer above the earnings limit cannot report the allowance, so no reform that widens it reached a carer who would claim once entitled: the April 2025 rise of the limit from £151 to £196 a week brought an estimated 61,000 more people into eligibility (Independent Review of Carer''s Allowance Overpayments, July 2025, chapter 7). One temporary engine materialization at the survey year, on the frame''s own values, gives each person''s is_gainfully_employed_for_carers_allowance (consumed only); the engine reads a year''s parameters at 30 April, so the limit is 2024-25''s £151. A person outside Scotland whose care_hours reach the engine''s gov.dwp.carers_allowance.min_hours (35), who reports no allowance and whom that test holds gainfully employed claims at the take-up contract''s carers_allowance_newly_entitled rate (0.6, María''s ruling of 2026-10-20, sensitivity 0.45 to 0.75) on the person''s identity-keyed uniform (seed 0, salt would_claim_carers_allowance): would_claim = reported OR (eligible AND u < rate). A reporter stays true; a carer under the limit who reports no allowance stays false, as the survey records them entitled and not claiming. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test. The earnings test is read before salary_sacrifice moves some contributors'' pension amounts out of their pay, so a drawn carer whom that conversion takes under the survey year''s limit keeps the flag although the file then shows them entitled and not reporting. The stage rebuilds the flag from reported receipt and refuses a frame whose flag no longer follows it. Its receipt bands support on distinct source households (household_source_id), and gives a weighted total only where ten or more carry it and the realised share only where neither side rests on one to nine; the stage has no health gate.' - stage: uc_deduction_attributes survey: DWP Universal Credit deductions statistics, March 2025 to February 2026 source: Department for Work and Pensions supplementary Tables 2, 5 and 6, sha-pinned by Chronicle package dwp-uc-deductions-march-2025-february-2026. diff --git a/packages/microcosm-build/src/microcosm/build/uk/take_up_contract.json b/packages/microcosm-build/src/microcosm/build/uk/take_up_contract.json index f641937ab..9d1f0adf2 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/take_up_contract.json +++ b/packages/microcosm-build/src/microcosm/build/uk/take_up_contract.json @@ -104,6 +104,27 @@ "status": "sourced_administrative" } }, + { + "key": "carers_allowance_newly_entitled", + "output": "would_claim_carers_allowance", + "entity": "person", + "values": { + "2024-01-01": 0.6 + }, + "source": { + "source": "Independent Review of Carer's Allowance Overpayments (July 2025), chapter 7, and DWP benefit statistics", + "agency": "DWP", + "citation": "The share of the carers a reform or a later year newly entitles to Carer's Allowance who claim it. No published rate exists for them: the Independent Review estimates that the April 2025 rise of the earnings limit from 151 to 196 pounds a week brought about 61,000 more people into eligibility, and gives no estimate of how many claim. 0.6 is the central rate of María's ruling of 2026-10-20 (sensitivity 0.45 to 0.75), to be checked against the 61,000 and against DWP's Carer's Allowance caseload by the earnings-limit back-test on the national file (microcosm#1319). Applied by carers_allowance_take_up to a person outside Scotland whose care hours meet the hours condition, who reports no Carer's Allowance and whom the earnings limit holds gainfully employed at the survey year, the year it is keyed at.", + "url": "https://www.gov.uk/government/publications/review-of-carers-allowance-overpayments/independent-review-of-carers-allowance-overpayments", + "caseload_url": "https://www.gov.uk/government/statistics/dwp-benefit-statistics-february-2026/dwp-benefit-statistics-february-2026", + "status": "frozen_by_adjudication", + "freeze": { + "decision": "María's ruling of 2026-10-20 on the microcosm#1319 plan: a flat 0.6, sensitivity 0.45 to 0.75, with no stage-health gate until a caseload target binds it", + "followup": "microcosm#1319" + } + }, + "population": "persons outside Scotland with care hours at the Carer's Allowance hours condition, no reported Carer's Allowance, and earnings above the limit at the survey year" + }, { "key": "universal_credit", "output": "would_claim_uc", diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/carers_allowance_take_up.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/carers_allowance_take_up.py new file mode 100644 index 000000000..925cd00ee --- /dev/null +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/carers_allowance_take_up.py @@ -0,0 +1,470 @@ +"""Carer's Allowance claims by the carers the earnings limit keeps out +(microcosm#1319). + +``frs_spine`` sets ``would_claim_carers_allowance`` from reported receipt, and +the SPI income chain re-derives it from the refilled receipt on the rows it +redraws, so that ``care_hours`` qualifies a carer for the Universal Credit +carer element without paying the allowance to every carer (#882). A carer +whose earnings are above the limit cannot report the allowance, so no reform +that widens it, such as the April 2025 rise of the limit from £151 to £196 a +week, reached a carer who would claim once entitled. + +This stage runs after the SPI income chain and the other take-up redraws. It +opens the flag to the carers the earnings limit alone keeps from the +allowance at the survey year: a person outside Scotland whose ``care_hours`` +reach the engine's ``gov.dwp.carers_allowance.min_hours``, who reports no +Carer's Allowance, and whom ``is_gainfully_employed_for_carers_allowance`` +holds gainfully employed at the survey year (the 2024-25 limit of £151 a +week; the engine reads a year's parameters at 30 April). Such a person claims +at the take-up contract's ``carers_allowance_newly_entitled`` rate, on an +identity-keyed uniform: + + would_claim = reported OR (eligible AND u < rate) + +A reporter stays true. A carer under the limit who reports no allowance +stays false, as the survey records them entitled and not claiming. Scotland +is left closed: Carer Support Payment reads the same flag and the engine +applies it no earnings test, so a draw there would pay it. The incoming flag +must still follow reported receipt, since the stage rebuilds it from that +anchor. + +The earnings test is read where the stage runs, before ``salary_sacrifice`` +moves some contributors' pension amounts out of their pay, which lowers the +earnings the engine tests by about half the amount moved. A drawn carer whom +that conversion takes under the survey year's limit keeps the flag, although +the released file then shows them entitled and not reporting. Reading the +converted pay would need the stage after ``salary_sacrifice``, with a draw +keyed on lineage so that the CGT clones keep their source's draw. + +The receipt is aggregate-only (UKDS disclosure control): support as bands of +distinct source households, a weighted total only where ten or more carry +it, and the realised share only where neither the drawn nor the undrawn side +rests on one to nine. +""" + +from __future__ import annotations + +from dataclasses import dataclass, field +from importlib import metadata +from pathlib import Path + +import numpy as np +import pandas as pd + +from microcosm.build.source_manifest import SourceStageSpec +from microcosm.build.stochastic_assignment import stable_identity_uniforms +from microcosm.build.uk_runtime.frs_release import resolve_uk_year_rule +from microcosm.build.uk_runtime.national_frame import ( + uk_household_weight_kind, + uk_national_frame, + uk_time_period, + validate_uk_national_frame, +) +from microcosm.build.uk_runtime.receipt_counts import ( + distinct_count, + small_cell_share, + source_household_ids, + support_band, +) +from microcosm.build.uk_runtime.take_up_contract import ( + UKTakeUpContract, + load_uk_take_up_contract, +) +from microcosm.frame import Frame +from microcosm.frame.rules import assert_rules_engine_country + +__all__ = [ + "CARERS_ALLOWANCE_ENGINE_VARIABLES", + "CARERS_ALLOWANCE_NEWLY_ENTITLED_RATE_KEY", + "CARERS_ALLOWANCE_TAKE_UP_OUTPUT", + "CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME", + "UKCarersAllowancePolicy", + "UKCarersAllowanceTakeUpResult", + "UKCarersAllowanceTakeUpStageTransform", + "carers_allowance_eligible", + "carers_allowance_take_up_operation_parameters", + "redraw_carers_allowance_take_up", + "uk_carers_allowance_policy", +] + +CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME = "carers_allowance_take_up" +CARERS_ALLOWANCE_TAKE_UP_OUTPUT = "would_claim_carers_allowance" +CARERS_ALLOWANCE_TAKE_UP_SEED = 0 +CARERS_ALLOWANCE_REPORTED = "carers_allowance_reported" +CARERS_ALLOWANCE_CARE_HOURS = "care_hours" +CARERS_ALLOWANCE_EARNINGS_TEST = "is_gainfully_employed_for_carers_allowance" +CARERS_ALLOWANCE_ENGINE_VARIABLES = (CARERS_ALLOWANCE_EARNINGS_TEST,) +#: The earnings test is read on the frame's own values at the survey year, the +#: limit the survey's carers were held to; the stage refuses any other period. +CARERS_ALLOWANCE_YEAR_RULE = "survey_year" +CARERS_ALLOWANCE_NEWLY_ENTITLED_RATE_KEY = "carers_allowance_newly_entitled" +#: Carer Support Payment replaces the allowance in Scotland and reads the same +#: flag with no earnings test in the engine, so Scotland is never drawn. +CARERS_ALLOWANCE_CLOSED_REGION = "SCOTLAND" +CARERS_ALLOWANCE_PARAMETERS = "gov.dwp.carers_allowance" +CARERS_ALLOWANCE_REPORTED_ANCHOR = "carers_allowance_reported > 0" +CARERS_ALLOWANCE_ELIGIBILITY = ( + "persons outside Scotland whose care_hours reach policyengine-uk's " + "gov.dwp.carers_allowance.min_hours, who report no Carer's Allowance, and " + "whom is_gainfully_employed_for_carers_allowance holds gainfully employed at " + "the survey year: the carers the earnings limit alone keeps from the " + "allowance. Scotland stays closed, since Carer Support Payment reads the same " + "flag and the engine applies it no earnings test" +) +CARERS_ALLOWANCE_RATE_DERIVATION = ( + "the take-up contract's carers_allowance_newly_entitled rate, drawn flat over " + "the eligible persons; would_claim = reported OR (eligible AND u < rate), so " + "a reporter stays true and every other person false" +) + + +@dataclass(frozen=True) +class UKCarersAllowancePolicy: + """The engine's hours condition and weekly earnings limit at one instant. + + ``min_hours`` forms the eligible set; the earnings test itself is the + engine's own ``is_gainfully_employed_for_carers_allowance``, so + ``earnings_limit`` is recorded for the receipt only. + """ + + min_hours: float + earnings_limit: float + instant: str + source: str + + +def uk_carers_allowance_policy(year: int | str) -> UKCarersAllowancePolicy: + """Read the hours condition and the earnings limit as the engine reads ``year``. + + policyengine-uk reads a yearly parameter at 30 April of the year + (``convert_to_fiscal_year_parameters``), so the survey year 2024 reads the + 2024-25 limit. + """ + + try: + import policyengine_uk + from policyengine_core.parameters import ParameterNode + except ImportError as exc: + raise ImportError( + "The Carer's Allowance take-up policy requires " + "`uv sync --all-packages --extra uk`." + ) from exc + + parameters = ParameterNode( + directory_path=str(Path(policyengine_uk.__file__).parent / "parameters") + ) + instant = f"{int(year)}-04-30" + carers_allowance = parameters.gov.dwp.carers_allowance + return UKCarersAllowancePolicy( + min_hours=float(carers_allowance.min_hours(instant)), + earnings_limit=float(carers_allowance.earnings_limit(instant)), + instant=instant, + source=( + f"policyengine-uk {metadata.version('policyengine-uk')} " + f"{CARERS_ALLOWANCE_PARAMETERS} at {instant}" + ), + ) + + +def carers_allowance_eligible( + *, + care_hours: np.ndarray, + reported: np.ndarray, + gainfully_employed: np.ndarray, + scotland: np.ndarray, + min_hours: float, +) -> np.ndarray: + """The carers the earnings limit alone keeps from the allowance.""" + + return ( + ~np.asarray(scotland, dtype=bool) + & (np.asarray(care_hours, dtype=np.float64) >= float(min_hours)) + & ~np.asarray(reported, dtype=bool) + & np.asarray(gainfully_employed, dtype=bool) + ) + + +@dataclass(frozen=True) +class UKCarersAllowanceTakeUpResult: + """Output frame and aggregate receipt for the Carer's Allowance draw.""" + + frame: Frame + receipt: dict[str, object] + + def evidence(self) -> dict[str, object]: + return {"stage": CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME, **self.receipt} + + +@dataclass(frozen=True) +class UKCarersAllowanceTakeUpStageTransform: + """Whole-stage callable for the post-SPI Carer's Allowance draw.""" + + stage: SourceStageSpec + engine: object + contract: UKTakeUpContract | None = None + policy: UKCarersAllowancePolicy | None = None + last_result: UKCarersAllowanceTakeUpResult | None = field(default=None, init=False) + + def __call__(self, frame: Frame) -> Frame: + _assert_stage_parameters(self.stage) + result = redraw_carers_allowance_take_up( + frame, + engine=self.engine, + contract=self.contract or load_uk_take_up_contract(), + policy=self.policy, + ) + object.__setattr__(self, "last_result", result) + return result.frame + + @staticmethod + def output_columns() -> tuple[str, ...]: + return () + + def checkpoint_metadata(self) -> dict[str, object]: + if self.last_result is None: + raise RuntimeError("checkpoint metadata requires a completed stage run.") + return {"evidence": self.last_result.evidence()} + + +def redraw_carers_allowance_take_up( + frame: Frame, + *, + engine: object, + contract: UKTakeUpContract, + policy: UKCarersAllowancePolicy | None = None, +) -> UKCarersAllowanceTakeUpResult: + """Open ``would_claim_carers_allowance`` to carers over the earnings limit.""" + + validate_uk_national_frame(frame) + assert_rules_engine_country(engine, "uk") + person = frame.table("person").copy() + household = frame.table("household").copy() + for table, columns, label in ( + ( + person, + ( + "person_id", + "person_household_id", + CARERS_ALLOWANCE_REPORTED, + CARERS_ALLOWANCE_CARE_HOURS, + CARERS_ALLOWANCE_TAKE_UP_OUTPUT, + ), + "person", + ), + (household, ("household_id", "region"), "household"), + ): + missing = sorted(set(columns) - set(table.columns)) + if missing: + raise ValueError( + f"Carer's Allowance take-up {label} columns missing: {missing}." + ) + # Compared as the label the frame carries, so that a "2024-25" or another + # year is refused by this message, not by a failed int(). + period = uk_time_period(frame) + survey_year = resolve_uk_year_rule(CARERS_ALLOWANCE_YEAR_RULE) + if period != str(survey_year): + raise ValueError( + "Carer's Allowance take-up reads the earnings test on the frame's " + f"{CARERS_ALLOWANCE_YEAR_RULE} {survey_year} values, but the frame's " + f"period is {period!r}." + ) + # The graph node is an open surface, so the lineage arrives with every + # other live cell; the receipt counts support by it. + household_sources = pd.Series( + source_household_ids(household, stage="The Carer's Allowance take-up stage"), + index=household["household_id"].to_numpy(), + ) + reported = ( + pd.to_numeric(person[CARERS_ALLOWANCE_REPORTED], errors="coerce") + .fillna(0.0) + .to_numpy() + > 0.0 + ) + previous = person[CARERS_ALLOWANCE_TAKE_UP_OUTPUT].fillna(False).to_numpy(bool) + if (previous != reported).any(): + raise ValueError( + f"{CARERS_ALLOWANCE_TAKE_UP_OUTPUT} must arrive as reported receipt " + f"({CARERS_ALLOWANCE_REPORTED_ANCHOR}), as frs_spine and the SPI " + "refresh set it: the stage rebuilds the flag from that anchor and " + "would overwrite another writer." + ) + resolved = policy or uk_carers_allowance_policy(survey_year) + rate = _rate(contract.rate(CARERS_ALLOWANCE_NEWLY_ENTITLED_RATE_KEY)) + materialized = engine.materialize( + frame, list(CARERS_ALLOWANCE_ENGINE_VARIABLES), period + ) + missing = sorted(set(CARERS_ALLOWANCE_ENGINE_VARIABLES) - set(materialized)) + if missing: + raise ValueError( + f"Carer's Allowance take-up engine outputs missing: {missing}." + ) + gainfully_employed = _aligned( + materialized[CARERS_ALLOWANCE_EARNINGS_TEST], + len(person), + CARERS_ALLOWANCE_EARNINGS_TEST, + ).astype(bool) + person_households = person["person_household_id"] + regions = person_households.map( + household.set_index("household_id")["region"].astype(str) + ) + if regions.isna().any(): + raise ValueError("Every person's household must carry a region.") + scotland = regions.eq(CARERS_ALLOWANCE_CLOSED_REGION).to_numpy(dtype=bool) + care_hours = ( + pd.to_numeric(person[CARERS_ALLOWANCE_CARE_HOURS], errors="coerce") + .fillna(0.0) + .to_numpy(dtype=np.float64) + ) + eligible = carers_allowance_eligible( + care_hours=care_hours, + reported=reported, + gainfully_employed=gainfully_employed, + scotland=scotland, + min_hours=resolved.min_hours, + ) + draws = stable_identity_uniforms( + person["person_id"].to_numpy(), + seed=CARERS_ALLOWANCE_TAKE_UP_SEED, + salt=CARERS_ALLOWANCE_TAKE_UP_OUTPUT, + ) + drawn = eligible & (draws < rate) + would_claim = reported | drawn + person[CARERS_ALLOWANCE_TAKE_UP_OUTPUT] = would_claim + result = uk_national_frame( + person=person, + benunit=frame.table("benunit").copy(), + household=household, + time_period=period, + weight_kind=uk_household_weight_kind(frame), + household_weights=frame.weights_for("household").values, + mass_log=frame.mass_log, + ) + validate_uk_national_frame(result) + + source_ids = person_households.map(household_sources).to_numpy() + weights = np.asarray(frame.resolve_weights("person").values, dtype=np.float64) + + # Weighted aggregates only; a figure one to nine source households carry + # is "<10" (UKDS disclosure control). + def sources(mask: np.ndarray) -> int: + return distinct_count(source_ids, mask, weights) + + eligible_sources = sources(eligible) + eligible_weight = float(weights[eligible].sum()) + # The share times the eligible weight gives back either side, so the share + # is given only where neither side rests on one to nine sources; the drawn + # weight is never given beside the eligible weight for the same reason. + if not eligible_weight: + share: float | str | None = None + elif 0 < min(sources(drawn), sources(eligible & ~drawn)) < 10: + share = "<10" + else: + share = small_cell_share( + float(weights[drawn].sum()) / eligible_weight, eligible_sources + ) + receipt = { + "seed": CARERS_ALLOWANCE_TAKE_UP_SEED, + "salt": CARERS_ALLOWANCE_TAKE_UP_OUTPUT, + "eligibility": CARERS_ALLOWANCE_ELIGIBILITY, + "rule": CARERS_ALLOWANCE_RATE_DERIVATION, + "rate_key": CARERS_ALLOWANCE_NEWLY_ENTITLED_RATE_KEY, + "rate": rate, + "survey_year": survey_year, + "min_hours": resolved.min_hours, + "weekly_earnings_limit": resolved.earnings_limit, + "policy_source": resolved.source, + "weights": "household weights at the stage, before calibration, per person", + "eligible_support": support_band(eligible_sources), + "eligible_weighted_persons": small_cell_share( + eligible_weight, eligible_sources + ), + "drawn_support": support_band(sources(drawn)), + "realized_share": share, + # Over-limit carers in Scotland stay closed: no Scottish person who + # reports no allowance carries the flag. + "scotland_left_closed_support": support_band( + sources( + scotland + & (care_hours >= resolved.min_hours) + & ~reported + & gainfully_employed + ) + ), + "scotland_closed": not bool((scotland & ~reported & would_claim).any()), + } + return UKCarersAllowanceTakeUpResult(frame=result, receipt=receipt) + + +def _rate(value: float) -> float: + rate = float(value) + if not 0.0 <= rate <= 1.0: + raise ValueError( + f"{CARERS_ALLOWANCE_NEWLY_ENTITLED_RATE_KEY} must be a rate in [0, 1], " + f"got {rate}." + ) + return rate + + +def _aligned(values: object, expected: int, label: str) -> np.ndarray: + array = np.asarray(values) + if array.shape != (expected,): + raise ValueError(f"{label} must align to the person table.") + if array.dtype != bool and not np.isfinite(array.astype(np.float64)).all(): + raise ValueError(f"{label} must be finite.") + return array + + +def carers_allowance_take_up_operation_parameters() -> dict[str, dict[str, object]]: + """The reviewed operation payload the manifests must carry verbatim.""" + + return { + "materialize_rules_engine_predictors": { + "predictors": list(CARERS_ALLOWANCE_ENGINE_VARIABLES), + "consumed_only": True, + "year_rule": CARERS_ALLOWANCE_YEAR_RULE, + }, + "assign_binary_from_rate": { + "output": CARERS_ALLOWANCE_TAKE_UP_OUTPUT, + "draw": CARERS_ALLOWANCE_TAKE_UP_OUTPUT, + "assignment_unit": "person", + "eligibility": CARERS_ALLOWANCE_ELIGIBILITY, + "reported_true_anchor": CARERS_ALLOWANCE_REPORTED_ANCHOR, + "rate_key": CARERS_ALLOWANCE_NEWLY_ENTITLED_RATE_KEY, + "rate_derivation": CARERS_ALLOWANCE_RATE_DERIVATION, + "seed": CARERS_ALLOWANCE_TAKE_UP_SEED, + }, + } + + +def _assert_stage_parameters(stage: SourceStageSpec) -> None: + if stage.stage != CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME: + raise ValueError( + f"Carer's Allowance take-up received stage {stage.stage!r}, expected " + f"{CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME!r}." + ) + expected = carers_allowance_take_up_operation_parameters() + kinds = [operation.kind for operation in stage.operations] + if kinds != list(expected): + raise ValueError( + f"{CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME} operation order drifted: " + f"expected {list(expected)}, got {kinds}." + ) + actual = { + operation.kind: dict(operation.parameters) for operation in stage.operations + } + if actual != expected: + drifted = sorted(kind for kind in expected if actual[kind] != expected[kind]) + raise ValueError( + f"{CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME} parameters drifted from the " + f"reviewed mapping on operation(s) {drifted}." + ) + if stage.outputs != () or stage.rewrites != (CARERS_ALLOWANCE_TAKE_UP_OUTPUT,): + raise ValueError( + f"{CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME} must declare no new outputs and " + f"exactly the rewrite {CARERS_ALLOWANCE_TAKE_UP_OUTPUT!r}." + ) + if stage.grain != "person": + raise ValueError( + f"{CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME} is person grain, got " + f"{stage.grain!r}." + ) diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/graph.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/graph.py index bb801e7fb..a995a9290 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/graph.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/graph.py @@ -125,6 +125,10 @@ # The Child Benefit redraw rewrites ``frs_take_up``'s two Child Benefit # flags, which the open-surface readers before it bind (microcosm#1063). "child_benefit_take_up", + # The Carer's Allowance draw rewrites ``would_claim_carers_allowance``, + # the root cell the SPI income stage refreshes, which the open-surface + # readers before it bind (microcosm#1319). + "carers_allowance_take_up", # ``frs_education_grant_split`` rewrites the root cell # ``education_grants`` that the open-surface ``frs_legacy_proxies`` # reader already bound to. In the root version that rewrite opened a @@ -342,6 +346,10 @@ # One temporary engine materialization of Child Benefit eligibility and # adjusted net income over the whole frame: an open surface. "child_benefit_take_up": None, + # One temporary engine materialization of the Carer's Allowance earnings + # test over the whole frame: an open surface, which also hands the stage + # the source lineage its receipt counts by (microcosm#1319). + "carers_allowance_take_up": None, "spi_benefit_coherence": frozenset( { ("person", "person_support_channel"), @@ -1008,6 +1016,9 @@ def _cells( _Cell("benunit", "would_claim_child_benefit", "bool"), _Cell("benunit", "child_benefit_opts_out", "bool"), ), + "carers_allowance_take_up": ( + _Cell("person", "would_claim_carers_allowance", "bool"), + ), "uc_deduction_attributes": ( _Cell("benunit", "uc_deduction_random_draw", "float64"), _Cell("benunit", "uc_deduction_type_random_draw", "float64"), @@ -1134,7 +1145,8 @@ def _cells( "is_enhanced_disabled_for_benefits", "is_severely_disabled_for_benefits", # #882: the carer take-up flag follows the refilled Carer's Allowance - # receipt on the SPI-redrawn rows. + # receipt on the SPI-redrawn rows; carers_allowance_take_up later opens it + # to carers over the earnings limit (microcosm#1319). "would_claim_carers_allowance", # uk-data#527: the UC start-up period holds on a redrawn row only while it # stays self-employed. diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_kernels.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_kernels.py index c295377cf..651da3485 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_kernels.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_kernels.py @@ -54,6 +54,7 @@ hmrc_property_rental, ledger_fact_vendoring, property_localisation, + receipt_counts, rowwise_geography, spi_income, spi_support, @@ -111,6 +112,7 @@ "uc_legacy_closure_take_up": "legacy_closure_take_up", "pension_credit_take_up": "pension_credit_take_up", "child_benefit_take_up": "child_benefit_take_up", + "carers_allowance_take_up": "carers_allowance_take_up", "uc_deduction_attributes": "uc_deduction_attributes", "high_value_home_support": "high_value_home_support", "regional_home_values": "regional_home_values", @@ -173,6 +175,10 @@ "pension_credit_take_up": (uc_capital_coherence, uk_engine_adapter), # The Child Benefit redraw shares the weight mapping and the adapter. "child_benefit_take_up": (uc_capital_coherence, uk_engine_adapter), + # The Carer's Allowance draw reads the earnings test through the adapter's + # engine materialization and counts its receipt's support on the source + # lineage (microcosm#1319). + "carers_allowance_take_up": (uk_engine_adapter, receipt_counts), # The stored attendance is one engine materialization (microcosm#1095). "private_school_attendance": (uk_engine_adapter,), } @@ -474,6 +480,7 @@ def _fixture_implementations(source: Path) -> Mapping[str, object]: from microcosm.frame.adapters.policyengine_uk import PolicyEngineUKEngine from .age_tail import UKAgeTailStageTransform + from .carers_allowance_take_up import UKCarersAllowanceTakeUpStageTransform from .cgt_asset_type import UKCGTAssetTypeStageTransform, UKCGTBADRParameters from .cgt_imputation import UKCGTPolicyParameters, uk_cgt_spine_stage_transform from .cgt_residential_split import UKCGTResidentialSplitStageTransform @@ -724,6 +731,9 @@ def _fixture_implementations(source: Path) -> Mapping[str, object]: "child_benefit_take_up": UKChildBenefitTakeUpStageTransform( stage=stages["child_benefit_take_up"], engine=engine ), + "carers_allowance_take_up": UKCarersAllowanceTakeUpStageTransform( + stage=stages["carers_allowance_take_up"], engine=engine + ), "uc_deduction_attributes": UKUCDeductionAttributesStageTransform( stage=stages["uc_deduction_attributes"] ), diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_income.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_income.py index 5f0d50f33..c8124319e 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_income.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_income.py @@ -2593,7 +2593,11 @@ def _refresh_carer_take_up_input( fill re-imputes that receipt on the redrawn rows, so the flag is re-derived here from the refilled amount. A stale flag would pay the allowance to a redrawn 35-hour carer whose refilled receipt is zero, or - withhold it from one whose refilled receipt is positive (#882). + withhold it from one whose refilled receipt is positive (#882). This is + the anchor ``carers_allowance_take_up`` reads after the SPI income chain: + it refuses a flag that no longer follows reported receipt, and opens it + to the carers the earnings limit alone keeps from the allowance + (microcosm#1319). """ if "would_claim_carers_allowance" not in person.columns: diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/spine_build.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/spine_build.py index 58f831c78..307aabfb3 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/spine_build.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/spine_build.py @@ -72,6 +72,9 @@ UK_SPINE_GATE_SCOPE, uk_scoped_gate_manifest, ) +from microcosm.build.uk_runtime.carers_allowance_take_up import ( + UKCarersAllowanceTakeUpStageTransform, +) from microcosm.build.uk_runtime.cgt_asset_type import ( uk_cgt_asset_type_stage_transform, ) @@ -1728,6 +1731,14 @@ def prepare_uk_spine_execution( stage=stages_by_name["child_benefit_take_up"], engine=engine, ) + if "carers_allowance_take_up" in stage_names: + implementations["carers_allowance_take_up"] = ( + UKCarersAllowanceTakeUpStageTransform( + stage=stages_by_name["carers_allowance_take_up"], + engine=engine, + contract=stochastic_contract, + ) + ) if "uc_deduction_attributes" in stage_names: implementations["uc_deduction_attributes"] = ( UKUCDeductionAttributesStageTransform( diff --git a/packages/microcosm-build/tests/engine/uk/test_uk_carers_allowance_take_up.py b/packages/microcosm-build/tests/engine/uk/test_uk_carers_allowance_take_up.py new file mode 100644 index 000000000..ed3a65eff --- /dev/null +++ b/packages/microcosm-build/tests/engine/uk/test_uk_carers_allowance_take_up.py @@ -0,0 +1,203 @@ +"""Engine lockstep for the Carer's Allowance take-up stage (microcosm#1319). + +The stage opens the claim flag to carers outside Scotland whose care hours +meet the engine's condition, who report no allowance, and whom the engine's +earnings test holds gainfully employed at the survey year. These tests fail if +policyengine-uk moves the hours condition or the earnings limit, adds a +condition the stage does not read, or starts applying an earnings test to +Carer Support Payment, whose absence keeps Scotland closed. +""" + +from __future__ import annotations + +from importlib import metadata + +import numpy as np +import pandas as pd + +from microcosm.build.uk_runtime import carers_allowance_take_up as ca +from microcosm.build.uk_runtime.national_frame import uk_national_frame +from microcosm.frame import WeightKind +from microcosm.frame.adapters.policyengine_uk import PolicyEngineUKEngine + +_TEST = ca.CARERS_ALLOWANCE_EARNINGS_TEST + + +def _simulation(people: dict, period: int, region: str = "WALES"): + """One-person benefit units and households, inputs at ``period``.""" + + import policyengine_uk + + situation = { + "people": { + name: {variable: {period: value} for variable, value in inputs.items()} + for name, inputs in people.items() + }, + "benunits": {f"b_{name}": {"members": [name]} for name in people}, + "households": { + f"h_{name}": {"members": [name], "region": {period: region}} + for name in people + }, + } + return policyengine_uk.Simulation(situation=situation) + + +def _carers(weekly_pay, *, hours: float = 35.0) -> dict: + return { + f"carer_{index}": { + "age": 40, + "care_hours": hours, + "employment_income": pay * 52, + "would_claim_carers_allowance": True, + } + for index, pay in enumerate(weekly_pay) + } + + +def test_the_policy_is_the_engines_hours_condition_and_limit() -> None: + assert ca.uk_carers_allowance_policy(2024) == ca.UKCarersAllowancePolicy( + min_hours=35.0, + earnings_limit=151.0, + instant="2024-04-30", + source=( + f"policyengine-uk {metadata.version('policyengine-uk')} " + "gov.dwp.carers_allowance at 2024-04-30" + ), + ) + # The April 2025 rise the drawn carers reach in the baseline. + assert ca.uk_carers_allowance_policy(2025).earnings_limit == 196.0 + + +def test_the_hours_condition_is_the_engines() -> None: + policy = ca.uk_carers_allowance_policy(2024) + # The FRS care-hours band edges, and one hour under the line. + hours = [0.0, 5.0, 10.0, 20.0, 34.0, 35.0, 50.0, 100.0] + simulation = _simulation( + { + f"carer_{index}": { + "age": 40, + "care_hours": value, + "would_claim_carers_allowance": True, + } + for index, value in enumerate(hours) + }, + 2024, + ) + assert not np.asarray(simulation.calculate(_TEST, 2024)).any() + entitled = np.asarray(simulation.calculate("carers_allowance_pre_overlap", 2024)) + np.testing.assert_array_equal(entitled > 0, np.asarray(hours) >= policy.min_hours) + + +def test_the_earnings_limit_is_the_only_bar_left_for_a_non_reporting_carer() -> None: + policy = ca.uk_carers_allowance_policy(2024) + weekly_pay = np.asarray([100.0, 151.0, 152.0, 180.0, 196.0, 197.0, 400.0]) + survey = _simulation(_carers(weekly_pay), 2024) + gainful = np.asarray(survey.calculate(_TEST, 2024)) + # Below the personal allowance pay is its own net earnings; above it the + # engine's PAYE and Class 1 still leave 400 a week over the limit. + np.testing.assert_array_equal(gainful, weekly_pay > policy.earnings_limit) + entitled = np.asarray(survey.calculate("carers_allowance_pre_overlap", 2024)) + # For a 35-hour carer outside Scotland who would claim, the earnings test + # is the whole difference between entitled and not: the stage's eligible + # set is exactly the carers the limit alone keeps out. + np.testing.assert_array_equal(entitled > 0, ~gainful) + + # The April 2025 rise: carers between the two limits, eligible for the + # draw at the survey year, are entitled at 2025. + later = _simulation(_carers(weekly_pay), 2025) + entitled_2025 = np.asarray(later.calculate("carers_allowance_pre_overlap", 2025)) + rise = (weekly_pay > 151.0) & (weekly_pay <= 196.0) + assert rise.sum() == 3 + assert (entitled_2025[rise] > 0).all() + assert (entitled_2025[weekly_pay > 196.0] == 0).all() + + +def test_scotland_stays_closed_because_carer_support_payment_has_no_earnings_test() -> ( + None +): + simulation = _simulation(_carers([400.0]), 2025, region="SCOTLAND") + # The stage reads Scotland off the household region; the engine's country + # follows it. A top-level calculate returns the enum decoded. + country = simulation.calculate("country", 2025, decode_enums=True) + assert [str(value) for value in country] == ["SCOTLAND"] + assert np.asarray(simulation.calculate(_TEST, 2025)).all() + # Gainfully employed, yet paid Carer Support Payment once the flag is + # true: a draw in Scotland would pay it. + assert ( + np.asarray(simulation.calculate("carer_support_payment_pre_overlap", 2025))[0] + > 0 + ) + assert ( + np.asarray(simulation.calculate("carers_allowance_pre_overlap", 2025))[0] == 0 + ) + + +class _CertainContract: + """Every eligible carer claims, so the flags are the eligible set.""" + + def rate(self, key: str, build_year: int | None = None) -> float: + assert key == ca.CARERS_ALLOWANCE_NEWLY_ENTITLED_RATE_KEY + return 1.0 + + +def _frame(): + """Four 35-hour carers: over the limit in Wales and in Scotland, under it + in Wales, and a reporter.""" + + weekly_pay = np.asarray([165.0, 165.0, 120.0, 100.0]) + reported = np.asarray([0.0, 0.0, 0.0, 81.9 * 52]) + person = pd.DataFrame( + { + "person_id": [11, 21, 31, 41], + "person_benunit_id": [1, 2, 3, 4], + "person_household_id": [1, 2, 3, 4], + "age": [40.0, 40.0, 40.0, 40.0], + "employment_income": weekly_pay * 52, + "care_hours": [35.0, 35.0, 35.0, 35.0], + "carers_allowance_reported": reported, + "would_claim_carers_allowance": reported > 0, + } + ) + benunit = pd.DataFrame({"benunit_id": [1, 2, 3, 4]}) + household = pd.DataFrame( + { + "household_id": [1, 2, 3, 4], + "region": ["WALES", "SCOTLAND", "WALES", "WALES"], + "council_tax": [0.0] * 4, + "tenure_type": ["OWNED_OUTRIGHT"] * 4, + "rent": [0.0] * 4, + "household_source_id": [1, 2, 3, 4], + } + ) + return uk_national_frame( + person=person, + benunit=benunit, + household=household, + household_weights=np.ones(4), + weight_kind=WeightKind.DESIGN, + time_period="2024", + ) + + +def test_the_stage_reaches_the_carers_the_2025_rise_entitles() -> None: + engine = PolicyEngineUKEngine() + result = ca.redraw_carers_allowance_take_up( + _frame(), engine=engine, contract=_CertainContract() + ) + flag = result.frame.table("person")["would_claim_carers_allowance"].tolist() + assert flag == [True, False, False, True] + assert result.evidence()["weekly_earnings_limit"] == 151.0 + # Projected from the survey year as the released file is, the Welsh carer + # over the 2024-25 limit and under 2025-26's is entitled and would claim; + # before the stage the flag kept the allowance from them. + before = engine.materialize( + _frame(), ["carers_allowance_pre_overlap"], 2025, dataset_period=2024 + )["carers_allowance_pre_overlap"] + after = engine.materialize( + result.frame, ["carers_allowance_pre_overlap"], 2025, dataset_period=2024 + )["carers_allowance_pre_overlap"] + assert before[0] == 0 + assert after[0] > 0 + # Scotland and the carer under the limit who reports nothing stay unpaid. + assert after[1] == 0 + assert after[2] == 0 diff --git a/packages/microcosm-build/tests/engine_free/shared/test_country_spec.py b/packages/microcosm-build/tests/engine_free/shared/test_country_spec.py index f71d0909e..b30b2c4ff 100644 --- a/packages/microcosm-build/tests/engine_free/shared/test_country_spec.py +++ b/packages/microcosm-build/tests/engine_free/shared/test_country_spec.py @@ -1037,8 +1037,9 @@ def test_uk_source_manifest_contains_only_canonical_spine_stages(self) -> None: # microcosm#1240 high_value_home_support between them, microcosm#1112 # regional_home_values after it, and microcosm#1095 property_purchases # after property_components and uc_legacy_closure_take_up after - # uc_capital_coherence. - assert len(spec.sources.stages) == 45 + # uc_capital_coherence; microcosm#1319 carers_allowance_take_up after + # child_benefit_take_up. + assert len(spec.sources.stages) == 46 assert not {"frs_hmrc_retained_leaves", "hmrc_spi_income"}.intersection( stage.stage for stage in spec.sources.stages ) diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_carers_allowance_take_up.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_carers_allowance_take_up.py new file mode 100644 index 000000000..bef59a44f --- /dev/null +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_carers_allowance_take_up.py @@ -0,0 +1,564 @@ +"""Carer's Allowance claims by the carers the earnings limit keeps out +(microcosm#1319).""" + +from __future__ import annotations + +import itertools +from dataclasses import replace + +import numpy as np +import pandas as pd +import pytest + +from microcosm.build.country_spec import load_country_spec +from microcosm.build.stochastic_assignment import stable_identity_uniforms +from microcosm.build.uk_runtime import carers_allowance_take_up as ca +from microcosm.build.uk_runtime.frs_take_up import UK_TAKE_UP_SIGNAL_OUTPUTS +from microcosm.build.uk_runtime.national_frame import uk_national_frame +from microcosm.build.uk_runtime.take_up_contract import load_uk_take_up_contract +from microcosm.frame import WeightKind + +_LIMIT = 151.0 +_POLICY = ca.UKCarersAllowancePolicy( + min_hours=35.0, earnings_limit=_LIMIT, instant="2024-04-30", source="test" +) +_OUTPUT = ca.CARERS_ALLOWANCE_TAKE_UP_OUTPUT + + +class _Contract: + def __init__(self, rate: float = 0.6) -> None: + self._rate = rate + self.keys: list[str] = [] + + def rate(self, key: str, build_year: int | None = None) -> float: + self.keys.append(key) + return self._rate + + +class _StubEngine: + """The engine's earnings test: weekly pay above the limit.""" + + country = "uk" + + def __init__(self) -> None: + self.calls: list[tuple[tuple[str, ...], str, object]] = [] + + def materialize(self, frame, variables, period, *, dataset_period=None): + self.calls.append((tuple(variables), str(period), dataset_period)) + pay = frame.table("person")["employment_income"].to_numpy(dtype=float) + return {ca.CARERS_ALLOWANCE_EARNINGS_TEST: pay / 52.0 > _LIMIT} + + +def _frame( + *, + care_hours, + reported, + weekly_pay, + regions=None, + weights=None, + source_ids=None, + lineage: bool = True, + flag=None, + time_period: str = "2024", +): + """One person per benefit unit per household; ``source_ids`` makes support + copies (each household's own id by default), ``lineage=False`` drops them.""" + + n = len(care_hours) + ids = np.arange(1, n + 1, dtype="int64") + reported = np.asarray(reported, dtype=float) + person = pd.DataFrame( + { + "person_id": ids * 10 + 1, + "person_household_id": ids, + "person_benunit_id": ids, + "age": np.full(n, 45, dtype="int64"), + "care_hours": np.asarray(care_hours, dtype=float), + "carers_allowance_reported": reported, + "employment_income": np.asarray(weekly_pay, dtype=float) * 52.0, + _OUTPUT: reported > 0 if flag is None else np.asarray(flag, dtype=bool), + } + ) + benunit = pd.DataFrame({"benunit_id": ids}) + household = pd.DataFrame( + { + "household_id": ids, + "region": pd.array( + ["WALES"] * n if regions is None else list(regions), dtype="string" + ), + } + ) + if lineage: + household["household_source_id"] = ( + ids if source_ids is None else np.asarray(source_ids, dtype="int64") + ) + return uk_national_frame( + person=person, + benunit=benunit, + household=household, + time_period=time_period, + weight_kind=WeightKind.DESIGN, + household_weights=np.ones(n) if weights is None else np.asarray(weights), + ) + + +def _run(frame, *, rate: float = 0.6, engine: _StubEngine | None = None): + return ca.redraw_carers_allowance_take_up( + frame, + engine=engine or _StubEngine(), + contract=_Contract(rate), + policy=_POLICY, + ) + + +def _stage(): + return load_country_spec("uk").sources.stage_map()[ + ca.CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME + ] + + +def test_eligibility_is_hours_no_report_and_over_the_limit_outside_scotland() -> None: + rows = list( + itertools.product( + [False, True], [34.0, 35.0, 50.0], [False, True], [False, True] + ) + ) + scotland, hours, reported, gainful = ( + np.asarray(column) for column in zip(*rows, strict=True) + ) + eligible = ca.carers_allowance_eligible( + care_hours=hours, + reported=reported, + gainfully_employed=gainful, + scotland=scotland, + min_hours=35.0, + ) + np.testing.assert_array_equal( + eligible, ~scotland & (hours >= 35.0) & ~reported & gainful + ) + # 35 and 50 hours, outside Scotland, reporting nothing, over the limit. + assert int(eligible.sum()) == 2 + + +def _groups(): + """Carers on every side of each condition, a hundred or more in each.""" + + groups = { + # Over the limit, no report, outside Scotland: the only drawn group. + "eligible": dict(care=35.0, reported=0.0, pay=200.0, region="WALES", n=400), + "eligible_ni": dict( + care=50.0, reported=0.0, pay=250.0, region="NORTHERN_IRELAND", n=100 + ), + "reporter": dict(care=35.0, reported=81.9, pay=100.0, region="WALES", n=100), + "reporter_over_limit": dict( + care=35.0, reported=81.9, pay=200.0, region="LONDON", n=100 + ), + "under_limit": dict(care=35.0, reported=0.0, pay=120.0, region="WALES", n=100), + "at_limit": dict(care=35.0, reported=0.0, pay=_LIMIT, region="WALES", n=100), + "scotland": dict(care=35.0, reported=0.0, pay=200.0, region="SCOTLAND", n=100), + "scotland_reporter": dict( + care=35.0, reported=81.9, pay=100.0, region="SCOTLAND", n=100 + ), + "short_hours": dict(care=20.0, reported=0.0, pay=200.0, region="WALES", n=100), + } + labels = np.concatenate([[name] * spec["n"] for name, spec in groups.items()]) + + def column(key): + return np.concatenate([[spec[key]] * spec["n"] for spec in groups.values()]) + + frame = _frame( + care_hours=column("care"), + reported=column("reported"), + weekly_pay=column("pay"), + regions=column("region"), + ) + return frame, labels + + +def test_the_draw_opens_the_flag_to_the_eligible_carers_only() -> None: + frame, labels = _groups() + result = _run(frame) + person = result.frame.table("person") + flag = person[_OUTPUT].to_numpy() + for group in ("reporter", "reporter_over_limit", "scotland_reporter"): + assert flag[labels == group].all(), group + # Under or at the limit the survey records them entitled and not claiming; + # Scotland stays closed; 20 hours do not meet the condition. + for group in ("under_limit", "at_limit", "scotland", "short_hours"): + assert not flag[labels == group].any(), group + eligible = np.isin(labels, ["eligible", "eligible_ni"]) + uniforms = stable_identity_uniforms( + person["person_id"].to_numpy(), seed=0, salt=_OUTPUT + ) + np.testing.assert_array_equal(flag[eligible], uniforms[eligible] < 0.6) + assert 0.5 < flag[eligible].mean() < 0.7 + assert person[_OUTPUT].dtype == bool + # A flag only: every other cell, the weights and the mass log pass through. + before = frame.table("person").drop(columns=[_OUTPUT]) + pd.testing.assert_frame_equal(person.drop(columns=[_OUTPUT]), before) + assert result.frame.mass_log == frame.mass_log + np.testing.assert_array_equal( + result.frame.weights_for("household").values, + frame.weights_for("household").values, + ) + evidence = result.evidence() + assert evidence["stage"] == ca.CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME + assert evidence["scotland_closed"] is True + assert evidence["scotland_left_closed_support"] == "30+" + assert evidence["eligible_support"] == "30+" + assert evidence["eligible_weighted_persons"] == pytest.approx(500.0) + assert evidence["realized_share"] == pytest.approx(flag[eligible].mean()) + + +def test_the_engine_reads_the_earnings_test_on_the_frame_at_the_survey_year() -> None: + frame, _ = _groups() + engine = _StubEngine() + _run(frame, engine=engine) + # One consumed-only read on the frame's own values, never projected. + assert engine.calls == [((ca.CARERS_ALLOWANCE_EARNINGS_TEST,), "2024", None)] + + +def test_the_weighted_share_drawn_is_the_rate() -> None: + rng = np.random.default_rng(7) + n = 6_000 + pay = rng.uniform(80.0, 400.0, n) + care = rng.choice([0.0, 20.0, 35.0, 50.0, 100.0], n) + reported = np.where(rng.random(n) < 0.1, 81.9, 0.0) + regions = rng.choice(["WALES", "LONDON", "SCOTLAND", "NORTHERN_IRELAND"], n) + weights = rng.uniform(0.5, 3.0, n) + frame = _frame( + care_hours=care, + reported=reported, + weekly_pay=pay, + regions=regions, + weights=weights, + ) + result = _run(frame) + flag = result.frame.table("person")[_OUTPUT].to_numpy() + eligible = ( + (regions != "SCOTLAND") & (care >= 35.0) & (reported == 0.0) & (pay > _LIMIT) + ) + share = weights[eligible & flag].sum() / weights[eligible].sum() + assert share == pytest.approx(0.6, abs=0.03) + evidence = result.evidence() + assert evidence["realized_share"] == pytest.approx(share) + assert evidence["eligible_weighted_persons"] == pytest.approx( + weights[eligible].sum() + ) + assert evidence["rate"] == 0.6 + assert evidence["weekly_earnings_limit"] == _LIMIT + assert evidence["min_hours"] == 35.0 + + +def test_draws_are_keyed_by_person_identity() -> None: + frame, _ = _groups() + first = _run(frame).frame.table("person")[_OUTPUT] + again = _run(frame).frame.table("person")[_OUTPUT] + pd.testing.assert_series_equal(first, again) + # A person's uniform reads its own id, so the stream does not depend on + # which other people the frame carries. + ids = frame.table("person")["person_id"].to_numpy() + subset = ids[np.random.default_rng(3).random(len(ids)) < 0.5] + full = pd.Series(stable_identity_uniforms(ids, seed=0, salt=_OUTPUT), index=ids) + np.testing.assert_array_equal( + full.loc[subset].to_numpy(), + stable_identity_uniforms(subset, seed=0, salt=_OUTPUT), + ) + + +def test_the_receipt_bands_support_copies_on_their_sources() -> None: + # UKDS disclosure control: twelve support copies of three source + # households carry nothing above "<10", however many rows copy them. + n = 12 + frame = _frame( + care_hours=np.full(n, 35.0), + reported=np.zeros(n), + weekly_pay=np.full(n, 300.0), + source_ids=np.arange(n) % 3, + ) + evidence = _run(frame, rate=1.0).evidence() + assert evidence["eligible_support"] == "<10" + assert evidence["eligible_weighted_persons"] == "<10" + assert evidence["drawn_support"] == "<10" + assert evidence["realized_share"] == "<10" + + +def test_the_share_hides_a_small_side() -> None: + # Forty eligible carers on forty sources, three of them drawn: the share + # times the eligible weight would give the three carers' weight back. + n = 40 + frame = _frame( + care_hours=np.full(n, 35.0), + reported=np.zeros(n), + weekly_pay=np.full(n, 300.0), + ) + uniforms = np.sort( + stable_identity_uniforms( + frame.table("person")["person_id"].to_numpy(), seed=0, salt=_OUTPUT + ) + ) + result = _run(frame, rate=float((uniforms[2] + uniforms[3]) / 2)) + assert int(result.frame.table("person")[_OUTPUT].sum()) == 3 + evidence = result.evidence() + assert evidence["eligible_support"] == "30+" + assert evidence["eligible_weighted_persons"] == pytest.approx(40.0) + assert evidence["drawn_support"] == "<10" + assert evidence["realized_share"] == "<10" + # All but three drawn: the share would give the three undrawn carers' + # weight back the same way. + result = _run(frame, rate=float((uniforms[36] + uniforms[37]) / 2)) + assert int(result.frame.table("person")[_OUTPUT].sum()) == 37 + evidence = result.evidence() + assert evidence["drawn_support"] == "30+" + assert evidence["realized_share"] == "<10" + + +def test_households_are_read_through_membership_not_position() -> None: + # Two people to a household, the person table shuffled against the + # households (group tables stay sorted by id), and a region, a weight and + # a lineage of each household's own: a positional read puts a carer in + # the wrong household. + rng = np.random.default_rng(11) + household_ids = np.arange(1001, 1025) + regions = np.asarray(["SCOTLAND", "WALES", "NORTHERN_IRELAND"] * 8) + weights = 1.0 + np.arange(24, dtype=float) + pay = np.r_[np.full(24, 300.0), np.full(24, 100.0)] + person = pd.DataFrame( + { + "person_id": np.r_[household_ids * 10 + 1, household_ids * 10 + 2], + "person_household_id": np.r_[household_ids, household_ids], + "person_benunit_id": np.r_[household_ids, household_ids], + "age": np.full(48, 45, dtype="int64"), + # The first member cares 35 hours over the limit; the second does + # not care. + "care_hours": np.r_[np.full(24, 35.0), np.zeros(24)], + "carers_allowance_reported": np.zeros(48), + "employment_income": pay * 52.0, + _OUTPUT: np.zeros(48, dtype=bool), + } + ).iloc[rng.permutation(48)] + household = pd.DataFrame( + { + "household_id": household_ids, + "region": pd.array(regions, dtype="string"), + "household_source_id": household_ids * 10, + } + ) + frame = uk_national_frame( + person=person.reset_index(drop=True), + benunit=pd.DataFrame({"benunit_id": household_ids}), + household=household, + time_period="2024", + weight_kind=WeightKind.DESIGN, + household_weights=weights, + ) + result = _run(frame, rate=1.0) + out = result.frame.table("person") + region_of = dict(zip(household_ids, regions, strict=True)) + scottish = out["person_household_id"].map(region_of).eq("SCOTLAND").to_numpy() + carer = out["care_hours"].to_numpy() >= 35.0 + np.testing.assert_array_equal(out[_OUTPUT].to_numpy(), carer & ~scottish) + evidence = result.evidence() + # Sixteen households outside Scotland, one eligible carer in each. + assert evidence["eligible_weighted_persons"] == pytest.approx( + weights[regions != "SCOTLAND"].sum() + ) + assert evidence["eligible_support"] == "10-29" + assert evidence["realized_share"] == 1.0 + assert evidence["scotland_left_closed_support"] == "<10" + + +def test_a_frame_without_eligible_carers_draws_nothing() -> None: + frame = _frame( + care_hours=np.full(3, 35.0), + reported=np.array([81.9, 0.0, 0.0]), + weekly_pay=np.array([100.0, 100.0, 120.0]), + ) + result = _run(frame) + assert result.frame.table("person")[_OUTPUT].tolist() == [True, False, False] + evidence = result.evidence() + assert evidence["eligible_support"] == 0 + assert evidence["eligible_weighted_persons"] == 0.0 + assert evidence["realized_share"] is None + + +@pytest.mark.parametrize("period", ["2023", "2025", "2024-25"]) +def test_the_stage_refuses_a_frame_off_the_survey_year(period) -> None: + frame = _frame( + care_hours=np.full(3, 35.0), + reported=np.zeros(3), + weekly_pay=np.full(3, 300.0), + time_period=period, + ) + engine = _StubEngine() + # The earnings test is read at the survey year's limit on the frame's own + # values: another year, or a fiscal-year label, is refused by name. + with pytest.raises(ValueError, match="survey_year 2024"): + _run(frame, engine=engine) + assert engine.calls == [] + + +def test_the_stage_refuses_a_frame_without_lineage() -> None: + frame = _frame( + care_hours=np.full(3, 35.0), + reported=np.zeros(3), + weekly_pay=np.full(3, 300.0), + lineage=False, + ) + with pytest.raises(ValueError, match="household_source_id"): + _run(frame) + + +def test_the_stage_refuses_a_null_lineage() -> None: + frame = _frame( + care_hours=np.full(3, 35.0), + reported=np.zeros(3), + weekly_pay=np.full(3, 300.0), + ) + frame.table("household")["household_source_id"] = pd.array( + [1, None, 3], dtype="Int64" + ) + # A null would drop out of a distinct count or count as one source. + with pytest.raises(ValueError, match="null"): + _run(frame) + + +def test_the_stage_refuses_a_flag_that_left_reported_receipt() -> None: + frame = _frame( + care_hours=np.full(3, 35.0), + reported=np.array([81.9, 0.0, 0.0]), + weekly_pay=np.full(3, 100.0), + flag=np.array([True, True, False]), + ) + engine = _StubEngine() + # The stage rebuilds the flag from reported receipt, so it refuses to + # overwrite another writer's flag. + with pytest.raises(ValueError, match="must arrive as reported receipt"): + _run(frame, engine=engine) + assert engine.calls == [] + + +def test_the_stage_refuses_missing_inputs() -> None: + frame = _frame( + care_hours=np.full(3, 35.0), + reported=np.zeros(3), + weekly_pay=np.full(3, 300.0), + ) + person = frame.table("person").drop(columns=["care_hours"]) + reduced = uk_national_frame( + person=person, + benunit=frame.table("benunit"), + household=frame.table("household"), + time_period="2024", + weight_kind=WeightKind.DESIGN, + household_weights=np.ones(3), + ) + with pytest.raises(ValueError, match=r"person columns missing: \['care_hours'\]"): + _run(reduced) + + +def test_the_transform_runs_the_packaged_stage_at_the_contract_rate() -> None: + transform = ca.UKCarersAllowanceTakeUpStageTransform( + stage=_stage(), engine=_StubEngine(), policy=_POLICY + ) + with pytest.raises(RuntimeError, match="completed stage run"): + transform.checkpoint_metadata() + frame, _ = _groups() + result = transform(frame) + assert transform.output_columns() == () + evidence = transform.checkpoint_metadata()["evidence"] + assert evidence["stage"] == ca.CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME + assert evidence["rate_key"] == ca.CARERS_ALLOWANCE_NEWLY_ENTITLED_RATE_KEY + assert evidence["rate"] == 0.6 + assert evidence["eligibility"] == ca.CARERS_ALLOWANCE_ELIGIBILITY + assert result.table("person")[_OUTPUT].any() + + +def test_the_packaged_stage_carries_the_reviewed_operations_in_order() -> None: + stage = _stage() + # Closed world: the transform refuses any drift from the code's constants. + ca._assert_stage_parameters(stage) + assert stage.grain == "person" + assert stage.outputs == () + assert stage.rewrites == (_OUTPUT,) + materialize, assign = stage.operations + assert tuple(materialize.parameters["predictors"]) == ( + ca.CARERS_ALLOWANCE_ENGINE_VARIABLES + ) + assert assign.parameters["rate_key"] == ca.CARERS_ALLOWANCE_NEWLY_ENTITLED_RATE_KEY + assert assign.parameters["seed"] == 0 + order = [stage.stage for stage in load_country_spec("uk").sources.stages] + position = order.index(ca.CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME) + # After the SPI income chain and the other take-up redraws, before the + # deduction attributes and every CGT clone. + assert order[position - 1] == "child_benefit_take_up" + assert order[position + 1] == "uc_deduction_attributes" + assert position > order.index("hmrc_spi_income_spine") + assert position < order.index("cgt_support_split") + + +def test_a_drifted_manifest_is_refused() -> None: + stage = _stage() + operations = tuple( + replace( + operation, + parameters={**operation.parameters, "rate_key": "pension_credit"}, + ) + if operation.kind == "assign_binary_from_rate" + else operation + for operation in stage.operations + ) + transform = ca.UKCarersAllowanceTakeUpStageTransform( + stage=replace(stage, operations=operations), + engine=_StubEngine(), + policy=_POLICY, + ) + frame, _ = _groups() + with pytest.raises(ValueError, match="parameters drifted"): + transform(frame) + with pytest.raises(ValueError, match="exactly the rewrite"): + ca._assert_stage_parameters(replace(stage, rewrites=())) + + +def test_the_contract_carries_the_newly_entitled_rate() -> None: + contract = load_uk_take_up_contract() + entry = contract.entry(ca.CARERS_ALLOWANCE_NEWLY_ENTITLED_RATE_KEY) + assert contract.rate(entry.key) == 0.6 + assert entry.raw["output"] == _OUTPUT + assert entry.raw["entity"] == "person" + # No published take-up rate exists for newly entitled carers: the value + # is a ruling, and the back-test against the Independent Review's 61,000 + # is its follow-up. + assert entry.source["status"] == "frozen_by_adjudication" + assert entry.source["freeze"]["followup"] == "microcosm#1319" + + +def test_the_flag_stays_out_of_the_terminal_signal_gate() -> None: + assert all(output != _OUTPUT for _, output, _ in UK_TAKE_UP_SIGNAL_OUTPUTS) + + +def test_the_graph_node_reads_the_lineage_and_rewrites_the_flag_on_its_own_boundary() -> ( + None +): + from microcosm.build.uk_runtime.graph import uk_spine_graph + + graph = uk_spine_graph(source_mode="split") + node = graph.node(ca.CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME) + inputs = { + (slice_.entity, column) for slice_ in node.inputs for column in slice_.columns + } + # An open surface: the receipt's lineage and the eligibility's inputs + # reach the stage in a graph build. + assert { + ("household", "household_source_id"), + ("household", "region"), + ("person", "care_hours"), + ("person", "carers_allowance_reported"), + } <= inputs + assert [ + (owned.entity, owned.column, owned.dtype, owned.rewrite) + for owned in node.outputs + ] == [("person", _OUTPUT, "bool", True)] + # The open-surface readers before it bind the incumbent flag, so the + # rewrite runs on a boundary of its own. + assert node.population == f"{ca.CARERS_ALLOWANCE_TAKE_UP_STAGE_NAME}.boundary" diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_graph.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_graph.py index 28a774fb0..55190d99b 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_graph.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_graph.py @@ -56,9 +56,9 @@ def test_uk_spine_graph_contains_every_manifest_stage() -> None: # microcosm#1095 the spi_benefit_coherence pass after uc_reporter_redraw, # microcosm#1106 property_components after the regional uprating, and # microcosm#1240 high_value_home_support between those two; microcosm#1095 - # adds property_purchases and uc_legacy_closure_take_up, and microcosm#1112 - # regional_home_values. - assert len(expected) == 45 + # adds property_purchases and uc_legacy_closure_take_up, microcosm#1112 + # regional_home_values, and microcosm#1319 carers_allowance_take_up. + assert len(expected) == 46 assert {"frs_hmrc_retained_leaves", "hmrc_spi_income"}.isdisjoint(expected) assert set(expected) <= ids assert {"frs_hmrc_retained_leaves", "hmrc_spi_income"}.isdisjoint(ids) diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_source_stages.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_source_stages.py index 83197aaf2..d4db01464 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_source_stages.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_source_stages.py @@ -90,6 +90,11 @@ CHILD_BENEFIT_TAKE_UP_STAGE_NAMES = [ "child_benefit_take_up", ] +# microcosm#1319: the Carer's Allowance draw reads the post-SPI earnings and +# the anchor the SPI income chain refreshes. +CARERS_ALLOWANCE_TAKE_UP_STAGE_NAMES = [ + "carers_allowance_take_up", +] E9_STAGE_NAMES = [ "uc_deduction_attributes", ] @@ -124,6 +129,7 @@ *UC_LEGACY_CLOSURE_TAKE_UP_STAGE_NAMES, *PENSION_CREDIT_TAKE_UP_STAGE_NAMES, *CHILD_BENEFIT_TAKE_UP_STAGE_NAMES, + *CARERS_ALLOWANCE_TAKE_UP_STAGE_NAMES, *E9_STAGE_NAMES, *E8_STAGE_NAMES, ] @@ -196,6 +202,7 @@ def test_e5_and_e6_follow_e7_and_precede_the_uc_rewrites(self) -> None: *UC_LEGACY_CLOSURE_TAKE_UP_STAGE_NAMES, *PENSION_CREDIT_TAKE_UP_STAGE_NAMES, *CHILD_BENEFIT_TAKE_UP_STAGE_NAMES, + *CARERS_ALLOWANCE_TAKE_UP_STAGE_NAMES, *E9_STAGE_NAMES, ] @@ -275,6 +282,7 @@ def test_country_stage_plan_assembles_spine_plan(self) -> None: "uc_legacy_closure_take_up": _identity, "pension_credit_take_up": _identity, "child_benefit_take_up": _identity, + "carers_allowance_take_up": _identity, "uc_deduction_attributes": _identity, "cgt_support_split": _identity, "cgt_incidence_clone": _identity, diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_spine_acceptance_receipt.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_spine_acceptance_receipt.py index 0c788ac62..fac9c8881 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_spine_acceptance_receipt.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_spine_acceptance_receipt.py @@ -139,6 +139,10 @@ def _apply_pending_roster_transformations( # post-SPI incomes, right after the Pension Credit redraw. assert "child_benefit_take_up" not in roster roster.insert(roster.index("pension_credit_take_up") + 1, "child_benefit_take_up") + # microcosm#1319 re-mint pending: the Carer's Allowance draw reads the + # post-SPI earnings, right after the Child Benefit redraw. + assert "carers_allowance_take_up" not in roster + roster.insert(roster.index("child_benefit_take_up") + 1, "carers_allowance_take_up") # microcosm#1095 re-mint pending: the SPI benefit pass runs after the last # UC report writer and before every UC, PC and CB consumer. assert "spi_benefit_coherence" not in roster diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_take_up_contract.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_take_up_contract.py index 60c859b98..c7919297f 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_take_up_contract.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_take_up_contract.py @@ -21,6 +21,7 @@ def test_uk_contract_loads_and_selects_build_year_rates() -> None: "pension_credit_guarantee_credit", "pension_credit_savings_credit_only", "pension_credit_newly_entitled", + "carers_allowance_newly_entitled", "universal_credit", "marriage_allowance", "tax_free_childcare", @@ -39,6 +40,8 @@ def test_uk_contract_loads_and_selects_build_year_rates() -> None: 0.69, 0.37, 0.37, + # microcosm#1319: María's ruling of 2026-10-20. + 0.6, 0.55, 0.5, # microcosm#1095 U2c: the v4 refit on the policyengine-uk 2.132.6 spine. diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_uc_capital_coherence.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_uc_capital_coherence.py index 07920245a..9317d19f2 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_uc_capital_coherence.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_uc_capital_coherence.py @@ -64,15 +64,16 @@ def test_stage_orders_after_every_universal_credit_report_writer() -> None: assert reporter_writers assert all(index < coherence_index for index, _ in reporter_writers) # The Move to UC claim draw (microcosm#1095), the Pension Credit take-up - # redraw (microcosm#1069 c7) and the Child Benefit redraw (microcosm#1063 - # c8) sit between the coherence stage and the deduction attributes; none - # writes a UC report. + # redraw (microcosm#1069 c7), the Child Benefit redraw (microcosm#1063 c8) + # and the Carer's Allowance draw (microcosm#1319) sit between the + # coherence stage and the deduction attributes; none writes a UC report. assert [ - stage.stage for stage in stages[coherence_index + 1 : coherence_index + 5] + stage.stage for stage in stages[coherence_index + 1 : coherence_index + 6] ] == [ "uc_legacy_closure_take_up", "pension_credit_take_up", "child_benefit_take_up", + "carers_allowance_take_up", "uc_deduction_attributes", ] diff --git a/packages/microcosm-frame/src/microcosm/frame/adapters/policyengine_uk_concepts.py b/packages/microcosm-frame/src/microcosm/frame/adapters/policyengine_uk_concepts.py index 807f5b496..93c722bef 100644 --- a/packages/microcosm-frame/src/microcosm/frame/adapters/policyengine_uk_concepts.py +++ b/packages/microcosm-frame/src/microcosm/frame/adapters/policyengine_uk_concepts.py @@ -80,8 +80,10 @@ "Whether this person would claim Carer's Allowance (or the Scottish " "Carer Support Payment) if entitled. Generated in a dataset from " "reported receipt ...", - "The UK build sets it from reported receipt (frs_spine.py). No concept " - "carries that receipt, so a seed threshold stands in for it.", + "The UK build sets it from reported receipt (frs_spine.py) and opens it " + "at one rate to carers the earnings limit alone keeps from the allowance " + "(carers_allowance_take_up.py). No concept carries that receipt, so a " + "seed threshold stands in for it.", ), "childcare_grant": ( "Whether this person would claim Childcare Grant if eligible.", diff --git a/tools/graph_uk_spine_fixture.py b/tools/graph_uk_spine_fixture.py index 00fe2a760..c18225b62 100644 --- a/tools/graph_uk_spine_fixture.py +++ b/tools/graph_uk_spine_fixture.py @@ -28,6 +28,9 @@ from microcosm.build.country_spec import country_stage_plan, load_country_spec from microcosm.build.source_manifest import SourceManifest, SourceStageSpec from microcosm.build.uk_runtime.age_tail import UKAgeTailStageTransform +from microcosm.build.uk_runtime.carers_allowance_take_up import ( + UKCarersAllowanceTakeUpStageTransform, +) from microcosm.build.uk_runtime.cgt_asset_type import ( CGT_ASSET_TYPE_NON_RESIDENTIAL_TYPES, CGT_ASSET_TYPE_RESIDENTIAL, @@ -195,7 +198,7 @@ _SPI_DONOR_SAMPLE_SIZE = 64 #: The packaged FRS spine roster the fixture exercises (manifest minus the #: certified-pair exclusions); moves whenever a spine stage is added. -UK_FIXTURE_STAGE_COUNT = 45 +UK_FIXTURE_STAGE_COUNT = 46 _QRF_ESTIMATORS = 4 # These are the complete object-string surface observed in the unchanged @@ -417,6 +420,12 @@ def _frs_tables() -> dict[str, pd.DataFrame]: "HBOTHAMT": 0.0, } ) + # HOURTOT care bands: every fifth adult cares 35-49 hours a week (code + # 5) and every seventh other 20-34 (code 4, below the Carer's Allowance + # line). Pay (INEARNS) rises with the household, so the carers fall on + # both sides of the earnings limit, in Scotland and outside it + # (microcosm#1319). + care_band = 5 if household_id % 5 == 1 else 4 if household_id % 7 == 0 else 0 adult = { "SERNUM": household_id, "BENUNIT": 1, @@ -490,6 +499,7 @@ def _frs_tables() -> dict[str, pd.DataFrame]: "GRTDIR1": 2.0, "GRTDIR2": 3.0, "HEARTVAL": 5.0, + "HOURTOT": care_band, } adults.append(adult) if has_child: @@ -567,6 +577,22 @@ def _frs_tables() -> dict[str, pd.DataFrame]: (3, 0, 7.0), ) ) + if household_id % 15 == 1: + # Carer's Allowance (BENEFIT 13) on every third 35-hour carer, at + # the 2024-25 weekly rate (microcosm#1319). + benefits.append( + { + "SERNUM": household_id, + "BENUNIT": 1, + "PERSON": 1, + "BENEFIT": 13, + "VAR2": 0, + "VAR3": 0, + "BENAMT": 81.9, + "UCSTART": "", + "UCHOUSEL": "", + } + ) if household_id % 3 == 0: # Universal Credit on every third household: a claim linked to a # recent start, one linked to an old start, and one unlinked. @@ -2041,6 +2067,11 @@ def capture_root(frame: Frame) -> Frame: "child_benefit_take_up": UKChildBenefitTakeUpStageTransform( stage=stages["child_benefit_take_up"], engine=engine ), + "carers_allowance_take_up": UKCarersAllowanceTakeUpStageTransform( + stage=stages["carers_allowance_take_up"], + engine=engine, + contract=contract, + ), "uc_deduction_attributes": UKUCDeductionAttributesStageTransform( stage=stages["uc_deduction_attributes"] ), From 366a1362bb22277efdcf6d440e0386a63a29ff12 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 13:55:01 +0100 Subject: [PATCH 12/21] Keep band receipts and exclusion reasons aggregate-only - The SPI band-donor receipt records a band's mean realised total income only where its carriers drew at least ten distinct tape records, and "<10" otherwise. - Twenty-three measure-exclusion reasons (the 1m-and-over and 500k-1m HMRC band cells, and the benefit-cap amount bands) are restated in aggregate terms. Their meaning, decisions and windows are unchanged. - hmrc_spi_income_spine binds spi_income as a helper module, so an edit there moves the stage's implementation hash, as it already did for property_components. A test holds both. Co-Authored-By: Claude Opus 5.5 --- .../uk/calibration_measure_exclusions.json | 46 +++++++++---------- .../build/uk_runtime/graph_kernels.py | 3 ++ .../microcosm/build/uk_runtime/spi_income.py | 30 ++++++++---- .../tests/engine_free/uk/test_uk_graph.py | 29 ++++++++++++ .../engine_free/uk/test_uk_spi_band_donors.py | 36 +++++++++------ 5 files changed, 100 insertions(+), 44 deletions(-) diff --git a/packages/microcosm-build/src/microcosm/build/uk/calibration_measure_exclusions.json b/packages/microcosm-build/src/microcosm/build/uk/calibration_measure_exclusions.json index f10bc6362..3d7f58de3 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/calibration_measure_exclusions.json +++ b/packages/microcosm-build/src/microcosm/build/uk/calibration_measure_exclusions.json @@ -21,7 +21,7 @@ "exclusions": [ { "name": "hmrc/employment_income_income_band_1_000_000_to_inf", - "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries capital gains to 20.4m and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", + "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries large capital gains and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", "tracking": "microcosm#757", "approved_by": "juaristi22", "adjudication": "microcosm#757 (the uk_target_fit dispositions, issue comment 5427936411); reason revised 2026-08-28 per microcosm#807 (the spine-i/j excluded-cell support re-measurement)", @@ -30,7 +30,7 @@ }, { "name": "hmrc/dividend_income_income_band_1_000_000_to_inf", - "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries capital gains to 20.4m and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", + "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries large capital gains and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", "tracking": "microcosm#757", "approved_by": "juaristi22", "adjudication": "microcosm#757 (the uk_target_fit dispositions, issue comment 5427936411); reason revised 2026-08-28 per microcosm#807 (the spine-i/j excluded-cell support re-measurement)", @@ -39,7 +39,7 @@ }, { "name": "hmrc/dividend_income_count_income_band_1_000_000_to_inf", - "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries capital gains to 20.4m and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", + "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries large capital gains and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", "tracking": "microcosm#757", "approved_by": "juaristi22", "adjudication": "microcosm#757 (the uk_target_fit dispositions, issue comment 5427936411); reason revised 2026-08-28 per microcosm#807 (the spine-i/j excluded-cell support re-measurement)", @@ -48,7 +48,7 @@ }, { "name": "hmrc/property_income_count_income_band_1_000_000_to_inf", - "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries capital gains to 20.4m and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", + "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries large capital gains and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", "tracking": "microcosm#757", "approved_by": "juaristi22", "adjudication": "microcosm#757 (the uk_target_fit dispositions, issue comment 5427936411); reason revised 2026-08-28 per microcosm#807 (the spine-i/j excluded-cell support re-measurement)", @@ -57,7 +57,7 @@ }, { "name": "hmrc/private_pension_income_income_band_1_000_000_to_inf", - "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries capital gains to 20.4m and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", + "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries large capital gains and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", "tracking": "microcosm#757", "approved_by": "juaristi22", "adjudication": "microcosm#757 (the uk_target_fit dispositions, issue comment 5427936411); reason revised 2026-08-28 per microcosm#807 (the spine-i/j excluded-cell support re-measurement)", @@ -66,7 +66,7 @@ }, { "name": "hmrc/private_pension_income_count_income_band_1_000_000_to_inf", - "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries capital gains to 20.4m and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", + "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries large capital gains and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", "tracking": "microcosm#757", "approved_by": "juaristi22", "adjudication": "microcosm#757 (the uk_target_fit dispositions, issue comment 5427936411); reason revised 2026-08-28 per microcosm#807 (the spine-i/j excluded-cell support re-measurement)", @@ -75,7 +75,7 @@ }, { "name": "hmrc/state_pension_income_band_1_000_000_to_inf", - "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries capital gains to 20.4m and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", + "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries large capital gains and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", "tracking": "microcosm#757", "approved_by": "juaristi22", "adjudication": "microcosm#757 (the uk_target_fit dispositions, issue comment 5427936411); reason revised 2026-08-28 per microcosm#807 (the spine-i/j excluded-cell support re-measurement)", @@ -84,7 +84,7 @@ }, { "name": "hmrc/state_pension_count_income_band_1_000_000_to_inf", - "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries capital gains to 20.4m and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", + "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m, under both the SPI assessable-income concept and the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries large capital gains and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", "tracking": "microcosm#757", "approved_by": "juaristi22", "adjudication": "microcosm#757 (the uk_target_fit dispositions, issue comment 5427936411); reason revised 2026-08-28 per microcosm#807 (the spine-i/j excluded-cell support re-measurement)", @@ -93,7 +93,7 @@ }, { "name": "hmrc/self_employment_income_income_band_1_000_000_to_inf", - "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): 0 in-band carrier records with total income above 1m under the SPI assessable-income concept and 2 under the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries capital gains to 20.4m and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", + "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m under the SPI assessable-income concept and fewer than ten under the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries large capital gains and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", "tracking": "microcosm#757", "approved_by": "juaristi22", "adjudication": "microcosm#757 (the uk_target_fit dispositions, issue comment 5427936411); reason revised 2026-08-28 per microcosm#807 (the spine-i/j excluded-cell support re-measurement)", @@ -102,7 +102,7 @@ }, { "name": "hmrc/self_employment_income_count_income_band_1_000_000_to_inf", - "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): 0 in-band carrier records with total income above 1m under the SPI assessable-income concept and 2 under the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries capital gains to 20.4m and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", + "reason": "Zero-support channel on total income (ITA 2007 s.23, which excludes capital gains): zero in-band carrier records with total income above 1m under the SPI assessable-income concept and fewer than ten under the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807, receipts uk-candidate-eval out/excluded_cell_support_spine_{i,j}.json). The spine carries large capital gains and thousands of records above 1m wealth; the premise is total-income support, never a wealth or gains cap, and a zero-support cell cannot be reached by reweighting.", "tracking": "microcosm#757", "approved_by": "juaristi22", "adjudication": "microcosm#757 (the uk_target_fit dispositions, issue comment 5427936411); reason revised 2026-08-28 per microcosm#807 (the spine-i/j excluded-cell support re-measurement)", @@ -264,7 +264,7 @@ }, { "name": "hmrc/dividend_income_income_band_500_000_to_1_000_000", - "reason": "Sparse cell support: 6 in-band carrier records under the SPI assessable-income concept and 10 under the component-sum proxy (6,914 weighted carriers), measured identically on spine-i and spine-j (microcosm#807) - too few for the solver to hit the published value without distorting neighbouring cells. One of the three thin 500k-1m cells retained when the microcosm#807 revision lifted the three mid-band cells whose measured support was in the hundreds; re-measure on the next spine build before renewal.", + "reason": "Sparse cell support: fewer than ten in-band carrier records under the SPI assessable-income concept and a similarly thin count under the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807) - too few for the solver to hit the published value without distorting neighbouring cells. One of the three thin 500k-1m cells retained when the microcosm#807 revision lifted the three mid-band cells whose measured support was in the hundreds; re-measure on the next spine build before renewal.", "tracking": "microcosm#757", "approved_by": "juaristi22", "adjudication": "microcosm#757 (the uk_target_fit dispositions, issue comment 5427936411); reason revised 2026-08-28 per microcosm#807 (the spine-i/j excluded-cell support re-measurement)", @@ -273,7 +273,7 @@ }, { "name": "hmrc/property_income_count_income_band_500_000_to_1_000_000", - "reason": "Sparse cell support: 2 in-band carrier records under the SPI assessable-income concept and 8 under the component-sum proxy (3,430 weighted carriers), measured identically on spine-i and spine-j (microcosm#807) - too few for the solver to hit the published value without distorting neighbouring cells. One of the three thin 500k-1m cells retained when the microcosm#807 revision lifted the three mid-band cells whose measured support was in the hundreds; re-measure on the next spine build before renewal.", + "reason": "Sparse cell support: fewer than ten in-band carrier records under the SPI assessable-income concept and under the component-sum proxy, measured identically on spine-i and spine-j (microcosm#807) - too few for the solver to hit the published value without distorting neighbouring cells. One of the three thin 500k-1m cells retained when the microcosm#807 revision lifted the three mid-band cells whose measured support was in the hundreds; re-measure on the next spine build before renewal.", "tracking": "microcosm#757", "approved_by": "juaristi22", "adjudication": "microcosm#757 (the uk_target_fit dispositions, issue comment 5427936411); reason revised 2026-08-28 per microcosm#807 (the spine-i/j excluded-cell support re-measurement)", @@ -390,7 +390,7 @@ }, { "name": "dwp.benefit_cap.capped_households_100_01_to_200", - "reason": "Support, not a weight question (#882): the benefit-cap amount band 100 .01 to 200 measures 6,689 against 24,274 (-72 percent) on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty and 14.2 percent of capped units sit above GBP 1,300 a month against 0.6 percent published, a tail of large families outside London (4.45 children on average, full child elements, housing element near GBP 1,350 a month). The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", + "reason": "Support, not a weight question (#882): the benefit-cap amount band 100 .01 to 200 measures far below its published count, outside the 25 percent bound on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty, and the share of capped units above GBP 1,300 a month is many times the published 0.6 percent, a tail of large families outside London on full child elements and large housing elements. The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", "tracking": "microcosm#882", "approved_by": "juaristi22", "adjudication": "microcosm#882 (the 2026-09-16 status comment, issuecomment-5694598278, whose next-steps list this repair works, and the repairs plan María approved on 2026-09-16 with her population ruling on the U8 take-up entry; approver as author per the register convention). Expiry 2026-12-08 aligns the whole UC-repair tranche with the zero-band clock already on the register (microcosm#877), so the next spine re-adjudicates them together. Receipts: experiments/882-uc-repairs-receipts.md (R2 and R5, tools/diagnose_uk_benefit_cap.py on the Q50f candidate and the twins).", @@ -399,7 +399,7 @@ }, { "name": "dwp.benefit_cap.capped_households_300_01_to_400", - "reason": "Support, not a weight question (#882): the benefit-cap amount band 300 .01 to 400 measures 3,118 against 10,562 (-70 percent) on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty and 14.2 percent of capped units sit above GBP 1,300 a month against 0.6 percent published, a tail of large families outside London (4.45 children on average, full child elements, housing element near GBP 1,350 a month). The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", + "reason": "Support, not a weight question (#882): the benefit-cap amount band 300 .01 to 400 measures far below its published count, outside the 25 percent bound on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty, and the share of capped units above GBP 1,300 a month is many times the published 0.6 percent, a tail of large families outside London on full child elements and large housing elements. The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", "tracking": "microcosm#882", "approved_by": "juaristi22", "adjudication": "microcosm#882 (the 2026-09-16 status comment, issuecomment-5694598278, whose next-steps list this repair works, and the repairs plan María approved on 2026-09-16 with her population ruling on the U8 take-up entry; approver as author per the register convention). Expiry 2026-12-08 aligns the whole UC-repair tranche with the zero-band clock already on the register (microcosm#877), so the next spine re-adjudicates them together. Receipts: experiments/882-uc-repairs-receipts.md (R2 and R5, tools/diagnose_uk_benefit_cap.py on the Q50f candidate and the twins).", @@ -408,7 +408,7 @@ }, { "name": "dwp.benefit_cap.capped_households_500_01_to_600", - "reason": "Support, not a weight question (#882): the benefit-cap amount band 500 .01 to 600 measures 8,267 against 4,431 (+87 percent) on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty and 14.2 percent of capped units sit above GBP 1,300 a month against 0.6 percent published, a tail of large families outside London (4.45 children on average, full child elements, housing element near GBP 1,350 a month). The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", + "reason": "Support, not a weight question (#882): the benefit-cap amount band 500 .01 to 600 measures far above its published count, outside the 25 percent bound on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty, and the share of capped units above GBP 1,300 a month is many times the published 0.6 percent, a tail of large families outside London on full child elements and large housing elements. The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", "tracking": "microcosm#882", "approved_by": "juaristi22", "adjudication": "microcosm#882 (the 2026-09-16 status comment, issuecomment-5694598278, whose next-steps list this repair works, and the repairs plan María approved on 2026-09-16 with her population ruling on the U8 take-up entry; approver as author per the register convention). Expiry 2026-12-08 aligns the whole UC-repair tranche with the zero-band clock already on the register (microcosm#877), so the next spine re-adjudicates them together. Receipts: experiments/882-uc-repairs-receipts.md (R2 and R5, tools/diagnose_uk_benefit_cap.py on the Q50f candidate and the twins).", @@ -417,7 +417,7 @@ }, { "name": "dwp.benefit_cap.capped_households_600_01_to_700", - "reason": "Support, not a weight question (#882): the benefit-cap amount band 600 .01 to 700 measures no model unit in the band on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty and 14.2 percent of capped units sit above GBP 1,300 a month against 0.6 percent published, a tail of large families outside London (4.45 children on average, full child elements, housing element near GBP 1,350 a month). The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", + "reason": "Support, not a weight question (#882): the benefit-cap amount band 600 .01 to 700 measures no model unit in the band on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty, and the share of capped units above GBP 1,300 a month is many times the published 0.6 percent, a tail of large families outside London on full child elements and large housing elements. The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", "tracking": "microcosm#882", "approved_by": "juaristi22", "adjudication": "microcosm#882 (the 2026-09-16 status comment, issuecomment-5694598278, whose next-steps list this repair works, and the repairs plan María approved on 2026-09-16 with her population ruling on the U8 take-up entry; approver as author per the register convention). Expiry 2026-12-08 aligns the whole UC-repair tranche with the zero-band clock already on the register (microcosm#877), so the next spine re-adjudicates them together. Receipts: experiments/882-uc-repairs-receipts.md (R2 and R5, tools/diagnose_uk_benefit_cap.py on the Q50f candidate and the twins).", @@ -426,7 +426,7 @@ }, { "name": "dwp.benefit_cap.capped_households_700_01_to_800", - "reason": "Support, not a weight question (#882): the benefit-cap amount band 700 .01 to 800 measures 6,977 against 1,902 (+267 percent) on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty and 14.2 percent of capped units sit above GBP 1,300 a month against 0.6 percent published, a tail of large families outside London (4.45 children on average, full child elements, housing element near GBP 1,350 a month). The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", + "reason": "Support, not a weight question (#882): the benefit-cap amount band 700 .01 to 800 measures far above its published count, outside the 25 percent bound on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty, and the share of capped units above GBP 1,300 a month is many times the published 0.6 percent, a tail of large families outside London on full child elements and large housing elements. The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", "tracking": "microcosm#882", "approved_by": "juaristi22", "adjudication": "microcosm#882 (the 2026-09-16 status comment, issuecomment-5694598278, whose next-steps list this repair works, and the repairs plan María approved on 2026-09-16 with her population ruling on the U8 take-up entry; approver as author per the register convention). Expiry 2026-12-08 aligns the whole UC-repair tranche with the zero-band clock already on the register (microcosm#877), so the next spine re-adjudicates them together. Receipts: experiments/882-uc-repairs-receipts.md (R2 and R5, tools/diagnose_uk_benefit_cap.py on the Q50f candidate and the twins).", @@ -435,7 +435,7 @@ }, { "name": "dwp.benefit_cap.capped_households_800_01_to_900", - "reason": "Support, not a weight question (#882): the benefit-cap amount band 800 .01 to 900 measures 3,041 against 1,328 (+129 percent) on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty and 14.2 percent of capped units sit above GBP 1,300 a month against 0.6 percent published, a tail of large families outside London (4.45 children on average, full child elements, housing element near GBP 1,350 a month). The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", + "reason": "Support, not a weight question (#882): the benefit-cap amount band 800 .01 to 900 measures far above its published count, outside the 25 percent bound on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty, and the share of capped units above GBP 1,300 a month is many times the published 0.6 percent, a tail of large families outside London on full child elements and large housing elements. The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", "tracking": "microcosm#882", "approved_by": "juaristi22", "adjudication": "microcosm#882 (the 2026-09-16 status comment, issuecomment-5694598278, whose next-steps list this repair works, and the repairs plan María approved on 2026-09-16 with her population ruling on the U8 take-up entry; approver as author per the register convention). Expiry 2026-12-08 aligns the whole UC-repair tranche with the zero-band clock already on the register (microcosm#877), so the next spine re-adjudicates them together. Receipts: experiments/882-uc-repairs-receipts.md (R2 and R5, tools/diagnose_uk_benefit_cap.py on the Q50f candidate and the twins).", @@ -444,7 +444,7 @@ }, { "name": "dwp.benefit_cap.capped_households_900_01_to_1000", - "reason": "Support, not a weight question (#882): the benefit-cap amount band 900 .01 to 1000 measures no model unit in the band on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty and 14.2 percent of capped units sit above GBP 1,300 a month against 0.6 percent published, a tail of large families outside London (4.45 children on average, full child elements, housing element near GBP 1,350 a month). The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", + "reason": "Support, not a weight question (#882): the benefit-cap amount band 900 .01 to 1000 measures no model unit in the band on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty, and the share of capped units above GBP 1,300 a month is many times the published 0.6 percent, a tail of large families outside London on full child elements and large housing elements. The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", "tracking": "microcosm#882", "approved_by": "juaristi22", "adjudication": "microcosm#882 (the 2026-09-16 status comment, issuecomment-5694598278, whose next-steps list this repair works, and the repairs plan María approved on 2026-09-16 with her population ruling on the U8 take-up entry; approver as author per the register convention). Expiry 2026-12-08 aligns the whole UC-repair tranche with the zero-band clock already on the register (microcosm#877), so the next spine re-adjudicates them together. Receipts: experiments/882-uc-repairs-receipts.md (R2 and R5, tools/diagnose_uk_benefit_cap.py on the Q50f candidate and the twins).", @@ -453,7 +453,7 @@ }, { "name": "dwp.benefit_cap.capped_households_1000_01_to_1100", - "reason": "Support, not a weight question (#882): the benefit-cap amount band 1000 .01 to 1100 measures no model unit in the band on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty and 14.2 percent of capped units sit above GBP 1,300 a month against 0.6 percent published, a tail of large families outside London (4.45 children on average, full child elements, housing element near GBP 1,350 a month). The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", + "reason": "Support, not a weight question (#882): the benefit-cap amount band 1000 .01 to 1100 measures no model unit in the band on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty, and the share of capped units above GBP 1,300 a month is many times the published 0.6 percent, a tail of large families outside London on full child elements and large housing elements. The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", "tracking": "microcosm#882", "approved_by": "juaristi22", "adjudication": "microcosm#882 (the 2026-09-16 status comment, issuecomment-5694598278, whose next-steps list this repair works, and the repairs plan María approved on 2026-09-16 with her population ruling on the U8 take-up entry; approver as author per the register convention). Expiry 2026-12-08 aligns the whole UC-repair tranche with the zero-band clock already on the register (microcosm#877), so the next spine re-adjudicates them together. Receipts: experiments/882-uc-repairs-receipts.md (R2 and R5, tools/diagnose_uk_benefit_cap.py on the Q50f candidate and the twins).", @@ -462,7 +462,7 @@ }, { "name": "dwp.benefit_cap.capped_households_1100_01_to_1200", - "reason": "Support, not a weight question (#882): the benefit-cap amount band 1100 .01 to 1200 measures 2,991 against 380 (+687 percent) on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty and 14.2 percent of capped units sit above GBP 1,300 a month against 0.6 percent published, a tail of large families outside London (4.45 children on average, full child elements, housing element near GBP 1,350 a month). The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", + "reason": "Support, not a weight question (#882): the benefit-cap amount band 1100 .01 to 1200 measures far above its published count, outside the 25 percent bound on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty, and the share of capped units above GBP 1,300 a month is many times the published 0.6 percent, a tail of large families outside London on full child elements and large housing elements. The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", "tracking": "microcosm#882", "approved_by": "juaristi22", "adjudication": "microcosm#882 (the 2026-09-16 status comment, issuecomment-5694598278, whose next-steps list this repair works, and the repairs plan María approved on 2026-09-16 with her population ruling on the U8 take-up entry; approver as author per the register convention). Expiry 2026-12-08 aligns the whole UC-repair tranche with the zero-band clock already on the register (microcosm#877), so the next spine re-adjudicates them together. Receipts: experiments/882-uc-repairs-receipts.md (R2 and R5, tools/diagnose_uk_benefit_cap.py on the Q50f candidate and the twins).", @@ -471,7 +471,7 @@ }, { "name": "dwp.benefit_cap.capped_households_1200_01_to_1300", - "reason": "Support, not a weight question (#882): the benefit-cap amount band 1200 .01 to 1300 measures no model unit in the band on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty and 14.2 percent of capped units sit above GBP 1,300 a month against 0.6 percent published, a tail of large families outside London (4.45 children on average, full child elements, housing element near GBP 1,350 a month). The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", + "reason": "Support, not a weight question (#882): the benefit-cap amount band 1200 .01 to 1300 measures no model unit in the band on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty, and the share of capped units above GBP 1,300 a month is many times the published 0.6 percent, a tail of large families outside London on full child elements and large housing elements. The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", "tracking": "microcosm#882", "approved_by": "juaristi22", "adjudication": "microcosm#882 (the 2026-09-16 status comment, issuecomment-5694598278, whose next-steps list this repair works, and the repairs plan María approved on 2026-09-16 with her population ruling on the U8 take-up entry; approver as author per the register convention). Expiry 2026-12-08 aligns the whole UC-repair tranche with the zero-band clock already on the register (microcosm#877), so the next spine re-adjudicates them together. Receipts: experiments/882-uc-repairs-receipts.md (R2 and R5, tools/diagnose_uk_benefit_cap.py on the Q50f candidate and the twins).", @@ -480,7 +480,7 @@ }, { "name": "dwp.benefit_cap.capped_households_1300_01_and_above", - "reason": "Support, not a weight question (#882): the benefit-cap amount band 1300 .01 and above measures 15,774 against 627 (+2416 percent) on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty and 14.2 percent of capped units sit above GBP 1,300 a month against 0.6 percent published, a tail of large families outside London (4.45 children on average, full child elements, housing element near GBP 1,350 a month). The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", + "reason": "Support, not a weight question (#882): the benefit-cap amount band 1300 .01 and above measures far above its published count, outside the 25 percent bound on the Q50f candidate at calibrated weights (November 2025 DWP Table 4, GB). The capped population rests on a handful of source households cloned many times: four of the fourteen bands are empty, and the share of capped units above GBP 1,300 a month is many times the published 0.6 percent, a tail of large families outside London on full child elements and large housing elements. The bound total (dwp.benefit_cap.capped_households) and the up-to-GBP-100 band, the one band inside the 25 percent bound, stay in the objective; fitting this band would move weight onto those clones (the #762 zero-band lesson). Measured on every evaluation with tools/diagnose_uk_benefit_cap.py; retire when support exists and the band sits inside the bound.", "tracking": "microcosm#882", "approved_by": "juaristi22", "adjudication": "microcosm#882 (the 2026-09-16 status comment, issuecomment-5694598278, whose next-steps list this repair works, and the repairs plan María approved on 2026-09-16 with her population ruling on the U8 take-up entry; approver as author per the register convention). Expiry 2026-12-08 aligns the whole UC-repair tranche with the zero-band clock already on the register (microcosm#877), so the next spine re-adjudicates them together. Receipts: experiments/882-uc-repairs-receipts.md (R2 and R5, tools/diagnose_uk_benefit_cap.py on the Q50f candidate and the twins).", diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_kernels.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_kernels.py index 651da3485..0b83ccbf8 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_kernels.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_kernels.py @@ -132,6 +132,9 @@ # helpers and the adapter's input-retention checks into every consuming stage. _STAGE_HELPER_MODULES = { "frs_hmrc_spine_leaves": (frs_hmrc_source,), + # The SPI income stage's imputation, band-donor resample and receipt live + # in spi_income, so an edit there moves the stage's hash (microcosm#1278). + "hmrc_spi_income_spine": (spi_income,), "frs_spine": (uc_relationships,), "frs_legacy_proxies": (uk_engine_adapter,), "frs_education_grant_split": (uk_engine_adapter,), diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_income.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_income.py index c8124319e..2450b4d58 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_income.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_income.py @@ -1305,6 +1305,26 @@ def _spi_agerange_codes(ages: np.ndarray) -> np.ndarray: return codes +def _band_mean_total_income( + realized: np.ndarray, drawn: np.ndarray +) -> float | str | None: + """A reserved band's mean realised total income, for its receipt row. + + A carrier's realised total income is its drawn tape record's own, so a + band whose carriers drew fewer than ten distinct records, as any band with + fewer than ten carriers does, would give back one record's value or come + close to it. Its mean is "<10" (UKDS disclosure control; see + ``receipt_counts``), and a band without carriers has none. No single + record's value, such as the band's lowest or highest, is recorded. + """ + + if not realized.size: + return None + if np.unique(drawn).size < 10: + return "<10" + return float(realized.mean()) + + def _resample_band_donor_leaves( person: pd.DataFrame, donor: pd.DataFrame, @@ -1554,14 +1574,8 @@ def _resample_band_donor_leaves( "regional_matched_carriers": int(matched[mask].sum()), "age_matched_carriers": int(age_matched[mask].sum()), "state_pension_age_matched_carriers": int(side_matched[mask].sum()), - "realized_min_total_income": ( - float(realized.min()) if realized.size else None - ), - "realized_mean_total_income": ( - float(realized.mean()) if realized.size else None - ), - "realized_max_total_income": ( - float(realized.max()) if realized.size else None + "realized_mean_total_income": _band_mean_total_income( + realized, drawn[mask] ), } ) diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_graph.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_graph.py index 55190d99b..02bf46133 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_graph.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_graph.py @@ -189,6 +189,35 @@ def changed_helper_bytes(path: Path) -> bytes: assert registry.implementation_hash(control_ref) == before[control_ref] +def test_spi_income_source_changes_invalidate_the_stages_that_run_it(monkeypatch): + # The SPI income stage's module only imports the imputation, the band-donor + # resample and its receipt from spi_income, so spi_income is bound as the + # stage's helper; the landlords' stage already binds it (microcosm#1278). + from microcosm.build.uk_runtime import spi_income + + graph = uk_spine_graph() + registry = uk_registry(graph=graph) + affected = [ + graph.node(stage).kernel + for stage in ("hmrc_spi_income_spine", "property_components") + ] + control = graph.node("frs_council_tax").kernel + before = {ref: registry.implementation_hash(ref) for ref in (*affected, control)} + helper_path = Path(spi_income.__file__).resolve() + original = Path.read_bytes + + def changed_helper_bytes(path: Path) -> bytes: + content = original(path) + if path.resolve() == helper_path: + return content + b"\n# A helper-only source change.\n" + return content + + monkeypatch.setattr(Path, "read_bytes", changed_helper_bytes) + for ref in affected: + assert registry.implementation_hash(ref) != before[ref] + assert registry.implementation_hash(control) == before[control] + + def test_uk_adapter_source_changes_invalidate_all_consuming_stages(monkeypatch): from microcosm.frame.adapters import policyengine_uk diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_spi_band_donors.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_spi_band_donors.py index 1c911e7e6..fac3ec738 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_spi_band_donors.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_spi_band_donors.py @@ -548,8 +548,13 @@ def test_resample_gives_carriers_band_conditional_leaves_and_receipts() -> None: assert receipt["carriers"] == 4 and receipt["weighting"] == "FACT" rows = {row["lower_bound"]: row for row in receipt["bands"]} assert rows[2_000_000]["pool_composite_records"] > 0 - assert rows[2_000_000]["realized_min_total_income"] >= 2_000_000 - assert rows[500_000]["realized_max_total_income"] < 1_000_000 + # No drawn record's own value, such as a band's lowest or highest, is in + # the receipt, and a band whose carriers drew fewer than ten records + # withholds its mean (UKDS disclosure control). + for row in receipt["bands"]: + assert "realized_min_total_income" not in row + assert "realized_max_total_income" not in row + assert row["realized_mean_total_income"] == "<10" assert all(row["carriers"] == 1 for row in receipt["bands"]) # A carrier matches its region only where that regional band pool holds @@ -571,20 +576,25 @@ def regional_pool(lower: int, upper: float, region: str) -> int: def test_resample_cuts_the_pools_on_the_total_income_a_record_realises() -> None: # Given: pay uprated threefold, so the tape's 80k records (published total # 84.8k, below every reserved band) realise 240k-and-over on the frame - # while the 260k records realise 780k-and-over. + # while the 260k records realise 780k-and-over. Twenty carriers in each + # band draw from at least ten of its records, so each band's mean is + # recorded rather than withheld. donor = prepare_spi_donor_table(_raw_tape(), seed=1) + per_band = 20 + ids = np.arange(1, 2 * per_band + 1) household = pd.DataFrame( { - "household_id": [1, 2], - "region": ["LONDON", "LONDON"], - SPI_INCOME_BAND_DONOR_LOWER_BOUND_COLUMN: [200_000.0, 500_000.0], + "household_id": ids, + "region": ["LONDON"] * len(ids), + SPI_INCOME_BAND_DONOR_LOWER_BOUND_COLUMN: [200_000.0] * per_band + + [500_000.0] * per_band, } ) person = pd.DataFrame( { - "person_id": [11, 21], - "person_household_id": [1, 2], - PERSON_IS_SPI_INCOME_BAND_CARRIER: [True, True], + "person_id": ids * 10 + 1, + "person_household_id": ids, + PERSON_IS_SPI_INCOME_BAND_CARRIER: [True] * len(ids), } ) for column in SPI_INCOME_QRF_OUTPUT_COLUMNS: @@ -595,16 +605,16 @@ def test_resample_cuts_the_pools_on_the_total_income_a_record_realises() -> None person, donor, household=household, - spi_people=pd.Series([True, True], index=person.index), + spi_people=pd.Series(True, index=person.index), uprating_factors=factors, lower_bounds=BANDS, regional_pool_minimum=5, seed=44, ) - # Then: the 200k carrier drew an 80k record (its uprated pay is 240k), the - # 500k carrier a 260k record, and the pools are the uprated bands. + # Then: every 200k carrier drew an 80k record (its uprated pay is 240k), + # every 500k carrier a 260k record, and the pools are the uprated bands. pay = updated.loc[updated[PERSON_IS_SPI_INCOME_BAND_CARRIER], "hmrc_spi_pay"] - assert pay.tolist() == [240_000.0, 780_000.0] + assert pay.tolist() == [240_000.0] * per_band + [780_000.0] * per_band rows = {row["lower_bound"]: row for row in receipt["bands"]} assert rows[200_000]["pool_records"] == int( (donor["hmrc_spi_pay"] == 80_000.0).sum() From c7d2fe38133a04da13b179e5bbe32e45b7baaef5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 14:05:50 +0100 Subject: [PATCH 13/21] Review the local binding on the build's date in the graph kernels (#1278) The uk.full.problem kernel and the rotated holdout kernel reviewed the local binding adjudications on the wall clock. The target compilation already reviews the measure exclusions on the build's review_date, and #1306 (E) let prepare_uk_full_solve and rotated_uk_local_holdout take a date (77febc5ee, 67e54c47f); the two kernels now pass it. - uk.full.problem carries review_date in its parameters, and its kernel passes it to prepare_uk_full_solve as now. - uk.full.holdout inherits it with the problem's parameters, and its kernel passes it to rotated_uk_local_holdout, so every fold reviews on it. Tests: a prepared build puts the solve's review date on both nodes. At the kernel level, the problem kernel passes its date and refuses one past the committed register's windows; the holdout kernel refuses such a date, and every fold it runs receives the build's date. These three fail on the old kernels. The review-date changelog fragment loses its "is a follow-up" sentence. No effect on a build before the Budget: the earliest local adjudication expires 2026-12-15. A changed review date now re-keys the problem and the holdout as well as the target compilation. Co-Authored-By: Claude Opus 5.5 --- .../1278-rowwise-binding-review-date.fixed.md | 4 +- .../build/uk_runtime/graph_targets.py | 6 + .../build/uk_runtime/graph_terminal.py | 5 + .../uk/test_uk_full_build_preparation.py | 10 +- .../engine_free/uk/test_uk_graph_terminal.py | 159 ++++++++++++++++++ 5 files changed, 181 insertions(+), 3 deletions(-) diff --git a/changelog.d/1278-rowwise-binding-review-date.fixed.md b/changelog.d/1278-rowwise-binding-review-date.fixed.md index c2c6f32bb..c7744ef4f 100644 --- a/changelog.d/1278-rowwise-binding-review-date.fixed.md +++ b/changelog.d/1278-rowwise-binding-review-date.fixed.md @@ -1,6 +1,6 @@ -The UK rowwise solve takes the date it reviews the local binding adjudications on (microcosm#1278). `prepare_uk_full_solve`, `solve_uk_rowwise_weights_under_doctrine` and `rotated_uk_local_holdout` accept `now` and pass it to `require_adjudicated_uk_local_binding`. Builds and the graph kernels still review on today's date; the `uk.full.problem` kernel and the holdout kernel taking the build's review date is a follow-up. +The UK rowwise solve takes the date it reviews the local binding adjudications on (microcosm#1278). `prepare_uk_full_solve`, `solve_uk_rowwise_weights_under_doctrine` and `rotated_uk_local_holdout` accept `now` and pass it to `require_adjudicated_uk_local_binding`. The graph kernels take the build's review date rather than the wall clock: `uk.full.problem` carries `review_date` in its parameters, the date the target compilation already reviews the measure exclusions on, and the rotated holdout inherits it with the problem's parameters, so both review on the date the build was prepared with (`--review-date`). The engine-free rowwise tests now review the committed register on its latest approval date (`COMMITTED_BINDING_NOW` in `test_support`), not today. Seventeen of them would otherwise have warned from 2027-01-07 and failed from 2027-01-15, when the six local adjudications renewed under #1278 lapse. On that date the review is a build's: a lapsed fence a fixture binds still fails, a dormant one does not, and nothing is asserted when the module is imported. -- **Tests.** Two new tests check that a solve and every holdout fold refuse a date past the register's windows. Another shows that all five folds receive the date. +- **Tests.** Two new tests check that a solve and every holdout fold refuse a date past the register's windows. Another shows that all five folds receive the date. At the kernel level, `uk.full.problem` and the holdout kernel each refuse a review date past the windows, every fold the holdout kernel runs receives its date, and a prepared build puts the solve's date on both nodes. - **The calendar's warning.** `test_no_committed_local_adjudication_is_about_to_lapse` fails fourteen days before the earliest local adjudication expires, as the uprating holds' clock does, while builds still pass. diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_targets.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_targets.py index 9986d79b1..b43a1a456 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_targets.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_targets.py @@ -675,6 +675,9 @@ def run(self, context: KernelContext) -> KernelResult: national_rows=national_rows, target_weight_rule=str(context.params["target_weight_rule"]), allow_empty_local_binding=inputs.country_only, + # The local binding adjudications are reviewed on the build's + # review date, not the wall clock (microcosm#1278). + now=date.fromisoformat(str(context.params["review_date"])), ) problem = build_constraint_matrix(frame, prepared.target_set, "household") if problem.skipped: @@ -847,6 +850,9 @@ def append_uk_target_nodes( **common, "sample_fraction": float(sample_fraction), "target_weight_rule": target_weight_rule, + # The binding adjudications' review date; the rotated holdout + # inherits it with these parameters (microcosm#1278). + "review_date": review_date, }, sources=("uk_ladder",), artifact_inputs=( diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_terminal.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_terminal.py index 4c90df46d..735733f80 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_terminal.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/graph_terminal.py @@ -1324,6 +1324,8 @@ def implementation_hash(self) -> str: ).hexdigest() def run(self, context: KernelContext) -> KernelResult: + from datetime import date + from microcosm.calibrate.artifacts import decode_problem from ..gate_battery import _json_safe @@ -1379,6 +1381,9 @@ def run(self, context: KernelContext) -> KernelResult: selection_pi_hi=float(context.params["selection_pi_hi"]), baseline_pi_floor=float(context.params["baseline_pi_floor"]), selection_initial_lambda=context.params.get("selection_initial_lambda"), + # Every fold reviews the binding on the build's review date, + # inherited from uk.full.problem (microcosm#1278). + now=date.fromisoformat(str(context.params["review_date"])), **{ key: context.params[key] for key in UK_SIZE_L2_PARAM_KEYS diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_full_build_preparation.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_full_build_preparation.py index 1c954f180..8e1afae46 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_full_build_preparation.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_full_build_preparation.py @@ -356,5 +356,13 @@ def test_a_later_gate_clock_rekeys_only_the_calibrated_gates_and_the_export( } calibrated = second.full.graph.node("uk.full.gates.calibrated") assert calibrated.params["review_date"] == gate - for node in ("uk.full.gates.preflight", "uk.full.target_compilation"): + # The problem and the rotated holdout review the local binding + # adjudications on the solve's date, as the target compilation reviews + # the measure exclusions (microcosm#1278). + for node in ( + "uk.full.gates.preflight", + "uk.full.target_compilation", + "uk.full.problem", + "uk.full.holdout", + ): assert second.full.graph.node(node).params["review_date"] == solve diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_graph_terminal.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_graph_terminal.py index a84bc78c9..10941274d 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_graph_terminal.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_graph_terminal.py @@ -510,6 +510,7 @@ def test_terminal_byte_materialization_recreates_exact_files(tmp_path): def test_holdout_kernel_preserves_existing_rotations_and_seed_settings(monkeypatch): import json + from datetime import date from types import SimpleNamespace from microcosm.build.uk_runtime import graph_targets, local_rowwise @@ -534,6 +535,7 @@ def test_holdout_kernel_preserves_existing_rotations_and_seed_settings(monkeypat ), ) calls = [] + reviewed_on = [] def solve(frame, training, **kwargs): calls.append( @@ -544,6 +546,7 @@ def solve(frame, training, **kwargs): kwargs["selection_initial_lambda"], ) ) + reviewed_on.append(kwargs["now"]) return SimpleNamespace(weights=np.ones(2), selected_support=np.array([0, 2])) monkeypatch.setattr(local_rowwise, "solve_uk_rowwise_weights_under_doctrine", solve) @@ -580,6 +583,8 @@ def solve(frame, training, **kwargs): "baseline_pi_floor": 0.0, # Every fold's budget search starts where the main search started. "selection_initial_lambda": 1.7e-7, + # Inherited from uk.full.problem: the binding's review date. + "review_date": "2026-10-20", }, artifacts={ "preflight": SimpleNamespace(payload=preflight_payload(), key="a" * 64), @@ -602,6 +607,160 @@ def solve(frame, training, **kwargs): key: value for key, value in result.items() if key != "graph_binding" } == expected assert calls == [(42, 2, 17, 1.7e-7)] * 10 + # Every fold the kernel ran reviewed the binding on the build's review + # date (microcosm#1278); the direct call above reviewed on today's. + assert reviewed_on == [date(2026, 10, 20)] * 5 + [None] * 5 + + +def _bound_problem_inputs(): + """A clone frame and a local problem that binds two fenced families.""" + + from types import SimpleNamespace + + from microcosm.build.uk_runtime import local_rowwise + from test_support.microcosm_build.uk_local_rowwise import ( + _assigned, + _clone_frame, + ) + + problem = local_rowwise.build_uk_rowwise_local_matrix( + pd.DataFrame( + {"households": [2.0, 1.0, 3.0], "tenure/social_rent": [1.0, 0.0, 1.0]}, + index=[101, 102, 103], + ), + _assigned(), + pd.DataFrame( + { + "code": ["E001", "S001"], + "households": [4.0, 2.0], + "tenure/social_rent": [1.0, 1.0], + } + ), + ) + return SimpleNamespace( + frame=_clone_frame(), + local_problem=problem, + national_rows=None, + bound_families=["census_households/constituency", "tenure/constituency"], + selection=None, + selected=(), + metadata={}, + full=None, + cross=None, + rung=None, + country_only=False, + ) + + +def test_problem_kernel_reviews_the_binding_on_the_build_review_date(monkeypatch): + """microcosm#1278: uk.full.problem reviews the local binding + adjudications on its review_date parameter, not the wall clock, so a date + past the committed register's windows is refused.""" + from datetime import date + from types import SimpleNamespace + + from microcosm.build.uk_runtime import graph_targets + from microcosm.build.uk_runtime.graph_targets import UKFullProblemKernel + + inputs = _bound_problem_inputs() + monkeypatch.setattr( + graph_targets, "reconstruct_uk_full_problem_inputs", lambda context: inputs + ) + + def context(review_date): + return SimpleNamespace( + params={"target_weight_rule": "uniform", "review_date": review_date}, + artifacts={}, + ) + + class ReviewedError(Exception): + pass + + reviewed_on = [] + + def prepare(*args, **kwargs): + reviewed_on.append(kwargs["now"]) + raise ReviewedError + + with monkeypatch.context() as patch: + patch.setattr(graph_targets, "prepare_uk_full_solve", prepare) + with pytest.raises(ReviewedError): + UKFullProblemKernel().run(context("2026-10-20")) + assert reviewed_on == [date(2026, 10, 20)] + with pytest.raises(ValueError, match="outside its reviewed window"): + UKFullProblemKernel().run(context("2099-01-01")) + + +def test_holdout_kernel_refuses_a_review_date_past_the_binding_windows(monkeypatch): + """microcosm#1278: every fold of the rotated holdout reviews the binding + on the review date the holdout inherits from uk.full.problem.""" + from types import SimpleNamespace + + from microcosm.build.uk_runtime import graph_targets, local_rowwise + from microcosm.build.uk_runtime.graph_terminal import UKFullHoldoutKernel + from microcosm.build.uk_runtime.national_frame import uk_national_frame + from microcosm.calibrate import Target, TargetSet, build_constraint_matrix + from microcosm.calibrate.artifacts import encode_problem + from test_support.microcosm_build.uk_full_calibration_graph import ( + preflight_payload, + ) + + # Five areas, so each of the five folds holds one out; the household + # counts bind a fenced family. + household_ids = [101, 102, 103, 104, 105] + area_codes = ["E001", "W001", "S001", "N001", "E002"] + frame = uk_national_frame( + person=pd.DataFrame( + { + "person_id": [1, 2, 3, 4, 5], + "person_household_id": household_ids, + "person_benunit_id": [11, 12, 13, 14, 15], + } + ), + benunit=pd.DataFrame({"benunit_id": [11, 12, 13, 14, 15]}), + household=pd.DataFrame( + {"household_id": household_ids, "household_weight": [1.0] * 5} + ), + time_period="2023", + weight_kind=WeightKind.IMPORTANCE, + ) + problem = local_rowwise.build_uk_rowwise_local_matrix( + pd.DataFrame({"households": np.ones(5)}, index=household_ids), + pd.Series(area_codes, index=household_ids), + pd.DataFrame({"code": area_codes, "households": [2.0] * 5}), + ) + inputs = SimpleNamespace( + frame=frame, local_problem=problem, national_rows=None, bound_families=None + ) + monkeypatch.setattr( + graph_targets, "reconstruct_uk_full_problem_inputs", lambda context: inputs + ) + original = encode_problem( + build_constraint_matrix( + frame, + TargetSet([Target("count", "household", lambda f: np.ones(5), 5.0)]), + "household", + ), + entity_ids=household_ids, + ) + context = SimpleNamespace( + params={ + "skip_holdout": False, + "target_weight_rule": "uniform", + "epochs": 1, + "learning_rate": 0.1, + "seed": 42, + "selection_pi_hi": 1.0, + "baseline_pi_floor": 0.0, + "review_date": "2099-01-01", + }, + artifacts={ + "preflight": SimpleNamespace(payload=preflight_payload(), key="a" * 64), + "problem": SimpleNamespace(payload=original, key="b" * 64), + }, + ) + with pytest.raises(ValueError, match="outside its reviewed window"): + UKFullHoldoutKernel().run(context) def test_holdout_kernel_refuses_a_floor_its_folds_cannot_honour(): From 35d96fcff15791d6c0767c54deb30e135071e091 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 13:57:29 +0100 Subject: [PATCH 14/21] Hold the ORR rail-support row out of the national objective (#1278) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit María's ruling of 2026-10-20: run a national arm with orr.rail_government_support held out beside the calibration-period fix's arm (#1324). Commit the hold-out only if the gates pass and the share of rows within 10 percent holds; otherwise keep the row bound and label the distributional tables. The arm passed: 7/7 terminal gates, and 99.1% of the rows both arms bind within 10 percent (98.8% with the row bound). The row binds ORR table 7270's broad total of government support to the railway. The frame's household rail subsidy sits far below it at design weights, so the solve closes the gap by moving weight onto rail-using households. That also moves untargeted columns that correlate with rail use. The 7270-versus-7271 basis ruling stays open (#890 G). The entry carries approved_on 2026-10-20 and expires_on 2026-12-11, which María confirmed on 2026-10-20, and tracks #1278. The exclusion census gains 'orr.' and the register 58 entries (57). The national arm reads the same file by --measure-exclusions. Co-Authored-By: Claude Opus 5.5 --- .../1278-orr-rail-support-held-out.changed.md | 1 + .../uk/calibration_measure_exclusions.json | 9 ++++++ .../uk/test_uk_measure_simulation.py | 31 +++++++++++++++++-- 3 files changed, 38 insertions(+), 3 deletions(-) create mode 100644 changelog.d/1278-orr-rail-support-held-out.changed.md diff --git a/changelog.d/1278-orr-rail-support-held-out.changed.md b/changelog.d/1278-orr-rail-support-held-out.changed.md new file mode 100644 index 000000000..8881dd042 --- /dev/null +++ b/changelog.d/1278-orr-rail-support-held-out.changed.md @@ -0,0 +1 @@ +`orr.rail_government_support` is held out of the national objective as a measured diagnostic, from 2026-10-20 to 2026-12-11 (María's ruling of 2026-10-20, microcosm#1278). The row binds ORR table 7270's broad total of government support to the railway. The frame's household rail subsidy sits far below that total at design weights, so a bound row closes the gap by moving weight onto rail-using households, and with it untargeted columns that correlate with rail use. The ruling holds the row out only if a national arm with it held out, run beside the calibration-period fix's arm, passes the gates and keeps the share of rows within 10 percent. Whether the household subsidy is measured against table 7270 or table 7271's narrower by-source series is still an open ruling (microcosm#890 G). The register has 58 measure exclusions (57). diff --git a/packages/microcosm-build/src/microcosm/build/uk/calibration_measure_exclusions.json b/packages/microcosm-build/src/microcosm/build/uk/calibration_measure_exclusions.json index 3d7f58de3..95e3f876d 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/calibration_measure_exclusions.json +++ b/packages/microcosm-build/src/microcosm/build/uk/calibration_measure_exclusions.json @@ -531,6 +531,15 @@ "adjudication": "María's ruling of 2026-10-16 on the microcosm#1301 local release plan: unbind the row as a measured diagnostic, rather than bind the FY2025-26 value or sign it gate-only, because modelling the allowance alone would close only part of the gap. The exclusion applies on both lines, since this register has no line scoping: the national objective drops the row too, and a national run given a frozen scoring register derived before this entry fails closed (the re-derived register differs from the frozen one), so the national build's frozen register is derived from a head that carries this entry. policyengine-uk#2459, split from policyengine-uk#1918 (which keeps the under-21 and apprentice zero rates), asks the engine to net the allowance out of ni_employer. The expiry gives the three-month window of the 2026-10-08 engine-factor diagnostic (obr.vat).", "approved_on": "2026-10-16", "expires_on": "2027-01-16" + }, + { + "name": "orr.rail_government_support", + "reason": "Basis, not a weight question: the row binds ORR table 7270's broad total of government support to the Great Britain railway, and the frame's household rail subsidy (rail_subsidy_spending, the engine's rail_usage times gov.dft.rail.fare_index) sits far below it at design weights. Bound, the solve closes the gap by moving weight onto rail-using households, which also moves untargeted columns that correlate with rail use. Whether the household subsidy is measured against table 7270's broad total or table 7271's narrower by-source series is an open ruling (microcosm#890 G, microcosm#736). Held out of the objective as a measured diagnostic and never fitted; rebind on that ruling, against the narrower series in the feed or a column scaled as uk-data scales it.", + "tracking": "microcosm#1278", + "approved_by": "juaristi22", + "adjudication": "María's ruling of 2026-10-20 on the pre-Budget PR (microcosm#1278): hold the row out only if a national arm with it held out, run beside the calibration-period fix's arm (microcosm#1324), passes the gates and keeps the share of rows within 10 percent; otherwise keep it bound and label the distributional tables. The 7270-versus-7271 basis ruling stays open (microcosm#890 G). The expiry, 2026-12-11, matches the uprating holds' renewal, after the Budget.", + "approved_on": "2026-10-20", + "expires_on": "2026-12-11" } ] } diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_measure_simulation.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_measure_simulation.py index 53ef91db1..46cdadb5a 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_measure_simulation.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_measure_simulation.py @@ -649,6 +649,11 @@ def test_exclusion_applier_warns_within_week_of_expiry(): # Allowance in the engine and priced on FY2025-26 rules over a window that # takes a quarter of FY2024-25, held out as a measured diagnostic. "obr.ni_employer": 1, + # microcosm#1278 (2026-10-20): ORR's broad rail-support total, far above + # the frame's household rail subsidy at design weights while the 7270 + # versus 7271 basis ruling is open (microcosm#890 G), held out after the + # national hold-out arm. + "orr.": 1, } # The carer and childcare rows were retired on 2026-09-16 with the repairs @@ -675,8 +680,9 @@ def test_packaged_exclusions_load(): exclusions = load_uk_calibration_measure_exclusions() names = [entry["name"] for entry in exclusions] # 65 less the nine payment bands the support floor covers (microcosm#1095 U3), - # plus the employer NICs diagnostic (microcosm#1301). - assert len(names) == len(set(names)) == 57 + # plus the employer NICs diagnostic (microcosm#1301) and the rail-support + # hold-out (microcosm#1278). + assert len(names) == len(set(names)) == 58 band_h_region_cells = [ entry for entry in exclusions @@ -747,8 +753,27 @@ def test_packaged_exclusions_load(): # #1063 stack arm retired 2026-10-16 (the support floor drops them), and # the plan-2 rows left the 2026-10-02 clock on their 2026-10-20 renewal. assert [e for e in exclusions if e["approved_on"] == "2026-10-02"] == [] - renewed = [e for e in exclusions if e["approved_on"] == "2026-10-20"] + # The other 2026-10-20 entry is the rail-support hold-out (below). + assert sorted( + e["name"] for e in exclusions if e["approved_on"] == "2026-10-20" + ) == sorted([*_A16_UNREACHABLE_ROWS[:2], "orr.rail_government_support"]) + renewed = [ + e + for e in exclusions + if e["approved_on"] == "2026-10-20" and e["name"] in _A16_UNREACHABLE_ROWS + ] assert sorted(e["name"] for e in renewed) == sorted(_A16_UNREACHABLE_ROWS[:2]) + # María's ruling of 2026-10-20 (microcosm#1278): the ORR row is held out + # only on a national arm whose gates pass and whose share of rows within + # 10 percent holds; the 7270 versus 7271 basis ruling stays open. + (rail,) = [e for e in exclusions if e["name"] == "orr.rail_government_support"] + assert rail["approved_by"] == "juaristi22" + assert (rail["approved_on"], rail["expires_on"]) == ("2026-10-20", "2026-12-11") + assert rail["tracking"] == "microcosm#1278" + assert "7270" in rail["reason"] and "7271" in rail["reason"] + assert "microcosm#890 G" in rail["reason"] + assert "never fitted" in rail["reason"] + assert "within 10 percent" in rail["adjudication"] # So did the two bands the engine bump of microcosm#1095 (policyengine-uk # 2.122.2) emptied, the 2026-10-07 entries. assert [e for e in exclusions if e["approved_on"] == "2026-10-07"] == [] From e64f2d133de64310f70470b35423f15ada9cca55 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 17:28:50 +0100 Subject: [PATCH 15/21] Regenerate the UK national target references and membership (pin pass) Regenerated with tools/generate_uk_target_references.py from the pinned feed abf0921 (source_fact_feed chronicle-uk-abf0921-consumer-facts). The active references go from 1,319 to 1,322 with the ONS single years of age 0, 1 and 2. The contract's measurement_period 2024 is mirrored onto ONS road fuel and the seven held bus and rail rows, and road fuel's selector reads its calendar-2024 observation. Co-Authored-By: Claude Opus 5.5 --- .../build/uk/target_reference_membership.json | 83 +++++++++++-- .../microcosm/build/uk/target_references.json | 117 ++++++++++++++++-- 2 files changed, 182 insertions(+), 18 deletions(-) diff --git a/packages/microcosm-build/src/microcosm/build/uk/target_reference_membership.json b/packages/microcosm-build/src/microcosm/build/uk/target_reference_membership.json index 8e0dac232..1478206d8 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/target_reference_membership.json +++ b/packages/microcosm-build/src/microcosm/build/uk/target_reference_membership.json @@ -1,11 +1,11 @@ { "source_fact_feed": "chronicle-uk-abf0921-consumer-facts", "target_period": 2025, - "candidate_count": 1341, - "contract_target_count": 359, - "active_reference_count": 1319, + "candidate_count": 1344, + "contract_target_count": 362, + "active_reference_count": 1322, "status_counts": { - "active": 1319, + "active": 1322, "no_fact_at_or_before_period": 5, "signed_excluded": 17 }, @@ -806,6 +806,18 @@ } ] }, + "ons.population.age_0": { + "geography_level": "country", + "geography_id": "K02000001" + }, + "ons.population.age_1": { + "geography_level": "country", + "geography_id": "K02000001" + }, + "ons.population.age_2": { + "geography_level": "country", + "geography_id": "K02000001" + }, "ons.population.female_0_4": { "geography_level": "country", "geography_id": "K02000001" @@ -4411,6 +4423,7 @@ "dwp.workplace_pension.employer_contributions", "nithc.public_transport_support", "ons.household_road_fuel_expenditure", + "ons.population.age_0", "ons.population.age_0_9_by_region@E12000001", "ons.population.age_0_9_by_region@E12000002", "ons.population.age_0_9_by_region@E12000003", @@ -4423,6 +4436,7 @@ "ons.population.age_0_9_by_region@N92000002", "ons.population.age_0_9_by_region@S92000003", "ons.population.age_0_9_by_region@W92000004", + "ons.population.age_1", "ons.population.age_10_19_by_region@E12000001", "ons.population.age_10_19_by_region@E12000002", "ons.population.age_10_19_by_region@E12000003", @@ -4435,6 +4449,7 @@ "ons.population.age_10_19_by_region@N92000002", "ons.population.age_10_19_by_region@S92000003", "ons.population.age_10_19_by_region@W92000004", + "ons.population.age_2", "ons.population.age_20_29_by_region@E12000001", "ons.population.age_20_29_by_region@E12000002", "ons.population.age_20_29_by_region@E12000003", @@ -7091,6 +7106,11 @@ "from": "2024", "to": "2025" }, + { + "name": "ons.household_road_fuel_expenditure", + "from": "2024", + "to": "2025" + }, { "name": "scotgov.bus.passenger_revenue", "from": "2024", @@ -16533,6 +16553,51 @@ } ] }, + "ons.population.age_0": { + "status": "active", + "candidates": [ + { + "name": "ons.population.age_0", + "status": "active", + "matched_fact_count_overall": 3, + "matched_fact_count_at_or_before_period": 3, + "resolved_period": 2025, + "resolved_value": 658357.0, + "resolved_fact_period": "2025", + "resolved_fact_key": "ledger_aggregate_fact_v2_0c75c3f83df0cd1090772ac6" + } + ] + }, + "ons.population.age_1": { + "status": "active", + "candidates": [ + { + "name": "ons.population.age_1", + "status": "active", + "matched_fact_count_overall": 3, + "matched_fact_count_at_or_before_period": 3, + "resolved_period": 2025, + "resolved_value": 679232.0, + "resolved_fact_period": "2025", + "resolved_fact_key": "ledger_aggregate_fact_v2_ab4bba642f61ca6bcc2f9722" + } + ] + }, + "ons.population.age_2": { + "status": "active", + "candidates": [ + { + "name": "ons.population.age_2", + "status": "active", + "matched_fact_count_overall": 3, + "matched_fact_count_at_or_before_period": 3, + "resolved_period": 2025, + "resolved_value": 696010.0, + "resolved_fact_period": "2025", + "resolved_fact_key": "ledger_aggregate_fact_v2_c617f5c67e886aa92ddef487" + } + ] + }, "ons.population.female_0_4": { "status": "active", "candidates": [ @@ -19612,12 +19677,12 @@ { "name": "ons.household_road_fuel_expenditure", "status": "active", - "matched_fact_count_overall": 6, - "matched_fact_count_at_or_before_period": 6, + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 35099000000.0, - "resolved_fact_period": "2025", - "resolved_fact_key": "ledger_aggregate_fact_v2_98696a3d0a85269f7b2445ff" + "resolved_value": 37025000000.0, + "resolved_fact_period": "2024", + "resolved_fact_key": "ledger_aggregate_fact_v2_d5c11a14d2062955b622275a" } ] }, diff --git a/packages/microcosm-build/src/microcosm/build/uk/target_references.json b/packages/microcosm-build/src/microcosm/build/uk/target_references.json index ff390bbb5..dbd13471c 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/target_references.json +++ b/packages/microcosm-build/src/microcosm/build/uk/target_references.json @@ -505,8 +505,11 @@ "ons.land.corporate_land_value": "ons.land", "ons.land.household_land_value": "ons.land", "ons.land.land_value": "ons.land", + "ons.population.age_0": "ons.population", "ons.population.age_0_9_by_region": "ons.population", + "ons.population.age_1": "ons.population", "ons.population.age_10_19_by_region": "ons.population", + "ons.population.age_2": "ons.population", "ons.population.age_20_29_by_region": "ons.population", "ons.population.age_30_39_by_region": "ons.population", "ons.population.age_40_49_by_region": "ons.population", @@ -854,8 +857,11 @@ "ons.land.corporate_land_value": "Corporate land value", "ons.land.household_land_value": "Household land value", "ons.land.land_value": "Land value", + "ons.population.age_0": "Age 0", "ons.population.age_0_9_by_region": "Age 0 9 by region", + "ons.population.age_1": "Age 1", "ons.population.age_10_19_by_region": "Age 10 19 by region", + "ons.population.age_2": "Age 2", "ons.population.age_20_29_by_region": "Age 20 29 by region", "ons.population.age_30_39_by_region": "Age 30 39 by region", "ons.population.age_40_49_by_region": "Age 40 49 by region", @@ -13814,6 +13820,87 @@ "value_operation": "sum", "expected_member_count": 10 }, + { + "name": "ons.population.age_0", + "ledger_selector": { + "source_name": "ons", + "source_concept": "ons.mid_year_population_estimate", + "dimension_values": { + "age": [ + 0 + ] + }, + "geography_level": "country", + "geography_id": "K02000001", + "dimensions": [ + "age" + ] + }, + "entity": "person", + "measure": "ons/age_0", + "family": "ons_population", + "period": 2025, + "metadata": { + "contract_target_id": "ons.population.age_0", + "measure_kind": "prepared_column" + }, + "value_operation": "sum", + "expected_member_count": 1 + }, + { + "name": "ons.population.age_1", + "ledger_selector": { + "source_name": "ons", + "source_concept": "ons.mid_year_population_estimate", + "dimension_values": { + "age": [ + 1 + ] + }, + "geography_level": "country", + "geography_id": "K02000001", + "dimensions": [ + "age" + ] + }, + "entity": "person", + "measure": "ons/age_1", + "family": "ons_population", + "period": 2025, + "metadata": { + "contract_target_id": "ons.population.age_1", + "measure_kind": "prepared_column" + }, + "value_operation": "sum", + "expected_member_count": 1 + }, + { + "name": "ons.population.age_2", + "ledger_selector": { + "source_name": "ons", + "source_concept": "ons.mid_year_population_estimate", + "dimension_values": { + "age": [ + 2 + ] + }, + "geography_level": "country", + "geography_id": "K02000001", + "dimensions": [ + "age" + ] + }, + "entity": "person", + "measure": "ons/age_2", + "family": "ons_population", + "period": 2025, + "metadata": { + "contract_target_id": "ons.population.age_2", + "measure_kind": "prepared_column" + }, + "value_operation": "sum", + "expected_member_count": 1 + }, { "name": "ons.population.female_0_4", "ledger_selector": { @@ -23891,7 +23978,8 @@ "metadata": { "contract_target_id": "dft.bus_net_support.england", "measure_kind": "prepared_column", - "observation_basis": "fiscal_year_flow" + "observation_basis": "fiscal_year_flow", + "measurement_period": "2024" }, "uprating_from_period": "2024", "uprating_to_period": 2025 @@ -23938,7 +24026,8 @@ "metadata": { "contract_target_id": "dft.bus_net_support.london", "measure_kind": "prepared_column", - "observation_basis": "fiscal_year_flow" + "observation_basis": "fiscal_year_flow", + "measurement_period": "2024" }, "uprating_from_period": "2024", "uprating_to_period": 2025 @@ -24221,7 +24310,8 @@ "metadata": { "contract_target_id": "orr.rail_government_support", "measure_kind": "prepared_column", - "observation_basis": "fiscal_year_flow" + "observation_basis": "fiscal_year_flow", + "measurement_period": "2024" }, "uprating_from_period": "2024", "uprating_to_period": 2025 @@ -24285,6 +24375,7 @@ "source_concept": "ons.household_expenditure.personal_transport_fuels_lubricants", "entity_name": "household", "period_type": "calendar_year", + "period_value": 2024, "dimension_values": { "coicop": "07.2.2", "frequency": "annual", @@ -24301,9 +24392,13 @@ "period": 2025, "metadata": { "contract_target_id": "ons.household_road_fuel_expenditure", - "measure_kind": "prepared_column" + "measure_kind": "prepared_column", + "measurement_period": "2024", + "source_period_policy": "exact_observation" }, - "value_operation": "sum" + "value_operation": "sum", + "uprating_from_period": "2024", + "uprating_to_period": 2025 }, { "name": "scotgov.bus.passenger_revenue", @@ -24323,7 +24418,8 @@ "metadata": { "contract_target_id": "scotgov.bus.passenger_revenue", "measure_kind": "prepared_column", - "observation_basis": "fiscal_year_flow" + "observation_basis": "fiscal_year_flow", + "measurement_period": "2024" }, "uprating_from_period": "2024", "uprating_to_period": 2025 @@ -24348,7 +24444,8 @@ "metadata": { "contract_target_id": "scotgov.bus.government_support", "measure_kind": "prepared_column", - "observation_basis": "fiscal_year_flow" + "observation_basis": "fiscal_year_flow", + "measurement_period": "2024" }, "uprating_from_period": "2024", "uprating_to_period": 2025 @@ -24377,7 +24474,8 @@ "metadata": { "contract_target_id": "welshgov.bus.public_support", "measure_kind": "prepared_column", - "observation_basis": "fiscal_year_flow" + "observation_basis": "fiscal_year_flow", + "measurement_period": "2024" }, "value_operation": "sum", "expected_member_count": 2, @@ -24436,7 +24534,8 @@ "metadata": { "contract_target_id": "nithc.public_transport_support", "measure_kind": "prepared_column", - "observation_basis": "fiscal_year_flow" + "observation_basis": "fiscal_year_flow", + "measurement_period": "2024" }, "value_operation": "sum", "expected_member_count": 2, From 7e5c8b37cd40737b91cc775b0c6b4b60aa6022c7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Tue, 20 Oct 2026 19:34:59 +0100 Subject: [PATCH 16/21] Regenerate the UK compile-parity receipts, coverage manifest and spine fixture (pin pass) The national compile-parity receipt (tools/build_uk_ledger_compile_parity_signed_differences.py --surface national) adds the three ONS age rows as ledger-only and reads road fuel's calendar-2024 figure; the local receipt does not move. The release input coverage manifest re-hashes the resources this PR changes, and the charter-H2 spine fixture is regenerated with the rows the fixture tool gains here. Both --check runs pass. Co-Authored-By: Claude Opus 5.5 --- ...ity_incumbent_2025_signed_differences.json | 29 +- .../uk/release_input_coverage_manifest.json | 44 +-- .../sources/cgt_asset_type_facts.json | 48 ++-- .../parity/uk_spine/sources/fixture.json | 96 +++++-- .../parity/uk_spine/sources/frs_raw/adult.tab | 272 +++++++++--------- .../uk_spine/sources/frs_raw/benefits.tab | 9 + .../uk_spine/sources/frs_raw/househol.tab | 272 +++++++++--------- .../parity/uk_spine/sources/household.csv | 2 +- .../parity/uk_spine/sources/person.csv | 270 ++++++++--------- .../sources/property_purchase_targets.json | 2 +- .../fixtures/parity/uk_spine/uk_spine.json | 2 +- 11 files changed, 558 insertions(+), 488 deletions(-) diff --git a/packages/microcosm-build/src/microcosm/build/uk/ledger_compile_parity_incumbent_2025_signed_differences.json b/packages/microcosm-build/src/microcosm/build/uk/ledger_compile_parity_incumbent_2025_signed_differences.json index 729516967..239f3140a 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/ledger_compile_parity_incumbent_2025_signed_differences.json +++ b/packages/microcosm-build/src/microcosm/build/uk/ledger_compile_parity_incumbent_2025_signed_differences.json @@ -1,11 +1,11 @@ { - "compiled_count": 1319, + "compiled_count": 1322, "counts_by_kind": { "calibration_drift": 561, "fixture_only": 46, - "ledger_only": 728 + "ledger_only": 731 }, - "difference_count": 1335, + "difference_count": 1338, "differences": [ { "fixture_value": 1608000.0, @@ -5259,7 +5259,7 @@ }, { "kind": "ledger_only", - "ledger_value": 35099000000.0, + "ledger_value": 37025000000.0, "name": "ons.household_road_fuel_expenditure", "period": 2025, "reason": "Ledger-compiled row has no fixture counterpart at this comparison period." @@ -5327,6 +5327,27 @@ "period": 2025, "reason": "Ledger-compiled row has no fixture counterpart at this comparison period." }, + { + "kind": "ledger_only", + "ledger_value": 658357.0, + "name": "ons.population.age_0", + "period": 2025, + "reason": "microcosm#1278 (the pre-Budget PR's plan, approved by María on 2026-10-20; microcosm#1095): one of the three all-persons rows for ages 0, 1 and 2, bound so the fit holds the single years inside the 0_4 sex bands, which stay bound beside them. The incumbent binds only the five-year bands, so this row has no fixture counterpart." + }, + { + "kind": "ledger_only", + "ledger_value": 679232.0, + "name": "ons.population.age_1", + "period": 2025, + "reason": "microcosm#1278 (the pre-Budget PR's plan, approved by María on 2026-10-20; microcosm#1095): one of the three all-persons rows for ages 0, 1 and 2, bound so the fit holds the single years inside the 0_4 sex bands, which stay bound beside them. The incumbent binds only the five-year bands, so this row has no fixture counterpart." + }, + { + "kind": "ledger_only", + "ledger_value": 696010.0, + "name": "ons.population.age_2", + "period": 2025, + "reason": "microcosm#1278 (the pre-Budget PR's plan, approved by María on 2026-10-20; microcosm#1095): one of the three all-persons rows for ages 0, 1 and 2, bound so the fit holds the single years inside the 0_4 sex bands, which stay bound beside them. The incumbent binds only the five-year bands, so this row has no fixture counterpart." + }, { "kind": "ledger_only", "ledger_value": 408119.0, diff --git a/packages/microcosm-build/src/microcosm/build/uk/release_input_coverage_manifest.json b/packages/microcosm-build/src/microcosm/build/uk/release_input_coverage_manifest.json index 2dcc5bd1f..1f6a23757 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/release_input_coverage_manifest.json +++ b/packages/microcosm-build/src/microcosm/build/uk/release_input_coverage_manifest.json @@ -470,7 +470,7 @@ "required_mass_change_reason": "Capital-gains incidence anchor moves the mass of non-liable clone households back to their paired originals until the sub-exempt and loss-making clone mass match the Advani-Summers reporter composition at the redrawn liable mass; every pair's mass and the total household mass are conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "Advani and Summers (2020), Capital Gains and UK Inequality, CAGE Working Paper 465", "survey": "Family Resources Survey 2024-25, SPI synthetic support, the HMRC Table 3 redrawn gains on the spine and Advani-Summers capital-gains incidence" @@ -493,7 +493,7 @@ "capital_gains" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "Advani and Summers (2020), Capital Gains and UK Inequality, CAGE Working Paper 465", "survey": "Family Resources Survey 2024-25, SPI synthetic support, and Advani-Summers capital-gains incidence" @@ -516,7 +516,7 @@ "required_mass_change_reason": "Capital-gains residential split divides every household carrying liable gainers into arms weighted by the solved residential probabilities, one arm per subset of residential gainers; every household's mass and the total household mass are conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "https://www.gov.uk/government/statistics/capital-gains-tax-statistics", "survey": "HMRC Capital Gains Tax statistics 2026 release, Table 8 (UK residential property disposals, 2024-25, administrative) on the amounts the Table 3 redraw placed" @@ -538,7 +538,7 @@ "required_mass_change_reason": "Capital-gains support split divides the wealthiest households of each HMRC Table 3 income band into light copies at equal weight; every household's mass and the total household mass are conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "HMRC Capital Gains Tax statistics, July 2026 release, Table 3 for 2024-25, via the vendored conditioning facts", "survey": "Family Resources Survey 2024-25, SPI synthetic support and HMRC Capital Gains Tax statistics Table 3 (2024-25 individuals by size of gain and taxable income)" @@ -567,7 +567,7 @@ "required_mass_change_reason": "ETB public-services imputation on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "UK Data Service SN 8856 Effects of Taxes and Benefits household tab, DfT rail fare index, and public NHS activity/cost table.", "survey": "Effects of Taxes and Benefits 1977-2024 and NHS age-gender public table" @@ -587,7 +587,7 @@ "required_mass_change_reason": "ETB VAT expenditure-rate imputation on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "UK Data Service SN 8856 Effects of Taxes and Benefits household tab and cited VAT anchor resource.", "survey": "Effects of Taxes and Benefits 1977-2024" @@ -609,7 +609,7 @@ "required_mass_change_reason": "High-value home support divides every owner household in the top value stratum of its region into light copies at equal weight; every household's mass and the total household mass are conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "Microcosm structural operator (microcosm#1240 fix 1); no publisher input", "survey": "Family Resources Survey 2024-25 and SPI synthetic support, after the WAS wealth draw and the regional property uprating" @@ -630,7 +630,7 @@ "required_mass_change_reason": "CGT asset-type assignment on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "https://www.gov.uk/government/statistics/capital-gains-tax-statistics", "survey": "HMRC Capital Gains Tax statistics 2026 release, Table 8 (UK residential property disposals, 2024-25, administrative), Table 4.1 (individuals claiming Business Asset Disposal Relief or Investors' Relief by band of qualifying gain, 2024-25, administrative) and Table 7 (disposals, proceeds and gains by asset type, 2023-24, sample-based), vendored from the pinned Chronicle feed" @@ -654,7 +654,7 @@ "capital_gains" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "conditioning_resource": "hmrc_cgt_conditioning_facts.json", "conditioning_resource_sha256": "054b1ee1a66cae6ed3793053eb0d3b9eea6b3f8976953479948ae11f7eedcd35", @@ -743,7 +743,7 @@ "full_frs_tei_band_unavailable" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "hmrc_surface": "2023-24", "mapped_build_period": "2024", @@ -785,7 +785,7 @@ "required_mass_change_reason": "LCFS consumption imputation on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "UK Data Service SN 9603 Living Costs and Food Survey 2024-25 (2nd edition) household/person tabs and the vendored Chronicle facts for NEED 2024 mean kWh, DESNZ Energy Trends and QEP average prices paid for calendar 2024, road-fuel outturn (DESNZ, HMRC, ONS Consumer Trends) and road fuel by vehicle type (DESNZ), ONS Consumer Trends household spending by COICOP division, the DfT VEH1103 licensed-car stock, NTS bus use, and the DfT and devolved bus finance tables and fares indices.", "survey": "Living Costs and Food Survey 2024-25" @@ -811,7 +811,7 @@ "required_mass_change_reason": "NTS bus-travel imputation on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "Department for Transport National Travel Survey, UK Data Service SN 5340 (End User Licence, 19th edition, November 2025), DOI 10.5255/UKDA-SN-5340-19; local licensed tab files (household, individual, trip); England residents only from 2013.", "survey": "National Travel Survey 2002-2024" @@ -831,7 +831,7 @@ "required_mass_change_reason": "Private-school attendance stored on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "policyengine-uk attends_private_school (the gov.simulation.private_school_vat attendance rates and factor), evaluated by the pinned engine", "survey": "policyengine-uk private-school attendance imputation, stored at the spine's weights" @@ -854,7 +854,7 @@ "property_finance_costs" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "https://www.gov.uk/government/statistics/property-rental-income-statistics", "survey": "Survey of Personal Incomes Public Use Tape 2022-23 and HMRC Property Rental Income Statistics 2026 (tax year 2024-25)" @@ -875,7 +875,7 @@ "required_mass_change_reason": "Annual property purchases imputed on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "https://www.gov.uk/government/statistics/uk-stamp-tax-statistics", "survey": "HMRC Annual Stamp Tax Statistics 2024 to 2025 (corrected 11 March 2026), Tables 6b, 8a and 8b" @@ -898,7 +898,7 @@ "property_wealth" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "uk/high_value_home_value_knots.json, built by tools/build_uk_high_value_home_stock.py from PolicyEngine/chronicle#343's registrations", "survey": "HM Land Registry Price Paid latest sales uprated with the UK House Price Index, owner-weighted by region (the dense value node's knots, region level)" @@ -922,7 +922,7 @@ "non_residential_property_value" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "MHCLG dwellings and the UK House Price Index regional average price averaged over the twelve months of calendar 2024 from the July 2026 full file, the frame's valuation basis, so the engine's annual uprating from 2024 projects the value once (microcosm#1240 fix 5).", "survey": "Public regional property reference" @@ -949,7 +949,7 @@ "employment_income" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "HMRC, Salary sacrifice reform for pension contributions effective from 6 April 2029", "survey": "Family Resources Survey 2024-25 salary-sacrifice respondents and HMRC salary-sacrifice reform analysis" @@ -982,7 +982,7 @@ "household_source_id" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "Reserved SPI support households for the HMRC Table 2.5 total-income bands from GBP 200,000, stacked at the published band taxpayer count over the donors per band (PolicyEngine/chronicle#280 lane).", "survey": "Survey of Personal Incomes Public Use Tape 2022-23 and HMRC Income Tax liabilities statistics July 2026 Table 2.5" @@ -1004,7 +1004,7 @@ "student_loan_plan" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "Explore Education Statistics Table 6a, Higher education total", "survey": "Family Resources Survey 2024-25 and Student Loans Company borrower forecasts for England" @@ -1026,7 +1026,7 @@ "required_mass_change_reason": "WAS Lifetime ISA imputation on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "Office for National Statistics Wealth and Assets Survey, UK Data Service SN 7215, DOI 10.5255/UKDA-SN-7215-20; local licensed round-8 person and household tabs (interviews April 2020 to March 2022, Great Britain).", "survey": "Wealth and Assets Survey round 8" @@ -1061,7 +1061,7 @@ "required_mass_change_reason": "WAS wealth imputation on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "929a688b052bd3d35951fe3315a141ae5c8e004cd8e22840eae470367d3ed88d", + "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", "source_vintages": { "source": "Office for National Statistics Wealth and Assets Survey, UK Data Service SN 7215, DOI 10.5255/UKDA-SN-7215-20; local licensed 2006-22 household tab.", "survey": "Wealth and Assets Survey round 8" diff --git a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/cgt_asset_type_facts.json b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/cgt_asset_type_facts.json index e64ed3150..79100c4e9 100644 --- a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/cgt_asset_type_facts.json +++ b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/cgt_asset_type_facts.json @@ -2,70 +2,70 @@ "resource": "synthetic-cgt-asset-type.json", "resource_sha256": "synthetic", "source_commit": "synthetic", - "table4_all_gains": 6341734.724429999, + "table4_all_gains": 6341728.91006761, "table4_all_tax": 0.0, - "table4_all_taxpayers": 15.640250289891858, + "table4_all_taxpayers": 15.64025028989186, "table4_bands": [ { - "gains": 5614.755055308437, + "gains": 5614.755050771031, "lower_bound": 0, "tax": null, - "taxpayers": 1.449861041223704, + "taxpayers": 1.4498610400415817, "upper_bound": 10000 }, { - "gains": 27080.12160600845, + "gains": 27083.345909709733, "lower_bound": 10000, "tax": null, - "taxpayers": 1.5144705021656795, + "taxpayers": 1.5144705014116808, "upper_bound": 25000 }, { - "gains": 76331.17900319055, + "gains": 76331.17897703486, "lower_bound": 25000, "tax": null, - "taxpayers": 2.1412992924367082, + "taxpayers": 2.1412992916855758, "upper_bound": 50000 }, { - "gains": 157905.09467308622, + "gains": 157905.0946424909, "lower_bound": 50000, "tax": null, - "taxpayers": 2.1780392870465786, + "taxpayers": 2.178039286606179, "upper_bound": 100000 }, { - "gains": 155213.69791341943, + "gains": 155213.69790998782, "lower_bound": 100000, "tax": null, - "taxpayers": 0.9562896654807813, + "taxpayers": 0.9562896654462721, "upper_bound": 250000 }, { - "gains": 604360.2751651776, + "gains": 604360.2752446379, "lower_bound": 250000, "tax": null, - "taxpayers": 1.7593341344988387, + "taxpayers": 1.7593341347179783, "upper_bound": 500000 }, { - "gains": 754806.8460223324, + "gains": 754797.8046933388, "lower_bound": 500000, "tax": null, - "taxpayers": 1.080533612048092, + "taxpayers": 1.0805336123429539, "upper_bound": 1000000 }, { - "gains": 4560422.7549914755, + "gains": 4560422.757639639, "lower_bound": 1000000, "tax": null, - "taxpayers": 4.5604227549914755, + "taxpayers": 4.560422757639639, "upper_bound": null } ], - "table4_individuals_gains": 6341734.724429999, + "table4_individuals_gains": 6341728.91006761, "table4_individuals_tax": 0.0, - "table4_individuals_taxpayers": 15.640250289891858, + "table4_individuals_taxpayers": 15.64025028989186, "table4_trusts_gains": 0.0, "table4_trusts_tax": 0.0, "table7_total_disposals": 2743095.2380952383, @@ -115,11 +115,11 @@ } ], "table8a_disposals_total": 29.493043403796086, - "table8a_gains_total": 36452887.05650567, - "table8a_tax_total": 7290577.411301135, + "table8a_gains_total": 36452873.707876876, + "table8a_tax_total": 7290574.741575375, "table8a_taxpayers_total": 26.811857639814622, - "table8b_all_gains": 36452887.05650567, + "table8b_all_gains": 36452873.707876876, "table8b_all_taxpayers": 26.811857639814622, - "table8b_individuals_gains": 36452887.05650567, + "table8b_individuals_gains": 36452873.707876876, "table8b_individuals_taxpayers": 26.811857639814622 } diff --git a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/fixture.json b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/fixture.json index c2044578f..b5023384e 100644 --- a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/fixture.json +++ b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/fixture.json @@ -94,6 +94,40 @@ "stage": "age_tail", "survey": "Family Resources Survey 2024-25 and ONS mid-year population estimates" }, + "carers_allowance_take_up": { + "artifacts": [], + "grain": "person", + "nonnegative_outputs": [], + "notes": "Runs after the SPI income chain, UC capital coherence and the Pension Credit and Child Benefit redraws, before CGT cloning, so every clone carries its source's draw (microcosm#1319). frs_spine sets would_claim_carers_allowance from reported receipt and the SPI income chain re-derives it from the refilled receipt on the rows it redraws, so that care_hours qualifies a carer for the Universal Credit carer element without paying the allowance to every carer (#882). A carer above the earnings limit cannot report the allowance, so no reform that widens it reached a carer who would claim once entitled: the April 2025 rise of the limit from \u00a3151 to \u00a3196 a week brought an estimated 61,000 more people into eligibility (Independent Review of Carer's Allowance Overpayments, July 2025, chapter 7). One temporary engine materialization at the survey year, on the frame's own values, gives each person's is_gainfully_employed_for_carers_allowance (consumed only); the engine reads a year's parameters at 30 April, so the limit is 2024-25's \u00a3151. A person outside Scotland whose care_hours reach the engine's gov.dwp.carers_allowance.min_hours (35), who reports no allowance and whom that test holds gainfully employed claims at the take-up contract's carers_allowance_newly_entitled rate (0.6, Mar\u00eda's ruling of 2026-10-20, sensitivity 0.45 to 0.75) on the person's identity-keyed uniform (seed 0, salt would_claim_carers_allowance): would_claim = reported OR (eligible AND u < rate). A reporter stays true; a carer under the limit who reports no allowance stays false, as the survey records them entitled and not claiming. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test. The earnings test is read before salary_sacrifice moves some contributors' pension amounts out of their pay, so a drawn carer whom that conversion takes under the survey year's limit keeps the flag although the file then shows them entitled and not reporting. The stage rebuilds the flag from reported receipt and refuses a frame whose flag no longer follows it. Its receipt bands support on distinct source households (household_source_id), and gives a weighted total only where ten or more carry it and the realised share only where neither side rests on one to nine; the stage has no health gate.", + "operations": [ + { + "consumed_only": true, + "kind": "materialize_rules_engine_predictors", + "predictors": [ + "is_gainfully_employed_for_carers_allowance" + ], + "year_rule": "survey_year" + }, + { + "assignment_unit": "person", + "draw": "would_claim_carers_allowance", + "eligibility": "persons outside Scotland whose care_hours reach policyengine-uk's gov.dwp.carers_allowance.min_hours, who report no Carer's Allowance, and whom is_gainfully_employed_for_carers_allowance holds gainfully employed at the survey year: the carers the earnings limit alone keeps from the allowance. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test", + "kind": "assign_binary_from_rate", + "output": "would_claim_carers_allowance", + "rate_derivation": "the take-up contract's carers_allowance_newly_entitled rate, drawn flat over the eligible persons; would_claim = reported OR (eligible AND u < rate), so a reporter stays true and every other person false", + "rate_key": "carers_allowance_newly_entitled", + "reported_true_anchor": "carers_allowance_reported > 0", + "seed": 0 + } + ], + "outputs": [], + "rewrites": [ + "would_claim_carers_allowance" + ], + "source": "Independent Review of Carer's Allowance Overpayments (July 2025), chapter 7, and DWP benefit statistics, through the UK take-up contract's carers_allowance_newly_entitled rate, applied to PolicyEngine-UK's Carer's Allowance earnings test after the SPI income chain.", + "stage": "carers_allowance_take_up", + "survey": "Family Resources Survey 2024-25" + }, "cgt_incidence_anchor": { "artifacts": [ { @@ -1074,8 +1108,8 @@ "locator": "househol.tab", "role": "frs_table", "runtime_sha256_required": true, - "sha256": "c16fdc0dfbe254127a1decd9ebd796cc0584ecd0cf9c372da6143f5e223227bb", - "size_bytes": 17280, + "sha256": "7b5fc26572d05bc21cee203b91e20fa9e743c170cabb497a284497b309eb3a89", + "size_bytes": 17554, "table": "househol", "vintage": "synthetic-h2" } @@ -1084,7 +1118,7 @@ "nonnegative_outputs": [ "council_tax" ], - "notes": "Re-reads raw househol.tab because spine council_tax_reported clips missing values. FRS 2024-25 CTANNUAL is the bill after discounts and council tax reduction, and the engine reads council_tax before the reduction, so a household reporting a reduction gets its CTREBAMT added back and the cells pool non-recipients only (uk-data#496/#499, microcosm#1095). Scottish water and sewerage charges are netted before cell means at the shares DWP's CTANNUAL carries (the gross charges in full for non-recipients, 65% for reduction recipients); no-donor cells impute zero. The dead ct_mean.replace(-1, ...) branch is intentionally dropped.", + "notes": "Re-reads raw househol.tab because spine council_tax_reported clips missing values. FRS 2024-25 CTANNUAL is the bill after discounts and council tax reduction, and the engine reads council_tax before the reduction, so a household reporting a reduction gets its CTREBAMT added back and the cells pool non-recipients only (uk-data#496/#499, microcosm#1095). Scottish water and sewerage charges are netted before cell means at the shares DWP's CTANNUAL carries (the gross charges in full for non-recipients, 65% for reduction recipients); no-donor cells impute zero. A household where someone pays council tax (CTPAID 1) with no reported reduction and a zero CTANNUAL owes a bill, so it takes its cell mean as a missing bill does (microcosm#1278). The dead ct_mean.replace(-1, ...) branch is intentionally dropped.", "operations": [ { "delimiter": "\t", @@ -1102,7 +1136,7 @@ ], "donor_filter": "raw ctreb != 1 and ctannual > 0", "kind": "impute_cell_means", - "missing": "raw ctannual < 0 or NaN", + "missing": "raw ctannual < 0 or NaN, or ctannual == 0 with ctpaid == 1 and ctreb != 1", "value": "council tax before council tax reduction: CTANNUAL net of the Scottish water and sewerage charges ((CWATAMT1 + CSEWAMT1) x 365.25/7, at 0.65 where CTREB is 1; CWATAMTD where CWATAMT1 is not positive), plus CTREBAMT x 365.25/7 where CTREB is 1 and CTREBAMT > 0; a CTREB 1 household without a positive CTREBAMT takes the larger of its netted CTANNUAL and its cell mean" } ], @@ -1154,8 +1188,8 @@ "locator": "adult.tab", "role": "frs_table", "runtime_sha256_required": true, - "sha256": "f41b0fcdbd39ea3aef4150454b87f40bbdc5b569d830e8eae7bd37c0198cb9d3", - "size_bytes": 31478, + "sha256": "5c6e326a755da49737d18b976eb90a3fa1e8fd95984ce6c88a8e8238954b7f31", + "size_bytes": 31756, "table": "adult", "vintage": "synthetic-h2" }, @@ -1273,8 +1307,8 @@ "locator": "adult.tab", "role": "frs_table", "runtime_sha256_required": true, - "sha256": "f41b0fcdbd39ea3aef4150454b87f40bbdc5b569d830e8eae7bd37c0198cb9d3", - "size_bytes": 31478, + "sha256": "5c6e326a755da49737d18b976eb90a3fa1e8fd95984ce6c88a8e8238954b7f31", + "size_bytes": 31756, "table": "adult", "vintage": "synthetic-h2" } @@ -1316,8 +1350,8 @@ "locator": "adult.tab", "role": "frs_table", "runtime_sha256_required": true, - "sha256": "f41b0fcdbd39ea3aef4150454b87f40bbdc5b569d830e8eae7bd37c0198cb9d3", - "size_bytes": 31478, + "sha256": "5c6e326a755da49737d18b976eb90a3fa1e8fd95984ce6c88a8e8238954b7f31", + "size_bytes": 31756, "table": "adult", "vintage": "synthetic-h2" }, @@ -1327,8 +1361,8 @@ "locator": "benefits.tab", "role": "frs_table", "runtime_sha256_required": true, - "sha256": "1df8dccae70d752fe287961ee7867fdf2887c1705bbaabf54d6c7af765347b91", - "size_bytes": 20049, + "sha256": "89446e64bb97825ba7f94c4080c160c9f189e22426f3af1e89d7d86eee8f2f3f", + "size_bytes": 20239, "table": "benefits", "vintage": "synthetic-h2" }, @@ -1534,8 +1568,8 @@ "locator": "adult.tab", "role": "frs_table", "runtime_sha256_required": true, - "sha256": "f41b0fcdbd39ea3aef4150454b87f40bbdc5b569d830e8eae7bd37c0198cb9d3", - "size_bytes": 31478, + "sha256": "5c6e326a755da49737d18b976eb90a3fa1e8fd95984ce6c88a8e8238954b7f31", + "size_bytes": 31756, "table": "adult", "vintage": "synthetic-h2" } @@ -1645,8 +1679,8 @@ "locator": "adult.tab", "role": "frs_table", "runtime_sha256_required": true, - "sha256": "f41b0fcdbd39ea3aef4150454b87f40bbdc5b569d830e8eae7bd37c0198cb9d3", - "size_bytes": 31478, + "sha256": "5c6e326a755da49737d18b976eb90a3fa1e8fd95984ce6c88a8e8238954b7f31", + "size_bytes": 31756, "table": "adult", "vintage": "synthetic-h2" }, @@ -1667,8 +1701,8 @@ "locator": "househol.tab", "role": "frs_table", "runtime_sha256_required": true, - "sha256": "c16fdc0dfbe254127a1decd9ebd796cc0584ecd0cf9c372da6143f5e223227bb", - "size_bytes": 17280, + "sha256": "7b5fc26572d05bc21cee203b91e20fa9e743c170cabb497a284497b309eb3a89", + "size_bytes": 17554, "table": "househol", "vintage": "synthetic-h2" } @@ -1876,8 +1910,8 @@ "locator": "adult.tab", "role": "frs_table", "runtime_sha256_required": true, - "sha256": "f41b0fcdbd39ea3aef4150454b87f40bbdc5b569d830e8eae7bd37c0198cb9d3", - "size_bytes": 31478, + "sha256": "5c6e326a755da49737d18b976eb90a3fa1e8fd95984ce6c88a8e8238954b7f31", + "size_bytes": 31756, "table": "adult", "vintage": "synthetic-h2" }, @@ -1887,8 +1921,8 @@ "locator": "benefits.tab", "role": "frs_table", "runtime_sha256_required": true, - "sha256": "1df8dccae70d752fe287961ee7867fdf2887c1705bbaabf54d6c7af765347b91", - "size_bytes": 20049, + "sha256": "89446e64bb97825ba7f94c4080c160c9f189e22426f3af1e89d7d86eee8f2f3f", + "size_bytes": 20239, "table": "benefits", "vintage": "synthetic-h2" }, @@ -1942,8 +1976,8 @@ "locator": "househol.tab", "role": "frs_table", "runtime_sha256_required": true, - "sha256": "c16fdc0dfbe254127a1decd9ebd796cc0584ecd0cf9c372da6143f5e223227bb", - "size_bytes": 17280, + "sha256": "7b5fc26572d05bc21cee203b91e20fa9e743c170cabb497a284497b309eb3a89", + "size_bytes": 17554, "table": "househol", "vintage": "synthetic-h2" }, @@ -2049,7 +2083,7 @@ "external_child_payments", "care_hours" ], - "notes": "Root E2 spine assembly. It carries direct raw mappings only; education-grant aggregate and council-tax reported fields remain raw carriers for E3. Benefit take-up, BRMA/LHA assignment, stochastic flags, and imputations are intentionally absent from this stage, except two identity-keyed draws. One is the UC start-up claim recency (uk-data#527). The other is each person's months_since_last_birthday, which policyengine-uk reads to place a date of birth (the two-child limit, the State Pension scheme, the Pension Credit qualifying age). Each single year of age and sex is spread evenly over the year at the FRS weights, in an order set by a draw on the person's stable id, as the engine spreads it when the column is unset, and the column is stored so every later engine read, the calibration's and the release's included, takes the same months whatever weights or identifiers the file carries (microcosm#1095). The UC start-up period needs the raw claim, interview and job dates only this stage reads, so a UC record without a linked claim date takes its claim recency from a benefit-unit-keyed draw at the linked share. The 2024-25 househol.tab is not sernum-ordered; the declared household sort guards stable identity. care_hours carries the FRS banded care-hours code as weekly hours (lower band edge) and would_claim_carers_allowance follows reported receipt, so the engine keeps Carer's Allowance on reported claimants while the hours qualify carers for the Universal Credit carer element (#882). SEINCAM2, the self-employment income the respondent gives, splits by its sign (uk-data#528), so profits go to self_employment_income and losses to trading_loss as a positive amount, the two inputs policyengine-uk reads from 2.131.0 (pe-uk#2085). The engine uprates trading_loss into each projected year as it does self_employment_income, so a loss persists like a profit; the engine documents that a one-off loss would be set to zero in later years, which a one-year survey cannot tell apart. Six of policyengine-uk's eleven owned-company inputs (pe-uk#1965) come from the FRS job tab (microcosm#1095). A director (DIRECTOR 1 or NATURE 1) who owns at least half of the company (DIRPERC 1 to 3, the ruling of 2026-10-16) stands as its sole owner or partner and works in it. The company is their main employment when the job is their first (JOBTYPE 1); it carries on a property business when the main job's SIC division is 68 and a trade otherwise, and its income share is the dividends the job records (DIVIDEND, after tax), the part of the company's profit the survey sees. A company held in another job carries on neither, since ADULT.SIC codes the main job only, which leaves the engine's company-owner rules off for it. The stocks and the intermediaries inputs keep the engine's defaults.", + "notes": "Root E2 spine assembly. It carries direct raw mappings only; education-grant aggregate and council-tax reported fields remain raw carriers for E3. Benefit take-up, BRMA/LHA assignment, stochastic flags, and imputations are intentionally absent from this stage, except two identity-keyed draws. One is the UC start-up claim recency (uk-data#527). The other is each person's months_since_last_birthday, which policyengine-uk reads to place a date of birth (the two-child limit, the State Pension scheme, the Pension Credit qualifying age). Each single year of age and sex is spread evenly over the year at the FRS weights, in an order set by a draw on the person's stable id, as the engine spreads it when the column is unset, and the column is stored so every later engine read, the calibration's and the release's included, takes the same months whatever weights or identifiers the file carries (microcosm#1095). The UC start-up period needs the raw claim, interview and job dates only this stage reads, so a UC record without a linked claim date takes its claim recency from a benefit-unit-keyed draw at the linked share. The 2024-25 househol.tab is not sernum-ordered; the declared household sort guards stable identity. care_hours carries the FRS banded care-hours code as weekly hours (lower band edge) and would_claim_carers_allowance follows reported receipt, so the engine keeps Carer's Allowance on reported claimants while the hours qualify carers for the Universal Credit carer element (#882); after the SPI income chain, carers_allowance_take_up opens the flag to carers the earnings limit alone keeps from the allowance (microcosm#1319). SEINCAM2, the self-employment income the respondent gives, splits by its sign (uk-data#528), so profits go to self_employment_income and losses to trading_loss as a positive amount, the two inputs policyengine-uk reads from 2.131.0 (pe-uk#2085). The engine uprates trading_loss into each projected year as it does self_employment_income, so a loss persists like a profit; the engine documents that a one-off loss would be set to zero in later years, which a one-year survey cannot tell apart. Six of policyengine-uk's eleven owned-company inputs (pe-uk#1965) come from the FRS job tab (microcosm#1095). A director (DIRECTOR 1 or NATURE 1) who owns at least half of the company (DIRPERC 1 to 3, the ruling of 2026-10-16) stands as its sole owner or partner and works in it. The company is their main employment when the job is their first (JOBTYPE 1); it carries on a property business when the main job's SIC division is 68 and a trade otherwise, and its income share is the dividends the job records (DIVIDEND, after tax), the part of the company's profit the survey sees. A company held in another job carries on neither, since ADULT.SIC codes the main job only, which leaves the engine's company-owner rules off for it. The stocks and the intermediaries inputs keep the engine's defaults.", "operations": [ { "delimiter": "\t", @@ -2077,11 +2111,17 @@ }, { "kind": "map_coded_amounts", - "scope": "region, tenure, accommodation, council tax band, benefit-code amount mappings (Scotland's Adult and Child Disability Payment codes 117/118 and 121/122 into the PIP and DLA columns they replace; benefit recovery codes 69 and 70 unmapped); adult HOURTOT care-hours band code to weekly care_hours at the band's lower edge (codes 5, 6, 7 and 10 reach the 35-hour Carer's Allowance line); would_claim_carers_allowance from positive reported Carer's Allowance" + "scope": "region, tenure, accommodation, council tax band, benefit-code amount mappings (Scotland's Adult and Child Disability Payment codes 117/118 and 121/122 into the PIP and DLA columns they replace; benefit recovery codes 69 and 70 unmapped); adult HOURTOT care-hours band code to weekly care_hours at the band's lower edge (codes 5, 6, 7 and 10 reach the 35-hour Carer's Allowance line); would_claim_carers_allowance from positive reported Carer's Allowance, the anchor carers_allowance_take_up opens to carers over the earnings limit (microcosm#1319)" }, { "kind": "annualize_periodic_amounts", - "weeks_in_year": 52.17857142857143 + "weeks_in_year": 52.17857142857143, + "weeks_in_year_exceptions": { + "state_pension_reported": { + "reason": "The State Pension is paid at weekly rates, and policyengine-uk reads state_pension_reported back to a weekly amount at 52 weeks a year before comparing it with the full rate, so at 365.25 / 7 a full-rate pensioner would read 0.34% above the full rate and the excess would become a protected payment. An exception for the State Pension alone to microcosm#1095's weekly amounts (Mar\u00eda's ruling of 2026-10-20, microcosm#1278).", + "weeks_in_year": 52 + } + } }, { "assignment_unit": "benefit unit", @@ -5257,7 +5297,7 @@ "artifacts": [], "grain": "person+benunit", "nonnegative_outputs": [], - "notes": "Runs on SPI-channel rows after uc_reporter_redraw, the last writer of Universal Credit reports, and before uc_capital_coherence and the Pension Credit and Child Benefit take-up stages (microcosm#1095, uk-data#514). The stage-2 forests of hmrc_spi_income_spine re-impute each SPI adult's benefit reports from age, gender, region and the new incomes, with nothing of the benefit unit's entitlement or claim history. This stage zeroes the SPI rows' contributory and income-based JSA, income-related ESA, Income Support, Working and Child Tax Credit, Severe Disablement Allowance and Sure Start Maternity Grant reports, whose award needs an existing legacy claim, an out-of-work test, or a claim the copied household's new incomes cannot carry (policyengine-uk pays income-related ESA as reported behind a capital test alone); restores Industrial Injuries Disablement Benefit, the Armed Forces Compensation Scheme and bereavement support from the FRS twin (person_source_id), since they follow an injury, service or a death; re-derives the disability flags (the categories, which read only AA, DLA and PIP, are asserted unchanged) and receives_benefits_in_own_right from the final reports; and redraws would_claim_uc for SPI benefit units as frs_take_up draws it for FRS units: a unit with a Universal Credit reporter claims, and the other units in frs_take_up's Universal Credit population (a UC claimant or partner aged 18 to under Pension Credit qualifying age) claim as the residual of the contract's universal_credit rate on draws keyed on the SPI unit's own identity. Contributory ESA, PIP, DLA, AA, Carer's Allowance, State Pension and Winter Fuel Payment keep their draws, and FRS rows are never modified; contributory ESA is open to new claims and not income-tested, and the incapacity it needs follows the person, whose health and disability reports the SPI copy keeps.", + "notes": "Runs on SPI-channel rows after uc_reporter_redraw, the last writer of Universal Credit reports, and before uc_capital_coherence and the Pension Credit, Child Benefit and Carer's Allowance take-up stages (microcosm#1095, uk-data#514). The stage-2 forests of hmrc_spi_income_spine re-impute each SPI adult's benefit reports from age, gender, region and the new incomes, with nothing of the benefit unit's entitlement or claim history. This stage zeroes the SPI rows' contributory and income-based JSA, income-related ESA, Income Support, Working and Child Tax Credit, Severe Disablement Allowance and Sure Start Maternity Grant reports, whose award needs an existing legacy claim, an out-of-work test, or a claim the copied household's new incomes cannot carry (policyengine-uk pays income-related ESA as reported behind a capital test alone); restores Industrial Injuries Disablement Benefit, the Armed Forces Compensation Scheme and bereavement support from the FRS twin (person_source_id), since they follow an injury, service or a death; re-derives the disability flags (the categories, which read only AA, DLA and PIP, are asserted unchanged) and receives_benefits_in_own_right from the final reports; and redraws would_claim_uc for SPI benefit units as frs_take_up draws it for FRS units: a unit with a Universal Credit reporter claims, and the other units in frs_take_up's Universal Credit population (a UC claimant or partner aged 18 to under Pension Credit qualifying age) claim as the residual of the contract's universal_credit rate on draws keyed on the SPI unit's own identity. Contributory ESA, PIP, DLA, AA, Carer's Allowance, State Pension and Winter Fuel Payment keep their draws (carers_allowance_take_up later opens the Carer's Allowance claim flag to carers over the earnings limit, microcosm#1319), and FRS rows are never modified; contributory ESA is open to new claims and not income-tested, and the incapacity it needs follows the person, whose health and disability reports the SPI copy keeps.", "operations": [ { "columns": [ diff --git a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/adult.tab b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/adult.tab index d21a4b738..30b788c71 100644 --- a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/adult.tab +++ b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/adult.tab @@ -1,136 +1,136 @@ -SERNUM BENUNIT PERSON AGE80 AGE SEX TOTHOURS HRPID UPERSON RELHRP R01 R02 R03 R04 R05 R06 R07 R08 R09 R10 R11 R12 R13 R14 MARITAL EMPSTATI SAMESIT SRENTAMT CONVBL SDEMP01 SDEMP02 SDEMP03 SDEMP04 SDEMP05 SDEMP06 SDEMP07 SDEMP08 SDEMP09 SDEMP10 SDEMP11 SDEMP12 MJOBSECT SIC FTED TYPEED2 EDUCQUAL TRAINEE EMAAMT CHEMAAMT INEARNS SEINCAM2 MNTUS1 MNTUSAM1 MNTAMT1 MNTAMT2 CVPAY ROYYR1 ROYYR2 ROYYR3 ROYYR4 ALLPAY2 ALLPAY3 ALLPAY4 CHAMTERN CHAMTTST APAMT APDAMT PAREAMT REDAMT SLREPAMT SLOS EDUCLEFT SSPADJ SMPADJ SPPADJ TUBORR ACCSSAMT ACCSSPD SPCREG1 SPCREG2 GRTDIR1 GRTDIR2 HEARTVAL -1 1 1 0 80 2 21 1 1 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 11 2 0 2 2 0.0 0.0 101.0 1.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 17 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -2 1 1 0 22 1 22 1 1 3 3 1 2 3 3 3 3 3 3 3 3 3 3 3 3 1 12 2 0 3 2 0.0 0.0 102.0 2.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 18 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -3 1 1 0 23 2 23 1 1 1 4 2 1 3 3 3 3 3 3 3 3 3 3 3 3 2 13 2 0 4 2 0.0 0.0 103.0 3.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 19 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -4 1 1 0 24 1 24 1 1 2 5 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 14 2 0 5 2 0.0 0.0 104.0 4.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 20 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -5 1 1 0 25 2 25 1 1 7 3 6 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 15 2 0 6 2 0.0 0.0 105.0 0.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 21 1.0 0.5 0.25 500.0 1.0 52.0 2 1 2.0 3.0 5.0 -6 1 1 0 26 1 26 1 1 1 7 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 16 2 0 7 2 0.0 0.0 106.0 1.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 22 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -7 1 1 0 27 2 27 1 1 2 8 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 17 2 0 8 2 0.0 0.0 107.0 2.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 23 1.0 0.5 0.25 500.0 1.0 52.0 1 2 2.0 3.0 5.0 -8 1 1 0 28 1 28 1 1 3 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 18 2 0 9 2 0.0 0.0 108.0 3.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 16 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -9 1 1 0 29 2 29 1 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 19 2 0 10 2 0.0 0.0 109.0 4.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 17 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -10 1 1 0 30 1 30 1 1 7 2 3 1 2 3 3 3 3 3 3 3 3 3 3 3 3 1 20 2 0 11 2 0.0 0.0 110.0 0.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 18 1.0 0.5 0.25 500.0 1.0 52.0 2 1 2.0 3.0 5.0 -11 1 1 0 31 2 31 1 1 3 4 2 1 3 3 3 3 3 3 3 3 3 3 3 3 2 21 2 0 12 2 0.0 0.0 111.0 1.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 19 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -12 1 1 0 32 1 32 1 1 1 5 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 22 2 0 13 2 0.0 0.0 112.0 2.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 20 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -13 1 1 0 33 2 33 1 1 2 6 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 23 2 0 14 2 0.0 0.0 113.0 3.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 21 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -14 1 1 0 34 1 34 1 1 3 7 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 24 2 0 15 2 0.0 0.0 114.0 4.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 22 1.0 0.5 0.25 500.0 1.0 52.0 1 2 2.0 3.0 5.0 -15 1 1 0 35 2 35 1 1 7 1 8 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 25 2 0 16 2 0.0 0.0 115.0 0.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 23 1.0 0.5 0.25 500.0 1.0 52.0 2 1 2.0 3.0 5.0 -16 1 1 0 36 1 36 1 1 2 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 26 2 0 17 2 0.0 0.0 116.0 1.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 16 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -17 1 1 0 37 2 37 1 1 3 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 27 2 0 18 2 0.0 0.0 117.0 2.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 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11.0 12.0 13.0 20.0 2.0 2 17 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -130 1 1 0 40 1 25 1 1 7 2 3 1 2 3 3 3 3 3 3 3 3 3 3 3 3 1 60 2 0 5 2 0.0 0.0 230.0 0.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 18 1.0 0.5 0.25 500.0 1.0 52.0 2 1 2.0 3.0 5.0 -131 1 1 0 41 2 26 1 1 3 4 2 1 3 3 3 3 3 3 3 3 3 3 3 3 2 61 2 0 6 2 0.0 0.0 231.0 1.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 19 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -132 1 1 0 42 1 27 1 1 1 5 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 62 2 0 7 2 0.0 0.0 232.0 2.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 20 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -133 1 1 0 43 2 28 1 1 2 6 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 63 2 0 8 2 0.0 0.0 233.0 3.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 21 1.0 0.5 0.25 500.0 1.0 52.0 1 2 2.0 3.0 5.0 -134 1 1 0 44 1 29 1 1 3 7 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 64 2 0 9 2 0.0 0.0 234.0 4.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 22 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 -135 1 1 0 45 2 30 1 1 7 1 8 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 65 2 0 10 2 0.0 0.0 235.0 0.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 23 1.0 0.5 0.25 500.0 1.0 52.0 2 1 2.0 3.0 5.0 +SERNUM BENUNIT PERSON AGE80 AGE SEX TOTHOURS HRPID UPERSON RELHRP R01 R02 R03 R04 R05 R06 R07 R08 R09 R10 R11 R12 R13 R14 MARITAL EMPSTATI SAMESIT SRENTAMT CONVBL SDEMP01 SDEMP02 SDEMP03 SDEMP04 SDEMP05 SDEMP06 SDEMP07 SDEMP08 SDEMP09 SDEMP10 SDEMP11 SDEMP12 MJOBSECT SIC FTED TYPEED2 EDUCQUAL TRAINEE EMAAMT CHEMAAMT INEARNS SEINCAM2 MNTUS1 MNTUSAM1 MNTAMT1 MNTAMT2 CVPAY ROYYR1 ROYYR2 ROYYR3 ROYYR4 ALLPAY2 ALLPAY3 ALLPAY4 CHAMTERN CHAMTTST APAMT APDAMT PAREAMT REDAMT SLREPAMT SLOS EDUCLEFT SSPADJ SMPADJ SPPADJ TUBORR ACCSSAMT ACCSSPD SPCREG1 SPCREG2 GRTDIR1 GRTDIR2 HEARTVAL HOURTOT +1 1 1 0 80 2 21 1 1 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 11 2 0 2 2 0.0 0.0 101.0 1.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 17 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 5 +2 1 1 0 22 1 22 1 1 3 3 1 2 3 3 3 3 3 3 3 3 3 3 3 3 1 12 2 0 3 2 0.0 0.0 102.0 2.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 18 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +3 1 1 0 23 2 23 1 1 1 4 2 1 3 3 3 3 3 3 3 3 3 3 3 3 2 13 2 0 4 2 0.0 0.0 103.0 3.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 19 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +4 1 1 0 24 1 24 1 1 2 5 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 14 2 0 5 2 0.0 0.0 104.0 4.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 20 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +5 1 1 0 25 2 25 1 1 7 3 6 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 15 2 0 6 2 0.0 0.0 105.0 0.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 21 1.0 0.5 0.25 500.0 1.0 52.0 2 1 2.0 3.0 5.0 0 +6 1 1 0 26 1 26 1 1 1 7 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 16 2 0 7 2 0.0 0.0 106.0 1.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 22 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 5 +7 1 1 0 27 2 27 1 1 2 8 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 17 2 0 8 2 0.0 0.0 107.0 2.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 23 1.0 0.5 0.25 500.0 1.0 52.0 1 2 2.0 3.0 5.0 4 +8 1 1 0 28 1 28 1 1 3 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 18 2 0 9 2 0.0 0.0 108.0 3.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 16 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +9 1 1 0 29 2 29 1 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 19 2 0 10 2 0.0 0.0 109.0 4.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 17 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +10 1 1 0 30 1 30 1 1 7 2 3 1 2 3 3 3 3 3 3 3 3 3 3 3 3 1 20 2 0 11 2 0.0 0.0 110.0 0.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 18 1.0 0.5 0.25 500.0 1.0 52.0 2 1 2.0 3.0 5.0 0 +11 1 1 0 31 2 31 1 1 3 4 2 1 3 3 3 3 3 3 3 3 3 3 3 3 2 21 2 0 12 2 0.0 0.0 111.0 1.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 19 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 5 +12 1 1 0 32 1 32 1 1 1 5 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 22 2 0 13 2 0.0 0.0 112.0 2.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 20 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +13 1 1 0 33 2 33 1 1 2 6 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 23 2 0 14 2 0.0 0.0 113.0 3.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 21 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +14 1 1 0 34 1 34 1 1 3 7 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 24 2 0 15 2 0.0 0.0 114.0 4.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 22 1.0 0.5 0.25 500.0 1.0 52.0 1 2 2.0 3.0 5.0 4 +15 1 1 0 35 2 35 1 1 7 1 8 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 25 2 0 16 2 0.0 0.0 115.0 0.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 23 1.0 0.5 0.25 500.0 1.0 52.0 2 1 2.0 3.0 5.0 0 +16 1 1 0 36 1 36 1 1 2 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 26 2 0 17 2 0.0 0.0 116.0 1.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 16 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 5 +17 1 1 0 37 2 37 1 1 3 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 27 2 0 18 2 0.0 0.0 117.0 2.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 17 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +18 1 1 0 38 1 38 1 1 1 3 1 2 3 3 3 3 3 3 3 3 3 3 3 3 1 28 2 0 1 2 0.0 0.0 118.0 3.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 18 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +19 1 1 0 39 2 39 1 1 2 4 2 1 3 3 3 3 3 3 3 3 3 3 3 3 2 29 2 0 2 2 0.0 0.0 119.0 4.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 19 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +20 1 1 0 40 1 40 1 1 7 3 5 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 30 2 0 3 2 0.0 0.0 120.0 0.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 20 1.0 0.5 0.25 500.0 1.0 52.0 2 1 2.0 3.0 5.0 0 +21 1 1 0 41 2 41 1 1 1 6 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 31 2 0 4 2 0.0 0.0 121.0 1.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 21 1.0 0.5 0.25 500.0 1.0 52.0 1 2 2.0 3.0 5.0 5 +22 1 1 0 42 1 42 1 1 2 7 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 32 2 0 5 2 0.0 0.0 122.0 2.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 22 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +23 1 1 0 43 2 43 1 1 3 8 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 33 2 0 6 2 0.0 0.0 123.0 3.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 23 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +24 1 1 0 44 1 44 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 34 2 0 7 2 0.0 0.0 124.0 4.0 2 1.0 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1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 56 2 0 1 2 0.0 0.0 226.0 1.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 22 1.0 0.5 0.25 500.0 1.0 52.0 1 2 2.0 3.0 5.0 5 +127 1 1 0 37 2 22 1 1 2 8 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 57 2 0 2 2 0.0 0.0 227.0 2.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 23 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +128 1 1 0 38 1 23 1 1 3 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 58 2 0 3 2 0.0 0.0 228.0 3.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 16 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +129 1 1 0 39 2 24 1 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 59 2 0 4 2 0.0 0.0 229.0 4.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 17 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +130 1 1 0 40 1 25 1 1 7 2 3 1 2 3 3 3 3 3 3 3 3 3 3 3 3 1 60 2 0 5 2 0.0 0.0 230.0 0.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 18 1.0 0.5 0.25 500.0 1.0 52.0 2 1 2.0 3.0 5.0 0 +131 1 1 0 41 2 26 1 1 3 4 2 1 3 3 3 3 3 3 3 3 3 3 3 3 2 61 2 0 6 2 0.0 0.0 231.0 1.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 19 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 5 +132 1 1 0 42 1 27 1 1 1 5 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 62 2 0 7 2 0.0 0.0 232.0 2.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 20 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +133 1 1 0 43 2 28 1 1 2 6 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 63 2 0 8 2 0.0 0.0 233.0 3.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 21 1.0 0.5 0.25 500.0 1.0 52.0 1 2 2.0 3.0 5.0 4 +134 1 1 0 44 1 29 1 1 3 7 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 64 2 0 9 2 0.0 0.0 234.0 4.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 22 1.0 0.5 0.25 500.0 1.0 52.0 2 2 2.0 3.0 5.0 0 +135 1 1 0 45 2 30 1 1 7 1 8 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 65 2 0 10 2 0.0 0.0 235.0 0.0 2 1.0 2.0 1.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 20.0 2.0 2 23 1.0 0.5 0.25 500.0 1.0 52.0 2 1 2.0 3.0 5.0 0 diff --git a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/benefits.tab b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/benefits.tab index bc4483642..b73d9b47b 100644 --- a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/benefits.tab +++ b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/benefits.tab @@ -6,6 +6,7 @@ SERNUM BENUNIT PERSON BENEFIT VAR2 VAR3 BENAMT UCSTART UCHOUSEL 1 1 1 5 0 0 1.0 1 1 1 6 0 0 6.0 1 1 1 3 0 0 7.0 +1 1 1 13 0 0 81.9 2 1 1 14 1 0 2.0 2 1 1 14 2 0 3.0 2 1 1 16 3 1 4.0 @@ -116,6 +117,7 @@ SERNUM BENUNIT PERSON BENEFIT VAR2 VAR3 BENAMT UCSTART UCHOUSEL 16 1 1 5 0 0 1.0 16 1 1 6 0 0 6.0 16 1 1 3 0 0 7.0 +16 1 1 13 0 0 81.9 17 1 1 14 1 0 2.0 17 1 1 14 2 0 3.0 17 1 1 16 3 2 4.0 @@ -226,6 +228,7 @@ SERNUM BENUNIT PERSON BENEFIT VAR2 VAR3 BENAMT UCSTART UCHOUSEL 31 1 1 5 0 0 1.0 31 1 1 6 0 0 6.0 31 1 1 3 0 0 7.0 +31 1 1 13 0 0 81.9 32 1 1 14 1 0 2.0 32 1 1 14 2 0 3.0 32 1 1 16 3 1 4.0 @@ -336,6 +339,7 @@ SERNUM BENUNIT PERSON BENEFIT VAR2 VAR3 BENAMT UCSTART UCHOUSEL 46 1 1 5 0 0 1.0 46 1 1 6 0 0 6.0 46 1 1 3 0 0 7.0 +46 1 1 13 0 0 81.9 47 1 1 14 1 0 2.0 47 1 1 14 2 0 3.0 47 1 1 16 3 2 4.0 @@ -446,6 +450,7 @@ SERNUM BENUNIT PERSON BENEFIT VAR2 VAR3 BENAMT UCSTART UCHOUSEL 61 1 1 5 0 0 1.0 61 1 1 6 0 0 6.0 61 1 1 3 0 0 7.0 +61 1 1 13 0 0 81.9 62 1 1 14 1 0 2.0 62 1 1 14 2 0 3.0 62 1 1 16 3 1 4.0 @@ -556,6 +561,7 @@ SERNUM BENUNIT PERSON BENEFIT VAR2 VAR3 BENAMT UCSTART UCHOUSEL 76 1 1 5 0 0 1.0 76 1 1 6 0 0 6.0 76 1 1 3 0 0 7.0 +76 1 1 13 0 0 81.9 77 1 1 14 1 0 2.0 77 1 1 14 2 0 3.0 77 1 1 16 3 2 4.0 @@ -666,6 +672,7 @@ SERNUM BENUNIT PERSON BENEFIT VAR2 VAR3 BENAMT UCSTART UCHOUSEL 91 1 1 5 0 0 1.0 91 1 1 6 0 0 6.0 91 1 1 3 0 0 7.0 +91 1 1 13 0 0 81.9 92 1 1 14 1 0 2.0 92 1 1 14 2 0 3.0 92 1 1 16 3 1 4.0 @@ -776,6 +783,7 @@ SERNUM BENUNIT PERSON BENEFIT VAR2 VAR3 BENAMT UCSTART UCHOUSEL 106 1 1 5 0 0 1.0 106 1 1 6 0 0 6.0 106 1 1 3 0 0 7.0 +106 1 1 13 0 0 81.9 107 1 1 14 1 0 2.0 107 1 1 14 2 0 3.0 107 1 1 16 3 2 4.0 @@ -886,6 +894,7 @@ SERNUM BENUNIT PERSON BENEFIT VAR2 VAR3 BENAMT UCSTART UCHOUSEL 121 1 1 5 0 0 1.0 121 1 1 6 0 0 6.0 121 1 1 3 0 0 7.0 +121 1 1 13 0 0 81.9 122 1 1 14 1 0 2.0 122 1 1 14 2 0 3.0 122 1 1 16 3 1 4.0 diff --git a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/househol.tab b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/househol.tab index 05317d9ec..6ba4eb8ba 100644 --- a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/househol.tab +++ b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/househol.tab @@ -1,136 +1,136 @@ -SERNUM GROSS4 GVTREGNO PTENTYP2 TYPEACC BEDROOM6 CTANNUAL CTBAND CTDISC CT25D50D CTREB CTREBAMT ADULTH HRPNUM CSEWAMT CWATAMTD CWATAMT1 CSEWAMT1 WATSEWRT NIRATLIA RT2REBAM HHRENT SUBRENT TENTYP2 MORTINT STRUINS CHRGAMT1 CHRGAMT2 CHRGAMT3 CHRGAMT4 CHRGAMT5 CHRGAMT6 CHRGAMT7 CHRGAMT8 CHRGAMT9 INTDATE HHSTAT -1 1.01 11 6 2 2 910.0 2 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23665.0 1 -2 1.02 12 5 3 3 920.0 3 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23666.0 1 -3 1.03 1 6 4 4 930.0 4 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23667.0 1 -4 1.04 8 5 1 1 940.0 5 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23668.0 1 -5 1.05 11 6 2 2 950.0 6 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23669.0 1 -6 1.06 12 5 3 3 960.0 7 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23670.0 1 -7 1.07 1 6 4 4 970.0 1 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23671.0 1 -8 1.08 8 5 1 1 980.0 2 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23672.0 1 -9 1.09 11 6 2 2 990.0 3 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23673.0 1 -10 1.1 12 5 3 3 1000.0 4 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23674.0 1 -11 1.11 1 6 4 4 1010.0 5 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23675.0 2 -12 1.12 8 5 1 1 1020.0 6 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23676.0 1 -13 1.13 11 6 2 2 1030.0 7 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23677.0 1 -14 1.1400000000000001 12 5 3 3 1040.0 1 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23678.0 1 -15 1.15 1 6 4 4 1050.0 2 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23679.0 1 -16 1.16 8 5 1 1 1060.0 3 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23680.0 1 -17 1.17 11 6 2 2 1070.0 4 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23681.0 1 -18 1.18 12 5 3 3 1080.0 5 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23682.0 1 -19 1.19 1 6 4 4 1090.0 6 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23683.0 1 -20 1.2 8 5 1 1 1100.0 7 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23684.0 1 -21 1.21 11 6 2 2 1110.0 1 1 1 1 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23685.0 1 -22 1.22 12 5 3 3 1120.0 2 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23686.0 2 -23 1.23 1 6 4 4 1130.0 3 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23687.0 1 -24 1.24 8 5 1 1 1140.0 4 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23688.0 1 -25 1.25 11 6 2 2 1150.0 5 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23689.0 1 -26 1.26 12 5 3 3 1160.0 6 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23690.0 1 -27 1.27 1 6 4 4 1170.0 7 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23691.0 1 -28 1.28 8 5 1 1 1180.0 1 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23692.0 1 -29 1.29 11 6 2 2 1190.0 2 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23693.0 1 -30 1.3 12 5 3 3 1200.0 3 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23694.0 1 -31 1.31 1 6 4 4 1210.0 4 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23695.0 1 -32 1.32 8 5 1 1 1220.0 5 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23696.0 1 -33 1.33 11 6 2 2 1230.0 6 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23697.0 2 -34 1.34 12 5 3 3 1240.0 7 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23698.0 1 -35 1.35 1 6 4 4 1250.0 1 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23699.0 1 -36 1.3599999999999999 8 5 1 1 1260.0 2 1 2 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23700.0 1 -37 1.37 11 6 2 2 1270.0 3 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23701.0 1 -38 1.38 12 5 3 3 1280.0 4 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23702.0 1 -39 1.3900000000000001 1 6 4 4 1290.0 5 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23703.0 1 -40 1.4 8 5 1 1 1300.0 6 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23704.0 1 -41 1.41 11 6 2 2 1310.0 7 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23705.0 1 -42 1.42 12 5 3 3 1320.0 1 1 1 1 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23706.0 1 -43 1.43 1 6 4 4 1330.0 2 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23707.0 1 -44 1.44 8 5 1 1 1340.0 3 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23708.0 2 -45 1.45 11 6 2 2 1350.0 4 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23709.0 1 -46 1.46 12 5 3 3 1360.0 5 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23710.0 1 -47 1.47 1 6 4 4 1370.0 6 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23711.0 1 -48 1.48 8 5 1 1 1380.0 7 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23712.0 1 -49 1.49 11 6 2 2 1390.0 1 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23713.0 1 -50 1.5 12 5 3 3 1400.0 2 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23714.0 1 -51 1.51 1 6 4 4 1410.0 3 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23715.0 1 -52 1.52 8 5 1 1 1420.0 4 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23716.0 1 -53 1.53 11 6 2 2 1430.0 5 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23717.0 1 -54 1.54 12 5 3 3 1440.0 6 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23718.0 1 -55 1.55 1 6 4 4 1450.0 7 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23719.0 2 -56 1.56 8 5 1 1 1460.0 1 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23720.0 1 -57 1.5699999999999998 11 6 2 2 1470.0 2 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23721.0 1 -58 1.58 12 5 3 3 1480.0 3 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23722.0 1 -59 1.5899999999999999 1 6 4 4 1490.0 4 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23723.0 1 -60 1.6 8 5 1 1 1500.0 5 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23724.0 1 -61 1.6099999999999999 11 6 2 2 1510.0 6 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23725.0 1 -62 1.62 12 5 3 3 1520.0 7 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23726.0 1 -63 1.63 1 6 4 4 1530.0 1 1 2 1 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23727.0 1 -64 1.6400000000000001 8 5 1 1 1540.0 2 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23728.0 1 -65 1.65 11 6 2 2 1550.0 3 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23729.0 1 -66 1.6600000000000001 12 5 3 3 1560.0 4 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23730.0 2 -67 1.67 1 6 4 4 1570.0 5 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23731.0 1 -68 1.6800000000000002 8 5 1 1 1580.0 6 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23732.0 1 -69 1.69 11 6 2 2 1590.0 7 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23733.0 1 -70 1.7 12 5 3 3 1600.0 1 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23734.0 1 -71 1.71 1 6 4 4 1610.0 2 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23735.0 1 -72 1.72 8 5 1 1 1620.0 3 1 2 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23736.0 1 -73 1.73 11 6 2 2 1630.0 4 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23737.0 1 -74 1.74 12 5 3 3 1640.0 5 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23738.0 1 -75 1.75 1 6 4 4 1650.0 6 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23739.0 1 -76 1.76 8 5 1 1 1660.0 7 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23740.0 1 -77 1.77 11 6 2 2 1670.0 1 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23741.0 2 -78 1.78 12 5 3 3 1680.0 2 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23742.0 1 -79 1.79 1 6 4 4 1690.0 3 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23743.0 1 -80 1.8 8 5 1 1 1700.0 4 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23744.0 1 -81 1.81 11 6 2 2 1710.0 5 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23745.0 1 -82 1.8199999999999998 12 5 3 3 1720.0 6 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23746.0 1 -83 1.83 1 6 4 4 1730.0 7 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23747.0 1 -84 1.8399999999999999 8 5 1 1 1740.0 1 1 1 1 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23748.0 1 -85 1.85 11 6 2 2 1750.0 2 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23749.0 1 -86 1.8599999999999999 12 5 3 3 1760.0 3 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23750.0 1 -87 1.87 1 6 4 4 1770.0 4 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23751.0 1 -88 1.88 8 5 1 1 1780.0 5 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23752.0 2 -89 1.8900000000000001 11 6 2 2 1790.0 6 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23753.0 1 -90 1.9 12 5 3 3 1800.0 7 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23754.0 1 -91 1.9100000000000001 1 6 4 4 1810.0 1 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23755.0 1 -92 1.92 8 5 1 1 1820.0 2 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23756.0 1 -93 1.9300000000000002 11 6 2 2 1830.0 3 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23757.0 1 -94 1.94 12 5 3 3 1840.0 4 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23758.0 1 -95 1.95 1 6 4 4 1850.0 5 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23759.0 1 -96 1.96 8 5 1 1 1860.0 6 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23760.0 1 -97 1.97 11 6 2 2 1870.0 7 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23761.0 1 -98 1.98 12 5 3 3 1880.0 1 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23762.0 1 -99 1.99 1 6 4 4 1890.0 2 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23763.0 2 -100 2.0 8 5 1 1 1900.0 3 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23764.0 1 -101 2.01 11 6 2 2 1910.0 4 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23765.0 1 -102 2.02 12 5 3 3 1920.0 5 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23766.0 1 -103 2.0300000000000002 1 6 4 4 1930.0 6 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23767.0 1 -104 2.04 8 5 1 1 1940.0 7 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23768.0 1 -105 2.05 11 6 2 2 1950.0 1 1 1 1 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23769.0 1 -106 2.06 12 5 3 3 1960.0 2 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23770.0 1 -107 2.0700000000000003 1 6 4 4 1970.0 3 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23771.0 1 -108 2.08 8 5 1 1 1980.0 4 1 2 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23772.0 1 -109 2.09 11 6 2 2 1990.0 5 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23773.0 1 -110 2.1 12 5 3 3 2000.0 6 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23774.0 2 -111 2.1100000000000003 1 6 4 4 2010.0 7 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23775.0 1 -112 2.12 8 5 1 1 2020.0 1 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23776.0 1 -113 2.13 11 6 2 2 2030.0 2 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23777.0 1 -114 2.1399999999999997 12 5 3 3 2040.0 3 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23778.0 1 -115 2.15 1 6 4 4 2050.0 4 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23779.0 1 -116 2.16 8 5 1 1 2060.0 5 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23780.0 1 -117 2.17 11 6 2 2 2070.0 6 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23781.0 1 -118 2.1799999999999997 12 5 3 3 2080.0 7 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23782.0 1 -119 2.19 1 6 4 4 2090.0 1 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23783.0 1 -120 2.2 8 5 1 1 2100.0 2 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23664.0 1 -121 2.21 11 6 2 2 2110.0 3 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23665.0 2 -122 2.2199999999999998 12 5 3 3 2120.0 4 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23666.0 1 -123 2.23 1 6 4 4 2130.0 5 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23667.0 1 -124 2.24 8 5 1 1 2140.0 6 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23668.0 1 -125 2.25 11 6 2 2 2150.0 7 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23669.0 1 -126 2.26 12 5 3 3 2160.0 1 1 2 1 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23670.0 1 -127 2.27 1 6 4 4 2170.0 2 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23671.0 1 -128 2.2800000000000002 8 5 1 1 2180.0 3 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23672.0 1 -129 2.29 11 6 2 2 2190.0 4 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23673.0 1 -130 2.3 12 5 3 3 2200.0 5 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23674.0 1 -131 2.31 1 6 4 4 2210.0 6 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23675.0 1 -132 2.3200000000000003 8 5 1 1 2220.0 7 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23676.0 2 -133 2.33 11 6 2 2 2230.0 1 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23677.0 1 -134 2.34 12 5 3 3 2240.0 2 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23678.0 1 -135 2.35 1 6 4 4 2250.0 3 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23679.0 1 +SERNUM GROSS4 GVTREGNO PTENTYP2 TYPEACC BEDROOM6 CTANNUAL CTPAID CTBAND CTDISC CT25D50D CTREB CTREBAMT ADULTH HRPNUM CSEWAMT CWATAMTD CWATAMT1 CSEWAMT1 WATSEWRT NIRATLIA RT2REBAM HHRENT SUBRENT TENTYP2 MORTINT STRUINS CHRGAMT1 CHRGAMT2 CHRGAMT3 CHRGAMT4 CHRGAMT5 CHRGAMT6 CHRGAMT7 CHRGAMT8 CHRGAMT9 INTDATE HHSTAT +1 1.01 11 6 2 2 910.0 1 2 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23665.0 1 +2 1.02 12 5 3 3 920.0 1 3 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23666.0 1 +3 1.03 1 6 4 4 930.0 1 4 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23667.0 1 +4 1.04 8 5 1 1 940.0 1 5 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23668.0 1 +5 1.05 11 6 2 2 950.0 1 6 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23669.0 1 +6 1.06 12 5 3 3 960.0 1 7 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23670.0 1 +7 1.07 1 6 4 4 970.0 1 1 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23671.0 1 +8 1.08 8 5 1 1 980.0 1 2 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23672.0 1 +9 1.09 11 6 2 2 990.0 1 3 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23673.0 1 +10 1.1 12 5 3 3 1000.0 1 4 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23674.0 1 +11 1.11 1 6 4 4 1010.0 1 5 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23675.0 2 +12 1.12 8 5 1 1 0.0 1 6 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23676.0 1 +13 1.13 11 6 2 2 1030.0 1 7 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23677.0 1 +14 1.1400000000000001 12 5 3 3 1040.0 1 1 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23678.0 1 +15 1.15 1 6 4 4 1050.0 1 2 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23679.0 1 +16 1.16 8 5 1 1 1060.0 1 3 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23680.0 1 +17 1.17 11 6 2 2 1070.0 1 4 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23681.0 1 +18 1.18 12 5 3 3 1080.0 1 5 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23682.0 1 +19 1.19 1 6 4 4 1090.0 1 6 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23683.0 1 +20 1.2 8 5 1 1 1100.0 1 7 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23684.0 1 +21 1.21 11 6 2 2 1110.0 1 1 1 1 1 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23685.0 1 +22 1.22 12 5 3 3 1120.0 1 2 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23686.0 2 +23 1.23 1 6 4 4 1130.0 1 3 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23687.0 1 +24 1.24 8 5 1 1 1140.0 1 4 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23688.0 1 +25 1.25 11 6 2 2 1150.0 1 5 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23689.0 1 +26 1.26 12 5 3 3 1160.0 1 6 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23690.0 1 +27 1.27 1 6 4 4 1170.0 1 7 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23691.0 1 +28 1.28 8 5 1 1 1180.0 1 1 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23692.0 1 +29 1.29 11 6 2 2 1190.0 1 2 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23693.0 1 +30 1.3 12 5 3 3 1200.0 1 3 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23694.0 1 +31 1.31 1 6 4 4 1210.0 1 4 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23695.0 1 +32 1.32 8 5 1 1 1220.0 1 5 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23696.0 1 +33 1.33 11 6 2 2 1230.0 1 6 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23697.0 2 +34 1.34 12 5 3 3 1240.0 1 7 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23698.0 1 +35 1.35 1 6 4 4 1250.0 1 1 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23699.0 1 +36 1.3599999999999999 8 5 1 1 1260.0 1 2 1 2 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23700.0 1 +37 1.37 11 6 2 2 1270.0 1 3 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23701.0 1 +38 1.38 12 5 3 3 1280.0 1 4 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23702.0 1 +39 1.3900000000000001 1 6 4 4 1290.0 1 5 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23703.0 1 +40 1.4 8 5 1 1 1300.0 1 6 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23704.0 1 +41 1.41 11 6 2 2 1310.0 1 7 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23705.0 1 +42 1.42 12 5 3 3 1320.0 1 1 1 1 1 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23706.0 1 +43 1.43 1 6 4 4 1330.0 1 2 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23707.0 1 +44 1.44 8 5 1 1 1340.0 1 3 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23708.0 2 +45 1.45 11 6 2 2 1350.0 1 4 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23709.0 1 +46 1.46 12 5 3 3 1360.0 1 5 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23710.0 1 +47 1.47 1 6 4 4 1370.0 1 6 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23711.0 1 +48 1.48 8 5 1 1 1380.0 1 7 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23712.0 1 +49 1.49 11 6 2 2 1390.0 1 1 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23713.0 1 +50 1.5 12 5 3 3 1400.0 1 2 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23714.0 1 +51 1.51 1 6 4 4 1410.0 1 3 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23715.0 1 +52 1.52 8 5 1 1 1420.0 1 4 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23716.0 1 +53 1.53 11 6 2 2 1430.0 1 5 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23717.0 1 +54 1.54 12 5 3 3 1440.0 1 6 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23718.0 1 +55 1.55 1 6 4 4 1450.0 1 7 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23719.0 2 +56 1.56 8 5 1 1 1460.0 1 1 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23720.0 1 +57 1.5699999999999998 11 6 2 2 1470.0 1 2 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23721.0 1 +58 1.58 12 5 3 3 1480.0 1 3 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23722.0 1 +59 1.5899999999999999 1 6 4 4 1490.0 1 4 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23723.0 1 +60 1.6 8 5 1 1 1500.0 1 5 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23724.0 1 +61 1.6099999999999999 11 6 2 2 1510.0 1 6 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23725.0 1 +62 1.62 12 5 3 3 1520.0 1 7 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23726.0 1 +63 1.63 1 6 4 4 1530.0 1 1 1 2 1 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23727.0 1 +64 1.6400000000000001 8 5 1 1 1540.0 1 2 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23728.0 1 +65 1.65 11 6 2 2 1550.0 1 3 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23729.0 1 +66 1.6600000000000001 12 5 3 3 1560.0 1 4 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23730.0 2 +67 1.67 1 6 4 4 1570.0 1 5 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23731.0 1 +68 1.6800000000000002 8 5 1 1 1580.0 1 6 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23732.0 1 +69 1.69 11 6 2 2 1590.0 1 7 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23733.0 1 +70 1.7 12 5 3 3 1600.0 1 1 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23734.0 1 +71 1.71 1 6 4 4 1610.0 1 2 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23735.0 1 +72 1.72 8 5 1 1 1620.0 1 3 1 2 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23736.0 1 +73 1.73 11 6 2 2 1630.0 1 4 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23737.0 1 +74 1.74 12 5 3 3 1640.0 1 5 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23738.0 1 +75 1.75 1 6 4 4 1650.0 1 6 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23739.0 1 +76 1.76 8 5 1 1 1660.0 1 7 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23740.0 1 +77 1.77 11 6 2 2 1670.0 1 1 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23741.0 2 +78 1.78 12 5 3 3 1680.0 1 2 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23742.0 1 +79 1.79 1 6 4 4 1690.0 1 3 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23743.0 1 +80 1.8 8 5 1 1 1700.0 1 4 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23744.0 1 +81 1.81 11 6 2 2 1710.0 1 5 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23745.0 1 +82 1.8199999999999998 12 5 3 3 1720.0 1 6 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23746.0 1 +83 1.83 1 6 4 4 1730.0 1 7 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23747.0 1 +84 1.8399999999999999 8 5 1 1 1740.0 1 1 1 1 1 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23748.0 1 +85 1.85 11 6 2 2 1750.0 1 2 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23749.0 1 +86 1.8599999999999999 12 5 3 3 1760.0 1 3 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23750.0 1 +87 1.87 1 6 4 4 1770.0 1 4 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23751.0 1 +88 1.88 8 5 1 1 1780.0 1 5 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23752.0 2 +89 1.8900000000000001 11 6 2 2 1790.0 1 6 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23753.0 1 +90 1.9 12 5 3 3 1800.0 1 7 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23754.0 1 +91 1.9100000000000001 1 6 4 4 1810.0 1 1 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23755.0 1 +92 1.92 8 5 1 1 1820.0 1 2 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23756.0 1 +93 1.9300000000000002 11 6 2 2 1830.0 1 3 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23757.0 1 +94 1.94 12 5 3 3 1840.0 1 4 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23758.0 1 +95 1.95 1 6 4 4 1850.0 1 5 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23759.0 1 +96 1.96 8 5 1 1 1860.0 1 6 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23760.0 1 +97 1.97 11 6 2 2 1870.0 1 7 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23761.0 1 +98 1.98 12 5 3 3 1880.0 1 1 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23762.0 1 +99 1.99 1 6 4 4 1890.0 1 2 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23763.0 2 +100 2.0 8 5 1 1 1900.0 1 3 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23764.0 1 +101 2.01 11 6 2 2 1910.0 1 4 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23765.0 1 +102 2.02 12 5 3 3 1920.0 1 5 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23766.0 1 +103 2.0300000000000002 1 6 4 4 1930.0 1 6 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23767.0 1 +104 2.04 8 5 1 1 1940.0 1 7 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23768.0 1 +105 2.05 11 6 2 2 1950.0 1 1 1 1 1 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23769.0 1 +106 2.06 12 5 3 3 1960.0 1 2 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23770.0 1 +107 2.0700000000000003 1 6 4 4 1970.0 1 3 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23771.0 1 +108 2.08 8 5 1 1 1980.0 1 4 1 2 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23772.0 1 +109 2.09 11 6 2 2 1990.0 1 5 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23773.0 1 +110 2.1 12 5 3 3 2000.0 1 6 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23774.0 2 +111 2.1100000000000003 1 6 4 4 2010.0 1 7 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23775.0 1 +112 2.12 8 5 1 1 2020.0 1 1 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23776.0 1 +113 2.13 11 6 2 2 2030.0 1 2 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23777.0 1 +114 2.1399999999999997 12 5 3 3 2040.0 1 3 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23778.0 1 +115 2.15 1 6 4 4 2050.0 1 4 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23779.0 1 +116 2.16 8 5 1 1 2060.0 1 5 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23780.0 1 +117 2.17 11 6 2 2 2070.0 1 6 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23781.0 1 +118 2.1799999999999997 12 5 3 3 2080.0 1 7 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23782.0 1 +119 2.19 1 6 4 4 2090.0 1 1 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23783.0 1 +120 2.2 8 5 1 1 2100.0 1 2 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23664.0 1 +121 2.21 11 6 2 2 2110.0 1 3 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23665.0 2 +122 2.2199999999999998 12 5 3 3 2120.0 1 4 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23666.0 1 +123 2.23 1 6 4 4 2130.0 1 5 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23667.0 1 +124 2.24 8 5 1 1 2140.0 1 6 2 1 1.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23668.0 1 +125 2.25 11 6 2 2 2150.0 1 7 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23669.0 1 +126 2.26 12 5 3 3 2160.0 1 1 1 2 1 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23670.0 1 +127 2.27 1 6 4 4 2170.0 1 2 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23671.0 1 +128 2.2800000000000002 8 5 1 1 2180.0 1 3 2 1 2.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23672.0 1 +129 2.29 11 6 2 2 2190.0 1 4 1 1 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23673.0 1 +130 2.3 12 5 3 3 2200.0 1 5 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23674.0 1 +131 2.31 1 6 4 4 2210.0 1 6 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23675.0 1 +132 2.3200000000000003 8 5 1 1 2220.0 1 7 1 1 2 0.0 1 1 0.0 4.0 5.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23676.0 2 +133 2.33 11 6 2 2 2230.0 1 1 2 1 1.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23677.0 1 +134 2.34 12 5 3 3 2240.0 1 2 2 1 2.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23678.0 1 +135 2.35 1 6 4 4 2250.0 1 3 1 2 2 0.0 1 1 0.0 3.0 0.0 0.0 5.0 0.0 5 7.0 8.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 23679.0 1 diff --git a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/household.csv b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/household.csv index f4501c43a..0e33e94e2 100644 --- a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/household.csv +++ b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/household.csv @@ -10,7 +10,7 @@ household_id,region,tenure_type,accommodation_type,num_bedrooms,council_tax_repo 9,WALES,OWNED_WITH_MORTGAGE,HOUSE_SEMI_DETACHED,2,9.9_0000000000000000e+02,C,0.0_0000000000000000e+00,1,1.5_6535714285714278e+02,0.0_0000000000000000e+00,2.6_0892857142857167e+02,0.0_0000000000000000e+00,3.6_5250000000000000e+02,1.0_0000000000000000e+01,4.1_7428571428571445e+02,2.3_4803571428571422e+03,1.0_4357142857142861e+02 10,SCOTLAND,OWNED_OUTRIGHT,HOUSE_TERRACED,3,1.0_0000000000000000e+03,D,5.2_1785714285714306e+01,1,0.0_0000000000000000e+00,0.0_0000000000000000e+00,2.6_0892857142857167e+02,0.0_0000000000000000e+00,3.6_5250000000000000e+02,1.0_0000000000000000e+01,4.1_7428571428571445e+02,2.3_4803571428571422e+03,1.0_4357142857142861e+02 11,NORTH_EAST,OWNED_WITH_MORTGAGE,FLAT,4,1.0_1000000000000000e+03,E,1.0_4357142857142861e+02,1,1.5_6535714285714278e+02,0.0_0000000000000000e+00,2.6_0892857142857167e+02,0.0_0000000000000000e+00,3.6_5250000000000000e+02,1.0_0000000000000000e+01,4.1_7428571428571445e+02,2.3_4803571428571422e+03,1.0_4357142857142861e+02 -12,LONDON,OWNED_OUTRIGHT,HOUSE_DETACHED,1,1.0_2000000000000000e+03,F,0.0_0000000000000000e+00,1,1.5_6535714285714278e+02,0.0_0000000000000000e+00,2.6_0892857142857167e+02,0.0_0000000000000000e+00,3.6_5250000000000000e+02,1.0_0000000000000000e+01,4.1_7428571428571445e+02,2.3_4803571428571422e+03,1.0_4357142857142861e+02 +12,LONDON,OWNED_OUTRIGHT,HOUSE_DETACHED,1,0.0_0000000000000000e+00,F,0.0_0000000000000000e+00,1,1.5_6535714285714278e+02,0.0_0000000000000000e+00,2.6_0892857142857167e+02,0.0_0000000000000000e+00,3.6_5250000000000000e+02,1.0_0000000000000000e+01,4.1_7428571428571445e+02,2.3_4803571428571422e+03,1.0_4357142857142861e+02 13,WALES,OWNED_WITH_MORTGAGE,HOUSE_SEMI_DETACHED,2,1.0_3000000000000000e+03,G,5.2_1785714285714306e+01,1,1.5_6535714285714278e+02,0.0_0000000000000000e+00,2.6_0892857142857167e+02,0.0_0000000000000000e+00,3.6_5250000000000000e+02,1.0_0000000000000000e+01,4.1_7428571428571445e+02,2.3_4803571428571422e+03,1.0_4357142857142861e+02 14,SCOTLAND,OWNED_OUTRIGHT,HOUSE_TERRACED,3,1.0_4000000000000000e+03,A,1.0_4357142857142861e+02,1,0.0_0000000000000000e+00,0.0_0000000000000000e+00,2.6_0892857142857167e+02,0.0_0000000000000000e+00,3.6_5250000000000000e+02,1.0_0000000000000000e+01,4.1_7428571428571445e+02,2.3_4803571428571422e+03,1.0_4357142857142861e+02 15,NORTH_EAST,OWNED_WITH_MORTGAGE,FLAT,4,1.0_5000000000000000e+03,B,0.0_0000000000000000e+00,1,1.5_6535714285714278e+02,0.0_0000000000000000e+00,2.6_0892857142857167e+02,0.0_0000000000000000e+00,3.6_5250000000000000e+02,1.0_0000000000000000e+01,4.1_7428571428571445e+02,2.3_4803571428571422e+03,1.0_4357142857142861e+02 diff --git a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/person.csv b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/person.csv index 0ef701026..dcd949158 100644 --- a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/person.csv +++ b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/person.csv @@ -1,163 +1,163 @@ person_id,person_benunit_id,person_household_id,age,gender,months_since_last_birthday,marital_status,hours_worked,care_hours,is_household_head,is_benunit_head,is_parent,is_blind,employment_income,self_employment_income,trading_loss,loss_relief,ni_class_4_losses_brought_forward,private_pension_income,tax_free_savings_income,savings_interest_income,dividend_income,stands_as_sole_owner_or_partner_of_company,is_engaged_in_owned_company_trade,owned_company_is_main_employment,owned_company_carries_on_trade,owned_company_carries_on_property_business,owned_company_income_share,property_income,reports_rent_from_other_property,maintenance_income,miscellaneous_income,private_transfer_income,lump_sum_income,student_loan_repayments,statutory_sick_pay,statutory_maternity_pay,statutory_paternity_pay,student_loans,access_fund,education_grants,healthy_start_vouchers,free_school_breakfasts,free_school_fruit_veg,free_school_meals,child_benefit_reported,income_support_reported,housing_benefit_reported,attendance_allowance_reported,dla_sc_reported,dla_m_reported,iidb_reported,carers_allowance_reported,sda_reported,afcs_reported,ssmg_reported,pension_credit_reported,child_tax_credit_reported,working_tax_credit_reported,state_pension_reported,winter_fuel_allowance_reported,incapacity_benefit_reported,universal_credit_reported,pip_m_reported,pip_dl_reported,jsa_contrib_reported,jsa_income_reported,esa_contrib_reported,esa_income_reported,esa_includes_support_component,bsp_reported,would_claim_carers_allowance,council_tax_benefit_reported,maintenance_expenses,childcare_expenses,personal_pension_contributions,employee_pension_contributions,pension_contributions_via_salary_sacrifice,salary_sacrifice_reported,salary_sacrifice_asked,is_uc_claimant,rent_paid_as_boarder,rent_paid_as_lodger,is_claimant_or_partner,is_hbai_dependent_child,uc_is_in_startup_period,uc_is_in_gainful_self_employment,__stratum__ 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private_school_attendance.","id":"private_school_attendance","inputs":[{"columns":["frs_benunit_capital","is_married","dependent_children","liable_for_share_of_household_rent","would_claim_child_benefit","child_benefit_opts_out","would_claim_pc","would_claim_uc","would_claim_tfc","would_claim_extended_childcare","would_claim_universal_childcare","would_claim_targeted_childcare","would_claim_uc_childcare","maximum_extended_childcare_hours_usage","benunit_source_id","benunit_support_channel","benunit_support_clone_index","uc_reported_capital","pension_credit_reported_capital","would_claim_uc_at_legacy_closure","has_mixed_age_couple_pension_credit_saving","uc_deduction_random_draw","uc_deduction_type_random_draw","uc_latent_deduction_rate","uc_deduction_combination"],"entity":"benunit","rows":"all"},{"columns":["region","tenure_type","accommodation_type","num_bedrooms","council_tax_reported","council_tax_band","council_tax_rebate","council_tax_single_adult_raw","water_and_sewerage_charges","domestic_rates","rent","subrent","mortgage_interest_repayment","mortgage_capital_repayment","structural_insurance_payments","housing_service_charges","external_child_payments","ons_household_type","council_tax","household_owns_tv","would_evade_tv_licence_fee","main_residential_property_purchased_is_first_home","property_purchased","brma","source_household_id","source_year","source_household_key","household_source_id","household_support_channel","household_support_clone_index","household_is_spi_synthetic","household_is_spi_income_band_donor","spi_income_band_donor_lower_bound","owned_land","property_wealth","corporate_wealth","private_pension_wealth","gross_financial_wealth","net_financial_wealth","main_residence_value","other_residential_property_value","non_residential_property_value","savings","num_vehicles","cash_isa","stocks_and_shares_isa","mortgage_debt","consumer_debt","household_lifetime_isa_balance","household_is_high_value_support_copy","high_value_support_copies","high_value_support_copy_index","main_residence_value_rank_basis","additional_residential_property_purchased","non_residential_property_purchased","household_local_bus_trips","food_and_non_alcoholic_beverages_consumption","alcohol_and_tobacco_consumption","clothing_and_footwear_consumption","housing_water_and_electricity_consumption","household_furnishings_consumption","health_consumption","transport_consumption","communication_consumption","recreation_consumption","education_consumption","restaurants_and_hotels_consumption","miscellaneous_consumption","petrol_spending","diesel_spending","bus_fare_spending","domestic_energy_consumption","electricity_consumption","gas_consumption","has_fuel_consumption","uses_energy_prepayment_meter","full_rate_vat_expenditure_rate","dfe_education_spending","rail_subsidy_spending","bus_subsidy_spending","rail_usage","household_is_cgt_support_copy","cgt_support_copies","cgt_support_copy_index","household_is_capital_gains_clone","household_is_cgt_residential_clone","cgt_residential_clone_index"],"entity":"household","rows":"all"},{"columns":["age","gender","months_since_last_birthday","marital_status","hours_worked","care_hours","is_household_head","is_benunit_head","is_parent","is_blind","is_uc_claimant","is_claimant_or_partner","is_hbai_dependent_child","uc_is_in_startup_period","uc_is_in_gainful_self_employment","rent_paid_as_boarder","rent_paid_as_lodger","employment_income","self_employment_income","trading_loss","loss_relief","ni_class_4_losses_brought_forward","private_pension_income","tax_free_savings_income","savings_interest_income","dividend_income","stands_as_sole_owner_or_partner_of_company","is_engaged_in_owned_company_trade","owned_company_is_main_employment","owned_company_carries_on_trade","owned_company_carries_on_property_business","owned_company_income_share","property_income","reports_rent_from_other_property","maintenance_income","miscellaneous_income","private_transfer_income","lump_sum_income","student_loan_repayments","statutory_sick_pay","statutory_maternity_pay","statutory_paternity_pay","student_loans","access_fund","education_grants","healthy_start_vouchers","free_school_breakfasts","free_school_fruit_veg","free_school_meals","council_tax_benefit_reported","maintenance_expenses","childcare_expenses","personal_pension_contributions","employee_pension_contributions","pension_contributions_via_salary_sacrifice","salary_sacrifice_reported","salary_sacrifice_asked","child_benefit_reported","income_support_reported","housing_benefit_reported","attendance_allowance_reported","dla_sc_reported","dla_m_reported","iidb_reported","carers_allowance_reported","would_claim_carers_allowance","sda_reported","afcs_reported","ssmg_reported","pension_credit_reported","child_tax_credit_reported","working_tax_credit_reported","state_pension_reported","winter_fuel_allowance_reported","incapacity_benefit_reported","universal_credit_reported","pip_m_reported","pip_dl_reported","jsa_contrib_reported","jsa_income_reported","esa_contrib_reported","esa_income_reported","esa_includes_support_component","bsp_reported","relationship_to_head","ons_family_role","ons_family_index","is_looked_after_by_local_authority","employment_status","employment_sector","sic_industry_division","aa_category","dla_sc_category","dla_m_category","pip_m_category","pip_dl_category","is_disabled_for_benefits","is_enhanced_disabled_for_benefits","is_severely_disabled_for_benefits","current_education","highest_education","is_in_non_advanced_education","is_in_approved_training","age_started_or_accepted_current_education_or_training","is_before_universal_credit_qualifying_young_person_terminal_date","adult_ema","child_ema","receives_benefits_in_own_right","reports_outstanding_student_loan","age_left_full_time_education","legacy_jobseeker_proxy","esa_health_condition_proxy","esa_support_group_proxy","disabled_students_allowance_eligible_expenses","would_claim_marriage_allowance","would_claim_scp","attends_private_school_random_draw","tax_free_childcare_spend_routed_share","hmrc_spi_pay","hmrc_spi_unemployment_benefit_income","hmrc_spi_incapacity_benefit_income","ossben_identifiable_subset","srp_regular_code5","employer_pension_contributions","person_source_id","person_support_channel","person_support_clone_index","person_is_spi_income_band_carrier","charitable_investment_gifts","gift_aid","other_investment_income","hmrc_spi_employment_benefits","hmrc_spi_employment_expenses","hmrc_spi_other_social_security_income","hmrc_spi_taxable_termination_pay","hmrc_spi_miscellaneous_employment_income","hmrc_spi_other_income","hmrc_spi_state_pension_income","property_finance_costs","hmrc_spi_employed_income","hmrc_spi_total_earned_income","hmrc_spi_total_investment_income","hmrc_spi_assessable_income","person_is_spi_income_recipient","student_loan_balance","has_lifetime_isa","lifetime_isa_balance","property_rental_income","local_bus_use_band","bus_in_london_trips","other_local_bus_trips","local_bus_trips","bus_pass_eligible","local_bus_single_fare_share","a_and_e_visits","admitted_patient_visits","outpatient_visits","nhs_a_and_e_spending","nhs_admitted_patient_spending","nhs_outpatient_spending","capital_gains","cgt_residential_probability","capital_gains_residential_property","capital_gains_asset_type","capital_gains_badr","salary_sacrifice_pre_conversion_pay","student_loan_plan"],"entity":"person","rows":"all"}],"kernel":"uk.stage.private_school_attendance@1","mass":"conserve","outputs":[{"column":"attends_private_school","dtype":"bool","entity":"person","ownership":"produced","rows":"all"}],"params":{"numerical_dependencies":[["policyengine-uk","2.134.4"],["policyengine-core","3.33.3"],["numpy","2.4.6"],["pandas","3.0.3"],["scikit-learn","1.8.0"],["quantile-forest","1.4.2"]],"stage":"private_school_attendance","stage_contract_sha256":"7e44379c0331fe4c9de05cd76a075c1a6aa22cf0dec6cd2f91b277e70f14a038","time_period":"2024"},"population":"cgt_residential_split","sources":["frs"],"structural":"none","weights":null}],"sources":[{"codec":"csv-tables","description":"Content-bound UK FRS and donor fixture/source bundle.","name":"frs"}]} From 9d545885dbfd473d7fb28e6cbe67d7b428d51d01 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Wed, 21 Oct 2026 12:26:53 +0100 Subject: [PATCH 17/21] Refuse the frame's period on a value the frame does not hold (#1324) A plain-column binding that declares the frame's period (2024) while the run calibrates at 2025 reads the stored column. An engine-computed value variable has no stored column, so the resolver computed it at 2025 and the row was measured there under the declared period, with nothing refusing (Vahid's review on #1329, finding 1). The guard now asks the adapter which period each value variable holds without the engine. UKFrameTargetAdapter.value_period gives the frame's period for a stored column, the year in the name for a dated CGT measure such as cgt_2024_tax, and none otherwise. The guard refuses unless every value_variable or value_expression term holds the declared period. The dated-measure rule moves to cgt_calibration.UK_CGT_DATED_MEASURE, so the measure provider and the adapter share one copy. No packaged row changes: the plain-column rows that declare 2024 read stored columns (petrol, diesel, bus and rail) or cgt_2024_tax. Co-Authored-By: Claude Opus 5.5 --- .../microcosm/build/target_materialization.py | 40 ++++++++-- .../build/uk_runtime/cgt_calibration.py | 17 +++++ .../build/uk_runtime/ledger_targets.py | 19 ++++- .../build/uk_runtime/measure_simulation.py | 7 +- .../uk/test_uk_measurement_period.py | 74 +++++++++++++++++++ 5 files changed, 143 insertions(+), 14 deletions(-) diff --git a/packages/microcosm-build/src/microcosm/build/target_materialization.py b/packages/microcosm-build/src/microcosm/build/target_materialization.py index 40a2dff4a..d0840607b 100644 --- a/packages/microcosm-build/src/microcosm/build/target_materialization.py +++ b/packages/microcosm-build/src/microcosm/build/target_materialization.py @@ -979,20 +979,44 @@ def _refuse_ignored_measurement_period( A plain-column value is read at the calibration period (through the provider, for a stored column) or, by declaration, at the frame's own period (the stored column as it is). Any other declared period would be - read at one of those two and is refused. + read at one of those two and is refused. So is the frame's period on a + value the frame does not hold at that period: the engine computes it at + the calibration period, so the row would be measured there under the + declared period. """ declared = binding.get("measurement_period") frame_period = getattr(adapter, "frame_period", None) - if declared is None or frame_period is None: + if declared is None or frame_period is None or str(declared) == str(period): return - if str(declared) in {str(period), str(frame_period)}: + name = getattr(spec, "name", "?") + if str(declared) != str(frame_period): + raise MeasurementPeriodError( + f"target {name!r} declares measurement period " + f"{declared!r}; a plain-column read honours only the calibration " + f"period {period!r} or the frame's period {frame_period!r}" + ) + value_period = getattr(adapter, "value_period", None) + if not callable(value_period): return - raise MeasurementPeriodError( - f"target {getattr(spec, 'name', '?')!r} declares measurement period " - f"{declared!r}; a plain-column read honours only the calibration " - f"period {period!r} or the frame's period {frame_period!r}" - ) + entity = str(binding.get("from_entity") or spec.entity) + for variable in _value_variables(binding): + if value_period(entity, variable) != str(declared): + raise MeasurementPeriodError( + f"target {name!r} declares the frame's period {declared!r}, " + f"but {entity}.{variable} is not held at that period on the " + f"frame, so the engine would compute it at the calibration " + f"period {period!r}" + ) + + +def _value_variables(binding: Mapping[str, Any]) -> tuple[str, ...]: + """The value variables a plain-column binding reads.""" + + if "value_expression" in binding: + parts = str(binding["value_expression"]).split("+") + return tuple(part.strip() for part in parts if part.strip()) + return (str(binding["value_variable"]),) def _binding_mask( diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/cgt_calibration.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/cgt_calibration.py index b0d93cb3b..77ec65666 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/cgt_calibration.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/cgt_calibration.py @@ -19,6 +19,7 @@ from __future__ import annotations +import re from dataclasses import dataclass import numpy as np @@ -36,12 +37,14 @@ __all__ = [ "UK_CGT_ANNUAL_EXEMPT_AMOUNTS", + "UK_CGT_DATED_MEASURE", "UK_CGT_GAINS_AMOUNT_COLUMN", "UK_CGT_SOURCE_COLUMN", "UK_CGT_TAXPAYER_COUNT_COLUMN", "UKCGTTargetMaterialization", "materialize_uk_cgt_calibration_frame", "uk_cgt_annual_exempt_amount", + "uk_cgt_dated_measure_year", ] #: The persisted person-level input the measures are derived from. @@ -50,6 +53,13 @@ UK_CGT_GAINS_AMOUNT_COLUMN = "uk_cgt_measure_gains_amount" UK_CGT_TAXPAYER_COUNT_COLUMN = "uk_cgt_measure_taxpayer_count" +#: A CGT calibration measure dated by its name, such as ``cgt_2024_gains``. +#: The measure provider computes it at the year in its name, whatever the +#: run's calibration period, so a binding may declare that year. +UK_CGT_DATED_MEASURE = re.compile( + r"^cgt_(20[0-9]{2})_(gains|tax|badr_gains|taxable_income)$" +) + #: CGT annual exempt amount by build period (tax year starting in that year). #: #: HMRC Capital Gains Tax rates and allowances: @@ -95,6 +105,13 @@ def uk_cgt_annual_exempt_amount(time_period: int | str) -> float: ) from None +def uk_cgt_dated_measure_year(variable: str) -> int | None: + """The year a dated CGT calibration measure is computed at, else None.""" + + match = UK_CGT_DATED_MEASURE.fullmatch(variable) + return int(match[1]) if match else None + + def materialize_uk_cgt_calibration_frame( national_frame: Frame, *, diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/ledger_targets.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/ledger_targets.py index 879153ced..40df39f35 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/ledger_targets.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/ledger_targets.py @@ -35,7 +35,10 @@ materialize_target_bindings, ) from microcosm.build.uk_runtime.bus_fare_pricing import bus_journey_appliers -from microcosm.build.uk_runtime.cgt_calibration import uk_cgt_annual_exempt_amount +from microcosm.build.uk_runtime.cgt_calibration import ( + uk_cgt_annual_exempt_amount, + uk_cgt_dated_measure_year, +) from microcosm.build.uk_runtime.cross_grain_declarations import ( assert_uk_cross_grain_coverage, load_uk_cross_grain_declarations, @@ -1630,6 +1633,20 @@ def __init__(self, frame: Frame): def has_column(self, entity: str, variable: str) -> bool: return variable in self.tables[entity] + def value_period(self, entity: str, variable: str) -> str | None: + """The period a value variable holds without the engine (microcosm#1324). + + A stored column holds the frame's own period, and a CGT calibration + measure dated by its name (``cgt_2024_gains``) is computed at that + year. Any other value comes from the engine at the run's calibration + period, so it holds no period of its own: None. + """ + + if variable in self.stored_columns.get(entity, ()): + return self.frame_period + year = uk_cgt_dated_measure_year(variable) + return None if year is None else str(year) + def column_at( self, entity: str, diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/measure_simulation.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/measure_simulation.py index 22f99903e..2aa5a5adb 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/measure_simulation.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/measure_simulation.py @@ -3,7 +3,6 @@ from __future__ import annotations import json -import re import warnings from collections.abc import Mapping from datetime import date @@ -17,6 +16,7 @@ from microcosm.build.uk_runtime.atomic_area_support import ( without_uk_native_alias_columns, ) +from microcosm.build.uk_runtime.cgt_calibration import UK_CGT_DATED_MEASURE from microcosm.build.uk_runtime.high_value_homes import ( high_value_home_mask, uk_high_value_home_thresholds, @@ -84,9 +84,6 @@ # Derived, not a policyengine-uk variable: see _cgt_taxable_income. "cgt_calibration_taxable_income": "cgt_taxable_income", } -_CGT_DATED_MEASURE = re.compile( - r"^cgt_(20[0-9]{2})_(gains|tax|badr_gains|taxable_income)$" -) #: The taxable income policyengine-uk's ``capital_gains_tax`` sets the CGT #: rate bands on, which the engine computes inline and exposes as no @@ -263,7 +260,7 @@ def _binding_variable_names(binding: Mapping[str, Any]) -> list[str]: def _cgt_model_measure(variable: str, default_year: int) -> tuple[str, int] | None: if variable in _CGT_CALIBRATION_VARIABLES: return _CGT_CALIBRATION_VARIABLES[variable], default_year - match = _CGT_DATED_MEASURE.fullmatch(variable) + match = UK_CGT_DATED_MEASURE.fullmatch(variable) if match: return _CGT_CALIBRATION_VARIABLES[f"cgt_calibration_{match[2]}"], int(match[1]) return None diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period.py index 3c953b35f..e150cde4b 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_measurement_period.py @@ -208,6 +208,80 @@ def test_a_declared_period_the_route_cannot_honour_refuses(monkeypatch, tmp_path ) +@pytest.mark.parametrize( + "binding", + [ + {"value_variable": "income_tax", "measurement_period": 2024}, + { + "value_expression": "employment_income + income_tax", + "measurement_period": 2024, + }, + ], +) +def test_the_frame_period_on_an_engine_value_refuses(binding): + # The frame stores no income_tax, so the engine would compute it at the + # calibration period and the row would be read there under 2024. + registry, contract = _registry({"engine_value": binding}) + adapter = UKFrameTargetAdapter(PeriodFrameStub()) + + with pytest.raises(MeasurementPeriodError, match="person.income_tax"): + materialize_target_bindings(adapter, registry, contract, period=2025) + + +def test_the_resolver_refuses_the_frame_period_on_an_engine_value( + monkeypatch, tmp_path +): + with pytest.raises(MeasurementPeriodError, match="person.income_tax"): + _resolve_and_materialize( + monkeypatch, + tmp_path, + { + "engine_value": { + "value_variable": "income_tax", + "measurement_period": 2024, + } + }, + ) + + +def test_a_cgt_measure_dated_by_its_name_holds_its_own_year(): + adapter = UKFrameTargetAdapter(PeriodFrameStub()) + + assert adapter.value_period("person", "employment_income") == "2024" + assert adapter.value_period("person", "cgt_2024_tax") == "2024" + assert adapter.value_period("person", "cgt_2025_gains") == "2025" + assert adapter.value_period("person", "income_tax") is None + + # The guard lets the dated measure through: the provider computes it at + # the year in its name. With no provider here, the read reports it missing. + registry, contract = _registry( + {"dated": {"value_variable": "cgt_2024_tax", "measurement_period": 2024}} + ) + materialized = materialize_target_bindings(adapter, registry, contract, period=2025) + assert [skip.name for skip in materialized.skipped] == ["dated"] + + registry, contract = _registry( + {"misdated": {"value_variable": "cgt_2025_tax", "measurement_period": 2024}} + ) + with pytest.raises(MeasurementPeriodError, match="person.cgt_2025_tax"): + materialize_target_bindings( + UKFrameTargetAdapter(PeriodFrameStub()), registry, contract, period=2025 + ) + + +def test_a_run_at_the_frame_period_declares_any_value_without_refusal(): + # Calibrating at the frame's own period, the engine computes every value + # at that period, so the declaration is honoured whatever the value. + registry, contract = _registry( + {"engine_value": {"value_variable": "income_tax", "measurement_period": 2024}} + ) + adapter = UKFrameTargetAdapter(PeriodFrameStub()) + + materialized = materialize_target_bindings(adapter, registry, contract, period=2024) + + assert [skip.name for skip in materialized.skipped] == ["engine_value"] + + def test_without_a_provider_the_frame_is_read_as_it_is(): frame = PeriodFrameStub() registry, contract = _registry( From 3c3b473d531269d79aab9e9a2916f6cccb3f4df9 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Wed, 21 Oct 2026 12:26:53 +0100 Subject: [PATCH 18/21] Say that policyengine-uk lacks Carer Support Payment's earnings limit (#1319) Scotland stays closed in the Carer's Allowance draw because Carer Support Payment reads the same flag. The reason given was that the engine applies CSP no earnings test, which read as if CSP had none. In law it has an earnings limit, as the allowance does (mygov.scot, "If you work"), and policyengine-uk's carer_support_payment_pre_overlap does not yet apply it (Vahid's review on #1329, finding 4). The module, the stage's eligibility and notes in sources.yaml and source_stages.json, and the changelog fragment now say so. The coverage manifest and the H2 fixture follow in the pin commit. Co-Authored-By: Claude Opus 5.5 --- changelog.d/1319-carers-allowance-take-up.added.md | 2 +- .../src/microcosm/build/uk/source_stages.json | 4 ++-- .../src/microcosm/build/uk/spec/sources.yaml | 4 ++-- .../build/uk_runtime/carers_allowance_take_up.py | 10 ++++++---- 4 files changed, 11 insertions(+), 9 deletions(-) diff --git a/changelog.d/1319-carers-allowance-take-up.added.md b/changelog.d/1319-carers-allowance-take-up.added.md index 557ca71b7..dccc52cd3 100644 --- a/changelog.d/1319-carers-allowance-take-up.added.md +++ b/changelog.d/1319-carers-allowance-take-up.added.md @@ -1 +1 @@ -The UK spine now draws `would_claim_carers_allowance` for the carers the Carer's Allowance earnings limit keeps out (microcosm#1319). The flag followed reported receipt (#882), and a carer above the limit cannot report the allowance, so no reform that widens it reached a new claimant; the Independent Review of Carer's Allowance Overpayments (July 2025) estimates that the April 2025 rise of the limit from £151 to £196 a week brought about 61,000 more people into eligibility. A new stage, `carers_allowance_take_up`, runs after `child_benefit_take_up` and keeps reported receipt as its anchor. One engine materialization at the survey year reads `is_gainfully_employed_for_carers_allowance` at the 2024-25 limit, and a person outside Scotland whose `care_hours` reach the engine's hours condition (35 a week), who reports no allowance and whom that test holds gainfully employed claims at the take-up contract's new `carers_allowance_newly_entitled` rate, 0.6 (María's ruling of 2026-10-20, sensitivity 0.45 to 0.75), on an identity-keyed uniform. Reporters stay true, and carers under the limit who report no allowance stay false. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test. The receipt bands support on distinct source households, the stage has no health gate, and the roster moves from 45 to 46 stages. +The UK spine now draws `would_claim_carers_allowance` for the carers the Carer's Allowance earnings limit keeps out (microcosm#1319). The flag followed reported receipt (#882), and a carer above the limit cannot report the allowance, so no reform that widens it reached a new claimant; the Independent Review of Carer's Allowance Overpayments (July 2025) estimates that the April 2025 rise of the limit from £151 to £196 a week brought about 61,000 more people into eligibility. A new stage, `carers_allowance_take_up`, runs after `child_benefit_take_up` and keeps reported receipt as its anchor. One engine materialization at the survey year reads `is_gainfully_employed_for_carers_allowance` at the 2024-25 limit, and a person outside Scotland whose `care_hours` reach the engine's hours condition (35 a week), who reports no allowance and whom that test holds gainfully employed claims at the take-up contract's new `carers_allowance_newly_entitled` rate, 0.6 (María's ruling of 2026-10-20, sensitivity 0.45 to 0.75), on an identity-keyed uniform. Reporters stay true, and carers under the limit who report no allowance stay false. Scotland stays closed, since Carer Support Payment reads the same flag and policyengine-uk does not yet apply its earnings limit. The receipt bands support on distinct source households, the stage has no health gate, and the roster moves from 45 to 46 stages. diff --git a/packages/microcosm-build/src/microcosm/build/uk/source_stages.json b/packages/microcosm-build/src/microcosm/build/uk/source_stages.json index cb4556e02..572590e5f 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/source_stages.json +++ b/packages/microcosm-build/src/microcosm/build/uk/source_stages.json @@ -5536,7 +5536,7 @@ "output": "would_claim_carers_allowance", "draw": "would_claim_carers_allowance", "assignment_unit": "person", - "eligibility": "persons outside Scotland whose care_hours reach policyengine-uk's gov.dwp.carers_allowance.min_hours, who report no Carer's Allowance, and whom is_gainfully_employed_for_carers_allowance holds gainfully employed at the survey year: the carers the earnings limit alone keeps from the allowance. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test", + "eligibility": "persons outside Scotland whose care_hours reach policyengine-uk's gov.dwp.carers_allowance.min_hours, who report no Carer's Allowance, and whom is_gainfully_employed_for_carers_allowance holds gainfully employed at the survey year: the carers the earnings limit alone keeps from the allowance. Scotland stays closed, since Carer Support Payment reads the same flag and policyengine-uk does not yet apply its earnings limit", "reported_true_anchor": "carers_allowance_reported > 0", "rate_key": "carers_allowance_newly_entitled", "rate_derivation": "the take-up contract's carers_allowance_newly_entitled rate, drawn flat over the eligible persons; would_claim = reported OR (eligible AND u < rate), so a reporter stays true and every other person false", @@ -5547,7 +5547,7 @@ "rewrites": [ "would_claim_carers_allowance" ], - "notes": "Runs after the SPI income chain, UC capital coherence and the Pension Credit and Child Benefit redraws, before CGT cloning, so every clone carries its source's draw (microcosm#1319). frs_spine sets would_claim_carers_allowance from reported receipt and the SPI income chain re-derives it from the refilled receipt on the rows it redraws, so that care_hours qualifies a carer for the Universal Credit carer element without paying the allowance to every carer (#882). A carer above the earnings limit cannot report the allowance, so no reform that widens it reached a carer who would claim once entitled: the April 2025 rise of the limit from £151 to £196 a week brought an estimated 61,000 more people into eligibility (Independent Review of Carer's Allowance Overpayments, July 2025, chapter 7). One temporary engine materialization at the survey year, on the frame's own values, gives each person's is_gainfully_employed_for_carers_allowance (consumed only); the engine reads a year's parameters at 30 April, so the limit is 2024-25's £151. A person outside Scotland whose care_hours reach the engine's gov.dwp.carers_allowance.min_hours (35), who reports no allowance and whom that test holds gainfully employed claims at the take-up contract's carers_allowance_newly_entitled rate (0.6, María's ruling of 2026-10-20, sensitivity 0.45 to 0.75) on the person's identity-keyed uniform (seed 0, salt would_claim_carers_allowance): would_claim = reported OR (eligible AND u < rate). A reporter stays true; a carer under the limit who reports no allowance stays false, as the survey records them entitled and not claiming. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test. The earnings test is read before salary_sacrifice moves some contributors' pension amounts out of their pay, so a drawn carer whom that conversion takes under the survey year's limit keeps the flag although the file then shows them entitled and not reporting. The stage rebuilds the flag from reported receipt and refuses a frame whose flag no longer follows it. Its receipt bands support on distinct source households (household_source_id), and gives a weighted total only where ten or more carry it and the realised share only where neither side rests on one to nine; the stage has no health gate." + "notes": "Runs after the SPI income chain, UC capital coherence and the Pension Credit and Child Benefit redraws, before CGT cloning, so every clone carries its source's draw (microcosm#1319). frs_spine sets would_claim_carers_allowance from reported receipt and the SPI income chain re-derives it from the refilled receipt on the rows it redraws, so that care_hours qualifies a carer for the Universal Credit carer element without paying the allowance to every carer (#882). A carer above the earnings limit cannot report the allowance, so no reform that widens it reached a carer who would claim once entitled: the April 2025 rise of the limit from £151 to £196 a week brought an estimated 61,000 more people into eligibility (Independent Review of Carer's Allowance Overpayments, July 2025, chapter 7). One temporary engine materialization at the survey year, on the frame's own values, gives each person's is_gainfully_employed_for_carers_allowance (consumed only); the engine reads a year's parameters at 30 April, so the limit is 2024-25's £151. A person outside Scotland whose care_hours reach the engine's gov.dwp.carers_allowance.min_hours (35), who reports no allowance and whom that test holds gainfully employed claims at the take-up contract's carers_allowance_newly_entitled rate (0.6, María's ruling of 2026-10-20, sensitivity 0.45 to 0.75) on the person's identity-keyed uniform (seed 0, salt would_claim_carers_allowance): would_claim = reported OR (eligible AND u < rate). A reporter stays true; a carer under the limit who reports no allowance stays false, as the survey records them entitled and not claiming. Scotland stays closed, since Carer Support Payment reads the same flag and policyengine-uk does not yet apply its earnings limit. The earnings test is read before salary_sacrifice moves some contributors' pension amounts out of their pay, so a drawn carer whom that conversion takes under the survey year's limit keeps the flag although the file then shows them entitled and not reporting. The stage rebuilds the flag from reported receipt and refuses a frame whose flag no longer follows it. Its receipt bands support on distinct source households (household_source_id), and gives a weighted total only where ten or more carry it and the realised share only where neither side rests on one to nine; the stage has no health gate." }, { "stage": "uc_deduction_attributes", diff --git a/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml b/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml index a2f1f7208..ee41fe54b 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml +++ b/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml @@ -4468,7 +4468,7 @@ stages: output: would_claim_carers_allowance draw: would_claim_carers_allowance assignment_unit: person - eligibility: 'persons outside Scotland whose care_hours reach policyengine-uk''s gov.dwp.carers_allowance.min_hours, who report no Carer''s Allowance, and whom is_gainfully_employed_for_carers_allowance holds gainfully employed at the survey year: the carers the earnings limit alone keeps from the allowance. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test' + eligibility: 'persons outside Scotland whose care_hours reach policyengine-uk''s gov.dwp.carers_allowance.min_hours, who report no Carer''s Allowance, and whom is_gainfully_employed_for_carers_allowance holds gainfully employed at the survey year: the carers the earnings limit alone keeps from the allowance. Scotland stays closed, since Carer Support Payment reads the same flag and policyengine-uk does not yet apply its earnings limit' reported_true_anchor: carers_allowance_reported > 0 rate_key: carers_allowance_newly_entitled rate_derivation: 'the take-up contract''s carers_allowance_newly_entitled rate, drawn flat over the eligible persons; would_claim = reported OR (eligible AND u < rate), so a reporter stays true and every other person false' @@ -4476,7 +4476,7 @@ stages: outputs: [] rewrites: - would_claim_carers_allowance - notes: 'Runs after the SPI income chain, UC capital coherence and the Pension Credit and Child Benefit redraws, before CGT cloning, so every clone carries its source''s draw (microcosm#1319). frs_spine sets would_claim_carers_allowance from reported receipt and the SPI income chain re-derives it from the refilled receipt on the rows it redraws, so that care_hours qualifies a carer for the Universal Credit carer element without paying the allowance to every carer (#882). A carer above the earnings limit cannot report the allowance, so no reform that widens it reached a carer who would claim once entitled: the April 2025 rise of the limit from £151 to £196 a week brought an estimated 61,000 more people into eligibility (Independent Review of Carer''s Allowance Overpayments, July 2025, chapter 7). One temporary engine materialization at the survey year, on the frame''s own values, gives each person''s is_gainfully_employed_for_carers_allowance (consumed only); the engine reads a year''s parameters at 30 April, so the limit is 2024-25''s £151. A person outside Scotland whose care_hours reach the engine''s gov.dwp.carers_allowance.min_hours (35), who reports no allowance and whom that test holds gainfully employed claims at the take-up contract''s carers_allowance_newly_entitled rate (0.6, María''s ruling of 2026-10-20, sensitivity 0.45 to 0.75) on the person''s identity-keyed uniform (seed 0, salt would_claim_carers_allowance): would_claim = reported OR (eligible AND u < rate). A reporter stays true; a carer under the limit who reports no allowance stays false, as the survey records them entitled and not claiming. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test. The earnings test is read before salary_sacrifice moves some contributors'' pension amounts out of their pay, so a drawn carer whom that conversion takes under the survey year''s limit keeps the flag although the file then shows them entitled and not reporting. The stage rebuilds the flag from reported receipt and refuses a frame whose flag no longer follows it. Its receipt bands support on distinct source households (household_source_id), and gives a weighted total only where ten or more carry it and the realised share only where neither side rests on one to nine; the stage has no health gate.' + notes: 'Runs after the SPI income chain, UC capital coherence and the Pension Credit and Child Benefit redraws, before CGT cloning, so every clone carries its source''s draw (microcosm#1319). frs_spine sets would_claim_carers_allowance from reported receipt and the SPI income chain re-derives it from the refilled receipt on the rows it redraws, so that care_hours qualifies a carer for the Universal Credit carer element without paying the allowance to every carer (#882). A carer above the earnings limit cannot report the allowance, so no reform that widens it reached a carer who would claim once entitled: the April 2025 rise of the limit from £151 to £196 a week brought an estimated 61,000 more people into eligibility (Independent Review of Carer''s Allowance Overpayments, July 2025, chapter 7). One temporary engine materialization at the survey year, on the frame''s own values, gives each person''s is_gainfully_employed_for_carers_allowance (consumed only); the engine reads a year''s parameters at 30 April, so the limit is 2024-25''s £151. A person outside Scotland whose care_hours reach the engine''s gov.dwp.carers_allowance.min_hours (35), who reports no allowance and whom that test holds gainfully employed claims at the take-up contract''s carers_allowance_newly_entitled rate (0.6, María''s ruling of 2026-10-20, sensitivity 0.45 to 0.75) on the person''s identity-keyed uniform (seed 0, salt would_claim_carers_allowance): would_claim = reported OR (eligible AND u < rate). A reporter stays true; a carer under the limit who reports no allowance stays false, as the survey records them entitled and not claiming. Scotland stays closed, since Carer Support Payment reads the same flag and policyengine-uk does not yet apply its earnings limit. The earnings test is read before salary_sacrifice moves some contributors'' pension amounts out of their pay, so a drawn carer whom that conversion takes under the survey year''s limit keeps the flag although the file then shows them entitled and not reporting. The stage rebuilds the flag from reported receipt and refuses a frame whose flag no longer follows it. Its receipt bands support on distinct source households (household_source_id), and gives a weighted total only where ten or more carry it and the realised share only where neither side rests on one to nine; the stage has no health gate.' - stage: uc_deduction_attributes survey: DWP Universal Credit deductions statistics, March 2025 to February 2026 source: Department for Work and Pensions supplementary Tables 2, 5 and 6, sha-pinned by Chronicle package dwp-uc-deductions-march-2025-february-2026. diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/carers_allowance_take_up.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/carers_allowance_take_up.py index 925cd00ee..55edf50b6 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/carers_allowance_take_up.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/carers_allowance_take_up.py @@ -23,8 +23,9 @@ A reporter stays true. A carer under the limit who reports no allowance stays false, as the survey records them entitled and not claiming. Scotland -is left closed: Carer Support Payment reads the same flag and the engine -applies it no earnings test, so a draw there would pay it. The incoming flag +is left closed: Carer Support Payment reads the same flag, and in law it has +the allowance's earnings limit, but policyengine-uk does not yet apply that +limit, so a draw there would pay it to carers over the limit. The incoming flag must still follow reported receipt, since the stage rebuilds it from that anchor. @@ -99,7 +100,8 @@ CARERS_ALLOWANCE_YEAR_RULE = "survey_year" CARERS_ALLOWANCE_NEWLY_ENTITLED_RATE_KEY = "carers_allowance_newly_entitled" #: Carer Support Payment replaces the allowance in Scotland and reads the same -#: flag with no earnings test in the engine, so Scotland is never drawn. +#: flag; policyengine-uk does not yet apply its earnings limit, so Scotland is +#: never drawn. CARERS_ALLOWANCE_CLOSED_REGION = "SCOTLAND" CARERS_ALLOWANCE_PARAMETERS = "gov.dwp.carers_allowance" CARERS_ALLOWANCE_REPORTED_ANCHOR = "carers_allowance_reported > 0" @@ -109,7 +111,7 @@ "whom is_gainfully_employed_for_carers_allowance holds gainfully employed at " "the survey year: the carers the earnings limit alone keeps from the " "allowance. Scotland stays closed, since Carer Support Payment reads the same " - "flag and the engine applies it no earnings test" + "flag and policyengine-uk does not yet apply its earnings limit" ) CARERS_ALLOWANCE_RATE_DERIVATION = ( "the take-up contract's carers_allowance_newly_entitled rate, drawn flat over " From d47b48c21f5156f44b00d63cbc79c3ad4be9cc80 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Wed, 21 Oct 2026 12:26:53 +0100 Subject: [PATCH 19/21] Quote the FRS methodology on the council-tax questions (#1278) The docstring and the changelog fragment said that from 2024-25 the FRS no longer asks the amount and that DWP derives CTANNUAL from the band. Section 1.3 of the FRS 2024-25 background information and methodology says that the band and some other Council Tax block questions left the field interview from April 2024, that editing teams input the band, and that the other answers are imputed during DWP's validation. It does not say that CTANNUAL is derived from the band, or whether CTPAID is asked or imputed. Both texts now quote it (Vahid's review on #1329, nit C). Co-Authored-By: Claude Opus 5.5 --- changelog.d/1278-council-tax-paying-zeros.fixed.md | 2 +- .../src/microcosm/build/uk_runtime/frs_council_tax.py | 9 +++++++-- 2 files changed, 8 insertions(+), 3 deletions(-) diff --git a/changelog.d/1278-council-tax-paying-zeros.fixed.md b/changelog.d/1278-council-tax-paying-zeros.fixed.md index 5df5f9e83..5c292a152 100644 --- a/changelog.d/1278-council-tax-paying-zeros.fixed.md +++ b/changelog.d/1278-council-tax-paying-zeros.fixed.md @@ -1 +1 @@ -A UK household where someone pays council tax but whose derived bill is zero now takes its cell's mean bill (microcosm#1278). From 2024-25 the FRS no longer asks how much council tax a household pays, and DWP derives `CTANNUAL` from the band, yet some households that answer yes to CTPaid ("Does anyone living here pay Council Tax?") and report no council tax reduction carry a zero `CTANNUAL`, which `frs_council_tax` kept, leaving England's share of zero bills well above Wales's and Scotland's. A household with `CTPAID` 1, `CTREB` not 1 and a zero `CTANNUAL` is now imputed as a missing bill is, from the mean of the positive non-recipient bills in its region, band and single-adult cell. A non-recipient's zero bill otherwise stays zero: the household does not have to pay (`CTPAID` 3), or says the council pays (`CTPAID` 2) without reporting a reduction. Reduction recipients keep their rules, and the bill level, low against published Band D averages, waits until after the Budget. The stage's `impute_cell_means` declaration names the new missing rule and the stage refuses a raw tab without `CTPAID`. The release input coverage manifest and the H2 spine fixture are regenerated. +A UK household where someone pays council tax but whose derived bill is zero now takes its cell's mean bill (microcosm#1278). From April 2024 the band and some other council-tax questions left the FRS field interview, and DWP imputes those answers during its validation (FRS 2024-25 background information and methodology, section 1.3), yet some households that answer yes to CTPaid ("Does anyone living here pay Council Tax?") and report no council tax reduction carry a zero `CTANNUAL`, which `frs_council_tax` kept, leaving England's share of zero bills well above Wales's and Scotland's. A household with `CTPAID` 1, `CTREB` not 1 and a zero `CTANNUAL` is now imputed as a missing bill is, from the mean of the positive non-recipient bills in its region, band and single-adult cell. A non-recipient's zero bill otherwise stays zero: the household does not have to pay (`CTPAID` 3), or says the council pays (`CTPAID` 2) without reporting a reduction. Reduction recipients keep their rules, and the bill level, low against published Band D averages, waits until after the Budget. The stage's `impute_cell_means` declaration names the new missing rule and the stage refuses a raw tab without `CTPAID`. The release input coverage manifest and the H2 spine fixture are regenerated. diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_council_tax.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_council_tax.py index e867e8791..358e9783d 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_council_tax.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/frs_council_tax.py @@ -170,8 +170,13 @@ def derive_council_tax( reduction and takes the larger of its bill and its cell's mean. Missing or negative bills take the cell mean. So does a zero bill where someone pays council tax (``CTPAID`` 1) and no reduction is reported, since such - a household owes a bill (microcosm#1278); from 2024-25 the FRS no longer - asks the amount, and DWP derives ``CTANNUAL`` from the band. A + a household owes a bill (microcosm#1278). From April 2024 the band and + "some other Council Tax block questions" left the FRS field interview: + editing teams input the band from Valuation Office Agency and Scottish + Assessors data, and the other answers "are then imputed during DWP's + validation processes" (FRS 2024-25 background information and + methodology, section 1.3). The methodology does not say whether + ``CTPAID`` itself is still asked or is imputed. A non-recipient's zero bill otherwise stays zero: the household does not have to pay (``CTPAID`` 3), or says the council pays (``CTPAID`` 2) without reporting a reduction. The cells pool non-recipients with a From 3d765aa707b7c42e62ba27bb0217f67793259add Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Wed, 21 Oct 2026 12:26:53 +0100 Subject: [PATCH 20/21] Note the bus fare cap caveat in the calibration-period changelog (#1324) England's bus fare receipts now read the engine's 2025 fares and end about 10% above their target, because policyengine-uk gives every single ticket in England outside London one uncapped fare. The fragment says so and points to policyengine-uk#2542 and microcosm#1331, so that a costing of a bus fare cap change on this release is not read as final (Vahid's review on #1329, finding 5). Co-Authored-By: Claude Opus 5.5 --- changelog.d/1324-uk-stored-values-at-their-period.fixed.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/changelog.d/1324-uk-stored-values-at-their-period.fixed.md b/changelog.d/1324-uk-stored-values-at-their-period.fixed.md index 600ab33d1..5880f3fcd 100644 --- a/changelog.d/1324-uk-stored-values-at-their-period.fixed.md +++ b/changelog.d/1324-uk-stored-values-at-their-period.fixed.md @@ -1 +1 @@ -UK calibration now measures a plain-column target's value at the binding's period (microcosm#1324). A value variable the frame stores holds the frame's own year (2024), so at the 2025 calibration period the measure resolver computes it through the engine, as it already did for every engine-computed variable; before, the stored column was read as it is and 76 £ rows compared 2024 values with 2025 targets. The engine values for stored names are injected under a reserved `engine_period__` name, so the stored columns that filters, conditions and bands read are never overwritten; those keep their stored reads, and a test lists the variables they read for review. A binding may declare the frame's period to read the stored column on purpose (ONS road fuel at calendar 2024 and the seven bus and rail outturn rows held without an index), and any other declared period refuses. The self-employment profit after loss relief reads the stored columns only at the frame's period. +UK calibration now measures a plain-column target's value at the binding's period (microcosm#1324). A value variable the frame stores holds the frame's own year (2024), so at the 2025 calibration period the measure resolver computes it through the engine, as it already did for every engine-computed variable; before, the stored column was read as it is and 76 £ rows compared 2024 values with 2025 targets. The engine values for stored names are injected under a reserved `engine_period__` name, so the stored columns that filters, conditions and bands read are never overwritten; those keep their stored reads, and a test lists the variables they read for review. A binding may declare the frame's period to read the stored column on purpose (ONS road fuel at calendar 2024 and the seven bus and rail outturn rows held without an index), and any other declared period refuses. The self-employment profit after loss relief reads the stored columns only at the frame's period. England's bus fare receipts now read the engine's 2025 fares and end about 10% above their target: policyengine-uk gives every single ticket in England outside London one uncapped fare, so the £3 cap raises those fares by about a quarter against DfT's fares index (policyengine-uk#2542, microcosm#1331). Until that changes, a costing of a bus fare cap change on this release likely overstates its cost and gains. From 2279fe8211ee48d26672d0783a581f400e116e21 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Mar=C3=ADa=20Juaristi?= <127882282+juaristi22@users.noreply.github.com> Date: Wed, 21 Oct 2026 12:44:57 +0100 Subject: [PATCH 21/21] Regenerate the coverage manifest and spine fixture after the review (pin pass) The Carer Support Payment rewording changes the carers_allowance_take_up stage's eligibility and notes in source_stages.json, so the release input coverage manifest re-hashes the stage manifest, and the charter-H2 spine fixture carries the new text. Both --check runs pass. The compile-parity receipts and the target references do not move. Co-Authored-By: Claude Opus 5.5 --- .../uk/release_input_coverage_manifest.json | 44 +++++++++---------- .../parity/uk_spine/sources/fixture.json | 4 +- .../fixtures/parity/uk_spine/uk_spine.json | 2 +- 3 files changed, 25 insertions(+), 25 deletions(-) diff --git a/packages/microcosm-build/src/microcosm/build/uk/release_input_coverage_manifest.json b/packages/microcosm-build/src/microcosm/build/uk/release_input_coverage_manifest.json index 1f6a23757..2c031116c 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/release_input_coverage_manifest.json +++ b/packages/microcosm-build/src/microcosm/build/uk/release_input_coverage_manifest.json @@ -470,7 +470,7 @@ "required_mass_change_reason": "Capital-gains incidence anchor moves the mass of non-liable clone households back to their paired originals until the sub-exempt and loss-making clone mass match the Advani-Summers reporter composition at the redrawn liable mass; every pair's mass and the total household mass are conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "Advani and Summers (2020), Capital Gains and UK Inequality, CAGE Working Paper 465", "survey": "Family Resources Survey 2024-25, SPI synthetic support, the HMRC Table 3 redrawn gains on the spine and Advani-Summers capital-gains incidence" @@ -493,7 +493,7 @@ "capital_gains" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "Advani and Summers (2020), Capital Gains and UK Inequality, CAGE Working Paper 465", "survey": "Family Resources Survey 2024-25, SPI synthetic support, and Advani-Summers capital-gains incidence" @@ -516,7 +516,7 @@ "required_mass_change_reason": "Capital-gains residential split divides every household carrying liable gainers into arms weighted by the solved residential probabilities, one arm per subset of residential gainers; every household's mass and the total household mass are conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "https://www.gov.uk/government/statistics/capital-gains-tax-statistics", "survey": "HMRC Capital Gains Tax statistics 2026 release, Table 8 (UK residential property disposals, 2024-25, administrative) on the amounts the Table 3 redraw placed" @@ -538,7 +538,7 @@ "required_mass_change_reason": "Capital-gains support split divides the wealthiest households of each HMRC Table 3 income band into light copies at equal weight; every household's mass and the total household mass are conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "HMRC Capital Gains Tax statistics, July 2026 release, Table 3 for 2024-25, via the vendored conditioning facts", "survey": "Family Resources Survey 2024-25, SPI synthetic support and HMRC Capital Gains Tax statistics Table 3 (2024-25 individuals by size of gain and taxable income)" @@ -567,7 +567,7 @@ "required_mass_change_reason": "ETB public-services imputation on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "UK Data Service SN 8856 Effects of Taxes and Benefits household tab, DfT rail fare index, and public NHS activity/cost table.", "survey": "Effects of Taxes and Benefits 1977-2024 and NHS age-gender public table" @@ -587,7 +587,7 @@ "required_mass_change_reason": "ETB VAT expenditure-rate imputation on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "UK Data Service SN 8856 Effects of Taxes and Benefits household tab and cited VAT anchor resource.", "survey": "Effects of Taxes and Benefits 1977-2024" @@ -609,7 +609,7 @@ "required_mass_change_reason": "High-value home support divides every owner household in the top value stratum of its region into light copies at equal weight; every household's mass and the total household mass are conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "Microcosm structural operator (microcosm#1240 fix 1); no publisher input", "survey": "Family Resources Survey 2024-25 and SPI synthetic support, after the WAS wealth draw and the regional property uprating" @@ -630,7 +630,7 @@ "required_mass_change_reason": "CGT asset-type assignment on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "https://www.gov.uk/government/statistics/capital-gains-tax-statistics", "survey": "HMRC Capital Gains Tax statistics 2026 release, Table 8 (UK residential property disposals, 2024-25, administrative), Table 4.1 (individuals claiming Business Asset Disposal Relief or Investors' Relief by band of qualifying gain, 2024-25, administrative) and Table 7 (disposals, proceeds and gains by asset type, 2023-24, sample-based), vendored from the pinned Chronicle feed" @@ -654,7 +654,7 @@ "capital_gains" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "conditioning_resource": "hmrc_cgt_conditioning_facts.json", "conditioning_resource_sha256": "054b1ee1a66cae6ed3793053eb0d3b9eea6b3f8976953479948ae11f7eedcd35", @@ -743,7 +743,7 @@ "full_frs_tei_band_unavailable" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "hmrc_surface": "2023-24", "mapped_build_period": "2024", @@ -785,7 +785,7 @@ "required_mass_change_reason": "LCFS consumption imputation on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "UK Data Service SN 9603 Living Costs and Food Survey 2024-25 (2nd edition) household/person tabs and the vendored Chronicle facts for NEED 2024 mean kWh, DESNZ Energy Trends and QEP average prices paid for calendar 2024, road-fuel outturn (DESNZ, HMRC, ONS Consumer Trends) and road fuel by vehicle type (DESNZ), ONS Consumer Trends household spending by COICOP division, the DfT VEH1103 licensed-car stock, NTS bus use, and the DfT and devolved bus finance tables and fares indices.", "survey": "Living Costs and Food Survey 2024-25" @@ -811,7 +811,7 @@ "required_mass_change_reason": "NTS bus-travel imputation on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "Department for Transport National Travel Survey, UK Data Service SN 5340 (End User Licence, 19th edition, November 2025), DOI 10.5255/UKDA-SN-5340-19; local licensed tab files (household, individual, trip); England residents only from 2013.", "survey": "National Travel Survey 2002-2024" @@ -831,7 +831,7 @@ "required_mass_change_reason": "Private-school attendance stored on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "policyengine-uk attends_private_school (the gov.simulation.private_school_vat attendance rates and factor), evaluated by the pinned engine", "survey": "policyengine-uk private-school attendance imputation, stored at the spine's weights" @@ -854,7 +854,7 @@ "property_finance_costs" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "https://www.gov.uk/government/statistics/property-rental-income-statistics", "survey": "Survey of Personal Incomes Public Use Tape 2022-23 and HMRC Property Rental Income Statistics 2026 (tax year 2024-25)" @@ -875,7 +875,7 @@ "required_mass_change_reason": "Annual property purchases imputed on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "https://www.gov.uk/government/statistics/uk-stamp-tax-statistics", "survey": "HMRC Annual Stamp Tax Statistics 2024 to 2025 (corrected 11 March 2026), Tables 6b, 8a and 8b" @@ -898,7 +898,7 @@ "property_wealth" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "uk/high_value_home_value_knots.json, built by tools/build_uk_high_value_home_stock.py from PolicyEngine/chronicle#343's registrations", "survey": "HM Land Registry Price Paid latest sales uprated with the UK House Price Index, owner-weighted by region (the dense value node's knots, region level)" @@ -922,7 +922,7 @@ "non_residential_property_value" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "MHCLG dwellings and the UK House Price Index regional average price averaged over the twelve months of calendar 2024 from the July 2026 full file, the frame's valuation basis, so the engine's annual uprating from 2024 projects the value once (microcosm#1240 fix 5).", "survey": "Public regional property reference" @@ -949,7 +949,7 @@ "employment_income" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "HMRC, Salary sacrifice reform for pension contributions effective from 6 April 2029", "survey": "Family Resources Survey 2024-25 salary-sacrifice respondents and HMRC salary-sacrifice reform analysis" @@ -982,7 +982,7 @@ "household_source_id" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "Reserved SPI support households for the HMRC Table 2.5 total-income bands from GBP 200,000, stacked at the published band taxpayer count over the donors per band (PolicyEngine/chronicle#280 lane).", "survey": "Survey of Personal Incomes Public Use Tape 2022-23 and HMRC Income Tax liabilities statistics July 2026 Table 2.5" @@ -1004,7 +1004,7 @@ "student_loan_plan" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "Explore Education Statistics Table 6a, Higher education total", "survey": "Family Resources Survey 2024-25 and Student Loans Company borrower forecasts for England" @@ -1026,7 +1026,7 @@ "required_mass_change_reason": "WAS Lifetime ISA imputation on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "Office for National Statistics Wealth and Assets Survey, UK Data Service SN 7215, DOI 10.5255/UKDA-SN-7215-20; local licensed round-8 person and household tabs (interviews April 2020 to March 2022, Great Britain).", "survey": "Wealth and Assets Survey round 8" @@ -1061,7 +1061,7 @@ "required_mass_change_reason": "WAS wealth imputation on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "650ef5121eb4f4178166bdd210f3466d7e2b9f76be17f1688b113aebf705de98", + "source_manifest_sha256": "8599f34df31a02c99296a7daa03edbee543898a18cb672187c3b0d441ab88491", "source_vintages": { "source": "Office for National Statistics Wealth and Assets Survey, UK Data Service SN 7215, DOI 10.5255/UKDA-SN-7215-20; local licensed 2006-22 household tab.", "survey": "Wealth and Assets Survey round 8" diff --git a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/fixture.json b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/fixture.json index b5023384e..889a18636 100644 --- a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/fixture.json +++ b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/fixture.json @@ -98,7 +98,7 @@ "artifacts": [], "grain": "person", "nonnegative_outputs": [], - "notes": "Runs after the SPI income chain, UC capital coherence and the Pension Credit and Child Benefit redraws, before CGT cloning, so every clone carries its source's draw (microcosm#1319). frs_spine sets would_claim_carers_allowance from reported receipt and the SPI income chain re-derives it from the refilled receipt on the rows it redraws, so that care_hours qualifies a carer for the Universal Credit carer element without paying the allowance to every carer (#882). A carer above the earnings limit cannot report the allowance, so no reform that widens it reached a carer who would claim once entitled: the April 2025 rise of the limit from \u00a3151 to \u00a3196 a week brought an estimated 61,000 more people into eligibility (Independent Review of Carer's Allowance Overpayments, July 2025, chapter 7). One temporary engine materialization at the survey year, on the frame's own values, gives each person's is_gainfully_employed_for_carers_allowance (consumed only); the engine reads a year's parameters at 30 April, so the limit is 2024-25's \u00a3151. A person outside Scotland whose care_hours reach the engine's gov.dwp.carers_allowance.min_hours (35), who reports no allowance and whom that test holds gainfully employed claims at the take-up contract's carers_allowance_newly_entitled rate (0.6, Mar\u00eda's ruling of 2026-10-20, sensitivity 0.45 to 0.75) on the person's identity-keyed uniform (seed 0, salt would_claim_carers_allowance): would_claim = reported OR (eligible AND u < rate). A reporter stays true; a carer under the limit who reports no allowance stays false, as the survey records them entitled and not claiming. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test. The earnings test is read before salary_sacrifice moves some contributors' pension amounts out of their pay, so a drawn carer whom that conversion takes under the survey year's limit keeps the flag although the file then shows them entitled and not reporting. The stage rebuilds the flag from reported receipt and refuses a frame whose flag no longer follows it. Its receipt bands support on distinct source households (household_source_id), and gives a weighted total only where ten or more carry it and the realised share only where neither side rests on one to nine; the stage has no health gate.", + "notes": "Runs after the SPI income chain, UC capital coherence and the Pension Credit and Child Benefit redraws, before CGT cloning, so every clone carries its source's draw (microcosm#1319). frs_spine sets would_claim_carers_allowance from reported receipt and the SPI income chain re-derives it from the refilled receipt on the rows it redraws, so that care_hours qualifies a carer for the Universal Credit carer element without paying the allowance to every carer (#882). A carer above the earnings limit cannot report the allowance, so no reform that widens it reached a carer who would claim once entitled: the April 2025 rise of the limit from \u00a3151 to \u00a3196 a week brought an estimated 61,000 more people into eligibility (Independent Review of Carer's Allowance Overpayments, July 2025, chapter 7). One temporary engine materialization at the survey year, on the frame's own values, gives each person's is_gainfully_employed_for_carers_allowance (consumed only); the engine reads a year's parameters at 30 April, so the limit is 2024-25's \u00a3151. A person outside Scotland whose care_hours reach the engine's gov.dwp.carers_allowance.min_hours (35), who reports no allowance and whom that test holds gainfully employed claims at the take-up contract's carers_allowance_newly_entitled rate (0.6, Mar\u00eda's ruling of 2026-10-20, sensitivity 0.45 to 0.75) on the person's identity-keyed uniform (seed 0, salt would_claim_carers_allowance): would_claim = reported OR (eligible AND u < rate). A reporter stays true; a carer under the limit who reports no allowance stays false, as the survey records them entitled and not claiming. Scotland stays closed, since Carer Support Payment reads the same flag and policyengine-uk does not yet apply its earnings limit. The earnings test is read before salary_sacrifice moves some contributors' pension amounts out of their pay, so a drawn carer whom that conversion takes under the survey year's limit keeps the flag although the file then shows them entitled and not reporting. The stage rebuilds the flag from reported receipt and refuses a frame whose flag no longer follows it. Its receipt bands support on distinct source households (household_source_id), and gives a weighted total only where ten or more carry it and the realised share only where neither side rests on one to nine; the stage has no health gate.", "operations": [ { "consumed_only": true, @@ -111,7 +111,7 @@ { "assignment_unit": "person", "draw": "would_claim_carers_allowance", - "eligibility": "persons outside Scotland whose care_hours reach policyengine-uk's gov.dwp.carers_allowance.min_hours, who report no Carer's Allowance, and whom is_gainfully_employed_for_carers_allowance holds gainfully employed at the survey year: the carers the earnings limit alone keeps from the allowance. Scotland stays closed, since Carer Support Payment reads the same flag and the engine applies it no earnings test", + "eligibility": "persons outside Scotland whose care_hours reach policyengine-uk's gov.dwp.carers_allowance.min_hours, who report no Carer's Allowance, and whom is_gainfully_employed_for_carers_allowance holds gainfully employed at the survey year: the carers the earnings limit alone keeps from the allowance. Scotland stays closed, since Carer Support Payment reads the same flag and policyengine-uk does not yet apply its earnings limit", "kind": "assign_binary_from_rate", "output": "would_claim_carers_allowance", "rate_derivation": "the take-up contract's carers_allowance_newly_entitled rate, drawn flat over the eligible persons; would_claim = reported OR (eligible AND u < rate), so a reporter stays true and every other person false", diff --git a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/uk_spine.json b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/uk_spine.json index f99251b74..12d556f13 100644 --- a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/uk_spine.json +++ b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/uk_spine.json @@ -1 +1 @@ -{"country":"uk","nodes":[{"artifact_outputs":[{"name":"stage_evidence","type":{"name":"microcosm.stage-evidence","schema_version":1}}],"base":null,"citation":"","description":"Load the source-bound UK FRS root 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