diff --git a/changelog.d/1418-spi-donor-savings-rebase.changed.md b/changelog.d/1418-spi-donor-savings-rebase.changed.md new file mode 100644 index 0000000000..345fd8fdff --- /dev/null +++ b/changelog.d/1418-spi-donor-savings-rebase.changed.md @@ -0,0 +1 @@ +The SPI income stage now rebases the 2022-23 tape's interest and other income to HMRC's published 2023-24 Table 3.7 amounts band by band (the published rows are vendored as `uk/hmrc_spi_table_3_7_savings_rows.json`), then carries both to the frame's year on the OBR's savings income growth (October 2026 EFO, Table 4.5), the path the Table 3.7 band targets take (#1418 savings follow-up, #1428). Before, each column moved by its engine index from 2022 to 2024: other income by GDP per head (x1.09) where SPI's own other income grew x1.65 in the single year to 2023-24, and interest by ONS household interest (x2.27) where SPI's grew x2.69 in that year. The frame then carried about 70 percent of the Table 3.7 savings rows at design weights, and the solve met them by stretching the weights of the few households that carry them. Each band's factor is the published amount over the FACT-weighted amount of the tape's taxpayers in the band, as Table 3.7 counts taxpayers only. The tape is banded on its income moved to 2023-24, repeating until the rebased savings move no record across a band edge, so the band-edge migration its consumers re-band on uprated income is counted once. A taxpayer is a record the tape flags (TAXPAYER 1) or one whose income crosses the Personal Allowance by 2023-24, so a saver who becomes a taxpayer counts once; a flagged taxpayer below the first band sits in it (note 8), and any other record takes the factor of all bands. A band too thin to gross (under a tenth of its published amount) takes the factor of all bands, a column whose tape does not gross to the published amounts is left as it is and grows on its engine index from 2022-23, and a tape whose TAXPAYER codes are not 1 or 2 is refused. On the tape, the £1m-and-over band's other income outweighs its interest, as in the published table, so the rebase also undoes the split the two indices had flipped. diff --git a/changelog.d/1428-dwp-jsa-income-based.added.md b/changelog.d/1428-dwp-jsa-income-based.added.md new file mode 100644 index 0000000000..c00627bb8e --- /dev/null +++ b/changelog.d/1428-dwp-jsa-income-based.added.md @@ -0,0 +1 @@ +The national calibration binds DWP's income-based Jobseeker's Allowance spending, `dwp.jsa.amount_income_based` (benefit expenditure and caseload tables, Spring Forecast 2026), at the calendar-2025 window of the fiscal years, as the pension-age Housing Benefit row is (#1428; María's ruling of 2026-10-31). Income-based JSA closes with the move to Universal Credit: £91.0m in FY2024-25 and under £1m from FY2025-26. Without the split, the calibration meets OBR's total JSA by scaling income-based reporters together with contributory claimants, far past DWP's income-based spending. diff --git a/changelog.d/1428-frs-other-income-definitions.changed.md b/changelog.d/1428-frs-other-income-definitions.changed.md new file mode 100644 index 0000000000..140b38854f --- /dev/null +++ b/changelog.d/1428-frs-other-income-definitions.changed.md @@ -0,0 +1 @@ +FRS rows now book NS&I income on SPI's definitions (#1428). NS&I Direct Saver and the other NS&I and bank products go to `savings_interest_income`, because SPI has counted all interest paid gross or net as bank interest since 2016-17 (Table 3.7 note 4); gilts stay in `other_investment_income`. Income from an annuity not bought with pension funds or from a trust or covenant (FRS PENTYPE 4 and 5) stays in `private_pension_income`, where policyengine-uk's means tests (Pension Credit, Universal Credit, Housing Benefit, Council Tax Reduction, Income Support), household income and tax read it. Its part is stored in a new calibration-only descriptor, `annuity_and_trust_income`, and SPI Table 3.7's other-income rows read `other_investment_income_spi_concept`: the engine's other income plus that share of the engine's private pension, as the table counts both payments as other income (note 6). A row the SPI stage draws holds the tape's pension, which excludes them, so its descriptor is zero. The FRS spine now refuses a pension tab without PENTYPE. diff --git a/changelog.d/1428-isa-fit-weight-records.fixed.md b/changelog.d/1428-isa-fit-weight-records.fixed.md new file mode 100644 index 0000000000..967a5f7d98 --- /dev/null +++ b/changelog.d/1428-isa-fit-weight-records.fixed.md @@ -0,0 +1 @@ +The ISA subscriptions stage no longer declares an empty list of fit-weight records (#1428). It fits no model, but the release-cut weights audit read its empty list as a fitting stage that recorded nothing, so every national certified after #1421 failed `uk_weights_audit`. diff --git a/changelog.d/1428-spi-employment-by-self-employment-band.added.md b/changelog.d/1428-spi-employment-by-self-employment-band.added.md new file mode 100644 index 0000000000..eb50132a4e --- /dev/null +++ b/changelog.d/1428-spi-employment-by-self-employment-band.added.md @@ -0,0 +1 @@ +The national calibration binds SPI 2023-24 Table 3.10's individuals with employment income by self-employment band, `hmrc.spi.employment_income.count_by_self_employment_income_band`, over the eight bands from £1 to £10,000 that the self-employment counts and amounts already bind (#1418; María's choice of 2026-10-30). With the self-employment counts alone, the solve could meet each band with traders who have no pay, while in Table 3.10 more than half of the traders below £3,000 also have employment income; an employee's side profit is taxed at their marginal rate, so the mix of small traders decides what the Budget's trading allowance measures cost. Each person with pay over the year (`employment_income_annual`, the variable Table 3.6's employment rows read) counts in their own self-employment band, taxpayer or not. Table 3.10's column is wider, income assessed under ITEPA 2003 plus other miscellaneous income, so like Table 3.6's employment rows the binding leaves out miscellaneous income and the contributory benefits; benefits in kind count on SPI rows, whose pay is the tape's PAY + EPB + TAXTERM, and not on FRS rows. Counts grow to 2025 with HMRC's projected growth of all taxpayers (Income Tax liabilities statistics Table 2.5), as the self-employment counts do, and the zero band and the bands from £10,000 are signed out row by row. diff --git a/changelog.d/1428-spi-gift-anchor.changed.md b/changelog.d/1428-spi-gift-anchor.changed.md new file mode 100644 index 0000000000..7ef70ce5a8 --- /dev/null +++ b/changelog.d/1428-spi-gift-anchor.changed.md @@ -0,0 +1 @@ +The SPI income stage anchors the drawn copies' Gift Aid and charitable investment gifts to the SPI tape's own weighted totals (#1428; María's ruling of 2026-10-31). Both are sparse leaves that the stage-1 chain draws after, and conditioned on, the income leaves, so a change to the savings draws reshuffles which few donors' gifts the copies draw. Each column's total over the drawn copies, at the stage's household weights, is scaled to the tape's FACT-weighted total. A column that the tape or the copies carry none of is left as drawn. The scaling fixes the totals, not how concentrated each column is. The stage evidence records each column's factor, never a total or a count. diff --git a/changelog.d/1428-spi-other-income-analogue.changed.md b/changelog.d/1428-spi-other-income-analogue.changed.md new file mode 100644 index 0000000000..c39db42253 --- /dev/null +++ b/changelog.d/1428-spi-other-income-analogue.changed.md @@ -0,0 +1 @@ +The SPI stage-1 transport now locates each copy's other-income draw at its FRS twin's own other income (gilt interest), as it does for the other investment leaves, instead of an identity uniform that ignored the twin's holdings (#1428). diff --git a/changelog.d/1428-trading-allowance-receipts.added.md b/changelog.d/1428-trading-allowance-receipts.added.md new file mode 100644 index 0000000000..d4f2c6f5e6 --- /dev/null +++ b/changelog.d/1428-trading-allowance-receipts.added.md @@ -0,0 +1 @@ +A new last spine stage, `trading_allowance_receipts`, stores the self-employed's gross receipts (`self_employment_gross_receipts`), so policyengine-uk applies the trading allowance against receipts as the law does (#1428; María's choice of 2026-10-31). Neither the FRS nor the SPI tape records turnover. Without receipts the engine relieved profits up to the allowance in full and nothing above it, so a rise in the allowance missed its main base: traders who already claim the £1,000 allowance against larger receipts. Under current law a claimant's receipts are their profit plus £1,000 exactly. Each trader with a positive profit is flagged as a claimant with probability 0.64 for profits up to £4,500, 0.32 from £4,500 to £9,000 and none above, drawn on their own `person_id`. A claimant's receipts are their profit plus £1,000; any other trader's are their profit plus £3,000, expenses at the raised allowance, since the costing books traders who switch to the allowance as behaviour. The rates are calibrated to HMRC's policy paper (about 400,000 taxpayers with a lower bill, by about £380 on average) until HMRC publishes claimant counts. Every trader with a positive profit is treated as filing, as the Table 3.10 counts the calibration binds are of filers, so a profit of £1,000 or less is now taxed where the engine used to relieve it in full. Two limits remain until policyengine-uk#2765 lets the stage store the claim status itself (#1439). A claimant's £1,000 grows with the mixed income index while the allowance is nominal, so the raise relieves £1,932 more in 2027-28, falling to £1,758 by 2031-32. The other traders' stored £3,000 grows the same way, so allowances above £3,000 are mis-scored. `self_employment_gross_receipts` leaves the register of engine inputs left at their default and joins the export surface's allowed columns. The stage spec and schema, the graph and kernel wiring, the spine build, the coverage manifest, the H2 fixture and the data contract's gate digests follow. diff --git a/changelog.d/1428-uc-take-up-passes-unmet-gaps.changed.md b/changelog.d/1428-uc-take-up-passes-unmet-gaps.changed.md new file mode 100644 index 0000000000..f057971ad9 --- /dev/null +++ b/changelog.d/1428-uc-take-up-passes-unmet-gaps.changed.md @@ -0,0 +1 @@ +The Universal Credit take-up stage now passes the gap of a pool that cannot meet DWP's count to its neighbouring pools, so each family type's caseload lands on DWP's wherever its entitled units allow (#1428; María's rulings of 2026-10-31 and 2026-11-01). The stage pools adjacent award bands within a family type until they rest on enough sources. A pool can't meet DWP's count when its reporters' and other undrawn units' expected claims already exceed it, or when the count exceeds every entitled unit. Such a pool used to keep its clipped rate, which left the family type's caseload off DWP's by the gap, and which bands fell short moved with small upstream changes. Now such a pool is held at its clip and its gap passes on. A shortfall and an excess elsewhere in the family type offset first. What remains goes to the other pools, nearest first, the one with more room first at equal distance and the lower band on a tie, each taking what its room allows. Every band keeps its own rate, so no band's drawn units claim against its own count to meet another's. The stage spec, the coverage manifest, the H2 fixture and the data contract's gate digests follow. diff --git a/docs/uk-income-anchors-280.md b/docs/uk-income-anchors-280.md index 6e944ed71a..0c9789dadd 100644 --- a/docs/uk-income-anchors-280.md +++ b/docs/uk-income-anchors-280.md @@ -62,8 +62,10 @@ membership carries the uprated value with its receipt. others take `policyengine_uk_parameter:`, the ratio of the pinned engine's parameter between 1 January of the fact's opening year and 1 January of the calibration year, the instants the SPI donor rebasing already - uses: dividends `obr.per_capita.gdp`. Savings interest takes two legs - (microcosm#1095): `ons.household_interest_income`, the index of its + uses: dividends `obr.per_capita.gdp`. Savings interest outside SPI Table + 3.7's rows takes two legs (microcosm#1095); Table 3.7's interest and other + income rows take the OBR's savings income path from 2023-24 instead, as the + next paragraph says (microcosm#1418): `ons.household_interest_income`, the index of its history, to the dataset's year, then `obr.per_capita.gdp`, the index the engine's dataset projection applies, to the calibration year (1.1420 x 1.0474 = 1.1961 on the pinned engine values; 1.0438 and 1.1920 before @@ -78,6 +80,27 @@ membership carries the uprated value with its receipt. by `tools/pin_uk_uprating_engine_values.py`, whose `--check` refuses drift), so it runs and reproduces without policyengine-uk; a `requires_uk` test holds the pins in lockstep with the installed engine, and an engine bump re-runs the tool. + + The SPI donors reach the frame's year apart from these indices for interest + and other income (microcosm#1418 savings follow-up). The income stage first + scales each donor's two columns to HMRC's published 2023-24 Table 3.7 amounts + in its band of total income (`spi_income.rebase_spi_donor_savings`, the rows + vendored as `uk/hmrc_spi_table_3_7_savings_rows.json`), then grows them on the + OBR's savings income path the Table 3.7 targets take + (`hmrc_uprating.uk_obr_savings_income_level`). Each band's factor is the + published amount over the FACT-weighted amount of the tape's taxpayers in + the band, as Table 3.7 counts taxpayers only (microcosm#1428). The tape is + banded on its income moved to 2023-24, each income leaf at its own factor, + repeating until the rebased savings move no record across a band edge, so + the band-edge migration the consumers re-band on uprated income is counted + once. A taxpayer is a record the tape flags (TAXPAYER 1) or one whose income + crosses the Personal Allowance by 2023-24; a flagged taxpayer below the first + band sits in it (note 8); any other record takes the factor of all bands. A + band the tape carries none of is left as it is, a band whose tape amount is + under a tenth of its published amount takes the factor of all bands, and a + column whose tape does not gross to the published amounts is left as it is + and grows on its engine index from 2022-23. From the frame's year on, the + engine projects the two columns on their own indices. - Count rows: `hmrc.itl_2026.taxpayer_count_growth_by_total_income_band`, HMRC's own projected growth in Income Tax payers for the Table 2.5 band that contains the SPI band (Income Tax liabilities statistics, July 2026), as the @@ -387,8 +410,9 @@ fold differs from its twin's, and a reference whose sign classes differ from the tape forest's on any located target. One difference between the two forests remains: the reference locates a leaf given the twin's observed earlier analogue leaves, while the tape forest draws it given every earlier -output, the three identity-uniform leaves (`other_investment_income`, -`gift_aid`, `charitable_investment_gifts`) included, so a located quantile is +output, the two identity-uniform leaves (`gift_aid`, +`charitable_investment_gifts`) included, since `other_investment_income` has +located at the twin's own other income from microcosm#1428, so a located quantile is read off a conditional those identity draws also shape; pay, which follows them in the chain, has the weakest rank fidelity, and moving the analogue targets ahead of the identity leaves is the follow-up to measure. Because the diff --git a/packages/microcosm-build/src/microcosm/build/source_manifest.py b/packages/microcosm-build/src/microcosm/build/source_manifest.py index 00d13a4cf5..36f979185b 100644 --- a/packages/microcosm-build/src/microcosm/build/source_manifest.py +++ b/packages/microcosm-build/src/microcosm/build/source_manifest.py @@ -58,6 +58,8 @@ "assign_student_loan_plan_cohorts", "assign_main_asset_type", "assign_trips_from_band_means", + # microcosm#1428: the self-employed's gross receipts. + "assign_trading_allowance_receipts", "assign_uniform_draw", "aggregate_person_to_benunit", "allocate_per_capita_from_cell_table", 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 51b7208ffa..d40dfeaf13 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 @@ -6612,6 +6612,75 @@ } } }, + { + "type": "object", + "additionalProperties": false, + "required": [ + "kind", + "output", + "profit", + "draw", + "seed", + "claimant_bands", + "claimant_expenses", + "other_expenses", + "calibration", + "rule" + ], + "properties": { + "kind": { + "const": "assign_trading_allowance_receipts" + }, + "output": { + "type": "string" + }, + "profit": { + "type": "string" + }, + "draw": { + "type": "string" + }, + "seed": { + "type": "integer" + }, + "claimant_bands": { + "type": "array", + "minItems": 1, + "items": { + "type": "object", + "additionalProperties": false, + "required": [ + "rate" + ], + "properties": { + "upper_inclusive": { + "type": "number", + "exclusiveMinimum": 0 + }, + "rate": { + "type": "number", + "minimum": 0, + "maximum": 1 + } + } + } + }, + "claimant_expenses": { + "type": "number", + "minimum": 0 + }, + "other_expenses": { + "type": "number", + "minimum": 0 + }, + "calibration": { + "type": "string" + }, + "rule": { + "type": "string" + } + } + }, { "type": "object", "additionalProperties": false, 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 19e60dfb8e..4d42127cd5 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 @@ -41,7 +41,8 @@ "hmrc.spi.private_pension_income.count_by_total_income_band", "hmrc.spi.state_pension.count_by_total_income_band", "hmrc.spi.savings_interest_income.count_by_total_income_band", - "hmrc.spi.self_employment_income.count_by_self_employment_income_band" + "hmrc.spi.self_employment_income.count_by_self_employment_income_band", + "hmrc.spi.employment_income.count_by_self_employment_income_band" ], "max_dropped_rows": 2, "max_dropped_published_share": 0.01 @@ -76,7 +77,7 @@ "reason": "Zero-support floor: a row in one of the floor's scopes (the UC payment-distribution and benefit-cap amount bands, the HMRC SPI income bands by total income and SPI Table 3.10's self-employment income bands, and the band-H council-tax rows by English region) whose compiled matrix row reaches no source household (household_source_id) with a positive prior weight cannot be fitted by any weights (the solver's initialiser refuses a nonzero target with no support), so it is dropped from the solve, not pooled. A row that some households carry stays bound however few they are; when fewer than 10 distinct source households carry it, its model figures are withheld from every written surface (the UK Data Service working floor, CD171 section 5.2.1). Each scope holds one unit, because its share ceiling sums published values. The floor's receipt reports each target's dropped published total and each scope's dropped share, and the run refuses when a scope's drops pass either of its ceilings or when a per-row exclusion names a row the floor drops.", "tracking": "microcosm#1095", "approved_by": "juaristi22", - "adjudication": "microcosm#1095 U3, ruled 2026-10-16 with the fifth ports PR (floor 10) and revised 2026-10-21 with #1333: a cell that rests on fewer than 10 records is no reason to leave a row out, only a measured distortion of the calibration is. The floor drops only rows no household carries, the benefit-cap amount bands join its scope and their per-row entries retire, and the figures of rows under 10 source households are withheld, as the BRMA rows' are. The thirteen entries it retired (the eleven benefit-cap amount bands and the two HMRC £500k to £1m cells) and the A/B that retired them: experiments/1095-uk-thin-row-binding-receipts.md. Extended on 2026-10-22 (María's ruling on the next policyengine-uk bump) to the HMRC SPI income-band families and the band-H council-tax rows by region, in scopes of one unit each with their own ceilings. On #1333's policyengine-uk 2.145.0 spine every HMRC £1m-and-over cell and every band-H region cell has carriers. The three band-H region entries retire and their rows bind, with their figures withheld where fewer than 10 source households carry them; the ten HMRC £1m-and-over cells, bound on arm 1, distorted their neighbours and stay held on that measurement, so the HMRC scopes cover the bands below them. Extended on 2026-10-29 in microcosm#1420, in answer to the independent review's finding 7 and pending María's confirmation, to the SPI families microcosm#1418 binds, Table 3.7's other income by total-income band and Table 3.10's self-employment bands from GBP 1 to GBP 10,000: a row of theirs that no household carries is dropped and receipted as its siblings' rows are, not refused. The ceilings are unchanged, so the HMRC amounts scope's 2-row cap, signed for seven families, now covers nine, and the counts scope's, signed for seven, now covers eight; María confirms or re-sizes them (the re-reviews of microcosm#1420, H and 4).", + "adjudication": "microcosm#1095 U3, ruled 2026-10-16 with the fifth ports PR (floor 10) and revised 2026-10-21 with #1333: a cell that rests on fewer than 10 records is no reason to leave a row out, only a measured distortion of the calibration is. The floor drops only rows no household carries, the benefit-cap amount bands join its scope and their per-row entries retire, and the figures of rows under 10 source households are withheld, as the BRMA rows' are. The thirteen entries it retired (the eleven benefit-cap amount bands and the two HMRC £500k to £1m cells) and the A/B that retired them: experiments/1095-uk-thin-row-binding-receipts.md. Extended on 2026-10-22 (María's ruling on the next policyengine-uk bump) to the HMRC SPI income-band families and the band-H council-tax rows by region, in scopes of one unit each with their own ceilings. On #1333's policyengine-uk 2.145.0 spine every HMRC £1m-and-over cell and every band-H region cell has carriers. The three band-H region entries retire and their rows bind, with their figures withheld where fewer than 10 source households carry them; the ten HMRC £1m-and-over cells, bound on arm 1, distorted their neighbours and stay held on that measurement, so the HMRC scopes cover the bands below them. Extended on 2026-10-29 in microcosm#1420, in answer to the independent review's finding 7 and pending María's confirmation, to the SPI families microcosm#1418 binds, Table 3.7's other income by total-income band and Table 3.10's self-employment bands from GBP 1 to GBP 10,000: a row of theirs that no household carries is dropped and receipted as its siblings' rows are, not refused. The ceilings are unchanged, so the HMRC amounts scope's 2-row cap, signed for seven families, now covers nine, and the counts scope's, signed for seven, now covers eight; María confirms or re-sizes them (the re-reviews of microcosm#1420, H and 4). Extended on 2026-11-01 in microcosm#1428, in answer to its independent review's finding 11, to Table 3.10's employment-income counts by self-employment band, which #1428 binds over the same bands: a row of theirs no household carries is dropped and receipted, not refused. The counts scope's 2-row cap now covers nine families.", "approved_on": "2026-10-22", "expires_on": "2027-01-08" }, @@ -171,6 +172,15 @@ "approved_on": "2026-10-23", "expires_on": "2027-01-23" }, + { + "name": "hmrc.spi.savings_interest_income.amount_by_total_income_band.band_1000000", + "reason": "Measured distortion, not thin support, as for the ten HMRC £1m-and-over cells (María's rule of 2026-10-21). With the SPI donors' interest and other income rebased to SPI's 2023-24 bands (microcosm#1428), the first national built from f3cb3ddd3 fitted every other interest and other-income band, the £1m-and-over other-income row included, and missed this row outside the uk_target_fit band. Held out of the objective and measured on every evaluation. The row rests on the SPI Public Use Tape, so its figures and its neighbours' stay out of this register.", + "tracking": "microcosm#1418", + "approved_by": "juaristi22", + "adjudication": "María's ruling of 2026-10-30 on the savings follow-up (microcosm#1428): hold the £1m-and-over savings interest amount row as a measured distortion, rebuild the national on the same spine and score it; how the rebase sits in the top bands at design weights is a follow-up.", + "approved_on": "2026-10-30", + "expires_on": "2027-01-30" + }, { "name": "slc.repayments.england_plan_5", "reason": "Structural under-support: the student-loans stage tops Plan 5 up to SLC's liable stock, which binds, and fewer than ten source households carry Plan 5 repayments on #1333's 2.145.0 spine, so no weights reach SLC's repayment figure; the row's model figures are withheld.", diff --git a/packages/microcosm-build/src/microcosm/build/uk/country_package.json b/packages/microcosm-build/src/microcosm/build/uk/country_package.json index 8d76a051ef..742266c71f 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/country_package.json +++ b/packages/microcosm-build/src/microcosm/build/uk/country_package.json @@ -157,6 +157,11 @@ "kind": "legacy_json", "schema_id": "legacy_json" }, + { + "path": "hmrc_spi_table_3_7_savings_rows.json", + "kind": "legacy_json", + "schema_id": "legacy_json" + }, { "path": "slc_liable_stocks.json", "kind": "legacy_json", diff --git a/packages/microcosm-build/src/microcosm/build/uk/cross_grain_declarations.json b/packages/microcosm-build/src/microcosm/build/uk/cross_grain_declarations.json index d751cd670f..15093a6275 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/cross_grain_declarations.json +++ b/packages/microcosm-build/src/microcosm/build/uk/cross_grain_declarations.json @@ -1074,10 +1074,11 @@ }, { "targets": [ + "hmrc.spi.employment_income.count_by_self_employment_income_band", "hmrc.spi.self_employment_income.amount_by_self_employment_income_band", "hmrc.spi.self_employment_income.count_by_self_employment_income_band" ], - "reason": "Banded by groupby on the person's own self-employment income after loss relief, SPI Table 3.10's range; the band is the fan-out dimension, not a measurement filter, and Table 3.10 counts taxpayers and non-taxpayers alike. Bound from GBP 1 to GBP 10,000 only, the bands above stay with Table 3.6's self-employment rows by total income, so the two tables do not pull against each other (microcosm#1418)." + "reason": "Banded by groupby on the person's own self-employment income after loss relief, SPI Table 3.10's range; the band is the fan-out dimension, not a measurement filter, and Table 3.10 counts taxpayers and non-taxpayers alike; its employment-income count adds the year's pay as a filter over the same bands. Bound from GBP 1 to GBP 10,000 only, the bands above stay with Table 3.6's self-employment rows by total income, so the two tables do not pull against each other (microcosm#1418)." } ] } diff --git a/packages/microcosm-build/src/microcosm/build/uk/gates.json b/packages/microcosm-build/src/microcosm/build/uk/gates.json index e4ac4fa3e3..7e19c6ecb9 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/gates.json +++ b/packages/microcosm-build/src/microcosm/build/uk/gates.json @@ -637,7 +637,7 @@ "check": "uc_take_up", "maximum_caseload_deviation": 0.055 }, - "notes": "Stage-time gate over the Universal Credit take-up receipt (microcosm#1334): every reporter claims and no unit outside the draw changes; in each DWP family type the pools whose target is reachable realize DWP's calendar-2025 caseload within 0.055 of it at the stage's weights, Great Britain only, counting units the engine moves off their legacy benefits at their expected claim at the closure; and the family type's caseload is no further from DWP's than before the redraw, give or take 0.055 of DWP's count. The tolerance was 0.05 until microcosm#1418: routing gilt interest out of dividend_income reshuffles the SPI channel's draws. On the spine of 2026-10-28 (da944f12c), single people's caseload ends 0.0523 of DWP's count further from it than before the redraw (0.0486 on the spine before, 3c0d11b6's), so 0.055 holds it with about 8,000 to spare; couples without children, lone parents and couples with children end closer than before by 0.53, 0.054 and 0.42 of their counts, and every family type's reachable pools realize DWP's count within 0.0015. The terminal take-up signal gate no longer measures would_claim_uc, whose rate is now set by award band and family type, not as one share of the age population." + "notes": "Stage-time gate over the Universal Credit take-up receipt (microcosm#1334): every reporter claims and no unit outside the draw changes; in each DWP family type the pools whose target is reachable realize DWP's calendar-2025 caseload within 0.055 of it at the stage's weights, Great Britain only, counting units the engine moves off their legacy benefits at their expected claim at the closure; and the family type's caseload is no further from DWP's than before the redraw, give or take 0.055 of DWP's count. The tolerance was 0.05 until microcosm#1418: routing gilt interest out of dividend_income reshuffles the SPI channel's draws. In the savings follow-up (microcosm#1428), small upstream changes moved single people's GBP 1,000 to 1,100 band into a pool whose DWP count exceeds its entitled units, and the family type's caseload ended 0.0568, then 0.0674, of DWP's count further from it than before the redraw. The stage now joins a pool that cannot meet its count to the adjacent pool with more room for its gap, so a family type's caseload lands on DWP's wherever its entitled units allow, and the tolerance stays at 0.055 (María's ruling of 2026-10-31). The terminal take-up signal gate no longer measures would_claim_uc, whose rate is now set by award band and family type, not as one share of the age population." }, { "id": "uk_stage_pension_credit_take_up", @@ -1251,6 +1251,8 @@ "person.private_pension_income_annual_share", "person.self_employment_income_annual_share", "person.self_employment_income_other_spells", + "person.self_employment_gross_receipts", + "person.annuity_and_trust_income", "person.esa_health_condition_proxy", "person.esa_includes_support_component", "person.esa_support_group_proxy", diff --git a/packages/microcosm-build/src/microcosm/build/uk/hmrc_spi_table_3_7_savings_rows.json b/packages/microcosm-build/src/microcosm/build/uk/hmrc_spi_table_3_7_savings_rows.json new file mode 100644 index 0000000000..ae2b4681f6 --- /dev/null +++ b/packages/microcosm-build/src/microcosm/build/uk/hmrc_spi_table_3_7_savings_rows.json @@ -0,0 +1,1217 @@ +{ + "schema_version": 1, + "country": "uk", + "kind": "uk_vendored_ledger_facts", + "resource": "hmrc_spi_table_3_7_savings_rows.json", + "purpose": "HMRC Survey of Personal Incomes 2023-24, Table 3.7 (income by source and range of total income, taxpayers): the United Kingdom interest from banks and building societies and other income amounts in each of the 13 total-income bands. Consumed by the SPI income stage, which rebases each donor's interest and other income from the 2022-23 tape to these 2023-24 amounts band by band before the OBR's savings income growth carries them to the frame's year (microcosm#1418 savings follow-up).", + "consumers": [ + "uk_runtime.spi_income" + ], + "planned_consumers": [], + "policy": "Rows are copied verbatim from the pinned Chronicle consumer feed named in source_fact_feed; every value is a publisher-stated fact. Consumers declare their own arithmetic on these rows and never edit this file by hand: regenerate it with tools/vendor_uk_ledger_facts.py.", + "generator": { + "tool": "tools/vendor_uk_ledger_facts.py", + "version": 1 + }, + "source_fact_feed": { + "source_repo": "PolicyEngine/chronicle", + "source_commit": "53815b24844cb63c103209f197f9d3d9e2e424a9", + "build": "build-bundle --suite uk -> build-consumer-artifact", + "artifact_schema_version": "policyengine_ledger.consumer_artifact.v2", + "fact_row_count": 1511063, + "facts_sha256": "4b0e5c1ad057946407807428a1c79c70d9b14e2f8539ea8fb93524573c026227", + "manifest_sha256": "708231c77432d2838bf1ee7d8f3080e49ca0e59edccdd45c36b3405db2cb45fb" + }, + "selections": [ + { + "label": "spi_2023_24_table_3_7_savings_rows", + "selector": { + "source_name": "hmrc", + "source_concept": [ + "hmrc.spi_savings_interest_income_amount", + "hmrc.spi_other_income_amount" + ], + "groupby_dimension": "hmrc.total_income_band", + "geography_id": "K02000001", + 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1403, + "compiled_count": 1412, "counts_by_kind": { "calibration_drift": 557, "fixture_only": 48, - "ledger_only": 814 + "ledger_only": 823 }, - "difference_count": 1419, + "difference_count": 1428, "differences": [ { "fixture_value": 1608000.0, @@ -679,6 +679,13 @@ "period": 2025, "reason": "Ledger-compiled row has no fixture counterpart at this comparison period." }, + { + "kind": "ledger_only", + "ledger_value": 23377178.788788605, + "name": "dwp.jsa.amount_income_based", + "period": 2025, + "reason": "Ledger-compiled row has no fixture counterpart at this comparison period." + }, { "kind": "ledger_only", "ledger_value": 1390586.25, @@ -2527,6 +2534,62 @@ "period": 2025, "reason": "Ledger-compiled row has no fixture counterpart at this comparison period." }, + { + "kind": "ledger_only", + "ledger_value": 136689.37329700272, + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_1000_2000", + "period": 2025, + "reason": "Ledger-compiled row has no fixture counterpart at this comparison period." + }, + { + "kind": "ledger_only", + "ledger_value": 72111.7166212534, + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_1_500", + "period": 2025, + "reason": "Ledger-compiled row has no fixture counterpart at this comparison period." + }, + { + "kind": "ledger_only", + "ledger_value": 110858.310626703, + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_2000_3000", + "period": 2025, + "reason": "Ledger-compiled row has no fixture counterpart at this comparison period." + }, + { + "kind": "ledger_only", + "ledger_value": 96866.48501362398, + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_3000_4000", + "period": 2025, + "reason": "Ledger-compiled row has no fixture counterpart at this comparison period." + }, + { + "kind": "ledger_only", + "ledger_value": 82874.65940054496, + "name": 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{ "kind": "ledger_only", "ledger_value": 617065102.3673128, diff --git a/packages/microcosm-build/src/microcosm/build/uk/ledger_fact_vendor_selections.json b/packages/microcosm-build/src/microcosm/build/uk/ledger_fact_vendor_selections.json index f427d46074..fa010a0c18 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/ledger_fact_vendor_selections.json +++ b/packages/microcosm-build/src/microcosm/build/uk/ledger_fact_vendor_selections.json @@ -1727,6 +1727,33 @@ } ] }, + { + "resource": "hmrc_spi_table_3_7_savings_rows.json", + "purpose": "HMRC Survey of Personal Incomes 2023-24, Table 3.7 (income by source and range of total income, taxpayers): the United Kingdom interest from banks and building societies and other income amounts in each of the 13 total-income bands. Consumed by the SPI income stage, which rebases each donor's interest and other income from the 2022-23 tape to these 2023-24 amounts band by band before the OBR's savings income growth carries them to the frame's year (microcosm#1418 savings follow-up).", + "consumers": [ + "uk_runtime.spi_income" + ], + "planned_consumers": [], + "selections": [ + { + "label": "spi_2023_24_table_3_7_savings_rows", + "selector": { + "source_name": "hmrc", + "source_concept": [ + "hmrc.spi_savings_interest_income_amount", + "hmrc.spi_other_income_amount" + ], + "groupby_dimension": "hmrc.total_income_band", + "geography_id": "K02000001", + "period_type": "tax_year", + "period_value": [ + 2023 + ] + }, + "expected_row_count": 26 + } + ] + }, { "resource": "hmrc_isa_statistics_facts.json", "purpose": "HMRC Annual savings statistics (September 2026 release), the rows the ISA subscriptions stage draws subscribers and amounts from and the Lifetime ISA anchor counts payers against (microcosm#1415): Table 9.7 2023-24 subscribers by total income and size of subscription, and the holders who made no further subscription, for all subscribers and each type paid into; Table 9.8 subscribers by age and sex; Table 9.9 subscribers by region; Table 9.4 accounts and amounts subscribed by component for 2023-24 and 2024-25 (the latest year provisional); Table 9.6 market values at 5 April 2025; the cash ISA limit reduction impact note's shares of under-65 cash subscribers either side of GBP 12,000 in 2022-23; and Lifetime ISA Table 1a withdrawals for 2024-25 and 2025-26. Tables 9.7 to 9.9 count individuals and Table 9.4 accounts. None is a calibration target: the stage's reviewed fence keeps them measured only. No value is derived here.", 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 a95a52ea06..61b10ca78b 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 @@ -472,7 +472,7 @@ "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": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -495,7 +495,7 @@ "capital_gains" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -518,7 +518,7 @@ "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": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -540,7 +540,7 @@ "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": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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)" @@ -569,7 +569,7 @@ "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": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -589,7 +589,7 @@ "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": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -611,7 +611,7 @@ "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": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -632,7 +632,7 @@ "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": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -656,7 +656,7 @@ "capital_gains" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "source_vintages": { "conditioning_resource": "hmrc_cgt_conditioning_facts.json", "conditioning_resource_sha256": "f7425784231e1f6aa657d0f26fc02591d9523600eb12fce5d35becf5dabf7569", @@ -746,7 +746,7 @@ "full_frs_tei_band_unavailable" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "source_vintages": { "hmrc_surface": "2023-24", "mapped_build_period": "2024", @@ -773,7 +773,7 @@ "required_mass_change_reason": "ISA subscriptions per adult from HMRC's ISA tables on the source spine: household weights pass through unchanged and total household mass is conserved.", "rewrites": [], "source_manifest": "source_stages.json", - "source_manifest_sha256": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "source_vintages": { "source": "HMRC Individual Savings Account statistics Tables 9.4, 9.6 and 9.7 to 9.9, the cash ISA limit reduction impact note and Lifetime ISA Table 1a, via the vendored facts; 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": "HMRC Annual savings statistics (September 2026 release); Wealth and Assets Survey round 8" @@ -838,7 +838,7 @@ "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": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -864,7 +864,7 @@ "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": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -884,7 +884,7 @@ "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": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -907,7 +907,7 @@ "property_finance_costs" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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)" @@ -928,7 +928,7 @@ "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": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -951,7 +951,7 @@ "property_wealth" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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)" @@ -975,7 +975,7 @@ "non_residential_property_value" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -1003,7 +1003,7 @@ "employment_income" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -1036,7 +1036,7 @@ "household_source_id" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -1058,7 +1058,7 @@ "student_loan_plan" ], "source_manifest": "source_stages.json", - "source_manifest_sha256": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -1066,6 +1066,26 @@ "stage": "student_loans", "status": "required_at_build" }, + "trading_allowance_receipts": { + "base_candidate_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", + "base_candidate_tier": "frs", + "effective_mass_requirements": {}, + "mass_change_semantics": "mass_conserving", + "output_weight_kind": "importance", + "outputs": [ + "self_employment_gross_receipts" + ], + "required_mass_change_reason": "Self-employed gross receipts 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": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", + "source_vintages": { + "source": "self_employment_income after the SPI income stage; HMRC's published gainers of the raise to GBP 3,000, about 400,000 taxpayers with a lower bill by about GBP 380 on average", + "survey": "The self-employed's own profit on the final spine, and HMRC's policy paper on the Budget 2026 trading allowance raise (calibration)" + }, + "stage": "trading_allowance_receipts", + "status": "required_at_build" + }, "was_lisa": { "base_candidate_sha256": "f17306ccb2aad7ff0130be3589b560afb2e2a12a943570911cd0c77f07934833", "base_candidate_tier": "frs", @@ -1080,7 +1100,7 @@ "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": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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" @@ -1119,7 +1139,7 @@ "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": "03692a33949bf12bd223a409c1ff1c1954839ad49ca53c013cf666185a5ffdb1", + "source_manifest_sha256": "da210d22e9948686e1a3afb4d459c1adb37028abf0e849f98f77e969e3b93197", "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-build/src/microcosm/build/uk/source_stages.json b/packages/microcosm-build/src/microcosm/build/uk/source_stages.json index 2b105e1505..e1b51ab741 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/source_stages.json +++ b/packages/microcosm-build/src/microcosm/build/uk/source_stages.json @@ -277,6 +277,7 @@ "loss_relief", "ni_class_4_losses_brought_forward", "private_pension_income", + "annuity_and_trust_income", "individual_savings_account_interest_income", "savings_interest_income", "dividend_income", @@ -379,6 +380,7 @@ "loss_relief", "ni_class_4_losses_brought_forward", "private_pension_income", + "annuity_and_trust_income", "individual_savings_account_interest_income", "savings_interest_income", "dividend_income", @@ -1954,7 +1956,7 @@ "dividend_income": "dividend_income", "private_pension_income": "private_pension_income", "property_income": "property_income", - "other_investment_income": null, + "other_investment_income": "other_investment_income", "gift_aid": null, "charitable_investment_gifts": null, "hmrc_spi_pay": "hmrc_spi_pay", @@ -2622,9 +2624,10 @@ "self_employment_income_annual_share", "self_employment_income_other_spells", "private_pension_income_annual_share", - "contributory_benefits_annual_share" + "contributory_benefits_annual_share", + "annuity_and_trust_income" ], - "notes": "Runs the SPI-trained income QRFs on the raw-spine support channel, drawing for its claimants and partners aged 16 and over so dependants aged 16 to 19 keep their FRS twin's values (uk-data#504, microcosm#1095), initializes FRS charity columns to zero, trains FRS-only stage 2 on the FRS rows' reported values, flags the rows it drew (person_is_spi_income_recipient) so later stages tell tape-concept rows from FRS-concept ones without re-deriving the recipient rule (microcosm#840), leaves every FRS-channel income as reported (no base-channel redraw of dividends; uk-data#498, microcosm#1095), and emits a sidecar-only 208-fact replay report for the spine path. Stage 2 also draws trading_loss, the year's trading loss the tape does not carry, from the FRS rows (uk-data#528), and a drawn row whose self_employment_income is positive keeps no loss, so profit and loss never both hold an amount, as on the FRS rows (microcosm#1095). The chain draws self_employment_income net of the tape's losses brought forward (LOSSBF), as the tape holds profits, and last of all, so no earlier draw moves, the year's profit before them and the losses. After the FRS-only fill and the HMRC aggregates the stage moves the losses out of the profit into loss_relief and ni_class_4_losses_brought_forward, the inputs policyengine-uk relieves them against (income tax under ITA 2007 s.83, Class 4 under SSCBA 1992 Sch 2 para 3), so Universal Credit, HBAI and market income read the year's profit; where the drawn net profit is positive the losses are its gap to the year's profit and where it is zero they are at least that profit, so the profit after the relief is the drawn net profit on every row, which the HMRC aggregates and the HMRC self-employment rows read (uk-data#528, microcosm#1095). The engine carries both losses into each projected year at their nominal value while the profit grows with its index. Stage 2 draws the six owner-manager inputs last, the five flags as 0 or 1 and then the income share, so each follows the drawn incomes; the root stage's rules then hold on the drawn rows (an owner works in the company, its other inputs need an owner, and a company carries on a trade or a property business, never both), since the tape carries no director answers (microcosm#1095). A drawn row's annual income descriptors follow its drawn incomes. The tape records the tax year's income, so its pay, profit and private pension shares are 1, and its contributory benefits, stage-2 draws on the current concept with no spell of their own, take share 1 too. It keeps its twin's other-spell pay only where it drew no pay, and its twin's ceased self-employment only where it drew no profit, since the bridge draws a record without pay for a twin who left a job in the year. An undrawn copy keeps its twin's descriptors with its twin's incomes." + "notes": "Runs the SPI-trained income QRFs on the raw-spine support channel, drawing for its claimants and partners aged 16 and over so dependants aged 16 to 19 keep their FRS twin's values (uk-data#504, microcosm#1095), initializes FRS charity columns to zero, trains FRS-only stage 2 on the FRS rows' reported values, flags the rows it drew (person_is_spi_income_recipient) so later stages tell tape-concept rows from FRS-concept ones without re-deriving the recipient rule (microcosm#840), leaves every FRS-channel income as reported (no base-channel redraw of dividends; uk-data#498, microcosm#1095), and emits a sidecar-only 208-fact replay report for the spine path. Stage 2 also draws trading_loss, the year's trading loss the tape does not carry, from the FRS rows (uk-data#528), and a drawn row whose self_employment_income is positive keeps no loss, so profit and loss never both hold an amount, as on the FRS rows (microcosm#1095). The chain draws self_employment_income net of the tape's losses brought forward (LOSSBF), as the tape holds profits, and last of all, so no earlier draw moves, the year's profit before them and the losses. After the FRS-only fill and the HMRC aggregates the stage moves the losses out of the profit into loss_relief and ni_class_4_losses_brought_forward, the inputs policyengine-uk relieves them against (income tax under ITA 2007 s.83, Class 4 under SSCBA 1992 Sch 2 para 3), so Universal Credit, HBAI and market income read the year's profit; where the drawn net profit is positive the losses are its gap to the year's profit and where it is zero they are at least that profit, so the profit after the relief is the drawn net profit on every row, which the HMRC aggregates and the HMRC self-employment rows read (uk-data#528, microcosm#1095). The engine carries both losses into each projected year at their nominal value while the profit grows with its index. Stage 2 draws the six owner-manager inputs last, the five flags as 0 or 1 and then the income share, so each follows the drawn incomes; the root stage's rules then hold on the drawn rows (an owner works in the company, its other inputs need an owner, and a company carries on a trade or a property business, never both), since the tape carries no director answers (microcosm#1095). A drawn row's annual income descriptors follow its drawn incomes. The tape records the tax year's income, so its pay, profit and private pension shares are 1, and its contributory benefits, stage-2 draws on the current concept with no spell of their own, take share 1 too. It keeps its twin's other-spell pay only where it drew no pay, and its twin's ceased self-employment only where it drew no profit, since the bridge draws a record without pay for a twin who left a job in the year. An undrawn copy keeps its twin's descriptors with its twin's incomes. A drawn row's annuity and trust descriptor is zero, since the tape's private pension excludes those payments and books them as other income (microcosm#1428)." }, { "stage": "spi_housing_shell", @@ -6189,13 +6192,13 @@ "family_type": "two FRS claimant or partner roles make a couple; children are UC children or qualifying young people and other non-claimants under 20 (the calibration measure's uc_calibration_family_type)", "award_bands": "GBP 1,200 a year (DWP's GBP 100 a month), (1,200 i, 1,200 (i + 1)] in whole pence for i < 25, and above GBP 30,000", "targets": "DWP Stat-Xplore Households on Universal Credit by family type and monthly award band, mean of April to December 2025", - "pooling": "adjacent bands within a family type, lowest first, until the drawn units rest on minimum_pool_sources distinct household_source_id values; a short last pool joins the one before it", + "pooling": "adjacent bands within a family type, lowest first, until the drawn units rest on minimum_pool_sources distinct household_source_id values; a short last pool joins the one before it. Then, lowest first, a pool that cannot meet DWP's count (its undrawn entitled units' expected claims exceed the count, or the count exceeds them plus the weight of every drawn unit) is held at the nearer of those ends and passes its gap to the other pools, nearest first, the one with more room first at equal distance and the lower on a tie, each taking what its room allows; a gap no pool can take leaves the family type unreachable", "minimum_pool_sources": 30, "drawn_units": "entitled, non-reporting units of the population that the engine does not move off their legacy benefits (legacy_benefits_closed) and that report none, since a legacy benefit the engine leaves in place ends once the unit claims UC", "undrawn_claims": "a reporter at 1, a moved unit at the claim probability uc_legacy_closure_take_up's rule gives it (dwp_move_to_uc_facts.json), a unit keeping income-related ESA at 0, any other at its stored flag", "kept_legacy_award": "a unit whose claimant or partner reports income-related ESA (esa_income_reported), and that neither reports Universal Credit nor is moved off its legacy benefits, claims no Universal Credit, since policyengine-uk ends that award once the family claims it", "weight_mapping": "household_to_benunit", - "residual_rate": "(T - F) / D, clipped to [0, 1]; T DWP's calendar-2025 mean count of the pool's bands, D the weight of the pool's drawn units and F the expected claims of its other entitled units, over Great Britain at the stage's household weights; realized by the drawn units claiming in the order of their uniform until their weight is nearest T - F, and applied at that uniform to Northern Ireland's drawn units too", + "residual_rate": "(T - F) / D, clipped to [0, 1]; T DWP's calendar-2025 mean count of the pool's bands after any gaps passed to or from it, D the weight of the pool's drawn units and F the expected claims of its other entitled units, over Great Britain at the stage's household weights; realized by the drawn units claiming in the order of their uniform until their weight is nearest T - F, and applied at that uniform to Northern Ireland's drawn units too", "solve_scope": "great_britain", "not_drawn": "keeps its stored flag, except a unit keeping income-related ESA, which claims none" } @@ -7712,6 +7715,52 @@ "source": "HMRC Individual Savings Account statistics Tables 9.4, 9.6 and 9.7 to 9.9, the cash ISA limit reduction impact note and Lifetime ISA Table 1a, via the vendored facts; 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).", "stage": "isa_subscriptions", "survey": "HMRC Annual savings statistics (September 2026 release); Wealth and Assets Survey round 8" + }, + { + "stage": "trading_allowance_receipts", + "survey": "The self-employed's own profit on the final spine, and HMRC's policy paper on the Budget 2026 trading allowance raise (calibration)", + "source": "self_employment_income after the SPI income stage; HMRC's published gainers of the raise to GBP 3,000, about 400,000 taxpayers with a lower bill by about GBP 380 on average", + "grain": "person", + "operations": [ + { + "kind": "assign_trading_allowance_receipts", + "output": "self_employment_gross_receipts", + "profit": "self_employment_income", + "draw": "trading_allowance_claimant", + "seed": 0, + "claimant_bands": [ + { + "upper_inclusive": 4500.0, + "rate": 0.64 + }, + { + "upper_inclusive": 9000.0, + "rate": 0.32 + }, + { + "rate": 0.0 + } + ], + "claimant_expenses": 1000.0, + "other_expenses": 3000.0, + "calibration": "HMRC's policy paper on the Budget 2026 trading allowance raise: about 400,000 taxpayers with a lower bill, by about GBP 380 on average, on the microcosm#1428 national b441bb5a0's final weights at 2028-29 prices, until HMRC publishes claimant counts (María's choice of 2026-10-31)", + "rule": "a person with a positive self_employment_income claims the allowance where their uniform falls below their profit band's rate; a claimant's receipts are their profit plus claimant_expenses, any other trader's their profit plus other_expenses, and a person with no positive profit keeps zero" + }, + { + "kind": "record_mass_conservation_receipt", + "entity": "household", + "reason": "Self-employed gross receipts stored on the source spine: household weights pass through unchanged and total household mass is conserved.", + "declared_factor": 1.0, + "gate_coupling": "The terminal family gate requires a valid mass-conserving MassChangeRecord carrying exactly this stage-specific reason." + } + ], + "outputs": [ + "self_employment_gross_receipts" + ], + "nonnegative_outputs": [ + "self_employment_gross_receipts" + ], + "notes": "The last spine stage (microcosm#1428). policyengine-uk applies the trading allowance against self_employment_gross_receipts, which neither the FRS nor the SPI tape records; without receipts a rise in the allowance relieves only profits up to the new allowance, in full, and misses its main base, the traders who already claim the GBP 1,000 allowance against larger receipts. Under current law a claimant's receipts are their profit plus GBP 1,000 exactly. Each trader with a positive profit is flagged a claimant at their profit band's rate, drawn on their own person_id: a claimant's receipts are their profit plus GBP 1,000, any other trader's their profit plus GBP 3,000 (expenses at the raised allowance, so the raise does not relieve them; the costing books switchers as behaviour), and a person with no positive profit keeps zero, which the engine reads as unknown. Every trader with a positive profit is treated as filing, as SPI Table 3.10's counts, which bind the frame's traders, are of filers, so a profit of GBP 1,000 or less is now taxed where the engine used to relieve it in full. The rates are calibrated to HMRC's policy paper until HMRC publishes claimant counts. The engine uprates receipts with profit, so a claimant's GBP 1,000 grows with the mixed income index while the allowance is nominal: the raise relieves GBP 1,932 more in 2027-28, falling to GBP 1,758 by 2031-32, 3.4% to 12.1% below GBP 2,000. The other traders' stored GBP 3,000 grows the same way, so an allowance above GBP 3,000 times that index relieves them from the stored expense, not from data: allowances above GBP 3,000 are mis-scored until policyengine-uk#2765 lets the stage store the claim status (microcosm#1439; María's ruling of 2026-11-01)." } ] } 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 f106b2d763..359943c988 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml +++ b/packages/microcosm-build/src/microcosm/build/uk/spec/sources.yaml @@ -408,6 +408,7 @@ stages: - loss_relief - ni_class_4_losses_brought_forward - private_pension_income + - annuity_and_trust_income - individual_savings_account_interest_income - savings_interest_income - dividend_income @@ -509,6 +510,7 @@ stages: - loss_relief - ni_class_4_losses_brought_forward - private_pension_income + - annuity_and_trust_income - individual_savings_account_interest_income - savings_interest_income - dividend_income @@ -1690,7 +1692,7 @@ stages: dividend_income: dividend_income private_pension_income: private_pension_income property_income: property_income - other_investment_income: null + other_investment_income: other_investment_income gift_aid: null charitable_investment_gifts: null hmrc_spi_pay: hmrc_spi_pay @@ -2248,7 +2250,8 @@ stages: - self_employment_income_other_spells - private_pension_income_annual_share - contributory_benefits_annual_share - notes: Runs the SPI-trained income QRFs on the raw-spine support channel, drawing for its claimants and partners aged 16 and over so dependants aged 16 to 19 keep their FRS twin's values (uk-data#504, microcosm#1095), initializes FRS charity columns to zero, trains FRS-only stage 2 on the FRS rows' reported values, flags the rows it drew (person_is_spi_income_recipient) so later stages tell tape-concept rows from FRS-concept ones without re-deriving the recipient rule (microcosm#840), leaves every FRS-channel income as reported (no base-channel redraw of dividends; uk-data#498, microcosm#1095), and emits a sidecar-only 208-fact replay report for the spine path. Stage 2 also draws trading_loss, the year's trading loss the tape does not carry, from the FRS rows (uk-data#528), and a drawn row whose self_employment_income is positive keeps no loss, so profit and loss never both hold an amount, as on the FRS rows (microcosm#1095). The chain draws self_employment_income net of the tape's losses brought forward (LOSSBF), as the tape holds profits, and last of all, so no earlier draw moves, the year's profit before them and the losses. After the FRS-only fill and the HMRC aggregates the stage moves the losses out of the profit into loss_relief and ni_class_4_losses_brought_forward, the inputs policyengine-uk relieves them against (income tax under ITA 2007 s.83, Class 4 under SSCBA 1992 Sch 2 para 3), so Universal Credit, HBAI and market income read the year's profit; where the drawn net profit is positive the losses are its gap to the year's profit and where it is zero they are at least that profit, so the profit after the relief is the drawn net profit on every row, which the HMRC aggregates and the HMRC self-employment rows read (uk-data#528, microcosm#1095). The engine carries both losses into each projected year at their nominal value while the profit grows with its index. Stage 2 draws the six owner-manager inputs last, the five flags as 0 or 1 and then the income share, so each follows the drawn incomes; the root stage's rules then hold on the drawn rows (an owner works in the company, its other inputs need an owner, and a company carries on a trade or a property business, never both), since the tape carries no director answers (microcosm#1095). A drawn row's annual income descriptors follow its drawn incomes. The tape records the tax year's income, so its pay, profit and private pension shares are 1, and its contributory benefits, stage-2 draws on the current concept with no spell of their own, take share 1 too. It keeps its twin's other-spell pay only where it drew no pay, and its twin's ceased self-employment only where it drew no profit, since the bridge draws a record without pay for a twin who left a job in the year. An undrawn copy keeps its twin's descriptors with its twin's incomes. + - annuity_and_trust_income + notes: Runs the SPI-trained income QRFs on the raw-spine support channel, drawing for its claimants and partners aged 16 and over so dependants aged 16 to 19 keep their FRS twin's values (uk-data#504, microcosm#1095), initializes FRS charity columns to zero, trains FRS-only stage 2 on the FRS rows' reported values, flags the rows it drew (person_is_spi_income_recipient) so later stages tell tape-concept rows from FRS-concept ones without re-deriving the recipient rule (microcosm#840), leaves every FRS-channel income as reported (no base-channel redraw of dividends; uk-data#498, microcosm#1095), and emits a sidecar-only 208-fact replay report for the spine path. Stage 2 also draws trading_loss, the year's trading loss the tape does not carry, from the FRS rows (uk-data#528), and a drawn row whose self_employment_income is positive keeps no loss, so profit and loss never both hold an amount, as on the FRS rows (microcosm#1095). The chain draws self_employment_income net of the tape's losses brought forward (LOSSBF), as the tape holds profits, and last of all, so no earlier draw moves, the year's profit before them and the losses. After the FRS-only fill and the HMRC aggregates the stage moves the losses out of the profit into loss_relief and ni_class_4_losses_brought_forward, the inputs policyengine-uk relieves them against (income tax under ITA 2007 s.83, Class 4 under SSCBA 1992 Sch 2 para 3), so Universal Credit, HBAI and market income read the year's profit; where the drawn net profit is positive the losses are its gap to the year's profit and where it is zero they are at least that profit, so the profit after the relief is the drawn net profit on every row, which the HMRC aggregates and the HMRC self-employment rows read (uk-data#528, microcosm#1095). The engine carries both losses into each projected year at their nominal value while the profit grows with its index. Stage 2 draws the six owner-manager inputs last, the five flags as 0 or 1 and then the income share, so each follows the drawn incomes; the root stage's rules then hold on the drawn rows (an owner works in the company, its other inputs need an owner, and a company carries on a trade or a property business, never both), since the tape carries no director answers (microcosm#1095). A drawn row's annual income descriptors follow its drawn incomes. The tape records the tax year's income, so its pay, profit and private pension shares are 1, and its contributory benefits, stage-2 draws on the current concept with no spell of their own, take share 1 too. It keeps its twin's other-spell pay only where it drew no pay, and its twin's ceased self-employment only where it drew no profit, since the bridge draws a record without pay for a twin who left a job in the year. An undrawn copy keeps its twin's descriptors with its twin's incomes. A drawn row's annuity and trust descriptor is zero, since the tape's private pension excludes those payments and books them as other income (microcosm#1428). - stage: spi_housing_shell survey: Family Resources Survey 2024-25 source: Family Resources Survey 2024-25 base households' housing (tenure, dwelling type, bedrooms, council tax, housing costs and the housing-linked benefit reports), imputed onto the SPI support households from their own region, composition and post-SPI incomes. @@ -4994,13 +4997,13 @@ stages: family_type: two FRS claimant or partner roles make a couple; children are UC children or qualifying young people and other non-claimants under 20 (the calibration measure's uc_calibration_family_type) award_bands: GBP 1,200 a year (DWP's GBP 100 a month), (1,200 i, 1,200 (i + 1)] in whole pence for i < 25, and above GBP 30,000 targets: DWP Stat-Xplore Households on Universal Credit by family type and monthly award band, mean of April to December 2025 - pooling: adjacent bands within a family type, lowest first, until the drawn units rest on minimum_pool_sources distinct household_source_id values; a short last pool joins the one before it + pooling: adjacent bands within a family type, lowest first, until the drawn units rest on minimum_pool_sources distinct household_source_id values; a short last pool joins the one before it. Then, lowest first, a pool that cannot meet DWP's count (its undrawn entitled units' expected claims exceed the count, or the count exceeds them plus the weight of every drawn unit) is held at the nearer of those ends and passes its gap to the other pools, nearest first, the one with more room first at equal distance and the lower on a tie, each taking what its room allows; a gap no pool can take leaves the family type unreachable minimum_pool_sources: 30 drawn_units: entitled, non-reporting units of the population that the engine does not move off their legacy benefits (legacy_benefits_closed) and that report none, since a legacy benefit the engine leaves in place ends once the unit claims UC undrawn_claims: a reporter at 1, a moved unit at the claim probability uc_legacy_closure_take_up's rule gives it (dwp_move_to_uc_facts.json), a unit keeping income-related ESA at 0, any other at its stored flag kept_legacy_award: a unit whose claimant or partner reports income-related ESA (esa_income_reported), and that neither reports Universal Credit nor is moved off its legacy benefits, claims no Universal Credit, since policyengine-uk ends that award once the family claims it weight_mapping: household_to_benunit - residual_rate: (T - F) / D, clipped to [0, 1]; T DWP's calendar-2025 mean count of the pool's bands, D the weight of the pool's drawn units and F the expected claims of its other entitled units, over Great Britain at the stage's household weights; realized by the drawn units claiming in the order of their uniform until their weight is nearest T - F, and applied at that uniform to Northern Ireland's drawn units too + residual_rate: (T - F) / D, clipped to [0, 1]; T DWP's calendar-2025 mean count of the pool's bands after any gaps passed to or from it, D the weight of the pool's drawn units and F the expected claims of its other entitled units, over Great Britain at the stage's household weights; realized by the drawn units claiming in the order of their uniform until their weight is nearest T - F, and applied at that uniform to Northern Ireland's drawn units too solve_scope: great_britain not_drawn: keeps its stored flag, except a unit keeping income-related ESA, which claims none outputs: [] @@ -6197,3 +6200,33 @@ stages: - stocks_and_shares_isa_subscriptions - lifetime_isa_payments notes: 'Imputes ISA subscriptions per adult by type, and the per-person ISA balances, on the final spine (microcosm#1415). Each household''s was_wealth cash and stocks-and-shares ISA totals are split across its adults by the holding pattern of a WAS round-8 donor household with the same number of adults, so person balances sum exactly to the household totals, which are unchanged. Subscribers in 2023-24 are adults aged 18 or over in households holding the type, raked by class (cash only, stocks and shares only, both) to Table 9.7''s income bands, Table 9.8''s age and sex and Table 9.9''s regions and selected by keyed walks, the both class first. Amounts follow Table 9.7''s subscription bands within each income band and class, uniform inside a band and exactly GBP 20,000 at the top; the both class splits each person''s amount by their balance shares, shifted so the class''s stocks-and-shares total is Table 9.4''s 2023-24 stocks-and-shares amount less the stocks-and-shares-only payments. People grow to 2024-25 by Table 9.4''s account growth (an upper bound on people, as from 6 April 2024 a person may pay into several ISAs of one type), and amounts scale to Table 9.4''s 2024-25 amounts per type, holding subscribers already at the GBP 20,000 overall limit and moving combined amounts between GBP 18,000 (Table 9.7''s last band floor below the limit) and the limit on a line up to it, so a factor below one leaves no empty range under the limit (María''s rulings of 29 October 2026): Table 9.7''s cash bands sit above Table 9.4, and growing that excess by Table 9.4''s ratio against the limit pushed the subscribers below it far up. Every Lifetime ISA holder aged 18 to 47 (the ages that can hold one in 2024-25) with room under the overall limit pays in, amounts in (0, GBP 4,000] drawn to Table 9.4''s 2024-25 Lifetime ISA amount. No ISA fact is a calibration target: binding the cells the stage draws to would be circular, so the reviewed fence keeps them measured only.' +- stage: trading_allowance_receipts + survey: The self-employed's own profit on the final spine, and HMRC's policy paper on the Budget 2026 trading allowance raise (calibration) + source: self_employment_income after the SPI income stage; HMRC's published gainers of the raise to GBP 3,000, about 400,000 taxpayers with a lower bill by about GBP 380 on average + grain: person + operations: + - kind: assign_trading_allowance_receipts + output: self_employment_gross_receipts + profit: self_employment_income + draw: trading_allowance_claimant + seed: 0 + claimant_bands: + - upper_inclusive: 4500.0 + rate: 0.64 + - upper_inclusive: 9000.0 + rate: 0.32 + - rate: 0.0 + claimant_expenses: 1000.0 + other_expenses: 3000.0 + calibration: 'HMRC''s policy paper on the Budget 2026 trading allowance raise: about 400,000 taxpayers with a lower bill, by about GBP 380 on average, on the microcosm#1428 national b441bb5a0''s final weights at 2028-29 prices, until HMRC publishes claimant counts (María''s choice of 2026-10-31)' + rule: a person with a positive self_employment_income claims the allowance where their uniform falls below their profit band's rate; a claimant's receipts are their profit plus claimant_expenses, any other trader's their profit plus other_expenses, and a person with no positive profit keeps zero + - kind: record_mass_conservation_receipt + entity: household + reason: 'Self-employed gross receipts stored on the source spine: household weights pass through unchanged and total household mass is conserved.' + declared_factor: 1.0 + gate_coupling: The terminal family gate requires a valid mass-conserving MassChangeRecord carrying exactly this stage-specific reason. + outputs: + - self_employment_gross_receipts + nonnegative_outputs: + - self_employment_gross_receipts + notes: 'The last spine stage (microcosm#1428). policyengine-uk applies the trading allowance against self_employment_gross_receipts, which neither the FRS nor the SPI tape records; without receipts a rise in the allowance relieves only profits up to the new allowance, in full, and misses its main base, the traders who already claim the GBP 1,000 allowance against larger receipts. Under current law a claimant''s receipts are their profit plus GBP 1,000 exactly. Each trader with a positive profit is flagged a claimant at their profit band''s rate, drawn on their own person_id: a claimant''s receipts are their profit plus GBP 1,000, any other trader''s their profit plus GBP 3,000 (expenses at the raised allowance, so the raise does not relieve them; the costing books switchers as behaviour), and a person with no positive profit keeps zero, which the engine reads as unknown. Every trader with a positive profit is treated as filing, as SPI Table 3.10''s counts, which bind the frame''s traders, are of filers, so a profit of GBP 1,000 or less is now taxed where the engine used to relieve it in full. The rates are calibrated to HMRC''s policy paper until HMRC publishes claimant counts. The engine uprates receipts with profit, so a claimant''s GBP 1,000 grows with the mixed income index while the allowance is nominal: the raise relieves GBP 1,932 more in 2027-28, falling to GBP 1,758 by 2031-32, 3.4% to 12.1% below GBP 2,000. The other traders'' stored GBP 3,000 grows the same way, so an allowance above GBP 3,000 times that index relieves them from the stored expense, not from data: allowances above GBP 3,000 are mis-scored until policyengine-uk#2765 lets the stage store the claim status (microcosm#1439; María''s ruling of 2026-11-01).' 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 9d89132b07..30e565ddeb 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 @@ -1,13 +1,13 @@ { "source_fact_feed": "chronicle-uk-53815b2-consumer-facts", "target_period": 2025, - "candidate_count": 1437, - "contract_target_count": 394, - "active_reference_count": 1403, + "candidate_count": 1453, + "contract_target_count": 396, + "active_reference_count": 1412, "status_counts": { - "active": 1403, + "active": 1412, "no_fact_at_or_before_period": 4, - "signed_excluded": 30 + "signed_excluded": 37 }, "geography_pins": { "obr.income_tax": { @@ -162,6 +162,10 @@ "geography_level": "country", "geography_id": "K02000001" }, + "hmrc.spi.employment_income.count_by_self_employment_income_band": { + "geography_level": "country", + "geography_id": "K02000001" + }, "hmrc.spi.dividend_income.amount_by_total_income_band": { "geography_level": "country", "geography_id": "K02000001" @@ -4484,6 +4488,10 @@ "geography_level": "country", "geography_id": "K03000001" }, + "dwp.jsa.amount_income_based": { + "geography_level": "country", + "geography_id": "K03000001" + }, "microcosm.high_value_homes.over_1m_by_region": { "geography_fanout": [ { @@ -5347,7 +5355,7 @@ "from": "2023", "to": "2025", "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "26000000.0" }, { @@ -5355,7 +5363,7 @@ "from": "2023", "to": "2025", "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "339000000.0" }, { @@ -5363,7 +5371,7 @@ "from": "2023", "to": "2025", "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "500000000.0" }, { @@ -5371,7 +5379,7 @@ "from": "2023", "to": "2025", "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "647000000.0" }, { @@ -5379,7 +5387,7 @@ "from": "2023", "to": "2025", "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "780000000.0" }, { @@ -5387,7 +5395,7 @@ "from": "2023", "to": "2025", "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "82000000.0" }, { @@ -5395,7 +5403,7 @@ "from": "2023", "to": "2025", "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "2540000000.0" }, { @@ -5403,15 +5411,79 @@ "from": "2023", "to": "2025", "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "3470000000.0" }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_1_500", + "from": "2023", + "to": "2025", + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "67000.0" + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_1000_2000", + "from": "2023", + "to": "2025", + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "127000.0" + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_2000_3000", + "from": "2023", + "to": "2025", + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "103000.0" + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_3000_4000", + "from": "2023", + "to": "2025", + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "90000.0" + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_4000_5000", + "from": "2023", + "to": "2025", + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "77000.0" + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_500_1000", + "from": "2023", + "to": "2025", + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "64000.0" + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_5000_7500", + "from": "2023", + "to": "2025", + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "148000.0" + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_7500_10000", + "from": "2023", + "to": "2025", + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "113000.0" + }, { "name": "hmrc/dividend_income_income_band_100_000_to_150_000", "from": "2023", "to": "2025", "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "6870000000.0" }, { @@ -5419,7 +5491,7 @@ "from": "2023", "to": "2025", "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "11100000000.0" }, { @@ -5427,7 +5499,7 @@ "from": "2023", "to": "2025", "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "175000000.0" }, { @@ -5435,7 +5507,7 @@ "from": "2023", "to": "2025", "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "855000000.0" }, { @@ -5443,7 +5515,7 @@ "from": "2023", "to": "2025", "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "3450000000.0" }, { @@ -5451,7 +5523,7 @@ "from": "2023", "to": "2025", "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "3330000000.0" }, { @@ -5459,7 +5531,7 @@ "from": "2023", "to": "2025", "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "3700000000.0" }, { @@ -5467,7 +5539,7 @@ "from": "2023", "to": "2025", "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "4700000000.0" }, { @@ -5475,7 +5547,7 @@ "from": "2023", "to": "2025", "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "3430000000.0" }, { @@ -5483,7 +5555,7 @@ "from": "2023", "to": "2025", "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "8400000000.0" }, { @@ -5491,7 +5563,7 @@ "from": "2023", "to": "2025", "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "12500000000.0" }, { @@ -5499,7 +5571,7 @@ "from": "2023", "to": "2025", "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "3820000000.0" }, { @@ -5507,7 +5579,7 @@ "from": "2023", "to": "2025", "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "9440000000.0" }, { @@ -12839,12 +12911,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 29058251.016552746, + "resolved_value": 28899522.63739463, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_5aff5e57f05ddba9ad025b36", "uprating": { "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "26000000.0" } }, @@ -12854,12 +12926,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 378874888.2542839, + "resolved_value": 376805314.3875684, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_fc3c7927013f5264698979d8", "uprating": { "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "339000000.0" } }, @@ -12902,12 +12974,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 558812519.5490913, + "resolved_value": 555760050.7191275, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_6b85f6be706ccfed238bf1f9", "uprating": { "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "500000000.0" } }, @@ -12928,12 +13000,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 723103400.2965242, + "resolved_value": 719153505.630551, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_5852a008bcd3cea2bc99b092", "uprating": { "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "647000000.0" } }, @@ -12954,12 +13026,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 871747530.4965824, + "resolved_value": 866985679.1218389, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_2d34b4d9693e393903c5f638", "uprating": { "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "780000000.0" } }, @@ -12969,12 +13041,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 91645253.20605098, + "resolved_value": 91144648.31793691, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_e493ddc5770b5a2e89c83fcf", "uprating": { "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "82000000.0" } }, @@ -12984,12 +13056,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 2838767599.309384, + "resolved_value": 2823261057.6531677, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_ae77cfe6ff63112b006c6a30", "uprating": { "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "2540000000.0" } }, @@ -13010,17 +13082,219 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 3878158885.6706934, + "resolved_value": 3856974751.9907446, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_91323471e9baa2fc4904040a", "uprating": { "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", - "factor": "1.11762503909818", + "factor": "1.11152010143825", "value_before_uprating": "3470000000.0" } } ] }, + "hmrc.spi.employment_income.count_by_self_employment_income_band": { + "status": "active", + "candidates": [ + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_0_1", + "status": "signed_excluded", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "signed_row": { + "dimension": "self_employment_income_lower_bound", + "value": 0 + }, + "signed_rationale": "SPI 2023-24 Table 3.10's zero band counts people with a self-employment source and no profit after loss relief. The binding bands people on their self-employment income alone, so a band from 0 to 1 would count every employee without self-employment income. It also lies outside the GBP 1 to GBP 10,000 range Mar\u00eda's ruling of 2026-10-29 binds, which her choice of 2026-10-30 extends to Table 3.10's employment-income counts. Signed out of the band fan-out; the eight bands from GBP 1 stay bound." + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_1_500", + "status": "active", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "resolved_period": 2025, + "resolved_value": 72111.7166212534, + "resolved_fact_period": "2023", + "resolved_fact_key": "ledger_aggregate_fact_v2_a8a50ebacc90efdf051f460b", + "uprating": { + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "67000.0" + } + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_1000_2000", + "status": "active", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "resolved_period": 2025, + "resolved_value": 136689.37329700272, + "resolved_fact_period": "2023", + "resolved_fact_key": "ledger_aggregate_fact_v2_e07428dae7ed2be1a4b3d793", + "uprating": { + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "127000.0" + } + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_10000_15000", + "status": "signed_excluded", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "signed_row": { + "dimension": "self_employment_income_lower_bound", + "value": 10000 + }, + "signed_rationale": "SPI 2023-24 Table 3.10's self-employment bands from GBP 10,000 stay with Table 3.6's rows by total income, so the two tables do not pull against each other: Mar\u00eda's ruling of 2026-10-29 binds Table 3.10 from GBP 1 to GBP 10,000, the small-profit end of the Budget's trading allowance measures (Table 6.1 line 15), and her choice of 2026-10-30 adds its employment-income counts over the same bands. Signed out of the band fan-out; the eight bands from GBP 1 stay bound." + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_100000_plus", + "status": "signed_excluded", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "signed_row": { + "dimension": "self_employment_income_lower_bound", + "value": 100000 + }, + "signed_rationale": "SPI 2023-24 Table 3.10's self-employment bands from GBP 10,000 stay with Table 3.6's rows by total income, so the two tables do not pull against each other: Mar\u00eda's ruling of 2026-10-29 binds Table 3.10 from GBP 1 to GBP 10,000, the small-profit end of the Budget's trading allowance measures (Table 6.1 line 15), and her choice of 2026-10-30 adds its employment-income counts over the same bands. Signed out of the band fan-out; the eight bands from GBP 1 stay bound." + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_15000_20000", + "status": "signed_excluded", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "signed_row": { + "dimension": "self_employment_income_lower_bound", + "value": 15000 + }, + "signed_rationale": "SPI 2023-24 Table 3.10's self-employment bands from GBP 10,000 stay with Table 3.6's rows by total income, so the two tables do not pull against each other: Mar\u00eda's ruling of 2026-10-29 binds Table 3.10 from GBP 1 to GBP 10,000, the small-profit end of the Budget's trading allowance measures (Table 6.1 line 15), and her choice of 2026-10-30 adds its employment-income counts over the same bands. Signed out of the band fan-out; the eight bands from GBP 1 stay bound." + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_2000_3000", + "status": "active", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "resolved_period": 2025, + "resolved_value": 110858.310626703, + "resolved_fact_period": "2023", + "resolved_fact_key": "ledger_aggregate_fact_v2_8f608695430804bf74928876", + "uprating": { + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "103000.0" + } + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_20000_30000", + "status": "signed_excluded", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "signed_row": { + "dimension": "self_employment_income_lower_bound", + "value": 20000 + }, + "signed_rationale": "SPI 2023-24 Table 3.10's self-employment bands from GBP 10,000 stay with Table 3.6's rows by total income, so the two tables do not pull against each other: Mar\u00eda's ruling of 2026-10-29 binds Table 3.10 from GBP 1 to GBP 10,000, the small-profit end of the Budget's trading allowance measures (Table 6.1 line 15), and her choice of 2026-10-30 adds its employment-income counts over the same bands. Signed out of the band fan-out; the eight bands from GBP 1 stay bound." + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_3000_4000", + "status": "active", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "resolved_period": 2025, + "resolved_value": 96866.48501362398, + "resolved_fact_period": "2023", + "resolved_fact_key": "ledger_aggregate_fact_v2_0814147e65171246cce164c0", + "uprating": { + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "90000.0" + } + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_30000_50000", + "status": "signed_excluded", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "signed_row": { + "dimension": "self_employment_income_lower_bound", + "value": 30000 + }, + "signed_rationale": "SPI 2023-24 Table 3.10's self-employment bands from GBP 10,000 stay with Table 3.6's rows by total income, so the two tables do not pull against each other: Mar\u00eda's ruling of 2026-10-29 binds Table 3.10 from GBP 1 to GBP 10,000, the small-profit end of the Budget's trading allowance measures (Table 6.1 line 15), and her choice of 2026-10-30 adds its employment-income counts over the same bands. Signed out of the band fan-out; the eight bands from GBP 1 stay bound." + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_4000_5000", + "status": "active", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "resolved_period": 2025, + "resolved_value": 82874.65940054496, + "resolved_fact_period": "2023", + "resolved_fact_key": "ledger_aggregate_fact_v2_5e447c3f14dc230f46520c1e", + "uprating": { + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "77000.0" + } + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_500_1000", + "status": "active", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "resolved_period": 2025, + "resolved_value": 68882.83378746595, + "resolved_fact_period": "2023", + "resolved_fact_key": "ledger_aggregate_fact_v2_1f44d42f7a3ba77a7f872437", + "uprating": { + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "64000.0" + } + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_5000_7500", + "status": "active", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "resolved_period": 2025, + "resolved_value": 159291.553133515, + "resolved_fact_period": "2023", + "resolved_fact_key": "ledger_aggregate_fact_v2_535bdfcf3c4c862eee078139", + "uprating": { + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "148000.0" + } + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_50000_100000", + "status": "signed_excluded", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "signed_row": { + "dimension": "self_employment_income_lower_bound", + "value": 50000 + }, + "signed_rationale": "SPI 2023-24 Table 3.10's self-employment bands from GBP 10,000 stay with Table 3.6's rows by total income, so the two tables do not pull against each other: Mar\u00eda's ruling of 2026-10-29 binds Table 3.10 from GBP 1 to GBP 10,000, the small-profit end of the Budget's trading allowance measures (Table 6.1 line 15), and her choice of 2026-10-30 adds its employment-income counts over the same bands. Signed out of the band fan-out; the eight bands from GBP 1 stay bound." + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_7500_10000", + "status": "active", + "matched_fact_count_overall": 1, + "matched_fact_count_at_or_before_period": 1, + "resolved_period": 2025, + "resolved_value": 121621.25340599455, + "resolved_fact_period": "2023", + "resolved_fact_key": "ledger_aggregate_fact_v2_52b23e53122bfddd68b77ca8", + "uprating": { + "index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "factor": "1.07629427792916", + "value_before_uprating": "113000.0" + } + } + ] + }, "hmrc.spi.dividend_income.amount_by_total_income_band": { "status": "active", "candidates": [ @@ -13030,12 +13304,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 7475572768.250349, + "resolved_value": 7475600207.41509, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_6fd01f132dc6b218c02326b1", "uprating": { "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "6870000000.0" } }, @@ -13045,12 +13319,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 12078436350.448162, + "resolved_value": 12078480684.469795, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_3c0cd54a0f0609d8ebc58a25", "uprating": { "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "11100000000.0" } }, @@ -13060,12 +13334,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 190425798.31787643, + "resolved_value": 190426497.27767697, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_b63a84056f85bed14b8ab8fd", "uprating": { "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "175000000.0" } }, @@ -13075,12 +13349,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 930366043.2101963, + "resolved_value": 930369458.1280789, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_3c4f22fc63944665033b18b3", "uprating": { "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "855000000.0" } }, @@ -13090,12 +13364,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 3754108595.409564, + "resolved_value": 3754122374.9027743, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_ced1a5840ced099b471d4e84", "uprating": { "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "3450000000.0" } }, @@ -13105,12 +13379,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 3623530905.1344485, + "resolved_value": 3623544205.340939, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_8a115e840b38a6603d618bc0", "uprating": { "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "3330000000.0" } }, @@ -13120,12 +13394,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 4026145450.1493874, + "resolved_value": 4026160228.1565986, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_0394e55216df7f3dcab84fb5", "uprating": { "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "3700000000.0" } }, @@ -13135,12 +13409,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 5114292869.108682, + "resolved_value": 5114311641.171896, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_ea93d59adaf66ef73e9dddbf", "uprating": { "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "4700000000.0" } }, @@ -13150,12 +13424,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 3732345647.030378, + "resolved_value": 3732359346.6424685, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_8d09d2287cbdb2e4f4004521", "uprating": { "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "3430000000.0" } }, @@ -13165,12 +13439,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 9140438319.258068, + "resolved_value": 9140471869.328495, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_0a4329a3eb027a530c6f02ec", "uprating": { "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "8400000000.0" } }, @@ -13180,12 +13454,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 13601842736.991173, + "resolved_value": 13601892662.691212, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_c11497ffe45250b909593f1d", "uprating": { "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "12500000000.0" } }, @@ -13195,12 +13469,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 4156723140.424503, + "resolved_value": 4156738397.7184343, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_dafc8ca1cd03e5d461b11d4e", "uprating": { "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "3820000000.0" } }, @@ -13210,12 +13484,12 @@ "matched_fact_count_overall": 1, "matched_fact_count_at_or_before_period": 1, "resolved_period": 2025, - "resolved_value": 10272111634.975735, + "resolved_value": 10272149338.864403, "resolved_fact_period": "2023", "resolved_fact_key": "ledger_aggregate_fact_v2_940e6ce9db10080ed5613faa", "uprating": { "index": "policyengine_uk_parameter:gov.economic_assumptions.indices.obr.per_capita.gdp", - "factor": "1.08814741895929", + "factor": "1.0881514130153", "value_before_uprating": "9440000000.0" } } @@ -31602,6 +31876,21 @@ } ] }, + "dwp.jsa.amount_income_based": { + "status": "active", + "candidates": [ + { + "name": "dwp.jsa.amount_income_based", + "status": "active", + "matched_fact_count_overall": 2, + "matched_fact_count_at_or_before_period": 2, + "resolved_period": 2025, + "resolved_value": 23377178.788788605, + "resolved_fact_period": "2025", + "resolved_fact_key": "ledger_aggregate_fact_v2_6d0a1e9a4006a42d57b637a2" + } + ] + }, "microcosm.high_value_homes.over_1m_by_region": { "status": "active", "candidates": [ @@ -32070,7 +32359,7 @@ { "family": "hmrc_spi", "status": "active_strict_band_pins", - "active_reference_count": 211, + "active_reference_count": 219, "signed_rationale": "SPI income-band targets fan out by strict total-income-band dimension pins, and SPI Table 3.10's by self-employment band, its bands outside GBP 1 to GBP 10,000 signed out row by row (microcosm#1418). The 13 property-income amount rows bind the SPI Table 3.7 net concept unscaled: landlords' profit after allowable expenses and before residential finance costs, which is what policyengine-uk's property_income means. The incumbent's x1.9 scaling (uk-data#311, uk-data#230) set the Property Rental Income Statistics' receipts before expenses against this net amount, so it is retired; the receipts are constructed on property_rental_income by the property_components stage and PRIS stays a diagnostic (microcosm#1106, Mar\u00eda's rulings of 2026-10-05 and 2026-10-08)." }, { diff --git a/packages/microcosm-build/src/microcosm/build/uk/target_reference_signed_exclusions.json b/packages/microcosm-build/src/microcosm/build/uk/target_reference_signed_exclusions.json index 55890b8d7e..624ddc8c4a 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/target_reference_signed_exclusions.json +++ b/packages/microcosm-build/src/microcosm/build/uk/target_reference_signed_exclusions.json @@ -271,6 +271,90 @@ "value": 100000 } }, + { + "target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "reason_id": "zero_band_counts_everyone_without_the_income", + "rationale": "SPI 2023-24 Table 3.10's zero band counts people with a self-employment source and no profit after loss relief. The binding bands people on their self-employment income alone, so a band from 0 to 1 would count every employee without self-employment income. It also lies outside the GBP 1 to GBP 10,000 range María's ruling of 2026-10-29 binds, which her choice of 2026-10-30 extends to Table 3.10's employment-income counts. Signed out of the band fan-out; the eight bands from GBP 1 stay bound.", + "tracking": "microcosm#1418", + "approved_by": "juaristi22", + "approved_on": "2026-10-30", + "row": { + "dimension": "self_employment_income_lower_bound", + "value": 0 + } + }, + { + "target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "reason_id": "bound_by_table_3_6_from_10000", + "rationale": "SPI 2023-24 Table 3.10's self-employment bands from GBP 10,000 stay with Table 3.6's rows by total income, so the two tables do not pull against each other: María's ruling of 2026-10-29 binds Table 3.10 from GBP 1 to GBP 10,000, the small-profit end of the Budget's trading allowance measures (Table 6.1 line 15), and her choice of 2026-10-30 adds its employment-income counts over the same bands. Signed out of the band fan-out; the eight bands from GBP 1 stay bound.", + "tracking": "microcosm#1418", + "approved_by": "juaristi22", + "approved_on": "2026-10-30", + "row": { + "dimension": "self_employment_income_lower_bound", + "value": 10000 + } + }, + { + "target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "reason_id": "bound_by_table_3_6_from_10000", + "rationale": "SPI 2023-24 Table 3.10's self-employment bands from GBP 10,000 stay with Table 3.6's rows by total income, so the two tables do not pull against each other: María's ruling of 2026-10-29 binds Table 3.10 from GBP 1 to GBP 10,000, the small-profit end of the Budget's trading allowance measures (Table 6.1 line 15), and her choice of 2026-10-30 adds its employment-income counts over the same bands. Signed out of the band fan-out; the eight bands from GBP 1 stay bound.", + "tracking": "microcosm#1418", + "approved_by": "juaristi22", + "approved_on": "2026-10-30", + "row": { + "dimension": "self_employment_income_lower_bound", + "value": 15000 + } + }, + { + "target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "reason_id": "bound_by_table_3_6_from_10000", + "rationale": "SPI 2023-24 Table 3.10's self-employment bands from GBP 10,000 stay with Table 3.6's rows by total income, so the two tables do not pull against each other: María's ruling of 2026-10-29 binds Table 3.10 from GBP 1 to GBP 10,000, the small-profit end of the Budget's trading allowance measures (Table 6.1 line 15), and her choice of 2026-10-30 adds its employment-income counts over the same bands. Signed out of the band fan-out; the eight bands from GBP 1 stay bound.", + "tracking": "microcosm#1418", + "approved_by": "juaristi22", + "approved_on": "2026-10-30", + "row": { + "dimension": "self_employment_income_lower_bound", + "value": 20000 + } + }, + { + "target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "reason_id": "bound_by_table_3_6_from_10000", + "rationale": "SPI 2023-24 Table 3.10's self-employment bands from GBP 10,000 stay with Table 3.6's rows by total income, so the two tables do not pull against each other: María's ruling of 2026-10-29 binds Table 3.10 from GBP 1 to GBP 10,000, the small-profit end of the Budget's trading allowance measures (Table 6.1 line 15), and her choice of 2026-10-30 adds its employment-income counts over the same bands. Signed out of the band fan-out; the eight bands from GBP 1 stay bound.", + "tracking": "microcosm#1418", + "approved_by": "juaristi22", + "approved_on": "2026-10-30", + "row": { + "dimension": "self_employment_income_lower_bound", + "value": 30000 + } + }, + { + "target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "reason_id": "bound_by_table_3_6_from_10000", + "rationale": "SPI 2023-24 Table 3.10's self-employment bands from GBP 10,000 stay with Table 3.6's rows by total income, so the two tables do not pull against each other: María's ruling of 2026-10-29 binds Table 3.10 from GBP 1 to GBP 10,000, the small-profit end of the Budget's trading allowance measures (Table 6.1 line 15), and her choice of 2026-10-30 adds its employment-income counts over the same bands. Signed out of the band fan-out; the eight bands from GBP 1 stay bound.", + "tracking": "microcosm#1418", + "approved_by": "juaristi22", + "approved_on": "2026-10-30", + "row": { + "dimension": "self_employment_income_lower_bound", + "value": 50000 + } + }, + { + "target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "reason_id": "bound_by_table_3_6_from_10000", + "rationale": "SPI 2023-24 Table 3.10's self-employment bands from GBP 10,000 stay with Table 3.6's rows by total income, so the two tables do not pull against each other: María's ruling of 2026-10-29 binds Table 3.10 from GBP 1 to GBP 10,000, the small-profit end of the Budget's trading allowance measures (Table 6.1 line 15), and her choice of 2026-10-30 adds its employment-income counts over the same bands. Signed out of the band fan-out; the eight bands from GBP 1 stay bound.", + "tracking": "microcosm#1418", + "approved_by": "juaristi22", + "approved_on": "2026-10-30", + "row": { + "dimension": "self_employment_income_lower_bound", + "value": 100000 + } + }, { "target_id": "hmrc.spi.self_employment_income.amount_by_self_employment_income_band", "reason_id": "bound_by_table_3_6_from_10000", 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 61d31b9adc..224c13a3a3 100644 --- a/packages/microcosm-build/src/microcosm/build/uk/target_references.json +++ b/packages/microcosm-build/src/microcosm/build/uk/target_references.json @@ -310,6 +310,7 @@ "dwp.hb.households_pension_age_social_rented": "dwp.legacy_benefits", "dwp.hb.households_private_rented": "dwp.housing_benefit", "dwp.hb.households_social_rented": "dwp.housing_benefit", + "dwp.jsa.amount_income_based": "dwp.legacy_benefits", "dwp.jsa_claimants": "dwp.legacy_benefits", "dwp.pension_credit.benefit_units": "dwp.pension_credit", "dwp.pension_credit.benefit_units_65_69": "dwp.pension_credit", @@ -426,6 +427,7 @@ "hmrc.spi.dividend_income.amount_by_total_income_band": "hmrc.survey_of_personal_incomes", "hmrc.spi.dividend_income.count_by_total_income_band": "hmrc.survey_of_personal_incomes", "hmrc.spi.employment_income.amount_by_total_income_band": "hmrc.survey_of_personal_incomes", + "hmrc.spi.employment_income.count_by_self_employment_income_band": "hmrc.survey_of_personal_incomes", "hmrc.spi.employment_income.count_by_total_income_band": "hmrc.survey_of_personal_incomes", "hmrc.spi.other_investment_income.amount_by_total_income_band": "hmrc.survey_of_personal_incomes", "hmrc.spi.private_pension_income.amount_by_total_income_band": "hmrc.survey_of_personal_incomes", @@ -695,6 +697,7 @@ "dwp.hb.households_pension_age_social_rented": "Housing Benefit benefit units, pension age, social rented sector", "dwp.hb.households_private_rented": "Housing Benefit claimants, private rented", "dwp.hb.households_social_rented": "Housing Benefit claimants, social rented", + "dwp.jsa.amount_income_based": "Jobseeker's Allowance spending, income-based", "dwp.jsa_claimants": "Jobseeker\u2019s Allowance claimants", "dwp.pension_credit.benefit_units": "Pension Credit benefit units, Great Britain", "dwp.pension_credit.benefit_units_65_69": "Pension Credit benefit units, claimant aged 65 to 69", @@ -811,6 +814,7 @@ "hmrc.spi.dividend_income.amount_by_total_income_band": "Amount by total income band", "hmrc.spi.dividend_income.count_by_total_income_band": "Count by total income band", "hmrc.spi.employment_income.amount_by_total_income_band": "Amount by total income band", + "hmrc.spi.employment_income.count_by_self_employment_income_band": "Count with employment income by self-employment income band", "hmrc.spi.employment_income.count_by_total_income_band": "Count by total income band", "hmrc.spi.other_investment_income.amount_by_total_income_band": "Amount by total income band", "hmrc.spi.private_pension_income.amount_by_total_income_band": "Amount by total income band", @@ -3311,6 +3315,206 @@ "uprating_from_period": "2023", "uprating_to_period": 2025 }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_1_500", + "ledger_selector": { + "source_name": "hmrc", + "source_concept": "hmrc.spi_table_3_10_employment_income_count", + "groupby_dimension": "hmrc.self_employment_income_band", + "entity_name": "person", + "geography_level": "country", + "geography_id": "K02000001", + "dimension_values": { + "self_employment_income_lower_bound": 1 + } + }, + "entity": "person", + "measure": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_1_500", + "family": "hmrc_spi", + "period": 2025, + "metadata": { + "contract_target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "measure_kind": "prepared_column" + }, + "uprating_index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "uprating_from_period": "2023", + "uprating_to_period": 2025 + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_1000_2000", + "ledger_selector": { + "source_name": "hmrc", + "source_concept": "hmrc.spi_table_3_10_employment_income_count", + "groupby_dimension": "hmrc.self_employment_income_band", + "entity_name": "person", + "geography_level": "country", + "geography_id": "K02000001", + "dimension_values": { + "self_employment_income_lower_bound": 1000 + } + }, + "entity": "person", + "measure": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_1000_2000", + "family": "hmrc_spi", + "period": 2025, + "metadata": { + "contract_target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "measure_kind": "prepared_column" + }, + "uprating_index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "uprating_from_period": "2023", + "uprating_to_period": 2025 + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_2000_3000", + "ledger_selector": { + "source_name": "hmrc", + "source_concept": "hmrc.spi_table_3_10_employment_income_count", + "groupby_dimension": "hmrc.self_employment_income_band", + "entity_name": "person", + "geography_level": "country", + "geography_id": "K02000001", + "dimension_values": { + "self_employment_income_lower_bound": 2000 + } + }, + "entity": "person", + "measure": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_2000_3000", + "family": "hmrc_spi", + "period": 2025, + "metadata": { + "contract_target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "measure_kind": "prepared_column" + }, + "uprating_index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "uprating_from_period": "2023", + "uprating_to_period": 2025 + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_3000_4000", + "ledger_selector": { + "source_name": "hmrc", + "source_concept": "hmrc.spi_table_3_10_employment_income_count", + "groupby_dimension": "hmrc.self_employment_income_band", + "entity_name": "person", + "geography_level": "country", + "geography_id": "K02000001", + "dimension_values": { + "self_employment_income_lower_bound": 3000 + } + }, + "entity": "person", + "measure": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_3000_4000", + "family": "hmrc_spi", + "period": 2025, + "metadata": { + "contract_target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "measure_kind": "prepared_column" + }, + "uprating_index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "uprating_from_period": "2023", + "uprating_to_period": 2025 + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_4000_5000", + "ledger_selector": { + "source_name": "hmrc", + "source_concept": "hmrc.spi_table_3_10_employment_income_count", + "groupby_dimension": "hmrc.self_employment_income_band", + "entity_name": "person", + "geography_level": "country", + "geography_id": "K02000001", + "dimension_values": { + "self_employment_income_lower_bound": 4000 + } + }, + "entity": "person", + "measure": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_4000_5000", + "family": "hmrc_spi", + "period": 2025, + "metadata": { + "contract_target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "measure_kind": "prepared_column" + }, + "uprating_index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "uprating_from_period": "2023", + "uprating_to_period": 2025 + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_500_1000", + "ledger_selector": { + "source_name": "hmrc", + "source_concept": "hmrc.spi_table_3_10_employment_income_count", + "groupby_dimension": "hmrc.self_employment_income_band", + "entity_name": "person", + "geography_level": "country", + "geography_id": "K02000001", + "dimension_values": { + "self_employment_income_lower_bound": 500 + } + }, + "entity": "person", + "measure": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_500_1000", + "family": "hmrc_spi", + "period": 2025, + "metadata": { + "contract_target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "measure_kind": "prepared_column" + }, + "uprating_index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "uprating_from_period": "2023", + "uprating_to_period": 2025 + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_5000_7500", + "ledger_selector": { + "source_name": "hmrc", + "source_concept": "hmrc.spi_table_3_10_employment_income_count", + "groupby_dimension": "hmrc.self_employment_income_band", + "entity_name": "person", + "geography_level": "country", + "geography_id": "K02000001", + "dimension_values": { + "self_employment_income_lower_bound": 5000 + } + }, + "entity": "person", + "measure": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_5000_7500", + "family": "hmrc_spi", + "period": 2025, + "metadata": { + "contract_target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "measure_kind": "prepared_column" + }, + "uprating_index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "uprating_from_period": "2023", + "uprating_to_period": 2025 + }, + { + "name": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_7500_10000", + "ledger_selector": { + "source_name": "hmrc", + "source_concept": "hmrc.spi_table_3_10_employment_income_count", + "groupby_dimension": "hmrc.self_employment_income_band", + "entity_name": "person", + "geography_level": "country", + "geography_id": "K02000001", + "dimension_values": { + "self_employment_income_lower_bound": 7500 + } + }, + "entity": "person", + "measure": "hmrc.spi.employment_income.count_by_self_employment_income_band.band_7500_10000", + "family": "hmrc_spi", + "period": 2025, + "metadata": { + "contract_target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "measure_kind": "prepared_column" + }, + "uprating_index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "uprating_from_period": "2023", + "uprating_to_period": 2025 + }, { "name": "hmrc/dividend_income_income_band_100_000_to_150_000", "ledger_selector": { @@ -48636,6 +48840,33 @@ "assertion_policy": "allow_source_projection", "value_operation": "calendar_year_window" }, + { + "name": "dwp.jsa.amount_income_based", + "ledger_selector": { + "source_name": "dwp", + "source_concept": "dwp.benefit_expenditure_amount", + "entity_name": "government", + "dimension_values": { + "benefit_forecast_line": "unemployment_benefits__jobseekers_allowance__income_based" + }, + "source_measure_id_by_opening_year": { + "2024": "expenditure_2024", + "2025": "expenditure_2025" + }, + "geography_level": "country", + "geography_id": "K03000001" + }, + "entity": "benunit", + "measure": "dwp/jsa/amount_income_based", + "family": "dwp_benefit_expenditure", + "period": 2025, + "metadata": { + "contract_target_id": "dwp.jsa.amount_income_based", + "measure_kind": "prepared_column" + }, + "assertion_policy": "allow_source_projection", + "value_operation": "calendar_year_window" + }, { "name": "microcosm.high_value_homes.over_1m_by_region@E12000001", "ledger_selector": { 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 c66fb0d282..143b16c274 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 @@ -836,6 +836,7 @@ "dwp.hb.households_pension_age_social_rented": "Post-freeze fact family (DWP Stat-Xplore Housing Benefit, pension age), no uk-data metric (microcosm#1069 c10).", "dwp.hb.households_pension_age_private_rented": "Post-freeze fact family (DWP Stat-Xplore Housing Benefit, pension age), no uk-data metric (microcosm#1069 c10).", "dwp.hb.amount_pension_age": "Post-freeze fact family (DWP benefit expenditure and caseload tables, pension-age Housing Benefit spending), no uk-data metric (microcosm#1095).", + "dwp.jsa.amount_income_based": "Post-freeze fact family (DWP benefit expenditure and caseload tables, income-based Jobseeker's Allowance spending), no uk-data metric (microcosm#1428).", "ons.households.english_regions": "Post-freeze fact family (each nation's official household estimate: LFS 2025 for England's regions, NRS 2025, Welsh Government rolled to 2025, Census 2021 rolled by LPS stock for Northern Ireland), no uk-data metric (microcosm#1123, nations win).", "nrs.households.scotland": "Post-freeze fact family (each nation's official household estimate: LFS 2025 for England's regions, NRS 2025, Welsh Government rolled to 2025, Census 2021 rolled by LPS stock for Northern Ireland), no uk-data metric (microcosm#1123, nations win).", "welshgov.households.wales": "Post-freeze fact family (each nation's official household estimate: LFS 2025 for England's regions, NRS 2025, Welsh Government rolled to 2025, Census 2021 rolled by LPS stock for Northern Ireland), no uk-data metric (microcosm#1123, nations win).", @@ -895,7 +896,8 @@ "hmrc.itl.savings_tax_at_additional_rate": "Post-freeze fact family (HMRC Income Tax liabilities statistics Table 2.6, July 2026, in Chronicle: Income Tax on savings income at each rate, all payers, the calendar-2025 window of the 2024-25 and 2025-26 projections), no uk-data metric (microcosm#1418).", "hmrc.spi.other_investment_income.amount_by_total_income_band": "New declaration backed by SPI 2023-24 Table 3.7 other income in Chronicle (spi_income_bands_2023_24); no uk-data metric holds other investment income by band (microcosm#1418).", "hmrc.spi.self_employment_income.count_by_self_employment_income_band": "New declaration backed by SPI 2023-24 Table 3.10 in Chronicle (spi_income_bands_2023_24, PolicyEngine/chronicle#394); no uk-data metric holds self-employment income by self-employment band (microcosm#1418).", - "hmrc.spi.self_employment_income.amount_by_self_employment_income_band": "New declaration backed by SPI 2023-24 Table 3.10 in Chronicle (spi_income_bands_2023_24, PolicyEngine/chronicle#394); no uk-data metric holds self-employment income by self-employment band (microcosm#1418)." + "hmrc.spi.self_employment_income.amount_by_self_employment_income_band": "New declaration backed by SPI 2023-24 Table 3.10 in Chronicle (spi_income_bands_2023_24, PolicyEngine/chronicle#394); no uk-data metric holds self-employment income by self-employment band (microcosm#1418).", + "hmrc.spi.employment_income.count_by_self_employment_income_band": "New declaration backed by SPI 2023-24 Table 3.10 in Chronicle (spi_income_bands_2023_24, PolicyEngine/chronicle#394); no uk-data metric holds employment income by self-employment band (microcosm#1418)." }, "suppressed_ancestors": { "hmrc/salary_sacrifice_it_relief_basic_rate": { @@ -971,6 +973,7 @@ "hmrc.spi.self_employment_income.count_by_total_income_band", "hmrc.spi.self_employment_income.count_by_self_employment_income_band", "hmrc.spi.self_employment_income.amount_by_self_employment_income_band", + "hmrc.spi.employment_income.count_by_self_employment_income_band", "hmrc.spi.dividend_income.amount_by_total_income_band", "hmrc.spi.dividend_income.count_by_total_income_band", "hmrc.spi.property_income.amount_by_total_income_band", @@ -1318,6 +1321,7 @@ "dwp.hb.households_pension_age_social_rented", "dwp.hb.households_pension_age_private_rented", "dwp.hb.amount_pension_age", + "dwp.jsa.amount_income_based", "microcosm.high_value_homes.over_1m_by_region", "microcosm.high_value_homes.over_1_5m_by_region", "microcosm.high_value_homes.over_2m_by_region", @@ -3848,6 +3852,54 @@ "uprating_index": "hmrc.itl_2026.taxpayer_count_growth_all_bands_times_obr_per_capita_mixed_income", "selector_note": "Uprated from the SPI 2023-24 fact to the 2025 calibration period as recipients times the amount per recipient: the count rows' index (HMRC's projected growth of all taxpayers over all income ranges, Income Tax liabilities statistics Table 2.5) times gov.economic_assumptions.indices.obr.per_capita.mixed_income on the pinned engine, the index policyengine-uk grows self_employment_income by. Each band's mean therefore moves as the engine moves incomes; growing the counts and amounts on unrelated indices would have made calibration add people to each band and tilt them toward its bottom edge (the independent review of microcosm#1420, finding 2). The calibration binds at calendar 2025 under María's ruling of 2026-09-22 (PolicyEngine/chronicle#280 lane)." }, + { + "target_id": "hmrc.spi.employment_income.count_by_self_employment_income_band", + "family": "hmrc_spi", + "geography_levels": [ + "country" + ], + "measurement": { + "entity": "person", + "map_to": "household", + "concept": "uk.person.count", + "groupby_dimension": "hmrc.self_employment_income_band" + }, + "bindings": { + "policyengine": { + "metric_name": "hmrc/employment_income_count_self_employment_income_band", + "value_variable": "person_count", + "from_entity": "person", + "map_to": "household", + "groupby_variable": "self_employment_income_after_loss_relief_annual", + "band_filter_dimension": "self_employment_income", + "band_upper_bound": 10000, + "band_upper_bound_inclusive": false, + "filters": [ + { + "variable": "employment_income_annual", + "operator": "!=", + "value": 0 + } + ], + "notes": "SPI 2023-24 Table 3.10: the individuals with a self-employment source, taxpayer or not, who also have employment income, by range of self-employment income. Bound for the eight bands from GBP 1 to GBP 10,000 beside the self-employment counts (María's rulings of 2026-10-29 and 2026-10-30, microcosm#1418): the counts alone let the solve meet each band with traders who have no pay, where more than half of Table 3.10's traders below GBP 3,000 have employment income too, and the trading allowance measures (Table 6.1 line 15) reach the ones who pay Income Tax. The target fans out over every published band and target_reference_signed_exclusions.json signs out the others. Banded by the person's own self-employment income after loss relief, half-open, with the top bound band closed at GBP 10,000 (band_upper_bound). Employment income is the year's pay, employment_income_annual, the variable Table 3.6's employment rows read." + }, + "axiom": { + "metric_name": "hmrc/employment_income_count_self_employment_income_band", + "status": "pending", + "value_rule": "uk.person.count" + } + }, + "ledger_selector": { + "source_name": "hmrc", + "source_concept": "hmrc.spi_table_3_10_employment_income_count", + "groupby_dimension": "hmrc.self_employment_income_band", + "entity_name": "person" + }, + "category_id": "hmrc.survey_of_personal_incomes", + "label": "Count with employment income by self-employment income band", + "uprating_index": "hmrc.itl_2026.taxpayer_count_growth_all_bands", + "selector_note": "Uprated from the SPI 2023-24 fact to the 2025 calibration period by HMRC's projected growth of all taxpayers over all income ranges (Income Tax liabilities statistics Table 2.5), as the self-employment counts by self-employment band are. Table 3.10's employment income is income assessed under the Income Tax (Earnings and Pensions) Act 2003 and other miscellaneous income (its note 4), wider than Table 3.6's: the binding reads employment_income_annual, as Table 3.6's employment rows do, so it leaves out miscellaneous income and Incapacity Benefit, contribution-based Employment and Support Allowance and Jobseeker's Allowance. Taxable benefits in kind count on SPI rows, whose employment_income holds the tape's pay, benefits and termination pay (PAY + EPB + TAXTERM), and not on FRS rows, whose pay is the cash pay reported (the #1428 review, finding 13). The calibration binds at calendar 2025 under María's ruling of 2026-09-22 (PolicyEngine/chronicle#280 lane)." + }, { "target_id": "hmrc.spi.dividend_income.amount_by_total_income_band", "family": "hmrc_spi", @@ -14820,7 +14872,7 @@ "value_expression": "savings_interest_income + tax_free_savings_income + other_investment_income", "from_entity": "person", "map_to": "household", - "notes": "uk-data holds the last actual flat for later years - a populace-side declaration (uk-data targets/sources/ons_savings.py:39-44 at 12a1e028afeef08d8b2d74ee03fd9de3a78b2dd3). The row measures cash interest in and outside tax-free accounts. From policyengine-uk 2.162.2 savings_interest_income is the interest outside them, which the frame stores so under the additive ISA income contract, with ISA interest apart in individual_savings_account_interest_income; the ISA part, tax_free_savings_income, adds it back (microcosm#1095, microcosm#1360). D.41 also counts interest on gilts, National Savings bonds and other securities, which the frame holds in other_investment_income: the SPI tape's other investment income on SPI rows and, from microcosm#1418, the FRS NS&I and gilt accounts on FRS rows. The engine taxes it as savings income beside savings_interest_income." + "notes": "uk-data holds the last actual flat for later years - a populace-side declaration (uk-data targets/sources/ons_savings.py:39-44 at 12a1e028afeef08d8b2d74ee03fd9de3a78b2dd3). The row measures cash interest in and outside tax-free accounts. From policyengine-uk 2.162.2 savings_interest_income is the interest outside them, which the frame stores so under the additive ISA income contract, with ISA interest apart in individual_savings_account_interest_income; the ISA part, tax_free_savings_income, adds it back (microcosm#1095, microcosm#1360). D.41 also counts interest on gilts, National Savings bonds and other securities, which the frame holds in other_investment_income: the SPI tape's other investment income on SPI rows and, from microcosm#1418, the FRS gilt accounts on FRS rows; FRS NS&I accounts are interest in savings_interest_income (microcosm#1428). The engine taxes it as savings income beside savings_interest_income." }, "axiom": { "metric_name": "ons/savings_interest_income", @@ -22011,12 +22063,12 @@ "bindings": { "policyengine": { "metric_name": "hmrc/other_investment_income_income_band", - "value_variable": "other_investment_income", + "value_variable": "other_investment_income_spi_concept", "from_entity": "person", "map_to": "household", "groupby_variable": "total_income_after_loss_relief_annual", "band_filter_dimension": "total_income", - "notes": "Other investment income of taxpayers by total-income band: SPI Table 3.7's 'Other income' [Note 6], the part of total investment income outside property, bank and building society interest and dividends (SPI's OTHERINV, which the SPI donors carry into other_investment_income). From microcosm#1418 the frame also holds the FRS NS&I and gilt accounts there, and the engine taxes the column as savings income beside savings_interest_income. Banded by person-level total income; band edges come from the fact dimension. No row held the column before, so the ITL Table 2.6 savings tax rows were met mostly through it: on PR A's national (microcosm#1419) it carried about GBP 9.5bn in 2024, where Table 3.7 publishes GBP 5.85bn for 2023-24 (María's ruling of 2026-10-29, microcosm#1418).", + "notes": "Other investment income of taxpayers by total-income band: SPI Table 3.7's 'Other income' [Note 6], the part of total investment income outside property, bank and building society interest and dividends (SPI's OTHERINV, which the SPI donors carry into other_investment_income). On FRS rows the column holds gilt interest, which the engine taxes as savings income beside savings_interest_income, and the measure (other_investment_income_spi_concept) adds the purchased-annuity and trust payments that FRS rows keep in private_pension_income, where the engine's means tests, household income and tax read them; the frame stores their part as annuity_and_trust_income (microcosm#1428). Banded by person-level total income; band edges come from the fact dimension. No row held the column before, so the ITL Table 2.6 savings tax rows were met mostly through it: on PR A's national (microcosm#1419) it carried about GBP 9.5bn in 2024, where Table 3.7 publishes GBP 5.85bn for 2023-24 (María's ruling of 2026-10-29, microcosm#1418).", "filters": [ { "variable": "income_tax_before_winter_fuel_payment_charge_annual", @@ -30186,6 +30238,79 @@ "label": "Housing Benefit spending, pension age", "value_operation": "calendar_year_window" }, + { + "target_id": "dwp.jsa.amount_income_based", + "family": "dwp_benefit_expenditure", + "geography_levels": [ + "country" + ], + "measurement": { + "entity": "benunit", + "concept": "uk.benefits.jsa_income.amount", + "filters": [ + { + "concept": "uk.geography.country", + "operator": "in", + "value": [ + "england", + "scotland", + "wales" + ] + } + ] + }, + "bindings": { + "policyengine": { + "metric_name": "dwp/jsa/amount_income_based", + "value_variable": "jsa_income", + "from_entity": "benunit", + "household_conditions": [ + { + "variable": "region", + "entity": "household", + "reduce": "any", + "operator": "in", + "value": [ + "NORTH_EAST", + "NORTH_WEST", + "YORKSHIRE", + "EAST_MIDLANDS", + "WEST_MIDLANDS", + "EAST_OF_ENGLAND", + "LONDON", + "SOUTH_EAST", + "SOUTH_WEST", + "WALES", + "SCOTLAND" + ], + "map_to": "benunit" + } + ], + "notes": "DWP benefit expenditure and caseload tables, Spring Forecast 2026: the Unemployment_benefits worksheet line 'Jobseeker's Allowance, income-based', nominal GBP, which DWP publishes for Great Britain plus residents overseas (Notes tab), so the model column sums Great Britain households only. Bound at the calendar-2025 window of the fiscal years (three twelfths of the FY2024-25 outturn, nine twelfths of the FY2025-26 forecast; calendar_year_window), as the pension-age Housing Benefit row is. Income-based JSA closes with the move to Universal Credit: GBP 144.7m in FY2023-24, GBP 91.0m in FY2024-25 and under GBP 1m forecast from FY2025-26. Without the split, the calibration met OBR's total JSA (obr.jobseekers_allowance) by scaling income-based reporters with contributory claimants, well above the window's level (microcosm#1428, María's ruling of 2026-10-31). The value is the engine's jsa_income, income-based JSA paid on the reported award." + }, + "axiom": { + "metric_name": "dwp/jsa/amount_income_based", + "status": "pending", + "value_rule": "uk.benefits.jsa_income.amount" + } + }, + "assertion_policy": "allow_source_projection", + "ledger_selector": { + "source_name": "dwp", + "source_concept": "dwp.benefit_expenditure_amount", + "entity_name": "government", + "dimension_values": { + "benefit_forecast_line": "unemployment_benefits__jobseekers_allowance__income_based" + }, + "source_measure_id_by_opening_year": { + "2024": "expenditure_2024", + "2025": "expenditure_2025" + } + }, + "category_id": "dwp.legacy_benefits", + "label": "Jobseeker's Allowance spending, income-based", + "value_operation": "calendar_year_window" + }, { "target_id": "microcosm.high_value_homes.over_1m_by_region", "family": "high_value_homes", 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 67333a5c63..8fe79cb322 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 @@ -220,6 +220,23 @@ "owned_company_carries_on_property_business", "owned_company_income_share", ) + +#: FRS PENSION.PENTYPE codes of an annuity not bought with pension funds (4) +#: and a trust or covenant (5), the ADULT ANYPEN4 and ANYPEN5 sources. Their +#: payments stay in private_pension_income, where policyengine-uk's means +#: tests, household income and tax read them: trust and covenant payments +#: are generally non-savings income (ITA 2007 s. 18), and the FRS records the +#: whole annuity payment, of which only the income element is savings income +#: (ITTOIA 2005 s. 717). SPI Table 3.7 counts both as other income (note 6), +#: so the part they make of private_pension_income is stored apart, in +#: ANNUITY_AND_TRUST_INCOME_COLUMN, a calibration-only descriptor that the +#: Table 3.7 other-income measure adds (microcosm#1428 review, finding 1). +FRS_ANNUITY_AND_TRUST_PENSION_TYPES = (4, 5) +#: The descriptor: each person's annual annuity and trust payments, already +#: inside private_pension_income. No engine input reads it. +ANNUITY_AND_TRUST_INCOME_COLUMN = "annuity_and_trust_income" + + OUTPUT_COLUMNS = ( "person_id", "person_benunit_id", @@ -248,6 +265,7 @@ "loss_relief", "ni_class_4_losses_brought_forward", "private_pension_income", + ANNUITY_AND_TRUST_INCOME_COLUMN, "individual_savings_account_interest_income", "savings_interest_income", "dividend_income", @@ -612,7 +630,9 @@ def _assemble_frame( # tape's into both inputs (microcosm#1095). pe_person["loss_relief"] = 0.0 pe_person["ni_class_4_losses_brought_forward"] = 0.0 - _add_private_pension(pe_person, person, frs["pension"]) + pe_person[ANNUITY_AND_TRUST_INCOME_COLUMN] = _add_private_pension( + pe_person, person, frs["pension"] + ) _add_accounts(pe_person, person, frs["accounts"]) owner_managers = frs_owner_manager_inputs(person, frs["job"]) for column in OWNER_MANAGER_COLUMNS: @@ -713,30 +733,43 @@ def _assemble_frame( def _add_private_pension( pe_person: pd.DataFrame, person: pd.DataFrame, pension: pd.DataFrame -) -> None: - pension_payment = _sum_to_entity( - _number(pension, "penpay") * (_number(pension, "penpay") > 0), - pension.get("person_id", pd.Series(dtype="float64")), - person["person_id"], - ) - pension_tax_paid = _sum_to_entity( - _number(pension, "ptamt") - * ((_number(pension, "ptinc") == 2) & (_number(pension, "ptamt") > 0)), - pension.get("person_id", pd.Series(dtype="float64")), - person["person_id"], - ) - pension_deductions_removed = _sum_to_entity( - _number(pension, "poamt") +) -> pd.Series: + """Write private pension income; return its annuity and trust part. + + Each row's gross weekly amount is the payment, any tax paid at source and + any deductions taken out. Every row is private pension income; the rows + of FRS_ANNUITY_AND_TRUST_PENSION_TYPES are also returned, annual, by + person, as the descriptor of that part. + """ + + penpay = _number(pension, "penpay") + ptamt = _number(pension, "ptamt") + poamt = _number(pension, "poamt") + gross = ( + penpay * (penpay > 0) + + ptamt * ((_number(pension, "ptinc") == 2) & (ptamt > 0)) + + poamt * ( ((_number(pension, "poinc") == 2) | (_number(pension, "penoth") == 1)) - & (_number(pension, "poamt") > 0) - ), - pension.get("person_id", pd.Series(dtype="float64")), - person["person_id"], + & (poamt > 0) + ) + ) + if len(pension) and "pentype" not in pension.columns: + raise ValueError( + "FRS PENSION tab needs PENTYPE to tell annuity and trust payments " + "from pensions." + ) + annuity_or_trust = _number(pension, "pentype").isin( + FRS_ANNUITY_AND_TRUST_PENSION_TYPES ) + person_ids = pension.get("person_id", pd.Series(dtype="float64")) pe_person["private_pension_income"] = ( - pension_payment + pension_tax_paid + pension_deductions_removed - ) * WEEKS_IN_YEAR + _sum_to_entity(gross, person_ids, person["person_id"]) * WEEKS_IN_YEAR + ) + return ( + _sum_to_entity(gross * annuity_or_trust, person_ids, person["person_id"]) + * WEEKS_IN_YEAR + ) #: FRS ACCOUNTS.ACCOUNT codes (FRS 2024-25 variable listing, SN 9563) by the @@ -747,25 +780,29 @@ def _add_private_pension( #: ISA interest under the producer's additive ISA income contract #: (microcosm#1360); policyengine-uk's tax_free_savings_income adds it. ISA_INTEREST_COLUMN = "individual_savings_account_interest_income" -#: Deposit interest, savings_interest_income: current (1), NS&I investment -#: (3), savings and investment (5), fixed-rate, guaranteed income and -#: guaranteed growth bond (25; no interest recorded on FRS 2024-25), basic -#: (27) and credit union (28) accounts. -FRS_DEPOSIT_INTEREST_ACCOUNTS = (1, 3, 5, 25, 27, 28) +#: Deposit interest, savings_interest_income: current (1), NS&I Direct Saver +#: (2), NS&I investment (3), savings and investment (5), National Savings +#: capital (10), Pensioners Guaranteed (13), income (16) and deposit (17) +#: bonds, First Option (18), fixed-rate, guaranteed income and guaranteed +#: growth (25) and guaranteed equity (26) bonds, basic (27) and credit union +#: (28) accounts. SPI has counted all interest paid gross or net, NS&I's +#: taxable products included, as interest from banks and building societies +#: since 2016-17 (Table 3.7 note 4), so the NS&I products sit here, not in +#: other income (microcosm#1428; PR A routed them to other income). On FRS +#: 2024-25 codes 16, 25 and 26 record no interest, and 10, 13, 17 and 18 do +#: not occur. +FRS_DEPOSIT_INTEREST_ACCOUNTS = (1, 2, 3, 5, 10, 13, 16, 17, 18, 25, 26, 27, 28) #: Other interest, other_investment_income, which policyengine-uk taxes as #: savings income beside deposit interest (taxable_savings_interest_income): -#: NS&I Direct Saver (2), gilts (6, booked as dividends before), National -#: Savings capital (10), income (16) and deposit (17) bonds, Pensioners -#: Guaranteed (13), First Option (18) and guaranteed equity (26) bonds. The -#: tax-free products stay out: National Savings certificates (11, 12), SAYE -#: (14), Premium Bonds (15), the Yearly Plan (19) and friendly society -#: investments (31). On FRS 2024-25 only the NS&I Direct Saver and gilts carry -#: interest in this group: codes 16 and 26 record none, and 10, 13, 17 and 18 -#: do not occur. Of the codes no list maps, only a share club (24) records -#: interest on FRS 2024-25: the club's returns are on shares, so they are out -#: of scope as interest; profit sharing (22), company share option plans (23), -#: an endowment policy not linked (29) and informal assets (32) record none. -FRS_OTHER_INTEREST_ACCOUNTS = (2, 6, 10, 13, 16, 17, 18, 26) +#: gilts (6, booked as dividends before microcosm#1418), the interest on +#: securities SPI counts as other income (Table 3.7 note 6). The tax-free +#: products stay out: National Savings certificates (11, 12), SAYE (14), +#: Premium Bonds (15), the Yearly Plan (19) and friendly society investments +#: (31). Of the codes no list maps, only a share club (24) records interest on +#: FRS 2024-25: the club's returns are on shares, so they are out of scope as +#: interest; profit sharing (22), company share option plans (23), an +#: endowment policy not linked (29) and informal assets (32) record none. +FRS_OTHER_INTEREST_ACCOUNTS = (6,) #: Dividends: unit and investment trusts (7) and stocks, shares and bonds (8). FRS_DIVIDEND_ACCOUNTS = (7, 8) 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 02351c6a56..05a759863f 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/graph.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/graph.py @@ -605,6 +605,12 @@ ("household", "stocks_and_shares_isa"), } ), + # The gross receipts are drawn on each person's final self-employment + # profit, and the receipt counts support by source household + # (microcosm#1428). + "trading_allowance_receipts": frozenset( + {("person", "self_employment_income"), ("household", "household_source_id")} + ), # The copies' childcare re-draw reads every household's clone path (the # lineage columns of each copy stage) and keeps the native units' cells: # an open surface, like the other take-up redraws. @@ -1219,6 +1225,9 @@ def _cells( "lifetime_isa_payments", ), ), + "trading_allowance_receipts": ( + _Cell("person", "self_employment_gross_receipts", "float64"), + ), "childcare_copy_take_up": ( *_cells( "benunit", @@ -1304,6 +1313,10 @@ def _cells( "self_employment_income_other_spells", "private_pension_income_annual_share", "contributory_benefits_annual_share", + # A drawn row's private pension is the tape's, which books annuity and + # trust payments as other income, so its annuity and trust descriptor is + # zero (microcosm#1428). + "annuity_and_trust_income", ) _HMRC_SPI_HIDDEN_STRING = ( "aa_category", 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 d89bd216fe..1f7e6bb2f3 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 @@ -135,6 +135,7 @@ "student_loans": "student_loans", "private_school_attendance": "private_school_attendance", "isa_subscriptions": "isa_subscriptions", + "trading_allowance_receipts": "trading_allowance_receipts", "childcare_copy_take_up": "childcare_copy_take_up", "age_tail": "age_tail", } @@ -230,6 +231,9 @@ hmrc_isa_statistics, receipt_counts, ), + # The claimant draw is keyed on identity and its receipt rounds its + # support (microcosm#1428). + "trading_allowance_receipts": (receipt_counts, stochastic_assignment), # The copies' childcare re-draw draws through frs_take_up's childcare # helper and reads each household's clone path. "childcare_copy_take_up": (frs_take_up, household_lineage), @@ -582,6 +586,7 @@ def _fixture_implementations(source: Path) -> Mapping[str, object]: ) from .student_loans import UKStudentLoansStageTransform from .take_up_contract import load_uk_take_up_contract + from .trading_allowance_receipts import UKTradingAllowanceReceiptsStageTransform from .uc_capital_coherence import UKUCCapitalCoherenceStageTransform from .uc_deduction_attributes import UKUCDeductionAttributesStageTransform from .uc_reporter_redraw import UKUCReporterRedrawStageTransform @@ -847,6 +852,9 @@ def _fixture_implementations(source: Path) -> Mapping[str, object]: donor_household=was, donor_person=was_person, ), + "trading_allowance_receipts": UKTradingAllowanceReceiptsStageTransform( + stage=stages["trading_allowance_receipts"] + ), "childcare_copy_take_up": UKChildcareCopyTakeUpStageTransform( contract=contract, stage=stages["childcare_copy_take_up"] ), diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/hmrc_uprating.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/hmrc_uprating.py index ab0dff656e..10f16a86ce 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/hmrc_uprating.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/hmrc_uprating.py @@ -1368,6 +1368,46 @@ def _savings_income_level( return value +def uk_obr_savings_income_level( + opening_year: int, + year: int, + *, + rows: list[Mapping[str, Any]] | None = None, +) -> tuple[float, dict[int, tuple[float, str]]]: + """Savings income in fiscal ``year`` over fiscal ``opening_year``. + + The OBR's growth rates chained between the two fiscal years, read from + the vendored resource the SPI savings rows grow by; returns the level and + each year's growth with its source record. The SPI income stage rebases + its donors' savings to the frame's year on it (microcosm#1418 savings + follow-up). A year the resource does not carry is refused. + """ + + if rows is None: + rows = list( + vendored_rows( + UK_OBR_SAVINGS_INCOME_GROWTH_RESOURCE, + concept=UK_OBR_SAVINGS_INCOME_GROWTH_CONCEPT, + period_type="fiscal_year", + ) + ) + if int(year) < int(opening_year): + raise ValueError( + f"The OBR savings income path runs forward only: fiscal year {year} " + f"is before {opening_year}." + ) + growth = _obr_savings_income_growth(rows) + used: dict[int, tuple[float, str]] = {} + level = _savings_income_level( + growth, + opening_year=int(opening_year), + year=int(year), + spec_name="SPI donor savings", + used=used, + ) + return level, used + + def align_hmrc_row_by_obr_savings_income_growth( reference: LedgerTargetReference, registry: TargetRegistry, @@ -1534,4 +1574,5 @@ def align_hmrc_count_row_by_taxpayer_growth( "installed_engine_version", "live_engine_parameter_value", "hmrc_uprating_appliers", + "uk_obr_savings_income_level", ] diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/isa_subscriptions.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/isa_subscriptions.py index c7145e9d17..f9054c4363 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/isa_subscriptions.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/isa_subscriptions.py @@ -60,7 +60,6 @@ import numpy as np import pandas as pd -from microcosm.build.gates import FitWeightRecord from microcosm.build.source_manifest import SourceStageSpec from microcosm.build.stochastic_assignment import stable_identity_uniforms from microcosm.build.uk_runtime.cgt_imputation import ( @@ -1643,10 +1642,6 @@ class UKISASubscriptionsStageTransform: statistics: HMRCISAStatistics | None = None last_receipt: Mapping[str, Any] | None = field(default=None, init=False) - @property - def fit_weight_records(self) -> tuple[FitWeightRecord, ...]: - return () - def _table( self, supplied: pd.DataFrame | None, 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 9496cfee74..bfa2ccd28d 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 @@ -40,6 +40,7 @@ SELF_EMPLOYMENT_INCOME_ANNUAL_SHARE, SELF_EMPLOYMENT_INCOME_OTHER_SPELLS, ) +from microcosm.build.uk_runtime.frs_spine import ANNUITY_AND_TRUST_INCOME_COLUMN from microcosm.build.uk_runtime.high_value_homes import ( high_value_home_mask, uk_high_value_home_thresholds, @@ -282,6 +283,33 @@ def savings_interest_outside_isas(frame: Any) -> np.ndarray: return np.maximum(interest, 0.0) +#: SPI Table 3.7's other income (note 6): the engine's other_investment_income +#: plus the purchased-annuity and trust payments that FRS rows keep in +#: private_pension_income, where the engine's means tests, household income +#: and tax read them (microcosm#1428). The frame stores each person's annuity +#: and trust payments at the dataset's year +#: (frs_spine.ANNUITY_AND_TRUST_INCOME_COLUMN), and their share of the stored +#: private pension carries them to the measurement year on the engine's own +#: private pension path. A frame without the column (the enhanced FRS +#: reference) reads the engine's other income alone. A reserved name. +UK_SPI_OTHER_INVESTMENT_INCOME = "other_investment_income_spi_concept" + + +def annuity_and_trust_share(frame: Any) -> np.ndarray: + """Each person's annuity and trust share of their stored private pension.""" + + person = frame.table("person") + if ( + ANNUITY_AND_TRUST_INCOME_COLUMN not in person + or "private_pension_income" not in person + ): + return np.zeros(len(person)) + part = person[ANNUITY_AND_TRUST_INCOME_COLUMN].to_numpy(dtype=float) + pension = person["private_pension_income"].to_numpy(dtype=float) + share = np.divide(part, pension, out=np.zeros(len(person)), where=pension > 0) + return np.clip(share, 0.0, 1.0) + + #: The named terms the resolver computes: measures declared once as #: expressions of the binding interpreter's grammar, evaluated from their #: leaves wherever a binding names them (a value, a band or a filter, on the @@ -543,6 +571,21 @@ def compute_uk_measure_input( else "frame_columns:savings_interest_income", ) + if variable == UK_SPI_OTHER_INVESTMENT_INCOME: + if entity != "person": + raise KeyError(f"{variable} is person-only: {entity}") + other, route = compute_uk_measure_input( + frame, simulation, "person", "other_investment_income", year + ) + pension, _ = compute_uk_measure_input( + frame, simulation, "person", "private_pension_income", year + ) + return ( + other + annuity_and_trust_share(frame) * pension, + "engine_components:other_investment_income" + f"+annuity_and_trust_share*private_pension_income:{route}", + ) + if variable in DFE_SPRING_TERM_MEASURES: if entity != "person": raise KeyError(f"DfE spring-term measures are person-only: {entity}") @@ -1040,11 +1083,12 @@ def __init__( "High-value home measures must not be persisted as source inputs: " f"{persisted_high_value}" ) - if UK_SAVINGS_INTEREST_OUTSIDE_ISAS in set(map(str, frame.table("person"))): - raise ValueError( - f"{UK_SAVINGS_INTEREST_OUTSIDE_ISAS} must not be persisted as a " - "source input." - ) + for reserved in ( + UK_SAVINGS_INTEREST_OUTSIDE_ISAS, + UK_SPI_OTHER_INVESTMENT_INCOME, + ): + if reserved in set(map(str, frame.table("person"))): + raise ValueError(f"{reserved} must not be persisted as a source input.") persisted_spring_term = sorted( set(DFE_SPRING_TERM_MEASURES) & set(map(str, frame.table("person"))) ) @@ -1168,6 +1212,12 @@ def knows(self, entity: str, variable: str) -> bool: return entity == "person" and "savings_interest_income" in set( map(str, self.frame.table("person")) ) + if variable == UK_SPI_OTHER_INVESTMENT_INCOME: + return ( + entity == "person" + and self.knows("person", "other_investment_income") + and self.knows("person", "private_pension_income") + ) if variable in DFE_SPRING_TERM_MEASURES: return entity == "person" and all( self.knows("person", name) for name in DFE_SPRING_TERM_ENGINE_INPUTS @@ -1212,7 +1262,10 @@ def entity_for(self, variable: str) -> str | None: return "household" if variable == UK_CHILD_BENEFIT_CHILD_COUNT: return "benunit" - if variable == UK_SAVINGS_INTEREST_OUTSIDE_ISAS: + if variable in ( + UK_SAVINGS_INTEREST_OUTSIDE_ISAS, + UK_SPI_OTHER_INVESTMENT_INCOME, + ): return "person" if _cgt_model_measure(variable, self.year) is not None: return "person" 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 b4213132cd..dbf22e5198 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 @@ -4,7 +4,7 @@ import hashlib import math -from collections.abc import Mapping, Sequence +from collections.abc import Collection, Mapping, Sequence from dataclasses import dataclass from functools import cache from importlib import import_module @@ -37,6 +37,7 @@ FRS_HMRC_UBISJA_COLUMN, ) from microcosm.build.uk_runtime.frs_spine import ( + ANNUITY_AND_TRUST_INCOME_COLUMN, FRS_LANDLORD_CARRIER_COLUMN, ISA_INTEREST_COLUMN, uc_gainful_self_employment, @@ -209,8 +210,39 @@ #: microcosm#1095) until microcosm#1418 moved them to the OBR's savings income #: forecast, so the calibration closes the gap between the two. The engine #: lockstep test holds both indices to the engine's. +#: +#: Since the microcosm#1418 savings follow-up, interest and other income +#: reach the frame's year on SPI's own path instead +#: (``rebase_spi_donor_savings``): HMRC's published 2023-24 Table 3.7 amounts +#: by range of total income, then the OBR's savings income growth, the path +#: the band targets take. On their engine indices the 2022-23 tape reached +#: 2024 at about half of SPI's 2023-24 other income (GDP per head, x1.09, +#: against x1.65 in that one year) and short of its interest, and the solve +#: met the band targets by stretching the few households that carry them. +#: Both columns run on the projection's index from the frame's year on, named +#: here. SPI_HISTORY_INDEX_DIFFERS_FROM_PROJECTION = { "savings_interest_income": "gov.economic_assumptions.indices.obr.per_capita.gdp", + "other_investment_income": "gov.economic_assumptions.indices.obr.per_capita.gdp", +} +#: The published rows the donor savings rebase reads (vendored from the +#: Chronicle feed pin), the year they describe, and each rebased column's +#: Table 3.7 concept. +SPI_SAVINGS_REBASE_RESOURCE = "hmrc_spi_table_3_7_savings_rows.json" +#: The prepared tape's taxpayer flag, the records the rebase factors read. +SPI_DONOR_TAXPAYER_COLUMN = "is_taxpayer" +#: The tape's TAXPAYER codes: 1, a taxpayer, and 2, not. +SPI_TAXPAYER_CODES = (1, 2) +#: The band factors assume the tape's FACT weights gross to the taxpayer +#: population. A column whose banded tape amount is under this share of the +#: published amount does not (a synthetic tape, whose factors would run to +#: millions), and is left as it is. The production tape holds about 0.37 of +#: the published interest and 0.6 of the other income. +SPI_SAVINGS_REBASE_MINIMUM_GROSSING = 0.1 +SPI_SAVINGS_REBASE_YEAR = 2023 +SPI_SAVINGS_REBASE_CONCEPTS = { + "savings_interest_income": "hmrc.spi_savings_interest_income_amount", + "other_investment_income": "hmrc.spi_other_income_amount", } # Use the pinned engine's variable-specific indices. None explicitly retains # nominal amounts where no same-scope indexed mapping has been reviewed; @@ -695,6 +727,7 @@ class UKSPIIncomeImputationResult: state_pension_age: int | None = None gainful_self_employment_refresh: Mapping[str, object] | None = None pension_coherence: Mapping[str, object] | None = None + gift_anchor: Mapping[str, object] | None = None @dataclass(frozen=True) @@ -852,6 +885,23 @@ def impute_uk_spi_income_support( raise TypeError("donor_table must be a pandas DataFrame.") raw_donor = donor_table.copy(deep=True) donor = _prepare_spi_donor(raw_donor, seed=seed, age_model=donor_age_model) + # The tape's interest and other income move to SPI's 2023-24 bands before + # any draw, so the forest and the band donors read the same rebased tape + # (microcosm#1418 savings follow-up). + savings_rebase = None + rebased_columns: frozenset[str] = frozenset() + if rebase_income_to_build_period and int(build_period) >= SPI_SAVINGS_REBASE_YEAR: + rebase_year_factors, _ = _spi_income_uprating_factors(SPI_SAVINGS_REBASE_YEAR) + donor, savings_rebase = rebase_spi_donor_savings( + donor, + spi_savings_rebase_published(), + income_factors=rebase_year_factors, + ) + rebased_columns = frozenset( + column + for column, entry in savings_rebase["columns"].items() + if "skipped" not in entry + ) donor_age_draw = { **donor.attrs.get("age_draw", {}), "stage1_query_age": SPI_STAGE1_QUERY_AGE_RULE, @@ -967,6 +1017,13 @@ def impute_uk_spi_income_support( columns=initialize_frs_channel_columns, ) person = _seed_frs_hmrc_auxiliary_leaves(person, spi_people=spi_people) + # The stage-1 transport reads each twin's analogue. A stage-1 output that is + # its own analogue and that the frame does not carry (other income, on a + # frame whose FRS rows hold none) is the stage-time zero the fill below + # writes, on every row, so the twins locate as non-carriers (microcosm#1428). + for column in SPI_INCOME_QRF_OUTPUT_COLUMNS: + if SPI_STAGE1_ANALOGUE_COLUMNS.get(column) == column and column not in person: + person[column] = 0.0 base_household = household[household_channel] == BASE_FRS_SUPPORT_CHANNEL if "clone_index" in household: @@ -1104,8 +1161,10 @@ def fit_reference(encoded: pd.DataFrame, observed: pd.DataFrame): uprating_factors = dict.fromkeys(SPI_INCOME_QRF_OUTPUT_COLUMNS, 1.0) if rebase_income_to_build_period: uprating_factors, income_uprating = _spi_income_uprating_factors( - int(build_period) + int(build_period), rebased_columns=rebased_columns ) + if savings_rebase is not None: + income_uprating = {**income_uprating, "savings_rebase": savings_rebase} stage1_draws = stage1_draws.mul(pd.Series(uprating_factors), axis="columns") nonnegative_stage1 = [ column @@ -1301,6 +1360,9 @@ def fit_reference(encoded: pd.DataFrame, observed: pd.DataFrame): ) guard_receipts.append(receipt) + person, gift_anchor = _anchor_spi_gifts_to_tape( + person, household, donor_full, spi_people=spi_people + ) # Non-ISA interest is the stage-1 taxable draw; ISA interest is the stage-2 # draw beside it (microcosm#1360). person.loc[spi_people, "savings_interest_income"] = taxable_interest_draw @@ -1316,6 +1378,7 @@ def fit_reference(encoded: pd.DataFrame, observed: pd.DataFrame): ) person = _refresh_landlord_carrier(person, spi_people=spi_people) person = _refresh_annual_income_descriptors(person, spi_people=spi_people) + person = _clear_annuity_and_trust_descriptor(person, spi_people=spi_people) # The flag is the stage's last new column, where the graph's typed cells # place it (the legacy oracle and the graph must agree on column order). person[SPI_INCOME_RECIPIENT_COLUMN] = ( @@ -1356,6 +1419,7 @@ def fit_reference(encoded: pd.DataFrame, observed: pd.DataFrame): state_pension_age=int(state_pension_age), gainful_self_employment_refresh=gainful_self_employment, pension_coherence=pension_coherence, + gift_anchor=gift_anchor, ) @@ -1674,10 +1738,23 @@ def _resample_band_donor_leaves( @cache -def _spi_income_uprating_factors(year: int): - """Rebase SPI money flows before conditioning on build-year FRS incomes.""" +def _spi_income_uprating_factors( + year: int, *, rebased_columns: Collection[str] | None = None +): + """Rebase SPI money flows before conditioning on build-year FRS incomes. + + ``rebased_columns`` names the savings columns rebase_spi_donor_savings + moved to 2023-24, which grow on the OBR's savings path from there; a + savings column it left as it was (a tape that does not gross) grows on + its engine index from 2022-23. None takes every rebased concept. + """ from policyengine_uk import CountryTaxBenefitSystem + from microcosm.build.uk_runtime.hmrc_uprating import ( + UK_OBR_SAVINGS_INCOME_GROWTH_INDEX_CONCEPT, + uk_obr_savings_income_level, + ) + if year < SPI_DONOR_INCOME_YEAR: raise ValueError("SPI income cannot be rebased before its source year.") if set(SPI_INCOME_UPRATING_VARIABLES) != set(SPI_INCOME_QRF_OUTPUT_COLUMNS): @@ -1688,6 +1765,31 @@ def _spi_income_uprating_factors(year: int): factors = {} columns = {} for column, variable_name in SPI_INCOME_UPRATING_VARIABLES.items(): + rebased = ( + column in SPI_SAVINGS_REBASE_CONCEPTS + if rebased_columns is None + else column in rebased_columns + ) + if rebased and year >= SPI_SAVINGS_REBASE_YEAR: + # rebase_spi_donor_savings has moved the column to SPI's 2023-24 + # bands; the OBR's savings income growth carries it on. + factor, used = uk_obr_savings_income_level(SPI_SAVINGS_REBASE_YEAR, year) + factors[column] = factor + columns[column] = { + "variable": variable_name, + "index": UK_OBR_SAVINGS_INCOME_GROWTH_INDEX_CONCEPT, + "factor": factor, + "basis": "spi_published_bands_then_obr_savings_income", + "from_period": SPI_SAVINGS_REBASE_YEAR, + "growth_by_year": { + str(fiscal_year): growth + for fiscal_year, (growth, _) in used.items() + }, + "dataset_projection_index": ( + SPI_HISTORY_INDEX_DIFFERS_FROM_PROJECTION[variable_name] + ), + } + continue path = None factor = 1.0 if variable_name is not None: @@ -1771,6 +1873,231 @@ def prepare_spi_donor_table( return _prepare_spi_donor(raw, seed=seed, age_model=age_model) +def spi_savings_rebase_published( + rows: Sequence[Mapping[str, Any]] | None = None, +) -> dict[str, dict[int, float]]: + """HMRC's 2023-24 Table 3.7 amounts by band, for each rebased column. + + Read from the vendored resource (``SPI_SAVINGS_REBASE_RESOURCE``): the + United Kingdom interest from banks and building societies and other + income of taxpayers, keyed by each band's lower bound of total income. + Both columns must name the same bands, once each. + """ + + if rows is None: + from microcosm.build.uk_runtime.ledger_fact_vendoring import vendored_rows + + rows = vendored_rows(SPI_SAVINGS_REBASE_RESOURCE) + columns = { + concept: column for column, concept in SPI_SAVINGS_REBASE_CONCEPTS.items() + } + published: dict[str, dict[int, float]] = { + column: {} for column in SPI_SAVINGS_REBASE_CONCEPTS + } + for row in rows: + column = columns.get(str(row.get("concept"))) + if column is None: + continue + period = int((row.get("period") or {}).get("value", -1)) + if period != SPI_SAVINGS_REBASE_YEAR: + raise ValueError( + f"{SPI_SAVINGS_REBASE_RESOURCE}: a {column} row describes {period}, " + f"not {SPI_SAVINGS_REBASE_YEAR}." + ) + bound = int((row.get("dimensions") or {})["total_income_lower_bound"]) + if bound in published[column]: + raise ValueError( + f"{SPI_SAVINGS_REBASE_RESOURCE}: {column} has two rows from {bound}." + ) + value = float(row["value"]) + if not np.isfinite(value) or value < 0.0: + raise ValueError( + f"{SPI_SAVINGS_REBASE_RESOURCE}: {column} from {bound} is {value!r}." + ) + published[column][bound] = value + bands = {column: tuple(sorted(by_bound)) for column, by_bound in published.items()} + if not all(bands.values()) or len(set(bands.values())) != 1: + raise ValueError( + f"{SPI_SAVINGS_REBASE_RESOURCE} must give every rebased column the " + f"same total-income bands: {bands}." + ) + return published + + +#: The rebase bands the tape on its income moved to 2023-24, the year the +#: published bands describe: each income leaf at its 2022-23 to 2023-24 factor, +#: the rebased savings as they stand, and the rest of the published total held +#: nominal, as the band donors' realised income is built. Its consumers band +#: again on income uprated to the frame's year, so banding on 2022-23 income +#: counted the band-edge migration twice (microcosm#1428 review, finding 6). +#: Rebased savings move income, so the banding repeats until no record changes +#: band, at most this many times. +SPI_SAVINGS_REBASE_MAX_ITERATIONS = 20 + + +def _tape_income_in_rebase_year( + donor: pd.DataFrame, + rebased: pd.DataFrame, + income_factors: Mapping[str, float], +) -> np.ndarray: + """The tape's total income moved to SPI_SAVINGS_REBASE_YEAR.""" + + columns = [ + column + for column in SPI_INCOME_QRF_OUTPUT_COLUMNS + if column in donor + and column not in (SPI_PROPERTY_FINANCE_COSTS_COLUMN, *SPI_LOSS_DRAW_COLUMNS) + ] + leaves = donor[columns].to_numpy(dtype=np.float64) + rest = np.maximum( + donor["total_income"].to_numpy(dtype=np.float64) - leaves.sum(axis=1), 0.0 + ) + moved = rebased[columns].to_numpy(dtype=np.float64) @ np.asarray( + [float(income_factors.get(column, 1.0)) for column in columns] + ) + return moved + rest + + +def rebase_spi_donor_savings( + donor: pd.DataFrame, + published: Mapping[str, Mapping[int, float]], + *, + income_factors: Mapping[str, float] | None = None, +) -> tuple[pd.DataFrame, dict[str, object]]: + """Move the tape's interest and other income to SPI's 2023-24 bands. + + Each taxpayer donor's column is scaled by its band's factor: HMRC's + published 2023-24 amount over the tape's FACT-weighted amount for the + taxpayers in the same range of total income, since Table 3.7 counts + taxpayers only. The tape is banded on its income moved to 2023-24 + (``income_factors``, each income leaf's 2022-23 to 2023-24 factor; none + holds the leaves nominal), repeating until the rebased savings move no + record across a band edge. A taxpayer is a record the tape flags + (TAXPAYER 1) or one whose income crosses the first band's lower bound, + the Personal Allowance, by 2023-24, so a saver who becomes a taxpayer is + counted once. A flagged taxpayer below the first band sits in it, as the + table's lowest band holds those taxpayers (note 8); a tape without the + flag counts every record at or above the first band. Any other donor + takes the factor of all bands together. The rebased tape reproduces the + published amounts band by band; the OBR's savings income growth then + carries both columns to the frame's year (``_spi_income_uprating_factors``). + A band the tape carries none of has nothing to scale, and a band whose tape + amount is under SPI_SAVINGS_REBASE_MINIMUM_GROSSING of its published amount + takes the factor of all bands; both are named in the receipt. A column + whose tape does not gross to the population is left as it is, and the + receipt says so. The receipt carries the factors only. + """ + + bounds = sorted(next(iter(published.values()))) + edges = np.asarray(bounds, dtype=np.float64) + weights = donor["FACT"].to_numpy(dtype=np.float64) + flagged = SPI_DONOR_TAXPAYER_COLUMN in donor + tape_taxpayer = ( + donor[SPI_DONOR_TAXPAYER_COLUMN].to_numpy(dtype=bool) + if flagged + else np.zeros(len(donor), dtype=bool) + ) + band_2022 = ( + np.searchsorted( + edges, donor["total_income"].to_numpy(dtype=np.float64), side="right" + ) + - 1 + ) + factors_in = dict(income_factors or {}) + rebased = donor.copy() + receipt: dict[str, object] = { + "resource": SPI_SAVINGS_REBASE_RESOURCE, + "from_period": SPI_DONOR_INCOME_YEAR, + "to_period": SPI_SAVINGS_REBASE_YEAR, + "band_by": "total_income_moved_to_2023_24", + "factors_over": ( + "taxpayers: TAXPAYER 1, or income crossing the first band by 2023-24" + if flagged + else "all_records_at_or_above_the_first_band" + ), + "band_lower_bounds": [int(bound) for bound in bounds], + "columns": {}, + } + original: dict[str, np.ndarray] = {} + targets: dict[str, np.ndarray] = {} + for column, by_bound in published.items(): + values = donor[column].to_numpy(dtype=np.float64) + target = np.asarray([float(by_bound[bound]) for bound in bounds]) + taxpayer = tape_taxpayer | (band_2022 >= 0) + tape = np.bincount( + np.clip(band_2022, 0, None)[taxpayer], + weights=(weights * values)[taxpayer], + minlength=len(bounds), + ) + carried = tape > 0.0 + # Over the bands the tape carries; an empty band is left as it is. + if ( + tape[carried].sum() + < SPI_SAVINGS_REBASE_MINIMUM_GROSSING * target[carried].sum() + ): + receipt["columns"][column] = { + "concept": SPI_SAVINGS_REBASE_CONCEPTS[column], + "skipped": "the tape's weights do not gross to the published amounts", + } + continue + original[column] = values + targets[column] = target + + band = None + converged = not original + passes = 0 + while original and passes < SPI_SAVINGS_REBASE_MAX_ITERATIONS: + passes += 1 + income = _tape_income_in_rebase_year(donor, rebased, factors_in) + moved_band = np.searchsorted(edges, income, side="right") - 1 + crossed = ~tape_taxpayer & (band_2022 < 0) & (moved_band >= 0) + taxpayer = tape_taxpayer | crossed if flagged else (moved_band >= 0) + moved_band = np.where(taxpayer, np.clip(moved_band, 0, None), moved_band) + if band is not None and np.array_equal(moved_band, band): + converged = True + break + band = moved_band + for column, values in original.items(): + target = targets[column] + tape = np.bincount( + band[taxpayer], + weights=(weights * values)[taxpayer], + minlength=len(bounds), + ) + carried = tape > 0.0 + thin = carried & (tape < SPI_SAVINGS_REBASE_MINIMUM_GROSSING * target) + usable = carried & ~thin + all_bands = ( + float(target[usable].sum() / tape[usable].sum()) + if usable.any() + else 1.0 + ) + factors = np.where(usable, target / np.where(usable, tape, 1.0), all_bands) + rebased[column] = values * np.where( + taxpayer, factors[np.clip(band, 0, None)], all_bands + ) + receipt["columns"][column] = { + "concept": SPI_SAVINGS_REBASE_CONCEPTS[column], + "band_factors": { + str(bound): float(factor) + for bound, factor, kept in zip(bounds, factors, usable, strict=True) + if kept + }, + "below_first_band_factor": all_bands, + "bands_without_tape_amounts": [ + int(bound) + for bound, kept in zip(bounds, carried, strict=True) + if not kept + ], + "bands_too_thin_to_gross": [ + int(bound) for bound, kept in zip(bounds, thin, strict=True) if kept + ], + } + receipt["banding_passes"] = passes + receipt["banding_converged"] = bool(converged) + return rebased, receipt + + def _prepare_spi_donor( raw: pd.DataFrame, *, @@ -1848,6 +2175,19 @@ def _prepare_spi_donor( # on the prepared tape for the band donors' propensity and band pools; # they are never QRF inputs or outputs. donor["total_income"] = numeric["TI"].to_numpy(dtype=float) + # Table 3.7 counts taxpayers only, so the savings rebase reads the tape's + # TAXPAYER flag (SPI_TAXPAYER_CODES: 1, a taxpayer; 2, not). A tape without + # it carries no flag, and the rebase's receipt says it counted every record + # at or above the first band (microcosm#1428). + if "TAXPAYER" in raw.columns: + taxpayer = pd.to_numeric(raw["TAXPAYER"], errors="coerce") + unknown = sorted(set(taxpayer.dropna().unique()) - set(SPI_TAXPAYER_CODES)) + if taxpayer.isna().any() or unknown: + raise ValueError( + "SPI TAXPAYER must be 1 (a taxpayer) or 2 (not) on every record; " + f"found {unknown or 'blanks'}." + ) + donor[SPI_DONOR_TAXPAYER_COLUMN] = taxpayer.eq(1).to_numpy() donor["is_composite"] = numeric["AGERANGE"].astype(int).eq(-1).to_numpy() # The published age band travels with the record so band pools can match # a carrier's age band; composites (-1) have none and never age-match. @@ -2589,6 +2929,56 @@ def _spi_pension_coherence( return person, receipt +#: Gift Aid and charitable investment gifts are sparse leaves the stage-1 +#: chain draws after, and conditioned on, the income leaves, so a change to +#: the donor savings rebase reshuffles which few donors' gifts the copies +#: draw: rebasing on the tape's taxpayers moved the copies' charitable +#: investment gifts far from the tape's own total (microcosm#1428). Their +#: totals over the drawn copies, at the stage's weights, are anchored to the +#: tape's own FACT-weighted totals (María's ruling of 2026-10-31). Both +#: columns are nominal, as their uprating mapping (None) keeps them. +SPI_GIFT_ANCHOR_COLUMNS = ("gift_aid", "charitable_investment_gifts") +SPI_GIFT_ANCHOR_BASIS = ( + "each column's total over the drawn copies at the stage's household " + "weights equals the prepared tape's FACT-weighted total; a column the " + "tape or the copies carry none of is left as drawn" +) + + +def _anchor_spi_gifts_to_tape( + person: pd.DataFrame, + household: pd.DataFrame, + donor: pd.DataFrame, + *, + spi_people: pd.Series, +) -> tuple[pd.DataFrame, dict[str, object]]: + """Scale the copies' gift leaves to the tape's FACT-weighted totals. + + The receipt records each column's factor only, never a total or a count. + """ + + weights = _person_household_weights(person, household).to_numpy(dtype=np.float64) + rows = spi_people.reindex(person.index).fillna(False).to_numpy(dtype=bool) + fact = donor["FACT"].to_numpy(dtype=np.float64) + factors: dict[str, float] = {} + for column in SPI_GIFT_ANCHOR_COLUMNS: + tape = float((fact * donor[column].to_numpy(dtype=np.float64)).sum()) + values = person[column].to_numpy(dtype=np.float64, copy=True) + drawn = float((weights[rows] * values[rows]).sum()) + if tape <= 0.0 or drawn <= 0.0: + factors[column] = 1.0 + continue + factor = tape / drawn + values[rows] = values[rows] * factor + person[column] = values + factors[column] = factor + return person, { + "columns": list(SPI_GIFT_ANCHOR_COLUMNS), + "basis": SPI_GIFT_ANCHOR_BASIS, + "factors": factors, + } + + def _person_household_weights( person: pd.DataFrame, household: pd.DataFrame, @@ -3011,6 +3401,29 @@ def _refresh_annual_income_descriptors( return person +def _clear_annuity_and_trust_descriptor( + person: pd.DataFrame, *, spi_people: pd.Series +) -> pd.DataFrame: + """Zero a drawn row's annuity and trust descriptor. + + A drawn row's private pension is the tape's, which excludes purchased + annuity and trust income: SPI books those as other income, in the drawn + other_investment_income (microcosm#1428). An undrawn copy keeps its twin's + descriptor with its twin's pension. + """ + + if ANNUITY_AND_TRUST_INCOME_COLUMN not in person: + return person + _assign_spi_values( + person, + spi_people, + ANNUITY_AND_TRUST_INCOME_COLUMN, + np.zeros(int(spi_people.sum())), + default=0.0, + ) + return person + + def _refresh_uc_gainful_self_employment( person: pd.DataFrame, *, spi_people: pd.Series ) -> tuple[pd.DataFrame, dict[str, object] | None]: diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_rank_transport.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_rank_transport.py index b8f1316c9f..fa58e1ebf1 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_rank_transport.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_rank_transport.py @@ -116,7 +116,12 @@ "dividend_income": "dividend_income", "private_pension_income": "private_pension_income", "property_income": "property_income", - "other_investment_income": None, + # The twin's own other income locates the draw (microcosm#1428): its gilt + # interest, so a copy's OTHERINV draw ranks with its twin's holdings + # instead of an identity uniform that ignores them. The twin's purchased + # annuity and trust payments stay in private_pension_income, whose + # analogue they join. + "other_investment_income": "other_investment_income", "gift_aid": None, "charitable_investment_gifts": None, SPI_HMRC_PAY_COLUMN: FRS_HMRC_PAY_COLUMN, diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_spine.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_spine.py index 0fcbd5724b..64746b11da 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_spine.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_spine.py @@ -29,6 +29,7 @@ _raw_source_person_ids, _read_raw_frs_table, ) +from microcosm.build.uk_runtime.frs_spine import ANNUITY_AND_TRUST_INCOME_COLUMN from microcosm.build.uk_runtime.frs_take_up import uk_take_up_population_policy from microcosm.build.uk_runtime.hmrc_income import ( HMRCIncomeTargetSet, @@ -215,8 +216,8 @@ "self_employment_income", "savings_interest_income", "dividend_income", - # The tape's OTHERINV on SPI rows; FRS rows carry their own NS&I and gilt - # interest from frs_spine (microcosm#1418). + # The tape's OTHERINV on SPI rows; FRS rows carry their own gilt interest + # from frs_spine (microcosm#1418), NS&I being interest (microcosm#1428). "other_investment_income", "private_pension_income", "property_income", @@ -270,6 +271,10 @@ # tape's income is the tax year's, so each share is 1, and the twin's # other spells stay only where the tape drew none of that income. *FRS_ANNUAL_INCOME_OUTPUT_COLUMNS, + # A drawn row's private pension is the tape's, which books annuity and + # trust payments as other income, so its descriptor of them is zero + # (microcosm#1428). + ANNUITY_AND_TRUST_INCOME_COLUMN, ) # Reviewed constants for every load-bearing manifest parameter the spine @@ -315,6 +320,7 @@ ) # Held to the drawn incomes by rule, not drawn by stage 2. and column not in FRS_ANNUAL_INCOME_OUTPUT_COLUMNS + and column != ANNUITY_AND_TRUST_INCOME_COLUMN ) #: Both forests are queried over every SPI-channel person aged 16 and over, #: and the dependants' rows are discarded (uk-data#504, microcosm#1095). @@ -405,6 +411,7 @@ def evidence(self) -> dict[str, object]: self.imputation.gainful_self_employment_refresh ), "pension_coherence": self.imputation.pension_coherence, + "gift_anchor": self.imputation.gift_anchor, "state_pension_age_guard": list(self.imputation.state_pension_age_guard), "targets": { "count": len(self.source_targets.targets), diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_support.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_support.py index 230b776fa8..8c8d7ed86b 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_support.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/spi_support.py @@ -138,9 +138,9 @@ # The enhanced-FRS FRS-only stage uses these six income predictors. OTHERINV # is a first-stage SPI draw and HMRC accounting component. The FRS base -# carries `other_investment_income` only from its NS&I and gilt accounts -# (microcosm#1418), not OTHERINV's concept, so it stays out of second-stage -# training. +# carries `other_investment_income` only from its gilt accounts (microcosm#1418, +# NS&I being interest since microcosm#1428), not OTHERINV's concept, so it stays +# out of second-stage training. FRS_ONLY_SPI_FILL_INCOME_PREDICTOR_COLUMNS = ( "employment_income", "self_employment_income", 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 add5eaa2d4..b1e7184161 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 @@ -203,6 +203,9 @@ from microcosm.build.uk_runtime.staging import UK_STAGING_REPOSITORY from microcosm.build.uk_runtime.student_loans import UKStudentLoansStageTransform from microcosm.build.uk_runtime.take_up_contract import load_uk_take_up_contract +from microcosm.build.uk_runtime.trading_allowance_receipts import ( + UKTradingAllowanceReceiptsStageTransform, +) from microcosm.build.uk_runtime.uc_capital_coherence import ( UKUCCapitalCoherenceStageTransform, ) @@ -1910,6 +1913,12 @@ def prepare_uk_spine_execution( contract=stochastic_contract, stage=stages_by_name["childcare_copy_take_up"], ) + if "trading_allowance_receipts" in stage_names: + implementations["trading_allowance_receipts"] = ( + UKTradingAllowanceReceiptsStageTransform( + stage=stages_by_name["trading_allowance_receipts"] + ) + ) if "age_tail" in stage_names: implementations["age_tail"] = UKAgeTailStageTransform( stage=stages_by_name["age_tail"] diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/terminal_gates.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/terminal_gates.py index 075ef0c8b4..97f2618ec3 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/terminal_gates.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/terminal_gates.py @@ -306,6 +306,12 @@ def __post_init__(self) -> None: "person.private_pension_income_annual_share", "person.self_employment_income_annual_share", "person.self_employment_income_other_spells", + # The self-employed's gross receipts for the trading allowance, which the + # enhanced FRS leaves at the engine's zero (microcosm#1428). + "person.self_employment_gross_receipts", + # The annuity and trust part of private_pension_income, a calibration-only + # descriptor no engine input reads (microcosm#1428). + "person.annuity_and_trust_income", "person.esa_health_condition_proxy", "person.esa_includes_support_component", "person.esa_support_group_proxy", diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/trading_allowance_receipts.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/trading_allowance_receipts.py new file mode 100644 index 0000000000..17be90b6d1 --- /dev/null +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/trading_allowance_receipts.py @@ -0,0 +1,372 @@ +"""Self-employed gross receipts for the trading allowance (microcosm#1428). + +policyengine-uk applies the trading allowance (ITTOIA 2005 Part 7A) against a +trader's gross receipts, ``self_employment_gross_receipts``. Neither the FRS +nor the SPI tape records turnover. Without receipts the engine treats a profit +within the allowance as receipts within it (full relief) and a larger profit +as already reflecting the better of expenses and the allowance (no relief). A +rise in the allowance then relieves only profits up to the new allowance, in +full, and misses its main base: traders who already claim the GBP 1,000 +allowance against larger receipts and gain the larger deduction. + +Under current law a trader who claims the allowance deducts GBP 1,000 from +receipts in place of expenses, so their receipts are their profit plus +GBP 1,000 exactly; a trader who deducts actual expenses has expenses above +GBP 1,000. This stage, the last of the spine, flags each trader with a +positive profit as a claimant with a probability by profit band, drawn on +their own ``person_id``, and stores their receipts: + +* a claimant's are their profit plus GBP 1,000; +* any other trader's are their profit plus GBP 3,000, expenses at the raised + allowance, so that the raise does not relieve them (the costing books the + traders who would switch to the allowance as behaviour); +* a person with no positive profit keeps zero, which the engine reads as + unknown. + +The engine then gives a claimant nothing more at GBP 1,000 and up to +GBP 2,000 more at GBP 3,000, and any other trader nothing at either. Every +trader with a positive profit is treated as filing, as SPI Table 3.10's +counts, which bind the frame's traders, are of filers. So a profit of GBP 1,000 +or less is now taxed where the engine used to relieve it in full. + +Until HMRC publishes claimant counts, the rates are calibrated to HMRC's +policy paper on the Budget 2026 raise (about 400,000 taxpayers with a lower +bill, by about GBP 380 on average) on the #1428 national b441bb5a0, at +2028-29 prices (María's choice of 2026-10-31). + +Two limits of encoding the claim in receipts (#1428 review, findings 2 and 8; +María's ruling of 2026-11-01 keeps them, documented, until policyengine-uk#2765 +lets the stage store the claim status itself, microcosm#1439): + +* The engine uprates receipts with profit, so a claimant's GBP 1,000 grows with + the mixed income index while the allowance is nominal: the raise relieves + GBP 1,932 more in 2027-28, falling to GBP 1,758 by 2031-32, 3.4% to 12.1% + below GBP 2,000. +* The other traders' stored GBP 3,000 grows the same way, so an allowance above + GBP 3,000 times that index relieves them from the stored expense, not from + data. Allowances above GBP 3,000 are mis-scored on this encoding. +""" + +from __future__ import annotations + +from collections.abc import Mapping +from dataclasses import dataclass, field + +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.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, + rounded_count, + small_cell_share, + source_household_ids, + support_band, +) +from microcosm.frame import Frame, MassChangeRecord + +__all__ = [ + "TRADING_ALLOWANCE_CLAIMANT_BANDS", + "TRADING_ALLOWANCE_RECEIPTS_OUTPUT", + "TRADING_ALLOWANCE_RECEIPTS_STAGE_NAME", + "UKTradingAllowanceReceiptsStageTransform", + "assign_trading_allowance_receipts", + "claimant_rates", + "store_trading_allowance_receipts", +] + +TRADING_ALLOWANCE_RECEIPTS_STAGE_NAME = "trading_allowance_receipts" +TRADING_ALLOWANCE_RECEIPTS_OUTPUT = "self_employment_gross_receipts" +TRADING_ALLOWANCE_PROFIT = "self_employment_income" +TRADING_ALLOWANCE_CLAIMANT_DRAW = "trading_allowance_claimant" +TRADING_ALLOWANCE_CLAIMANT_SEED = 0 +#: The allowance a claimant deducts in place of expenses (2024-25). +TRADING_ALLOWANCE_CLAIMANT_EXPENSES = 1_000.0 +#: Any other trader's expenses: at the raised allowance, which then gives them +#: nothing. +TRADING_ALLOWANCE_OTHER_EXPENSES = 3_000.0 +#: The claimant probability by the person's profit, upper bounds inclusive, +#: over profits above zero; the last band has no upper bound. +TRADING_ALLOWANCE_CLAIMANT_BANDS: tuple[tuple[float | None, float], ...] = ( + (4_500.0, 0.64), + (9_000.0, 0.32), + (None, 0.0), +) +TRADING_ALLOWANCE_CALIBRATION = ( + "HMRC's policy paper on the Budget 2026 trading allowance raise: about " + "400,000 taxpayers with a lower bill, by about GBP 380 on average, on the " + "microcosm#1428 national b441bb5a0's final weights at 2028-29 prices, " + "until HMRC publishes claimant counts (María's choice of 2026-10-31)" +) +TRADING_ALLOWANCE_RECEIPTS_MASS_CHANGE_REASON = ( + "Self-employed gross receipts stored on the source spine: household weights " + "pass through unchanged and total household mass is conserved." +) +_MASS_GATE_COUPLING = ( + "The terminal family gate requires a valid mass-conserving MassChangeRecord " + "carrying exactly this stage-specific reason." +) +TRADING_ALLOWANCE_RECEIPTS_RULE = ( + "a person with a positive self_employment_income claims the allowance " + "where their uniform falls below their profit band's rate; a claimant's " + "receipts are their profit plus claimant_expenses, any other trader's their " + "profit plus other_expenses, and a person with no positive profit keeps zero" +) + + +def _expected_operations() -> tuple[tuple[str, Mapping[str, object]], ...]: + bands: list[dict[str, object]] = [] + for upper, rate in TRADING_ALLOWANCE_CLAIMANT_BANDS: + band: dict[str, object] = {"rate": rate} + if upper is not None: + band = {"upper_inclusive": upper, **band} + bands.append(band) + return ( + ( + "assign_trading_allowance_receipts", + { + "output": TRADING_ALLOWANCE_RECEIPTS_OUTPUT, + "profit": TRADING_ALLOWANCE_PROFIT, + "draw": TRADING_ALLOWANCE_CLAIMANT_DRAW, + "seed": TRADING_ALLOWANCE_CLAIMANT_SEED, + "claimant_bands": bands, + "claimant_expenses": TRADING_ALLOWANCE_CLAIMANT_EXPENSES, + "other_expenses": TRADING_ALLOWANCE_OTHER_EXPENSES, + "calibration": TRADING_ALLOWANCE_CALIBRATION, + "rule": TRADING_ALLOWANCE_RECEIPTS_RULE, + }, + ), + ( + "record_mass_conservation_receipt", + { + "entity": "household", + "reason": TRADING_ALLOWANCE_RECEIPTS_MASS_CHANGE_REASON, + "declared_factor": 1.0, + "gate_coupling": _MASS_GATE_COUPLING, + }, + ), + ) + + +def claimant_rates(profit: np.ndarray) -> np.ndarray: + """Each person's claimant probability by their profit band (zero at none).""" + + profit = np.asarray(profit, dtype=np.float64) + rates = np.zeros(profit.shape, dtype=np.float64) + lower = 0.0 + for upper, rate in TRADING_ALLOWANCE_CLAIMANT_BANDS: + in_band = profit > lower + if upper is not None: + in_band &= profit <= upper + rates[in_band] = rate + if upper is None: + break + lower = upper + return rates + + +def assign_trading_allowance_receipts( + person_ids: np.ndarray, + profit: np.ndarray, + *, + seed: int = TRADING_ALLOWANCE_CLAIMANT_SEED, + salt: str = TRADING_ALLOWANCE_CLAIMANT_DRAW, +) -> tuple[np.ndarray, np.ndarray]: + """Each person's gross receipts and claimant flag.""" + + profit = np.asarray(profit, dtype=np.float64) + ids = np.asarray(person_ids) + if ids.shape != profit.shape: + raise ValueError("Trading allowance person ids must align to the profits.") + if not np.isfinite(profit).all(): + raise ValueError("Trading allowance profits must be finite.") + trader = profit > 0.0 + claimant = np.zeros(profit.shape, dtype=bool) + if trader.any(): + uniforms = stable_identity_uniforms(ids[trader], seed=seed, salt=salt) + claimant[trader] = uniforms < claimant_rates(profit[trader]) + receipts = np.where( + claimant, + profit + TRADING_ALLOWANCE_CLAIMANT_EXPENSES, + np.where(trader, profit + TRADING_ALLOWANCE_OTHER_EXPENSES, 0.0), + ) + return receipts, claimant + + +@dataclass(frozen=True) +class UKTradingAllowanceReceiptsResult: + """The frame with the stored receipts, and the stage's receipt.""" + + frame: Frame + traders: int + claimants: int + bands: tuple[Mapping[str, object], ...] + + def evidence(self) -> dict[str, object]: + return { + "stage": TRADING_ALLOWANCE_RECEIPTS_STAGE_NAME, + "seed": TRADING_ALLOWANCE_CLAIMANT_SEED, + "draw": TRADING_ALLOWANCE_CLAIMANT_DRAW, + # Record counts are rounded, never exact (UKDS CD137 cl. 8). + "traders": rounded_count(self.traders), + "claimants": rounded_count(self.claimants), + "bands": [dict(band) for band in self.bands], + } + + +@dataclass(frozen=True) +class UKTradingAllowanceReceiptsStageTransform: + """Whole-stage callable storing the self-employed's gross receipts.""" + + stage: SourceStageSpec + last_result: UKTradingAllowanceReceiptsResult | None = field( + default=None, init=False + ) + + def __call__(self, frame: Frame) -> Frame: + _assert_stage_parameters(self.stage) + result = store_trading_allowance_receipts(frame) + object.__setattr__(self, "last_result", result) + return result.frame + + @staticmethod + def output_columns() -> tuple[str, ...]: + return (TRADING_ALLOWANCE_RECEIPTS_OUTPUT,) + + 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 store_trading_allowance_receipts(frame: Frame) -> UKTradingAllowanceReceiptsResult: + """Store each person's gross receipts; nothing else moves.""" + + validate_uk_national_frame(frame) + person = frame.table("person").copy() + household = frame.table("household").copy() + if TRADING_ALLOWANCE_RECEIPTS_OUTPUT in person.columns: + raise ValueError( + f"{TRADING_ALLOWANCE_RECEIPTS_OUTPUT!r} is already stored: this stage " + "is its only writer." + ) + if TRADING_ALLOWANCE_PROFIT not in person.columns: + raise KeyError( + f"person.{TRADING_ALLOWANCE_PROFIT} is missing; the receipts are " + "drawn on the final self-employment profit." + ) + if pd.Series(person["person_id"]).duplicated().any(): + raise ValueError( + "person_id must be unique: the trading allowance draw is keyed on it." + ) + profit = pd.to_numeric(person[TRADING_ALLOWANCE_PROFIT], errors="raise") + receipts, claimant = assign_trading_allowance_receipts( + person["person_id"].to_numpy(), profit.to_numpy(dtype=np.float64) + ) + person[TRADING_ALLOWANCE_RECEIPTS_OUTPUT] = receipts + + household_weights = frame.weights_for("household") + weight_by_household = dict( + zip( + household["household_id"].to_numpy(), + np.asarray(household_weights.values, dtype=float), + strict=True, + ) + ) + source_by_household = dict( + zip( + household["household_id"].to_numpy(), + source_household_ids( + household, stage=TRADING_ALLOWANCE_RECEIPTS_STAGE_NAME + ), + strict=True, + ) + ) + weights = person["person_household_id"].map(weight_by_household).to_numpy(float) + sources = person["person_household_id"].map(source_by_household).to_numpy() + rates = claimant_rates(profit.to_numpy(dtype=np.float64)) + trader = profit.to_numpy(dtype=np.float64) > 0.0 + bands: list[dict[str, object]] = [] + for rate in sorted(set(rates[trader].tolist()), reverse=True): + in_band = trader & (rates == rate) + supported = distinct_count(sources, in_band, weights) + weighted = float(weights[in_band].sum()) + bands.append( + { + "rate": rate, + "support": support_band(supported), + # Weighted totals over the band's traders at the spine's weights. + "weighted_traders": small_cell_share(weighted, supported), + "weighted_claimant_share": small_cell_share( + float(weights[in_band & claimant].sum()) / weighted + if weighted > 0.0 + else 0.0, + supported, + ), + } + ) + mass = MassChangeRecord( + entity="household", + old_total=household_weights.total, + new_total=household_weights.total, + declared_factor=1.0, + reason=TRADING_ALLOWANCE_RECEIPTS_MASS_CHANGE_REASON, + ) + result = uk_national_frame( + person=person, + benunit=frame.table("benunit").copy(), + household=household, + time_period=uk_time_period(frame), + weight_kind=uk_household_weight_kind(frame), + household_weights=household_weights.values, + mass_log=(*frame.mass_log, mass), + ) + validate_uk_national_frame(result) + return UKTradingAllowanceReceiptsResult( + frame=result, + traders=int(trader.sum()), + claimants=int(claimant.sum()), + bands=tuple(bands), + ) + + +def _assert_stage_parameters(stage: SourceStageSpec) -> None: + """Bind the stage's operation closed-world.""" + + if stage.stage != TRADING_ALLOWANCE_RECEIPTS_STAGE_NAME: + raise ValueError( + f"Trading allowance receipts received stage {stage.stage!r}, expected " + f"{TRADING_ALLOWANCE_RECEIPTS_STAGE_NAME!r}." + ) + expected = _expected_operations() + operations = tuple(stage.operations) + if tuple(operation.kind for operation in operations) != tuple( + kind for kind, _ in expected + ): + raise ValueError( + "trading_allowance_receipts operation order drifted: " + f"{[operation.kind for operation in operations]!r}." + ) + for operation, (kind, parameters) in zip(operations, expected, strict=True): + if dict(operation.parameters) != dict(parameters): + raise ValueError( + f"trading_allowance_receipts {kind} parameters drifted: " + f"{dict(operation.parameters)!r} != {dict(parameters)!r}." + ) + if tuple(stage.outputs) != (TRADING_ALLOWANCE_RECEIPTS_OUTPUT,): + raise ValueError( + f"{TRADING_ALLOWANCE_RECEIPTS_STAGE_NAME} must declare exactly the " + f"{TRADING_ALLOWANCE_RECEIPTS_OUTPUT} output." + ) + if stage.grain != "person": + raise ValueError( + f"{TRADING_ALLOWANCE_RECEIPTS_STAGE_NAME} is person grain, got " + f"{stage.grain!r}." + ) diff --git a/packages/microcosm-build/src/microcosm/build/uk_runtime/uc_take_up.py b/packages/microcosm-build/src/microcosm/build/uk_runtime/uc_take_up.py index 9d901698cc..a93fa5bd6c 100644 --- a/packages/microcosm-build/src/microcosm/build/uk_runtime/uc_take_up.py +++ b/packages/microcosm-build/src/microcosm/build/uk_runtime/uc_take_up.py @@ -119,6 +119,7 @@ "UC_TAKE_UP_ENTITLEMENT_VARIABLES", "UC_TAKE_UP_MINIMUM_POOL_SOURCES", "UC_TAKE_UP_OPERATION_KIND", + "UC_TAKE_UP_POOLING", "UC_TAKE_UP_RECORD_SETS", "UC_TAKE_UP_RESOURCE", "UC_TAKE_UP_STAGE_NAME", @@ -187,9 +188,20 @@ f"£{100 * _BOUND_BANDS}.01 or over", ) UC_TAKE_UP_MINIMUM_POOL_SOURCES = 30 +UC_TAKE_UP_POOLING = ( + "adjacent bands within a family type, lowest first, until the drawn units " + "rest on minimum_pool_sources distinct household_source_id values; a short " + "last pool joins the one before it. Then, lowest first, a pool that cannot " + "meet DWP's count (its undrawn entitled units' expected claims exceed the " + "count, or the count exceeds them plus the weight of every drawn unit) is " + "held at the nearer of those ends and passes its gap to the other pools, " + "nearest first, the one with more room first at equal distance and the " + "lower on a tie, each taking what its room allows; a gap no pool can take " + "leaves the family type unreachable" +) UC_TAKE_UP_RESIDUAL_RATE = ( "(T - F) / D, clipped to [0, 1]; T DWP's calendar-2025 mean count of the " - "pool's bands, D the weight of the pool's drawn units and F the expected " + "pool's bands after any gaps passed to or from it, D the weight of the pool's drawn units and F the expected " "claims of its other entitled units, over Great Britain at the stage's " "household weights; realized by the drawn units claiming in the order of " "their uniform until their weight is nearest T - F, and applied at that " @@ -332,6 +344,78 @@ def _pools( return pools +def _pass_unmet_gaps( + sums: Sequence[tuple[float, float, float]], +) -> tuple[list[float], list[float]]: + """Each pool's count after the unmet pools pass their gaps on. + + ``sums`` gives each pool's DWP count ``T``, the expected claims ``F`` of + its undrawn entitled units and the weight ``D`` of its drawn units, lowest + band first. A pool realizes between ``F`` and ``F + D`` claims; one whose + count lies outside is held at the nearer end, and its gap is the claims it + cannot add (a shortfall) or give up (an excess). A shortfall and an excess + offset each other in the family type's total, so they cancel first, nearest + pools first. What remains goes to the other pools, nearest first, the one + with more room first at equal distance and the lower on a tie, each taking + what its room allows (``F + D - T`` for a shortfall, ``T - F`` for an + excess). Joining an unmet pool to its neighbour applied one rate to both, + so the drawn units of an overshooting band started claiming and those of + a short band stopped; held at its clip, each band realizes as near its own + count as it can, and the family type's total is unchanged wherever its + entitled units allow (microcosm#1428 review, finding 7). Returns each + pool's count and the part of its gap no pool could take. + """ + + targets = [float(target) for target, _, _ in sums] + lows = [float(undrawn) for _, undrawn, _ in sums] + highs = [float(undrawn) + float(drawn) for _, undrawn, drawn in sums] + counts = [ + min(max(t, lo), hi) for t, lo, hi in zip(targets, lows, highs, strict=True) + ] + gaps = [t - count for t, count in zip(targets, counts, strict=True)] + for index, target in enumerate(targets): + if abs(gaps[index]) <= 1e-9 * max(1.0, abs(target)): + gaps[index] = 0.0 + + def nearest(index: int) -> list[int]: + return sorted( + (other for other in range(len(sums)) if other != index), + key=lambda other: (abs(other - index), other), + ) + + for index in range(len(sums)): + for other in nearest(index): + if gaps[index] == 0.0: + break + if gaps[index] * gaps[other] < 0.0: + offset = min(abs(gaps[index]), abs(gaps[other])) + gaps[index] -= np.sign(gaps[index]) * offset + gaps[other] -= np.sign(gaps[other]) * offset + for index, gap in enumerate(gaps): + if gap == 0.0: + continue + short = gap > 0.0 + + def room(other: int, *, short: bool = short) -> float: + return max( + highs[other] - counts[other] if short else counts[other] - lows[other], + 0.0, + ) + + remaining = abs(gap) + for other in sorted( + nearest(index), + key=lambda other: (abs(other - index), -room(other), other), + ): + take = min(remaining, room(other)) + counts[other] += take if short else -take + remaining -= take + if remaining <= 0.0: + break + gaps[index] = remaining if short else -remaining + return counts, gaps + + def _realized_rate( residual: float, *, need: float, draws: np.ndarray, weights: np.ndarray ) -> float: @@ -452,39 +536,50 @@ def assign_award_band_take_up( def sources(mask: np.ndarray) -> int: return distinct_count(source_ids, mask, weights) + def balance( + name: str, in_family: np.ndarray, bands: list[int] + ) -> tuple[float, float, float]: + solve = in_family & np.isin(band, bands) & gb + return ( + float(sum(targets[(name, index)] for index in bands)), + float((weights * fixed)[solve & ~drawable].sum()), + float(weights[solve & drawable].sum()), + ) + pools: list[dict[str, object]] = [] for name, _ in UC_FAMILY_TYPES: in_family = family == name - for bands in _pools( + family_pools = _pools( band=band, in_family=in_family, drawable_gb=drawable & gb, source_ids=source_ids, weights=weights, minimum_sources=minimum_pool_sources, + ) + sums = [balance(name, in_family, bands) for bands in family_pools] + counts, unplaced = _pass_unmet_gaps(sums) + feasible = not any(unplaced) + for bands, (target, undrawn, drawn), count in zip( + family_pools, sums, counts, strict=True ): in_pool = in_family & np.isin(band, bands) solve = in_pool & gb - target = float(sum(targets[(name, index)] for index in bands)) - undrawn = float((weights * fixed)[solve & ~drawable].sum()) - drawn = float(weights[solve & drawable].sum()) - # Where the undrawn claims reach DWP's count, or the count exceeds - # every entitled unit, the clipped rate cannot meet it. if drawn > 0.0: - residual = (target - undrawn) / drawn rates[in_pool & drawable] = _realized_rate( - residual, - need=target - undrawn, + (count - undrawn) / drawn, + need=count - undrawn, draws=draws[solve & drawable], weights=weights[solve & drawable], ) - else: - residual = 0.0 if undrawn >= target else 1.0 + # Where the undrawn claims reach DWP's count, or the count exceeds + # every entitled unit, the pool cannot meet it alone: it is held + # at its clip and its gap passed on. unreachable = ( "undrawn_claims_reach_target" - if residual <= 0.0 + if target <= undrawn else "target_exceeds_entitled" - if residual >= 1.0 + if target >= undrawn + drawn else None ) pools.append( @@ -494,6 +589,7 @@ def sources(mask: np.ndarray) -> int: "mask": solve, "target": target, "unreachable": unreachable, + "feasible_family": feasible, } ) would_claim = np.where(drawable, draws < rates, previous | reporter) @@ -526,7 +622,10 @@ def sources(mask: np.ndarray) -> int: ), } ) - if pool["unreachable"] is None: + # A family type whose gaps every pool could take realizes its + # count over all its pools; one whose count exceeds what its + # entitled units can realize has no reachable pool. + if pool["feasible_family"]: reachable |= solve reachable_target += float(pool["target"]) supported = sources(basis) @@ -946,12 +1045,7 @@ def uc_take_up_operation_parameters() -> tuple[tuple[str, dict[str, object]], .. "DWP Stat-Xplore Households on Universal Credit by family type " "and monthly award band, mean of April to December 2025" ), - "pooling": ( - "adjacent bands within a family type, lowest first, until the " - "drawn units rest on minimum_pool_sources distinct " - "household_source_id values; a short last pool joins the one " - "before it" - ), + "pooling": UC_TAKE_UP_POOLING, "minimum_pool_sources": UC_TAKE_UP_MINIMUM_POOL_SOURCES, "drawn_units": ( "entitled, non-reporting units of the population that the " diff --git a/packages/microcosm-build/tests/engine/uk/test_uk_hmrc_uprating.py b/packages/microcosm-build/tests/engine/uk/test_uk_hmrc_uprating.py index 8092026019..b98f756458 100644 --- a/packages/microcosm-build/tests/engine/uk/test_uk_hmrc_uprating.py +++ b/packages/microcosm-build/tests/engine/uk/test_uk_hmrc_uprating.py @@ -35,10 +35,11 @@ def test_spi_band_targets_move_by_the_engines_dataset_projection() -> None: (microcosm#1418); Table 3.10's amounts move by their count index times the engine's index for self-employment income (the independent review of microcosm#1420); and a measure derived from an input moves by the input's - index. The SPI donors still reach the dataset's year by savings interest's - own history index and run on the projection's from there - (``spi_income.SPI_HISTORY_INDEX_DIFFERS_FROM_PROJECTION``), so both are - held to the engine's.""" + index. The SPI donors reach the dataset's year with interest and other + income on SPI's 2023-24 bands and the OBR's savings income growth (the + microcosm#1418 savings follow-up) and run on the projection's index from + there (``spi_income.SPI_HISTORY_INDEX_DIFFERS_FROM_PROJECTION``), so the + projection's index is held to the engine's.""" import json from importlib.resources import files @@ -74,7 +75,8 @@ def test_spi_band_targets_move_by_the_engines_dataset_projection() -> None: } variables = policyengine_uk.CountryTaxBenefitSystem().variables assert SPI_HISTORY_INDEX_DIFFERS_FROM_PROJECTION == { - "savings_interest_income": UK_SPI_SAVINGS_INTEREST_PROJECTION_PARAMETER + "savings_interest_income": UK_SPI_SAVINGS_INTEREST_PROJECTION_PARAMETER, + "other_investment_income": projection["other_investment_income"], } assert ( UK_SPI_SAVINGS_INTEREST_PROJECTION_PARAMETER @@ -120,11 +122,13 @@ def test_spi_band_targets_move_by_the_engines_dataset_projection() -> None: assert len(checked) > 1 -def test_savings_interest_targets_take_the_donors_path() -> None: - """The SPI donors reach 2025 by the history index to the frame's year, - then the engine's projection. The band targets took the same path until - they moved to the OBR's savings income forecast (microcosm#1418), so the - gap between the two is now the calibration's to close.""" +def test_the_two_leg_savings_interest_factor() -> None: + """Savings interest outside SPI Table 3.7's rows reaches 2025 by the history + index to the frame's year, then the engine's projection (microcosm#1095). + The SPI donors and Table 3.7's rows took the same path until + microcosm#1418, when they moved to the published 2023-24 bands and the + OBR's savings income growth; the earlier start below pins only the + history index's 2022-23 step (the #1428 review, finding 13).""" history = "gov.economic_assumptions.indices.ons.household_interest_income" projection = "gov.economic_assumptions.indices.obr.per_capita.gdp" @@ -135,13 +139,13 @@ def ratio(path: str, start: int, end: int) -> float: ) target_factor = ratio(history, 2023, 2024) * ratio(projection, 2024, 2025) - donor_path = ratio(history, 2022, 2024) * ratio(projection, 2024, 2025) + earlier_start = ratio(history, 2022, 2024) * ratio(projection, 2024, 2025) # 1.1920 until policyengine-uk 2.155.0 took population from the OBR's # March 2026 long-term determinants (PolicyEngine/policyengine-uk#2611), # and 1.1961 until 2.164.1's October 2026 outlook (microcosm#1415). assert target_factor == pytest.approx(1.1932, abs=1e-4) - # The donors start a year earlier and so carry one more year of history. - assert donor_path / target_factor == pytest.approx( + # A path starting a year earlier carries one more year of history. + assert earlier_start / target_factor == pytest.approx( ratio(history, 2022, 2023), rel=1e-12 ) diff --git a/packages/microcosm-build/tests/engine/uk/test_uk_release_input_coverage.py b/packages/microcosm-build/tests/engine/uk/test_uk_release_input_coverage.py index 40eea7a7b7..aa152cecbe 100644 --- a/packages/microcosm-build/tests/engine/uk/test_uk_release_input_coverage.py +++ b/packages/microcosm-build/tests/engine/uk/test_uk_release_input_coverage.py @@ -474,6 +474,7 @@ def test_shipped_manifest_is_current(self) -> None: "was_wealth", "was_lisa", "isa_subscriptions", + "trading_allowance_receipts", "regional_property_uprating", "high_value_home_support", "regional_home_values", diff --git a/packages/microcosm-build/tests/engine/uk/test_uk_spi_income.py b/packages/microcosm-build/tests/engine/uk/test_uk_spi_income.py index 174e03e7ac..60b8200d33 100644 --- a/packages/microcosm-build/tests/engine/uk/test_uk_spi_income.py +++ b/packages/microcosm-build/tests/engine/uk/test_uk_spi_income.py @@ -1,6 +1,8 @@ """Tests split from packages/microcosm-build/tests/test_uk_spi_income.py.""" # ruff: noqa: F403, F405 +from microcosm.build.uk_runtime.hmrc_uprating import uk_obr_savings_income_level +from microcosm.build.uk_runtime.spi_income import SPI_SAVINGS_REBASE_CONCEPTS from test_support.microcosm_build.uk_spi_income import * @@ -45,7 +47,8 @@ def test_spi_preserves_observed_children_outside_the_donor_age_domain( ) assert result.spi_prediction_rows == int(person[channel].eq("spi").sum()) - 1 adults = person[channel].eq("spi") & person.age.ge(16) - assert result.person.loc[adults, "gift_aid"].eq(10).all() + factor = result.gift_anchor["factors"]["gift_aid"] + assert result.person.loc[adults, "gift_aid"].eq(10.0 * factor).all() def test_spi_rebases_income_before_frs_fill_and_preserves_child_inputs( @@ -66,9 +69,23 @@ def test_spi_rebases_income_before_frs_fill_and_preserves_child_inputs( monkeypatch.setattr( spi_income, "_spi_income_uprating_factors", - lambda year: (factors, {"from_period": 2022, "to_period": year}), + lambda year, *, rebased_columns=None: ( + factors, + {"from_period": 2022, "to_period": year}, + ), raising=False, ) + # The donor savings rebase runs on the prepared tape when the stage rebases + # to the build year, and only then (microcosm#1418 savings follow-up), + # banding the tape on its income moved to 2023-24 (microcosm#1428). + rebased = [] + + def rebase(donor, published, *, income_factors=None): + rebased.append(sorted(published)) + assert income_factors == factors + return donor, {"rebased": True, "columns": {}} + + monkeypatch.setattr(spi_income, "rebase_spi_donor_savings", rebase) options = dict( seed=9, n_estimators=3, @@ -77,6 +94,7 @@ def test_spi_rebases_income_before_frs_fill_and_preserves_child_inputs( allow_in_sample_reference=True, ) reference = impute_uk_spi_income_support(support, donor_path, **options) + assert rebased == [] result = impute_uk_spi_income_support( support, donor_path, @@ -102,7 +120,12 @@ def test_spi_rebases_income_before_frs_fill_and_preserves_child_inputs( result.person.loc[base, "dividend_income"], person.loc[base, "dividend_income"], ) - assert result.income_uprating == {"from_period": 2022, "to_period": 2024} + assert rebased == [sorted(SPI_SAVINGS_REBASE_CONCEPTS)] + assert result.income_uprating == { + "from_period": 2022, + "to_period": 2024, + "savings_rebase": {"rebased": True, "columns": {}}, + } def test_child_exclusion_keeps_the_other_recipients_draws( @@ -394,8 +417,19 @@ def test_spi_qrf_stages_use_typed_weights_and_keep_isa_interest_apart( .all() ) assert result.person.loc[spi_people, "other_investment_income"].eq(25.0).all() - assert result.person.loc[spi_people, "gift_aid"].eq(10.0).all() - assert result.person.loc[spi_people, "charitable_investment_gifts"].eq(2.0).all() + # The gift leaves are the forest's draws scaled to the tape's FACT-weighted + # totals, 300 of Gift Aid and 30 of investment gifts (microcosm#1428). + factors = result.gift_anchor["factors"] + weights = result.person.loc[spi_people, "person_household_id"].map( + support.household.set_index("household_id")["household_weight"] + ) + for column, draw, tape in ( + ("gift_aid", 10.0, 300.0), + ("charitable_investment_gifts", 2.0, 30.0), + ): + gifts = result.person.loc[spi_people, column] + assert gifts.eq(draw * factors[column]).all() + assert (weights * gifts).sum() == pytest.approx(tape) assert ( result.person.loc[ spi_people, @@ -712,6 +746,10 @@ def test_spi_uprating_uses_actual_engine_indices_and_explicit_nominal_holdouts() for column, row in receipt["columns"].items() if row["basis"] == "held_nominal" } == nominal + # Interest and other income are rebased to SPI's 2023-24 bands first and + # grow on the OBR's savings income path from there (microcosm#1418 savings + # follow-up). + obr_level, _ = uk_obr_savings_income_level(2023, 2024) for column, row in receipt["columns"].items(): if column in nominal: assert row == { @@ -720,6 +758,10 @@ def test_spi_uprating_uses_actual_engine_indices_and_explicit_nominal_holdouts() "factor": 1.0, "basis": "held_nominal", } + elif column in SPI_SAVINGS_REBASE_CONCEPTS: + assert row["basis"] == "spi_published_bands_then_obr_savings_income" + assert row["from_period"] == 2023 + assert factors[column] == pytest.approx(obr_level) else: path, ratio = expected[row["variable"]] assert row["index"] == "gov.economic_assumptions.indices." + path @@ -779,13 +821,13 @@ def test_spi_rebasing_index_is_the_projections_except_where_named() -> None: else: assert row["index"] == projection[row["variable"]], column assert "dataset_projection_index" not in row - savings = receipt["columns"]["savings_interest_income"] - assert savings["index"] == ( - "gov.economic_assumptions.indices.ons.household_interest_income" - ) - # 2.2692 until policyengine-uk 2.164.1's October 2026 outlook revised the - # ONS interest history (microcosm#1415). - assert savings["factor"] == pytest.approx(2.2686, abs=1e-4) + # Interest and other income reach the frame's year on SPI's own path, the + # 2023-24 bands then the OBR's savings income growth (+35.0% in 2024-25), + # and run on the projection's GDP per head from there. + for column in SPI_SAVINGS_REBASE_CONCEPTS: + savings = receipt["columns"][column] + assert savings["index"] == "obr.efo_2026_10.savings_income_growth" + assert savings["factor"] == pytest.approx(1.3496108, abs=1e-7) def _zero_taxable_income(person: pd.DataFrame, rows) -> None: @@ -847,7 +889,8 @@ def test_undrawn_twins_keep_their_values_and_are_receipted( result.person.loc[copy[0], kept], person.loc[copy[0], kept], check_names=False ) others = person.index[(person[channel] == "spi") & (person["age"] >= 16)].drop(copy) - assert result.person.loc[others, "gift_aid"].eq(10.0).all() + factor = result.gift_anchor["factors"]["gift_aid"] + assert result.person.loc[others, "gift_aid"].eq(10.0 * factor).all() # The stage flags the rows it drew, and only those, for the later stages # that tell tape-concept rows from FRS-concept ones. flag = result.person["person_is_spi_income_recipient"] 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 dc7648f379..eb61c03f90 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 @@ -945,6 +945,7 @@ def test_spi_spine_adds_no_country_package_resources(self) -> None: "bonus_sacrifice_anchor.json", "obr_salary_sacrifice_costing_facts.json", "obr_savings_income_growth_facts.json", + "hmrc_spi_table_3_7_savings_rows.json", "slc_liable_stocks.json", "hmrc_income_release_gate_report.json", "hmrc_income_replay_report.json", @@ -1053,8 +1054,9 @@ def test_uk_source_manifest_contains_only_canonical_spine_stages(self) -> None: # uc_capital_coherence; microcosm#1319 carers_allowance_take_up after # child_benefit_take_up; childcare_copy_take_up last, after every copy # stage; microcosm#1334 uc_take_up after uc_capital_coherence and - # frs_annual_income_spells after frs_hmrc_spine_leaves. - assert len(spec.sources.stages) == 50 + # frs_annual_income_spells after frs_hmrc_spine_leaves; microcosm#1428 + # trading_allowance_receipts last. + assert len(spec.sources.stages) == 51 assert not {"frs_hmrc_retained_leaves", "hmrc_spi_income"}.intersection( stage.stage for stage in spec.sources.stages ) @@ -1108,6 +1110,7 @@ def test_uk_package_loads(self) -> None: "bonus_sacrifice_anchor.json", "obr_salary_sacrifice_costing_facts.json", "obr_savings_income_growth_facts.json", + "hmrc_spi_table_3_7_savings_rows.json", "slc_liable_stocks.json", "hmrc_income_release_gate_report.json", "hmrc_income_replay_report.json", diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_fit_weight_records_roster.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_fit_weight_records_roster.py new file mode 100644 index 0000000000..2fc979ec50 --- /dev/null +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_fit_weight_records_roster.py @@ -0,0 +1,69 @@ +"""Which UK stage transforms declare fit-weight records (microcosm#1428). + +The release-cut weights audit reads an empty list of fit-weight records as a +fitting stage that recorded nothing, and fails (``uk_weights_audit``). The ISA +subscriptions stage declared an empty tuple although it fits no model, and +every national certified after #1421 failed. This roster pins the stage +transforms that declare the hook, read from the source so it runs without +the engine: a new one must be reviewed, and either record each fit it makes +or declare nothing (the #1428 review, finding 3). +""" + +from __future__ import annotations + +import ast +from pathlib import Path + +from microcosm.build import uk_runtime + +#: The stage transforms that fit a model and record its weights. +FITTING_STAGE_TRANSFORMS = frozenset( + { + "etb_services.UKETBServicesStageTransform", + "etb_vat.UKETBVATStageTransform", + "lcfs_consumption.UKLCFSConsumptionStageTransform", + "nts_bus_travel.UKNTSBusTravelStageTransform", + "property_components.UKPropertyComponentsStageTransform", + "spi_spine.UKSPIIncomeSpineStageTransform", + "was_lisa.UKWASLISAStageTransform", + "was_wealth.UKWASWealthStageTransform", + } +) + + +def _declares_hook(node: ast.ClassDef) -> bool: + for item in node.body: + if ( + isinstance(item, ast.FunctionDef | ast.AsyncFunctionDef) + and item.name == "fit_weight_records" + ): + return True + if isinstance(item, ast.AnnAssign | ast.Assign) and "fit_weight_records" in { + target.id + for target in ( + [item.target] if isinstance(item, ast.AnnAssign) else item.targets + ) + if isinstance(target, ast.Name) + }: + return True + return False + + +def test_only_the_reviewed_stage_transforms_declare_fit_weight_records() -> None: + declared = set() + for path in sorted(Path(uk_runtime.__file__).parent.glob("*.py")): + tree = ast.parse(path.read_text(encoding="utf-8")) + for node in ast.walk(tree): + if ( + isinstance(node, ast.ClassDef) + and node.name.endswith("StageTransform") + and _declares_hook(node) + ): + declared.add(f"{path.stem}.{node.name}") + assert declared == FITTING_STAGE_TRANSFORMS + + +def test_the_isa_subscriptions_stage_declares_nothing() -> None: + assert "isa_subscriptions.UKISASubscriptionsStageTransform" not in ( + FITTING_STAGE_TRANSFORMS + ) 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 1b863ab4b9..5aa108e0aa 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 @@ -393,13 +393,29 @@ def _fixture_tables() -> dict[str, list[dict[str, object]]]: "SERNUM": 1, "BENUNIT": 1, "PERSON": 1, + "PENTYPE": 1, "PENPAY": 10.0, "PTAMT": 2.0, "PTINC": 2, "POAMT": 3.0, "POINC": 2, "PENOTH": 0, - } + }, + # Income from a trust (PENTYPE 5) stays private pension income, + # where the engine's means tests read it; its part is stored for + # SPI Table 3.7's other income (microcosm#1428). + { + "SERNUM": 2, + "BENUNIT": 1, + "PERSON": 1, + "PENTYPE": 5, + "PENPAY": 6.0, + "PTAMT": 0.0, + "PTINC": 0, + "POAMT": 0.0, + "POINC": 0, + "PENOTH": 0, + }, ], "oddjob": [{"SERNUM": 1, "BENUNIT": 1, "PERSON": 1, "OJAMT": 4.0, "OJNOW": 1}], "accounts": [ @@ -430,8 +446,9 @@ def _fixture_tables() -> dict[str, list[dict[str, object]]]: "ACCTAX": 0, "INVTAX": 0, }, - # Other interest (microcosm#1418): an NS&I Direct Saver paid after - # tax and a gilt paid after tax, both grossed up at the basic rate. + # An NS&I Direct Saver paid after tax, deposit interest since + # microcosm#1428 (SPI Table 3.7 note 4), and a gilt paid after tax, + # other interest (microcosm#1418), both grossed up at the basic rate. { "SERNUM": 1, "BENUNIT": 1, @@ -1247,12 +1264,20 @@ def test_direct_person_mapping_values_are_ported(tmp_path: Path) -> None: assert adult["individual_savings_account_interest_income"] == pytest.approx( 1 * WEEKS_IN_YEAR ) - assert adult["savings_interest_income"] == pytest.approx(2.5 * WEEKS_IN_YEAR) + # The current account (2 x 1.25) and the NS&I Direct Saver (2 x 1.25), + # deposit interest since microcosm#1428 (SPI Table 3.7 note 4). + assert adult["savings_interest_income"] == pytest.approx(5.0 * WEEKS_IN_YEAR) assert "tax_free_savings_income" not in adult # The gilt is other interest, no longer a dividend (microcosm#1418). assert adult["dividend_income"] == pytest.approx(3 * WEEKS_IN_YEAR) - assert adult["other_investment_income"] == pytest.approx(7.5 * WEEKS_IN_YEAR) + assert adult["other_investment_income"] == pytest.approx(5.0 * WEEKS_IN_YEAR) + # Household 2's trust income stays private pension, where the engine's + # means tests and household income read it, and its part is stored as + # the descriptor SPI Table 3.7's other-income measure adds (microcosm#1428). assert other["other_investment_income"] == 0.0 + assert other["private_pension_income"] == pytest.approx(6.0 * WEEKS_IN_YEAR) + assert other["annuity_and_trust_income"] == pytest.approx(6.0 * WEEKS_IN_YEAR) + assert adult["annuity_and_trust_income"] == 0.0 # ROYYR1 2 only: CVPAY (1 a week) is rent the adult pays as a lodger # (rent_paid_as_lodger, pe-uk#2006), not their own income, and household 1 # does not sub-let. @@ -1564,6 +1589,21 @@ def test_frs_spine_refuses_an_adult_tab_without_alimony( build_uk_frs_spine_frame(tmp_path, stage=stage) +def test_frs_spine_refuses_a_pension_tab_without_pentype(tmp_path: Path) -> None: + """A vintage without PENTYPE refuses; it never reads every annuity and + trust payment as a pension (microcosm#1428).""" + + tables = _fixture_tables() + tables["pension"] = [ + {key: value for key, value in row.items() if key != "PENTYPE"} + for row in tables["pension"] + ] + stage = _write_fixture(tmp_path, tables) + + with pytest.raises(ValueError, match="PENTYPE"): + build_uk_frs_spine_frame(tmp_path, stage=stage) + + def test_frs_spine_refuses_an_adult_tab_without_sppadj(tmp_path: Path) -> None: """A vintage without SPPADJ refuses; it never sets nobody's paternity pay.""" 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 1e126d1d19..55241b8b77 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 @@ -59,8 +59,9 @@ def test_uk_spine_graph_contains_every_manifest_stage() -> None: # adds property_purchases and uc_legacy_closure_take_up, microcosm#1112 # regional_home_values, microcosm#1319 carers_allowance_take_up, the # copies' childcare re-draw childcare_copy_take_up, and microcosm#1334 - # uc_take_up and frs_annual_income_spells. - assert len(expected) == 50 + # uc_take_up and frs_annual_income_spells; microcosm#1428 the last stage, + # trading_allowance_receipts. + assert len(expected) == 51 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_isa_subscriptions.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_isa_subscriptions.py index 9b0697df75..b11dc5592b 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_isa_subscriptions.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_isa_subscriptions.py @@ -9,6 +9,7 @@ import pytest from microcosm.build.source_manifest import SourceOperationSpec +from microcosm.build.stage_evidence import snapshot_stage_evidence from microcosm.build.uk_runtime import isa_subscriptions as stage from microcosm.build.uk_runtime.cgt_imputation import ( UK_CGT_TAXABLE_INCOME_PROXY_COMPONENTS, @@ -392,6 +393,17 @@ def test_the_whole_stage_writes_its_columns_within_every_invariant(statistics): assert gate.passed, (gate_id, gate.failures) +def test_the_stage_declares_no_fit_weight_records(statistics): + """The stage fits no model. A declared empty list read as a fitting stage + that recorded nothing, which failed the release-cut weights audit + (microcosm#1428).""" + + transform = _transform(statistics) + transform(_stage_frame()) + evidence = snapshot_stage_evidence("isa_subscriptions", transform) + assert "fit_weight_records" not in evidence + + def test_reordering_the_rows_moves_no_draw(statistics): """Every draw is keyed on identity, so row order moves none. @@ -550,7 +562,8 @@ def test_the_committed_declaration_carries_the_tested_operations(): lisa = {artifact["role"]: artifact for artifact in stages["was_lisa"].artifacts} for role in ("was_qrf_donor", "was_person_tab"): assert roles[role] == lisa[role] - assert list(stages)[-1] == "isa_subscriptions" + # Only the self-employed's gross receipts run after it (microcosm#1428). + assert list(stages)[-2:] == ["isa_subscriptions", "trading_allowance_receipts"] def test_no_calibration_target_reads_an_isa_fact(): 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 6e8fa3d3e8..d0ab4852a5 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 @@ -13,6 +13,7 @@ from microcosm.build.uk_runtime.income_tax_rate_classes import UK_RATE_CLASS_ALLOCATION from microcosm.build.uk_runtime.measure_simulation import ( UK_SAVINGS_INTEREST_OUTSIDE_ISAS, + UK_SPI_OTHER_INVESTMENT_INCOME, UKMeasureResolver, apply_uk_calibration_measure_exclusions, compute_uk_measure_input, @@ -606,6 +607,9 @@ def test_exclusion_applier_warns_within_week_of_expiry(): # stage assigns no postgraduate plan) and Plan 5's liable stock binds; the # Plan 5 repayments and the two Plan 2 stocks stay. "_1_000_000_to_inf": 10, + # The SPI Table 3.7 £1m-and-over interest amount row, held on the savings + # follow-up's measured distortion (microcosm#1428, 2026-10-30). + "hmrc.spi.savings_interest_income.amount_by_total_income_band.band_1000000": 1, "slc.": 3, # microcosm#1095 (2026-10-07): two bands whose few supporting awards # policyengine-uk 2.122.2 moves out join the uk-data#452 class. @@ -734,8 +738,10 @@ def test_packaged_exclusions_load(): # electricity row again (María's ruling of 2026-10-28), and holds the ONS # gas row again for bottled gas (María's ruling of 2026-10-29). The # betting and gaming row stays held: the solve cannot yet measure its - # 2024 duty (microcosm#1420). - assert len(names) == len(set(names)) == 39 + # 2024 duty (microcosm#1420). The savings follow-up holds the SPI £1m-and-over + # interest amount row on its measured distortion (microcosm#1428, María's + # ruling of 2026-10-30). + assert len(names) == len(set(names)) == 40 (gas,) = [ entry for entry in exclusions @@ -2070,6 +2076,62 @@ def test_the_resolver_routes_interest_outside_isas_to_persons( ) +def _annuity_frame() -> FrameStub: + """A pensioner with a purchased annuity inside the stored pension, a + gilt holder, and a person with no stored pension (microcosm#1428).""" + + frame = FrameStub() + frame._tables["person"] = frame._tables["person"].assign( + private_pension_income=[4_000.0, 0.0, 0.0], + annuity_and_trust_income=[1_000.0, 0.0, 0.0], + ) + return frame + + +def test_spi_other_income_adds_the_annuity_and_trust_part_of_pensions(): + """SPI Table 3.7's other income counts purchased-annuity and trust + payments, which FRS rows keep in private pension for the engine's means + tests: the measure adds their share of the engine's pension, so they grow + on its private pension path (microcosm#1428).""" + + simulation = SimulationStub( + { + "other_investment_income": ("person", np.array([0.0, 500.0, 0.0])), + "private_pension_income": ("person", np.array([4_400.0, 0.0, 0.0])), + } + ) + values, route = compute_uk_measure_input( + _annuity_frame(), simulation, "person", UK_SPI_OTHER_INVESTMENT_INCOME, 2025 + ) + # A quarter of the stored pension, grown by the engine's 10%. + np.testing.assert_allclose(values, [1_100.0, 500.0, 0.0]) + assert route.startswith("engine_components:other_investment_income") + # A frame without the descriptor (the enhanced FRS reference) reads the + # engine's other income alone. + np.testing.assert_allclose( + compute_uk_measure_input( + FrameStub(), simulation, "person", UK_SPI_OTHER_INVESTMENT_INCOME, 2025 + )[0], + [0.0, 500.0, 0.0], + ) + with pytest.raises(KeyError, match="person-only"): + compute_uk_measure_input( + _annuity_frame(), + simulation, + "household", + UK_SPI_OTHER_INVESTMENT_INCOME, + 2025, + ) + + +def test_the_spi_other_income_rows_read_the_annuity_measure(): + targets = measure_simulation._uk_contract_targets() + binding = targets["hmrc.spi.other_investment_income.amount_by_total_income_band"][ + "bindings" + ]["policyengine"] + assert binding["value_variable"] == UK_SPI_OTHER_INVESTMENT_INCOME + + def _stub_engine_term_calendar(monkeypatch) -> None: """policyengine-uk's year of terms, without the engine installed.""" diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_pension_age_benefit_targets.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_pension_age_benefit_targets.py index d02836f8c0..35bcfb49b4 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_pension_age_benefit_targets.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_pension_age_benefit_targets.py @@ -160,3 +160,50 @@ def test_winter_fuel_diagnostic_carries_the_published_count() -> None: assert metadata[f"{prefix}_status"] == "available" assert float(metadata[f"{prefix}_value_count"]) == 11_003_237 assert metadata[f"{prefix}_ledger_geography_id"] == "K04000001" + + +def test_income_based_jsa_spending_reads_the_dwp_calendar_window() -> None: + # DWP's income-based JSA line beside OBR's total JSA, so the solve meets + # OBR's total on contributory claimants (microcosm#1428; its review's + # finding 12 asked for this pin, as the Housing Benefit row has). + target = _targets()["dwp.jsa.amount_income_based"] + selector = target["ledger_selector"] + assert selector["source_concept"] == "dwp.benefit_expenditure_amount" + assert selector["dimension_values"] == { + "benefit_forecast_line": ( + "unemployment_benefits__jobseekers_allowance__income_based" + ) + } + assert target["value_operation"] == "calendar_year_window" + assert selector["source_measure_id_by_opening_year"] == { + "2024": "expenditure_2024", + "2025": "expenditure_2025", + } + assert target["assertion_policy"] == "allow_source_projection" + assert target["family"] == "dwp_benefit_expenditure" + binding = target["bindings"]["policyengine"] + assert binding["value_variable"] == "jsa_income" + assert binding["from_entity"] == "benunit" + assert "filters" not in binding + # Great Britain, the scope of DWP's line. + (condition,) = binding["household_conditions"] + assert condition["variable"] == "region" + assert "NORTHERN_IRELAND" not in condition["value"] + + +def test_the_table_3_10_employment_counts_read_annual_pay_by_profit_band() -> None: + # Table 3.10's individuals with employment income over the self-employment + # bands from GBP 1 to GBP 10,000 (microcosm#1428; review finding 12). + target = _targets()[ + "hmrc.spi.employment_income.count_by_self_employment_income_band" + ] + binding = target["bindings"]["policyengine"] + assert binding["value_variable"] == "person_count" + assert binding["groupby_variable"] == ( + "self_employment_income_after_loss_relief_annual" + ) + assert binding["filters"] == [ + {"variable": "employment_income_annual", "operator": "!=", "value": 0} + ] + assert binding["band_upper_bound"] == 10_000 + assert binding["band_upper_bound_inclusive"] is False 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 50bb70db71..a017b658a7 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 @@ -258,8 +258,9 @@ def test_uk_population_targets_shape_order_and_registry_accounting() -> None: # rates, three national rows, SPI pension income and the taxpayers with # it by constituency and local authority, SPI Table 3.7's other income by # total-income band, and SPI Table 3.10's self-employment counts and - # amounts by self-employment band. - assert len(resource["targets"]) == 456 + # amounts by self-employment band and the counts with employment income + # among them, and DWP's income-based Jobseeker's Allowance spending. + assert len(resource["targets"]) == 458 providers = resource["hierarchy"]["providers"] categories = resource["hierarchy"]["categories"] @@ -273,10 +274,10 @@ 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) == 394 + assert len(registry_scope) == 396 assert len(profile_scope) == 62 - assert target_ids[:394] == registry_scope - assert target_ids[394:] == profile_scope + assert target_ids[:396] == registry_scope + assert target_ids[396:] == profile_scope parity = resource["registry_parity"] assert parity["pinned_ref"] == "12a1e028afeef08d8b2d74ee03fd9de3a78b2dd3" @@ -303,9 +304,10 @@ def test_uk_population_targets_shape_order_and_registry_accounting() -> None: # OBR excise rows have no uk-data metric (uk-data never measured excise # duty), nor microcosm#1069's two Income Tax payer by age rows, nor # microcosm#1418's three Income Tax on savings rows, its SPI other income - # row or its two Table 3.10 rows. + # row or its three Table 3.10 rows, nor microcosm#1428's income-based JSA + # spending row. assert len(mapped_target_ids) == 183 - assert len(unmapped_declarations) == 211 + assert len(unmapped_declarations) == 213 suppressed_ancestors = parity["suppressed_ancestors"] assert len(suppressed_ancestors) == 5 assert set(suppressed_ancestors).isdisjoint(parity["mapped"]) @@ -812,7 +814,7 @@ 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) == 456 + assert len(target_ids) == 458 assert len(target_ids) == len(set(target_ids)) @@ -1315,7 +1317,7 @@ 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) == 456 + assert len(targets) == 458 assert not any( f.get("variable") == "uc_calibration_child_entitlement" for target in targets @@ -1565,7 +1567,7 @@ def test_household_composition_cells_do_not_share_the_household_total_signature( def test_only_the_uc_award_bands_read_whole_pence() -> None: """microcosm#1095: the four UC payment families opt in to whole-pence, - upper-closed bands; the other 31 banded bindings keep the half-open + upper-closed bands; the other 32 banded bindings keep the half-open reading.""" banded = { @@ -1578,7 +1580,7 @@ def test_only_the_uc_award_bands_read_whole_pence() -> None: for target_id, binding in banded.items() if binding.get("band_semantics") == "whole_pence_upper_closed" } - assert len(banded) == 35 + assert len(banded) == 36 assert whole_pence == { f"dwp.uc.payment_distribution_{family}" for family in ( diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_private_school_attendance.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_private_school_attendance.py index cc02204d5c..a163fbb496 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_private_school_attendance.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_private_school_attendance.py @@ -107,15 +107,19 @@ def test_the_stage_needs_the_stored_draw_and_writes_attendance_once(): store_private_school_attendance(stored, engine=engine, calibration_year=2025) -def test_only_the_isa_subscriptions_follow_the_stage(): +def test_only_the_isa_subscriptions_and_receipts_follow_the_stage(): """No later stage copies or re-keys a person, so the stored flags reach - the release as the engine set them. Only the ISA subscriptions follow it, - writing person ISA columns on the rows they are given (microcosm#1415).""" + the release as the engine set them. Only the ISA subscriptions and the + self-employed's gross receipts follow it, each writing person columns on + the rows they are given (microcosm#1415, microcosm#1428).""" stages = load_country_spec("uk").sources.stages names = [stage.stage for stage in stages] later = stages[names.index("private_school_attendance") + 1 :] - assert [stage.stage for stage in later] == ["isa_subscriptions"] + assert [stage.stage for stage in later] == [ + "isa_subscriptions", + "trading_allowance_receipts", + ] for stage in later: assert PRIVATE_SCHOOL_ATTENDANCE_OUTPUT not in { *stage.outputs, 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 ca36548984..eb56bae3f4 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 @@ -122,9 +122,12 @@ "childcare_copy_take_up", # microcosm#1095: the stored private-school attendance runs after them. "private_school_attendance", - # microcosm#1415: the ISA subscriptions run last, on final incomes; nothing - # reads their outputs. + # microcosm#1415: the ISA subscriptions run after them, on final incomes; + # nothing reads their outputs. "isa_subscriptions", + # microcosm#1428: the self-employed's gross receipts run last, on final + # profits; only the engine's trading allowance reads them. + "trading_allowance_receipts", ] UK_SOURCE_STAGE_NAMES = [ "frs_spine", @@ -312,6 +315,7 @@ def test_country_stage_plan_assembles_spine_plan(self) -> None: "student_loans": _identity, "private_school_attendance": _identity, "isa_subscriptions": _identity, + "trading_allowance_receipts": _identity, "childcare_copy_take_up": _identity, "age_tail": _identity, "frs_relationships": _identity, diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_spi_savings_rebase.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_spi_savings_rebase.py new file mode 100644 index 0000000000..fa214784b1 --- /dev/null +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_spi_savings_rebase.py @@ -0,0 +1,438 @@ +"""The SPI donors' savings rebase (microcosm#1418 savings follow-up). + +The 2022-23 tape's interest and other income move to HMRC's published +2023-24 Table 3.7 amounts band by band, then on the OBR's savings income +growth to the frame's year, in place of each column's engine index. +""" + +from __future__ import annotations + +import sys +from types import SimpleNamespace + +import pandas as pd +import pytest + +from microcosm.build.uk_runtime import spi_income +from microcosm.build.uk_runtime.hmrc_uprating import uk_obr_savings_income_level +from microcosm.build.uk_runtime.spi_income import ( + SPI_HISTORY_INDEX_DIFFERS_FROM_PROJECTION, + SPI_SAVINGS_REBASE_CONCEPTS, + SPI_SAVINGS_REBASE_YEAR, + rebase_spi_donor_savings, + spi_savings_rebase_published, +) + +PUBLISHED = { + "savings_interest_income": {12_570: 1_500.0, 50_000: 2_000.0, 1_000_000: 3_000.0}, + "other_investment_income": {12_570: 400.0, 50_000: 400.0, 1_000_000: 18_000.0}, +} + + +def _rows(amounts): + return [ + { + "concept": SPI_SAVINGS_REBASE_CONCEPTS[column], + "period": {"type": "tax_year", "value": SPI_SAVINGS_REBASE_YEAR}, + "dimensions": {"total_income_lower_bound": bound}, + "value": value, + } + for column, by_bound in amounts.items() + for bound, value in by_bound.items() + ] + + +def _donor() -> pd.DataFrame: + return pd.DataFrame( + { + "total_income": [5_000.0, 15_000.0, 15_000.0, 50_000.0, 2_000_000.0], + "FACT": [10.0, 5.0, 5.0, 2.0, 1.0], + "savings_interest_income": [100.0, 40.0, 60.0, 500.0, 1_000.0], + "other_investment_income": [0.0, 10.0, 30.0, 100.0, 9_000.0], + "dividend_income": [1.0, 2.0, 3.0, 4.0, 5.0], + } + ) + + +def test_the_rebased_tape_reproduces_the_published_bands() -> None: + donor = _donor() + rebased, receipt = rebase_spi_donor_savings(donor, PUBLISHED) + + # A donor at a band's lower bound sits in that band. + rows_by_band = {12_570: [1, 2], 50_000: [3], 1_000_000: [4]} + for column, by_bound in PUBLISHED.items(): + for bound, rows in rows_by_band.items(): + weighted = rebased.loc[rows, column] * rebased.loc[rows, "FACT"] + assert weighted.sum() == pytest.approx(by_bound[bound]) + # Interest: the tape's 500, 1,000 and 1,000 against 1,500, 2,000 and + # 3,000; a donor below the first band takes all bands' 6,500 over 2,500. + assert receipt["columns"]["savings_interest_income"]["band_factors"] == { + "12570": 3.0, + "50000": 2.0, + "1000000": 3.0, + } + assert rebased.loc[0, "savings_interest_income"] == pytest.approx(100.0 * 2.6) + assert receipt["columns"]["savings_interest_income"][ + "below_first_band_factor" + ] == pytest.approx(2.6) + # Other columns, and the tape passed in, are left as they were. + pd.testing.assert_series_equal(rebased["dividend_income"], donor["dividend_income"]) + assert donor.loc[0, "savings_interest_income"] == 100.0 + assert receipt["from_period"] == 2022 and receipt["to_period"] == 2023 + # The receipt carries factors, never a count of tape records. + assert set(receipt["columns"]["other_investment_income"]) == { + "concept", + "band_factors", + "below_first_band_factor", + "bands_without_tape_amounts", + "bands_too_thin_to_gross", + } + assert ( + receipt["columns"]["other_investment_income"]["bands_without_tape_amounts"] + == [] + ) + + +def test_a_band_the_tape_does_not_carry_is_left_as_it_is() -> None: + # A synthetic tape need not carry every band; there is nothing to scale + # there, and the receipt names the band. + donor = _donor() + donor.loc[4, "other_investment_income"] = 0.0 + rebased, receipt = rebase_spi_donor_savings(donor, PUBLISHED) + other = receipt["columns"]["other_investment_income"] + assert other["bands_without_tape_amounts"] == [1_000_000] + assert "1000000" not in other["band_factors"] + assert rebased.loc[4, "other_investment_income"] == 0.0 + # The other bands, and below the first, still rebase: 800 over 400. + assert other["below_first_band_factor"] == pytest.approx(2.0) + assert rebased.loc[3, "other_investment_income"] == pytest.approx(200.0) + + +def test_the_published_rows_are_checked() -> None: + rows = _rows(PUBLISHED) + assert spi_savings_rebase_published(rows) == PUBLISHED + stale = [dict(rows[0], period={"type": "tax_year", "value": 2022}), *rows[1:]] + with pytest.raises(ValueError, match="describes 2022"): + spi_savings_rebase_published(stale) + with pytest.raises(ValueError, match="two rows from"): + spi_savings_rebase_published([*rows, rows[0]]) + uneven = [ + row + for row in rows + if not ( + row["concept"] == SPI_SAVINGS_REBASE_CONCEPTS["other_investment_income"] + and row["dimensions"]["total_income_lower_bound"] == 50_000 + ) + ] + with pytest.raises(ValueError, match="same total-income bands"): + spi_savings_rebase_published(uneven) + + +def test_the_committed_rows_give_both_columns_table_3_7s_thirteen_bands() -> None: + published = spi_savings_rebase_published() + assert {column: len(bands) for column, bands in published.items()} == { + "savings_interest_income": 13, + "other_investment_income": 13, + } + assert min(published["savings_interest_income"]) == 12_570 + # SPI 2023-24 Table 3.7, all bands: GBP 18.34bn of interest and GBP + # 5.85bn of other income. + assert sum(published["savings_interest_income"].values()) == pytest.approx( + 18.343e9, rel=1e-3 + ) + assert sum(published["other_investment_income"].values()) == pytest.approx( + 5.846e9, rel=1e-3 + ) + + +def test_the_savings_columns_grow_on_the_obr_path_from_2023_24(monkeypatch) -> None: + variables = { + name: SimpleNamespace(uprating="index") + for name in spi_income.SPI_INCOME_UPRATING_VARIABLES.values() + if name is not None + } + + def parameters(period): + return SimpleNamespace(index=100.0 if period.startswith("2022") else 120.0) + + system = SimpleNamespace(variables=variables, parameters=parameters) + monkeypatch.setitem( + sys.modules, + "policyengine_uk", + SimpleNamespace(CountryTaxBenefitSystem=lambda: system), + ) + factors, receipt = spi_income._spi_income_uprating_factors.__wrapped__(2024) + + level, used = uk_obr_savings_income_level(2023, 2024) + # The OBR's +35.0% for 2024-25 (October 2026 EFO, Table 4.5). + assert level == pytest.approx(1.3496108, abs=1e-7) + assert sorted(used) == [2024] + for column in SPI_SAVINGS_REBASE_CONCEPTS: + row = receipt["columns"][column] + assert row["basis"] == "spi_published_bands_then_obr_savings_income" + assert row["from_period"] == SPI_SAVINGS_REBASE_YEAR + assert factors[column] == pytest.approx(level) + assert ( + row["dataset_projection_index"] + == (SPI_HISTORY_INDEX_DIFFERS_FROM_PROJECTION[column]) + ) + # Every other indexed column keeps its engine index from the tape's year. + assert factors["dividend_income"] == pytest.approx(1.2) + # Before 2023-24 there is nothing to rebase to: the source year is the + # identity, and the path refuses to run backwards. + unchanged, _ = spi_income._spi_income_uprating_factors.__wrapped__(2022) + assert unchanged["other_investment_income"] == pytest.approx(1.0) + with pytest.raises(ValueError, match="runs forward only"): + uk_obr_savings_income_level(2024, 2023) + + +def test_the_factors_read_the_tapes_taxpayers() -> None: + # Table 3.7 counts taxpayers only, so a band's factor is its published + # amount over the tape's taxpayers' amount there; a donor who pays no tax + # takes the factor of all bands together (option F of the microcosm#1428 + # other-income investigation). + donor = _donor() + donor[spi_income.SPI_DONOR_TAXPAYER_COLUMN] = [False, True, False, True, True] + rebased, receipt = rebase_spi_donor_savings(donor, PUBLISHED) + interest = receipt["columns"]["savings_interest_income"] + assert receipt["factors_over"].startswith("taxpayers") + # The £12,570 band's taxpayers hold 5 x 40 = 200 of the tape's interest + # there: 1,500 over 200. All bands: 6,500 over 2,200. + assert interest["band_factors"]["12570"] == pytest.approx(7.5) + assert rebased.loc[1, "savings_interest_income"] == pytest.approx(40.0 * 7.5) + all_bands = 6_500.0 / 2_200.0 + assert interest["below_first_band_factor"] == pytest.approx(all_bands) + assert rebased.loc[2, "savings_interest_income"] == pytest.approx(60.0 * all_bands) + # The band's taxpayers reproduce its published amount. + weighted = rebased.loc[[1], "savings_interest_income"] * rebased.loc[[1], "FACT"] + assert weighted.sum() == pytest.approx(1_500.0) + # Without the flag every record counts, as before. + _, plain = rebase_spi_donor_savings(_donor(), PUBLISHED) + assert plain["factors_over"] == "all_records_at_or_above_the_first_band" + + +def test_a_tape_that_does_not_gross_to_the_population_is_left_as_it_is() -> None: + # A synthetic tape's weights do not gross to the published amounts, and its + # factors would run to millions; the rebase leaves such a column as it is. + donor = _donor() + donor["FACT"] = donor["FACT"] / 1e6 + rebased, receipt = rebase_spi_donor_savings(donor, PUBLISHED) + for column in PUBLISHED: + assert "skipped" in receipt["columns"][column] + pd.testing.assert_series_equal(rebased[column], donor[column]) + + +def test_gift_leaves_are_anchored_to_the_tapes_weighted_totals() -> None: + # Two copies drawn, one FRS row and one undrawn copy; the tape's + # FACT-weighted totals are 3,000 of Gift Aid and 600 of investment gifts. + person = pd.DataFrame( + { + "person_id": [1, 2, 3, 4], + "person_household_id": [10, 20, 30, 40], + "gift_aid": [100.0, 300.0, 50.0, 70.0], + "charitable_investment_gifts": [0.0, 400.0, 0.0, 9.0], + } + ) + household = pd.DataFrame( + {"household_id": [10, 20, 30, 40], "household_weight": [2.0, 3.0, 5.0, 7.0]} + ) + donor = pd.DataFrame( + { + "FACT": [10.0, 20.0], + "gift_aid": [100.0, 100.0], + "charitable_investment_gifts": [0.0, 30.0], + } + ) + drawn = pd.Series([True, True, False, False]) + anchored, receipt = spi_income._anchor_spi_gifts_to_tape( + person.copy(), household, donor, spi_people=drawn + ) + weights = pd.Series([2.0, 3.0]) + # The drawn copies carried 1,100 of Gift Aid and 1,200 of investment gifts. + assert (weights * anchored.loc[:1, "gift_aid"]).sum() == pytest.approx(3_000.0) + assert (weights * anchored.loc[:1, "charitable_investment_gifts"]).sum() == ( + pytest.approx(600.0) + ) + assert receipt["factors"] == pytest.approx( + {"gift_aid": 3_000.0 / 1_100.0, "charitable_investment_gifts": 0.5} + ) + # Rows the stage did not draw keep their values. + assert anchored.loc[2:, "gift_aid"].tolist() == [50.0, 70.0] + assert anchored.loc[2:, "charitable_investment_gifts"].tolist() == [0.0, 9.0] + # A column the tape carries none of is left as drawn. + _, receipt = spi_income._anchor_spi_gifts_to_tape( + person.copy(), + household, + donor.assign(charitable_investment_gifts=0.0), + spi_people=drawn, + ) + assert receipt["factors"]["charitable_investment_gifts"] == 1.0 + + +def test_drawn_rows_drop_their_twins_annuity_and_trust_descriptor() -> None: + # A drawn row's private pension is the tape's, which books annuity and + # trust payments as other income; an undrawn copy keeps its twin's part + # (microcosm#1428). + person = pd.DataFrame({"annuity_and_trust_income": [500.0, 700.0, 0.0]}) + drawn = pd.Series([True, False, False]) + cleared = spi_income._clear_annuity_and_trust_descriptor( + person.copy(), spi_people=drawn + ) + assert cleared["annuity_and_trust_income"].tolist() == [0.0, 700.0, 0.0] + # A frame without the descriptor is left as it is. + bare = pd.DataFrame({"private_pension_income": [1.0]}) + assert spi_income._clear_annuity_and_trust_descriptor( + bare.copy(), spi_people=pd.Series([True]) + ).equals(bare) + + +INTEREST_ONLY = {"savings_interest_income": {12_570: 100.0, 50_000: 400.0}} + + +def _edge_donor() -> pd.DataFrame: + # A just below the £50,000 edge in 2022-23, B well above it. + return pd.DataFrame( + { + "total_income": [49_950.0, 60_000.0], + "FACT": [100.0, 100.0], + "savings_interest_income": [1.0, 1.0], + "dividend_income": [5_000.0, 0.0], + } + ) + + +def test_the_tape_is_banded_on_its_income_moved_to_2023_24() -> None: + # Banded on its 2022-23 income, A sits in the £12,570 band. Moved to + # 2023-24 (dividends x1.1), it crosses the £50,000 edge, the band the + # consumers will find it in after uprating, so its migration is counted + # once (microcosm#1428 review, finding 6). + held, held_receipt = rebase_spi_donor_savings(_edge_donor(), INTEREST_ONLY) + assert held["savings_interest_income"].tolist() == pytest.approx([1.0, 4.0]) + moved, receipt = rebase_spi_donor_savings( + _edge_donor(), INTEREST_ONLY, income_factors={"dividend_income": 1.1} + ) + assert moved["savings_interest_income"].tolist() == pytest.approx([2.0, 2.0]) + assert receipt["columns"]["savings_interest_income"]["band_factors"] == { + "50000": pytest.approx(2.0) + } + assert receipt["band_by"] == "total_income_moved_to_2023_24" + assert receipt["banding_converged"] is True + + +def test_a_saver_who_becomes_a_taxpayer_counts_once() -> None: + # C pays no tax in 2022-23 and crosses the Personal Allowance by 2023-24; + # D is a taxpayer throughout. Both are 2023-24 taxpayers in the £12,570 + # band, so their 2,000 meets its 4,000 at a factor of 2. Counting only D + # (factor 4) and giving C the all-bands factor would count C twice + # (microcosm#1428 review, finding 10). + donor = pd.DataFrame( + { + "total_income": [12_000.0, 20_000.0], + "FACT": [10.0, 10.0], + "savings_interest_income": [100.0, 100.0], + "dividend_income": [1_000.0, 0.0], + spi_income.SPI_DONOR_TAXPAYER_COLUMN: [False, True], + } + ) + rebased, receipt = rebase_spi_donor_savings( + donor, + {"savings_interest_income": {12_570: 4_000.0, 50_000: 1.0}}, + income_factors={"dividend_income": 1.6}, + ) + assert receipt["columns"]["savings_interest_income"]["band_factors"][ + "12570" + ] == pytest.approx(2.0) + weighted = rebased["savings_interest_income"] * rebased["FACT"] + assert weighted.sum() == pytest.approx(4_000.0) + + +def test_a_flagged_taxpayer_below_the_first_band_sits_in_it() -> None: + # Table 3.7's lowest band holds taxpayers below the Personal Allowance + # (note 8): a flagged taxpayer there shares the band's factor. + donor = pd.DataFrame( + { + "total_income": [8_000.0, 20_000.0], + "FACT": [10.0, 10.0], + "savings_interest_income": [100.0, 100.0], + spi_income.SPI_DONOR_TAXPAYER_COLUMN: [True, True], + } + ) + rebased, _ = rebase_spi_donor_savings( + donor, {"savings_interest_income": {12_570: 6_000.0, 50_000: 1.0}} + ) + assert rebased["savings_interest_income"].tolist() == pytest.approx([300.0, 300.0]) + + +def test_a_band_too_thin_to_gross_takes_the_all_bands_factor() -> None: + # The £50,000 band's tape holds 10 against a published 1,000, under a + # tenth: its factor would be 100, so it takes the all-bands factor and is + # named (microcosm#1428 review, finding 10). + donor = pd.DataFrame( + { + "total_income": [20_000.0, 60_000.0], + "FACT": [10.0, 1.0], + "savings_interest_income": [100.0, 10.0], + } + ) + rebased, receipt = rebase_spi_donor_savings( + donor, {"savings_interest_income": {12_570: 2_000.0, 50_000: 1_000.0}} + ) + interest = receipt["columns"]["savings_interest_income"] + assert interest["bands_too_thin_to_gross"] == [50_000] + assert "50000" not in interest["band_factors"] + assert rebased.loc[1, "savings_interest_income"] == pytest.approx( + 10.0 * interest["below_first_band_factor"] + ) + + +def test_a_skipped_column_keeps_its_engine_index_from_2022_23(monkeypatch) -> None: + variables = { + name: SimpleNamespace(uprating="index") + for name in spi_income.SPI_INCOME_UPRATING_VARIABLES.values() + if name is not None + } + + def parameters(period): + return SimpleNamespace(index=100.0 if period.startswith("2022") else 120.0) + + monkeypatch.setitem( + sys.modules, + "policyengine_uk", + SimpleNamespace( + CountryTaxBenefitSystem=lambda: SimpleNamespace( + variables=variables, parameters=parameters + ) + ), + ) + factors, receipt = spi_income._spi_income_uprating_factors.__wrapped__( + 2024, rebased_columns=frozenset({"other_investment_income"}) + ) + # Interest the rebase left as it was grows on its engine index from + # 2022-23, not on the OBR's path from 2023-24 (microcosm#1428 review). + assert receipt["columns"]["savings_interest_income"]["basis"] == "model_index" + assert factors["savings_interest_income"] == pytest.approx(1.2) + assert receipt["columns"]["other_investment_income"]["basis"] == ( + "spi_published_bands_then_obr_savings_income" + ) + + +def test_the_tape_taxpayer_flag_is_validated(tmp_path) -> None: + from test_support.microcosm_build.uk_spi_income import _write_donor + + path = tmp_path / "donor.tab" + _write_donor(path) + raw = pd.read_csv(path, delimiter="\t") + # Without the flag the prepared tape carries none. + assert spi_income.SPI_DONOR_TAXPAYER_COLUMN not in ( + spi_income.prepare_spi_donor_table(raw, seed=0) + ) + flagged = raw.assign(TAXPAYER=[1, 2, 1, 2]) + prepared = spi_income.prepare_spi_donor_table(flagged, seed=0) + assert prepared[spi_income.SPI_DONOR_TAXPAYER_COLUMN].tolist() == [ + True, + False, + True, + False, + ] + with pytest.raises(ValueError, match="TAXPAYER"): + spi_income.prepare_spi_donor_table(raw.assign(TAXPAYER=[1, 0, 1, 2]), seed=0) diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_spi_spine.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_spi_spine.py index c137c57ef7..2705085a75 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_spi_spine.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_spi_spine.py @@ -62,6 +62,8 @@ def _base_frame(*, time_period: str = "2023") -> object: "dividend_income": [20.0, 10.0], "private_pension_income": [0.0, 0.0], "property_income": [0.0, 0.0], + # The twin's other income locates the copy's draw (microcosm#1428). + "other_investment_income": [0.0, 0.0], "employee_pension_contributions": [3.0, 2.0], "employer_pension_contributions": [9.0, 6.0], "hmrc_spi_pay": [0.0, 0.0], @@ -609,7 +611,7 @@ def test_spi_spine_parsed_inputs_match_the_path_resolution( # This test checks parsed/path source resolution, independently of the engine. # Real index coverage lives in test_uk_spi_income.py. - def uprating_factors(year): + def uprating_factors(year, *, rebased_columns=None): return ( {column: 1.25 for column in SPI_INCOME_QRF_OUTPUT_COLUMNS}, {"from_period": 2022, "to_period": year, "basis": "synthetic_test"}, 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 15dc71994e..dd34958050 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 @@ -176,9 +176,13 @@ def _apply_pending_roster_transformations( # follows the copies' childcare re-draw. assert "private_school_attendance" not in roster roster.append("private_school_attendance") - # microcosm#1415 re-mint pending: the ISA subscriptions run last. + # microcosm#1415 re-mint pending: the ISA subscriptions follow it. assert "isa_subscriptions" not in roster roster.append("isa_subscriptions") + # microcosm#1428 re-mint pending: the self-employed's gross receipts run + # last. + assert "trading_allowance_receipts" not in roster + roster.append("trading_allowance_receipts") return tuple(roster) diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_stage_health.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_stage_health.py index fa4a989e18..54ea2e9c51 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_stage_health.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_stage_health.py @@ -2322,7 +2322,8 @@ def family(dwp, before, after, reachable, realized): "reachable_pools_caseload_after": realized, } - # 0.05 until microcosm#1418. + # 0.05 until microcosm#1418; the savings follow-up (microcosm#1428) joins + # unmet pools instead of widening it. parameters = { "stage": "uc_take_up", "check": "uc_take_up", diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_support_floor.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_support_floor.py index 734f040c46..4209f87b3b 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_support_floor.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_support_floor.py @@ -360,10 +360,12 @@ def test_the_packaged_floor_drops_only_unsupported_bands_and_binds_thin_ones(): }, # Extended on María's ruling of 2026-10-22 (the next policyengine-uk # bump), then to the SPI families microcosm#1418 binds: Table 3.7's - # other income and Table 3.10's self-employment bands. + # other income and Table 3.10's self-employment bands, and to the + # employment counts over those bands microcosm#1428 binds. "hmrc_spi_income_band_counts": { *(f"hmrc.spi.{family}.count_by_total_income_band" for family in spi), "hmrc.spi.self_employment_income.count_by_self_employment_income_band", + "hmrc.spi.employment_income.count_by_self_employment_income_band", }, "hmrc_spi_income_band_amounts": { *(f"hmrc.spi.{family}.amount_by_total_income_band" for family in spi), 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 06e697074f..91b58ab79c 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 @@ -76,7 +76,10 @@ # national calibration tests read it from the committed membership, or not at # all, so a change to the target set moves this pin alone. How it is made up: # microcosm#1418 PR C: + 13, SPI Table 3.7's other income by band, and + 16, -# SPI Table 3.10's self-employment bands from GBP 1 to GBP 10,000; +# SPI Table 3.10's self-employment bands from GBP 1 to GBP 10,000; its +# savings follow-up (microcosm#1428): + 8, Table 3.10's individuals with +# employment income over the same bands, and + 1, DWP's income-based +# Jobseeker's Allowance spending; # microcosm#1418: + 3, HMRC's Income Tax on savings at each rate; # microcosm#1069: + 24, HMRC's Income Tax payers of State Pension age and aged # 65 and over in the twelve region-tier areas; microcosm#1095 (the bump after @@ -122,7 +125,7 @@ # thresholds over England's regions and Wales), which the national line drops # after the compile, less the North East and Wales rows over £2m, signed out # below the small-cell floor -ACTIVE_REFERENCE_COUNT = 1403 +ACTIVE_REFERENCE_COUNT = 1412 REGION_TIER_LEVEL = {code: level for level, code in UK_REGION_TIER} @@ -1072,7 +1075,7 @@ def test_uk_target_reference_membership_report_is_packaged() -> None: assert membership["status_counts"] == { "active": ACTIVE_REFERENCE_COUNT, "no_fact_at_or_before_period": 4, - "signed_excluded": 30, + "signed_excluded": 37, } assert membership["genuine_sum_residue"] assert membership["uprating_holds"] @@ -1088,7 +1091,7 @@ def test_uk_target_reference_membership_report_is_packaged() -> None: { "family": "hmrc_spi", "status": "active_strict_band_pins", - "active_reference_count": 211, + "active_reference_count": 219, "signed_rationale": ( "SPI income-band targets fan out by strict total-income-band " "dimension pins, and SPI Table 3.10's by self-employment band, " diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_trading_allowance_receipts.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_trading_allowance_receipts.py new file mode 100644 index 0000000000..9cbe9332e8 --- /dev/null +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_trading_allowance_receipts.py @@ -0,0 +1,147 @@ +"""The self-employed's gross receipts for the trading allowance (microcosm#1428).""" + +from __future__ import annotations + +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.national_frame import uk_national_frame +from microcosm.build.uk_runtime.receipt_counts import rounded_count, small_cell_share +from microcosm.build.uk_runtime.trading_allowance_receipts import ( + TRADING_ALLOWANCE_RECEIPTS_OUTPUT, + TRADING_ALLOWANCE_RECEIPTS_STAGE_NAME, + UKTradingAllowanceReceiptsStageTransform, + assign_trading_allowance_receipts, + claimant_rates, +) + + +def _stage(): + return load_country_spec("uk").sources.stage_map()[ + TRADING_ALLOWANCE_RECEIPTS_STAGE_NAME + ] + + +def _frame(profit: np.ndarray): + ids = np.arange(1, len(profit) + 1, dtype=np.int64) + household = pd.DataFrame( + { + "household_id": ids, + "household_source_id": ids, + "household_weight": 2.0, + "region": "LONDON", + } + ) + person = pd.DataFrame( + { + "person_id": ids, + "person_benunit_id": ids, + "person_household_id": ids, + "age": 40, + "self_employment_income": np.asarray(profit, dtype=np.float64), + } + ) + benunit = pd.DataFrame({"benunit_id": ids}) + return uk_national_frame( + person=person, benunit=benunit, household=household, time_period="2024" + ) + + +def test_claimant_rates_follow_the_profit_bands_with_inclusive_upper_bounds() -> None: + profit = np.asarray([-500.0, 0.0, 0.01, 4_500.0, 4_500.01, 9_000.0, 9_000.01]) + assert claimant_rates(profit).tolist() == [0.0, 0.0, 0.64, 0.64, 0.32, 0.32, 0.0] + + +def test_claimants_add_the_allowance_and_other_traders_the_raised_one() -> None: + profit = np.asarray([0.0, -1_200.0, 800.0, 6_000.0, 25_000.0] * 200) + ids = np.arange(len(profit)) + receipts, claimant = assign_trading_allowance_receipts(ids, profit) + trader = profit > 0.0 + # No positive profit: no receipts, which the engine reads as unknown. + assert (receipts[~trader] == 0.0).all() + assert not claimant[~trader].any() + np.testing.assert_allclose(receipts[claimant], profit[claimant] + 1_000.0) + np.testing.assert_allclose( + receipts[trader & ~claimant], profit[trader & ~claimant] + 3_000.0 + ) + # Nobody above GBP 9,000 claims; the draw is the person's own uniform. + assert not claimant[profit > 9_000.0].any() + uniforms = stable_identity_uniforms( + ids[trader], seed=0, salt="trading_allowance_claimant" + ) + assert ( + claimant[trader].tolist() + == (uniforms < claimant_rates(profit[trader])).tolist() + ) + # Two hundred draws per band land near the band's rate. + assert claimant[profit == 800.0].mean() == pytest.approx(0.64, abs=0.1) + assert claimant[profit == 6_000.0].mean() == pytest.approx(0.32, abs=0.1) + + +def test_the_stage_stores_receipts_deterministically_and_moves_nothing_else() -> None: + profit = np.tile([0.0, 900.0, 3_000.0, 7_000.0, 40_000.0], 40) + frame = _frame(profit) + first = UKTradingAllowanceReceiptsStageTransform(stage=_stage())(frame) + second = UKTradingAllowanceReceiptsStageTransform(stage=_stage())(frame) + person = first.table("person") + pd.testing.assert_series_equal( + person[TRADING_ALLOWANCE_RECEIPTS_OUTPUT], + second.table("person")[TRADING_ALLOWANCE_RECEIPTS_OUTPUT], + ) + expenses = ( + person[TRADING_ALLOWANCE_RECEIPTS_OUTPUT] - person["self_employment_income"] + ) + assert set(np.round(expenses[profit > 0.0], 6)) <= {1_000.0, 3_000.0} + assert (person.loc[profit <= 0.0, TRADING_ALLOWANCE_RECEIPTS_OUTPUT] == 0.0).all() + before = frame.table("person") + pd.testing.assert_frame_equal( + person.drop(columns=[TRADING_ALLOWANCE_RECEIPTS_OUTPUT]), before + ) + np.testing.assert_array_equal( + first.weights_for("household").values, frame.weights_for("household").values + ) + (record,) = first.mass_log[len(frame.mass_log) :] + assert record.declared_factor == 1.0 + assert record.old_total == record.new_total + + +def test_the_receipt_rounds_counts_and_bands_shares() -> None: + transform = UKTradingAllowanceReceiptsStageTransform(stage=_stage()) + transform(_frame(np.tile([500.0, 6_000.0, 20_000.0], 50))) + evidence = transform.checkpoint_metadata()["evidence"] + assert evidence["traders"] == 150 + assert isinstance(evidence["claimants"], int) + assert [band["rate"] for band in evidence["bands"]] == [0.64, 0.32, 0.0] + assert all(band["support"] == "30+" for band in evidence["bands"]) + assert evidence["bands"][0]["weighted_traders"] == pytest.approx(100.0) + # Fewer than ten source households behind a band print the small-cell + # label, whatever the rounding rules make it (microcosm#1428 review). + transform(_frame(np.asarray([500.0] * 5))) + small = transform.checkpoint_metadata()["evidence"] + assert small["traders"] == rounded_count(5) + assert small["bands"][0]["weighted_traders"] == small_cell_share(10.0, 5) + + +def test_the_stage_refuses_drifted_parameters_and_a_second_writer() -> None: + stage = _stage() + operation, receipt = stage.operations + drifted = replace( + stage, + operations=( + replace( + operation, + parameters={**dict(operation.parameters), "claimant_expenses": 900.0}, + ), + receipt, + ), + ) + with pytest.raises(ValueError, match="parameters drifted"): + UKTradingAllowanceReceiptsStageTransform(stage=drifted)(_frame([500.0])) + frame = UKTradingAllowanceReceiptsStageTransform(stage=stage)(_frame([500.0])) + with pytest.raises(ValueError, match="only writer"): + UKTradingAllowanceReceiptsStageTransform(stage=stage)(frame) diff --git a/packages/microcosm-build/tests/engine_free/uk/test_uk_uc_take_up.py b/packages/microcosm-build/tests/engine_free/uk/test_uk_uc_take_up.py index ba9ed57c27..1730e58c63 100644 --- a/packages/microcosm-build/tests/engine_free/uk/test_uk_uc_take_up.py +++ b/packages/microcosm-build/tests/engine_free/uk/test_uk_uc_take_up.py @@ -11,6 +11,7 @@ from microcosm.build.country_spec import load_country_spec from microcosm.build.source_manifest import SourceStageSpec +from microcosm.build.uk_runtime import uc_take_up from microcosm.build.uk_runtime.frs_take_up import ( UK_TAKE_UP_SIGNAL_OUTPUTS, UKTakeUpPopulationPolicy, @@ -233,9 +234,11 @@ def test_a_pool_nearer_zero_than_its_first_unit_draws_no_claimant() -> None: assert would_claim.tolist() == [True, False] -def test_clipped_pools_are_flagged_unreachable() -> None: - # Band 0: reporters alone exceed DWP's count, so no drawn unit claims. - # Band 2: DWP's count exceeds every entitled unit, so all of them claim. +def test_a_family_type_that_cannot_meet_its_count_is_flagged_unreachable() -> None: + # Band 0: reporters alone exceed DWP's count; band 2: the count exceeds + # every entitled unit. Each band keeps its own pool: the two gaps offset, + # the remaining shortfall takes band 0's one drawn unit, and the family + # type still falls short, so every drawn unit claims (microcosm#1428). award = np.asarray([100.0] * 4 + [3_000.0] * 4) reporter = np.asarray([True, True, True, False, False, False, False, False]) would_claim, receipt = _assign( @@ -246,38 +249,94 @@ def test_clipped_pools_are_flagged_unreachable() -> None: source_ids=np.arange(8), minimum_pool_sources=1, ) - assert would_claim.tolist() == [True, True, True, False, True, True, True, True] - flags = { - tuple(pool["bands"]): pool["target_unreachable"] - for pool in receipt["pools"] - if pool["family_type"] == "SINGLE" - } - assert flags[(UC_AWARD_BAND_LABELS[0],)] == "<10" - pools = receipt["pools"] - assert all("rate" not in pool for pool in pools) - # With ten or more sources behind a pool the flag says which side it is on. - many = np.asarray([100.0] * 12 + [3_000.0] * 12) + assert would_claim.all() + pools = [pool for pool in receipt["pools"] if pool["family_type"] == "SINGLE"] + assert [pool["bands"][0] for pool in pools] == list(UC_AWARD_BAND_LABELS[:2]) + assert all(pool["target_unreachable"] == "<10" for pool in pools) + assert all("rate" not in pool for pool in receipt["pools"]) + # With ten or more sources behind a pool the flag says which side it is + # on: the singles' reporters exceed their count, and the couples' count + # exceeds every entitled unit. + family = np.asarray(["SINGLE"] * 12 + ["COUPLE_NO_CHILDREN"] * 12, dtype=object) _, receipt = _assign( - award=many, - reporter=np.asarray([True] * 10 + [False] * 14), - targets=_targets(SINGLE_0=2.0, SINGLE_2=50.0), + award=np.asarray([100.0] * 12 + [3_000.0] * 12), + family=family, + reporter=np.asarray([True] * 12 + [False] * 12), + targets=_targets(SINGLE_0=2.0, COUPLE_NO_CHILDREN_2=50.0), minimum_pool_sources=1, ) + flags = { + pool["family_type"]: pool["target_unreachable"] + for pool in receipt["pools"] + if pool["family_type"] in {"SINGLE", "COUPLE_NO_CHILDREN"} + } + assert flags == { + "SINGLE": "undrawn_claims_reach_target", + "COUPLE_NO_CHILDREN": "target_exceeds_entitled", + } + # No pool is reachable, so the gate's reachable totals are empty. + assert receipt["families"]["SINGLE"]["reachable_pools_dwp_caseload"] == 0.0 - # Band 1 holds no unit, so it pools with band 2, and the empty bands above - # join that pool. - def flag(label): - return next( - pool["target_unreachable"] - for pool in receipt["pools"] - if pool["family_type"] == "SINGLE" and label in pool["bands"] - ) - assert flag(UC_AWARD_BAND_LABELS[0]) == "undrawn_claims_reach_target" - assert flag(UC_AWARD_BAND_LABELS[2]) == "target_exceeds_entitled" +def test_an_unmet_pool_passes_its_gap_to_the_neighbour_with_more_room() -> None: + # Band 0: four drawn units and a count of 3 (one to spare); band 2: two + # drawn units and a count of 5 (three short); band 4: ten drawn units and a + # count of 5 (five to spare). Band 2 is held at its two claims and passes + # its three to band 4, which has more room; band 0 keeps its own count, and + # the singles land on DWP's 13 (microcosm#1428 review, finding 7). + award = np.asarray([600.0] * 4 + [3_000.0] * 2 + [5_500.0] * 10) + would_claim, receipt = _assign( + award=award, targets=_targets(SINGLE_0=3.0, SINGLE_2=5.0, SINGLE_4=5.0) + ) + assert int(would_claim[:4].sum()) == 3 + assert would_claim[4:6].all() + assert int(would_claim[6:].sum()) == 8 single = receipt["families"]["SINGLE"] - # No pool is reachable, so the gate's reachable totals are empty. - assert single["reachable_pools_dwp_caseload"] == 0.0 + assert single["caseload_after"] == pytest.approx(13.0) + assert single["reachable_pools_dwp_caseload"] == pytest.approx(13.0) + # On equal room the lower neighbour takes the gap. + award = np.asarray([600.0] * 3 + [3_000.0] + [5_500.0] * 3) + would_claim, _ = _assign( + award=award, targets=_targets(SINGLE_0=1.0, SINGLE_2=2.0, SINGLE_4=1.0) + ) + assert [ + int(would_claim[:3].sum()), + int(would_claim[3]), + int(would_claim[4:].sum()), + ] == [2, 1, 1] + + +def test_an_overshooting_pool_passes_its_excess_to_one_with_drawn_claims() -> None: + # Band 0: three reporters, one drawn unit and a count of 1 (two over); + # band 2: six drawn units and a count of 4. Band 0 is held at its + # reporters and its drawn unit does not claim; its two over come off band + # 2, whose drawn units carry the two claims DWP's 5 leaves. A joined pool + # had let band 0's drawn unit claim (microcosm#1428 review, finding 7). + award = np.asarray([600.0] * 4 + [3_000.0] * 6) + reporter = np.asarray([True] * 3 + [False] * 7) + would_claim, receipt = _assign( + award=award, reporter=reporter, targets=_targets(SINGLE_0=1.0, SINGLE_2=4.0) + ) + assert would_claim[:3].all() + assert not would_claim[3] + assert int(would_claim[4:].sum()) == 2 + assert receipt["families"]["SINGLE"]["caseload_after"] == pytest.approx(5.0) + + +def test_gaps_offset_before_they_pass() -> None: + # One pool overshoots by 1 and another falls short by 6: the excess + # offsets the shortfall, and only the remaining 5 look for room + # (microcosm#1428 review, finding 7). + counts, unplaced = uc_take_up._pass_unmet_gaps([(2.0, 3.0, 1.0), (10.0, 0.0, 4.0)]) + assert counts == [4.0, 4.0] + assert unplaced == [0.0, 4.0] + # A feasible family type keeps its total: 3 + 5 + 5 over pools that hold + # 0-4, 0-2 and 0-10. + counts, unplaced = uc_take_up._pass_unmet_gaps( + [(3.0, 0.0, 4.0), (5.0, 0.0, 2.0), (5.0, 0.0, 10.0)] + ) + assert counts == [3.0, 2.0, 8.0] + assert not any(unplaced) def test_undrawn_units_keep_their_flag_and_count_at_their_expected_claim() -> None: diff --git a/packages/microcosm-data/src/microcosm/data/contract.py b/packages/microcosm-data/src/microcosm/data/contract.py index 27856156e9..edb5688930 100644 --- a/packages/microcosm-data/src/microcosm/data/contract.py +++ b/packages/microcosm-data/src/microcosm/data/contract.py @@ -451,13 +451,13 @@ def compatibility_claim_declarer_error(declared_by: object) -> str | None: # fingerprint derives from the manifest digest. Editing the spec moves all # three here in the same reviewed change. _UK_GATE_BATTERY_POLICY_SHA256 = ( - "29c866ba365999cfd39a5ddceb94e159396759e575a8ac99de619e3f03525653" + "37c1649af59eda1027e96b5993adff3ed982a04d5bafd8b21cea636490c568f5" ) _UK_GATE_BATTERY_GATES_MANIFEST_SHA256 = ( - "a9e1187a619794b9e159b209a6f6476a24260791df6bb14ae72f9f9bfcaa7514" + "49747ecb3eb2f02c337bb350748609ec822e0826d12406b1ce3a1ee794d711f4" ) _UK_GATE_BATTERY_SPEC_FINGERPRINT = ( - "6bd701aa0257a7faad66f5ee8f80f8e4afb664298b70c7093e5b0e220677049d" + "63b1107a53b3ee2a821ddb3a62128b735d08712a6569e74ba86caa546664ef13" ) #: Spec entry id -> the legacy gate name whose observable detail checks #: apply unchanged (the battery re-keys the report by entry id; the gate @@ -964,7 +964,7 @@ def _uk_line_cut_tag_re(release_id: str) -> re.Pattern[str] | None: _UK_CERTIFICATION_PART_DIGESTS: Mapping[str, Mapping[str, str]] = { "spine": { "gates_manifest_sha256": ( - "06f62df651d151e586d6102ed2110b3b2348bd881826d4d6d66621e4ab8abb1f" + "f8ba93bf165c3aa67b7b1893161d1e517ad36f27b52eb4c5b224f150fca05657" ), "policy_sha256": ( "390a79297f7817def126c7805f492328c447e6a0d6d376dc8b946b98b9f96725" @@ -980,10 +980,10 @@ def _uk_line_cut_tag_re(release_id: str) -> re.Pattern[str] | None: }, "release_cut": { "gates_manifest_sha256": ( - "c44ce8629cfc9a48e6aaeb9d77012c4fad382b8ef0e232476b9bc8c8e83dbefc" + "bc55902443076fdc74a34bbdb6ec0ce5491603f8ea0b0c8d66008ed69c3c4aa2" ), "policy_sha256": ( - "b335bef4e20b9803b60e728bfb2f045d282d16309429b00d72bf86dd4f4bafd8" + "d74ea8e21e60092dfcbddd40cbdde3acb190500e4d419128ca8317dc318bafdf" ), }, } diff --git a/packages/microcosm-data/tests/engine_free/shared/test_contract.py b/packages/microcosm-data/tests/engine_free/shared/test_contract.py index 37e33febf5..f1fe926bf9 100644 --- a/packages/microcosm-data/tests/engine_free/shared/test_contract.py +++ b/packages/microcosm-data/tests/engine_free/shared/test_contract.py @@ -220,13 +220,13 @@ def _trusted_terminal_gate_signing_key(monkeypatch) -> None: UK_GATE_BATTERY_PRODUCER = "microcosm.build.gate_battery" UK_GATE_BATTERY_SIGNING_KEY_ENV = "MICROCOSM_UK_TERMINAL_GATE_SIGNING_KEY" UK_GATE_BATTERY_POLICY_SHA256 = ( - "29c866ba365999cfd39a5ddceb94e159396759e575a8ac99de619e3f03525653" + "37c1649af59eda1027e96b5993adff3ed982a04d5bafd8b21cea636490c568f5" ) UK_GATE_BATTERY_GATES_MANIFEST_SHA256 = ( - "a9e1187a619794b9e159b209a6f6476a24260791df6bb14ae72f9f9bfcaa7514" + "49747ecb3eb2f02c337bb350748609ec822e0826d12406b1ce3a1ee794d711f4" ) UK_GATE_BATTERY_SPEC_FINGERPRINT = ( - "6bd701aa0257a7faad66f5ee8f80f8e4afb664298b70c7093e5b0e220677049d" + "63b1107a53b3ee2a821ddb3a62128b735d08712a6569e74ba86caa546664ef13" ) UK_GATE_BATTERY_DEGENERATE_EVIDENCE_SHA256 = ( "f246388de42654dd68dbbb40c42282001b5b0a8bf48976162bcb1199085cb1d3" 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 8c524f6843..7cbd06a026 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 @@ -246,18 +246,6 @@ #: Other engine inputs the build leaves at the engine's default, each signed as #: an approximation with the error it can make (microcosm#1095). UK_ENGINE_DEFAULT_INPUTS: dict[str, str] = { - "self_employment_gross_receipts": ( - "No source of the self-employed's turnover is read yet (the FRS job " - "record and the SPI tape are the candidates, as #1145 found landlords' " - "receipts). Since policyengine-uk 2.108.0 the trading allowance replaces " - "expenses and does not stack on them, so without receipts " - "trading_allowance_deduction relieves a profit of GBP 1,000 or less in " - "full and gives a larger profit no allowance. Taxable profit is off by at " - "most GBP 1,000 a person: too low where receipts above GBP 1,000 leave a " - "small profit, too high just above GBP 1,000 where the allowance would " - "beat the expenses. Signed as an approximation with the plan for the " - "next policyengine-uk bump, approved on 2026-10-23." - ), "housing_benefit_residential_capital_exception": ( "The working-age residential capital tariff exception (Housing Benefit " "Regulations 2006 reg. 52(4)-(5), (8)-(9); NI reg. 49) covers residents " 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 40bf20145e..bfa6eaad6e 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": 6472476.363235764, + "table4_all_gains": 6567779.158835469, "table4_all_tax": 0.0, - "table4_all_taxpayers": 15.64584768489452, + "table4_all_taxpayers": 15.645847684894523, "table4_bands": [ { - "gains": 6343.7876538201135, + "gains": 6262.290969943808, "lower_bound": 0, "tax": null, - "taxpayers": 1.4508598323557498, + "taxpayers": 1.4320098873010005, "upper_bound": 10000 }, { - "gains": 31485.760340906432, + "gains": 24063.64355992752, "lower_bound": 10000, "tax": null, - "taxpayers": 1.9244306390596129, + "taxpayers": 1.4653704559490115, "upper_bound": 25000 }, { - "gains": 63324.14855305699, + "gains": 81614.98942021298, "lower_bound": 25000, "tax": null, - "taxpayers": 1.7239151594793525, + "taxpayers": 2.2495857610440857, "upper_bound": 50000 }, { - "gains": 140800.40954871886, + "gains": 134940.71583113162, "lower_bound": 50000, "tax": null, - "taxpayers": 2.0175072572478596, + "taxpayers": 1.9395983558176588, "upper_bound": 100000 }, { - "gains": 155344.30651445186, + "gains": 142317.70165223547, "lower_bound": 100000, "tax": null, - "taxpayers": 0.9869230277893157, + "taxpayers": 0.9050403178705543, "upper_bound": 250000 }, { - "gains": 630694.061491824, + "gains": 622123.2583176545, "lower_bound": 250000, "tax": null, - "taxpayers": 1.7500749317552278, + "taxpayers": 1.725490737653384, "upper_bound": 500000 }, { - "gains": 790243.0554791468, + "gains": 848903.2550118314, "lower_bound": 500000, "tax": null, - "taxpayers": 1.1378960035535624, + "taxpayers": 1.2211988651862962, "upper_bound": 1000000 }, { - "gains": 4654240.833653839, + "gains": 4707553.304072532, "lower_bound": 1000000, "tax": null, - "taxpayers": 4.654240833653839, + "taxpayers": 4.7075533040725315, "upper_bound": null } ], - "table4_individuals_gains": 6472476.363235764, + "table4_individuals_gains": 6567779.158835469, "table4_individuals_tax": 0.0, - "table4_individuals_taxpayers": 15.64584768489452, + "table4_individuals_taxpayers": 15.645847684894523, "table4_trusts_gains": 0.0, "table4_trusts_tax": 0.0, "table7_total_disposals": 2743095.2380952383, @@ -115,11 +115,11 @@ } ], "table8a_disposals_total": 29.50359849151538, - "table8a_gains_total": 36909134.810149446, - "table8a_tax_total": 7381826.962029889, + "table8a_gains_total": 37385992.48877222, + "table8a_tax_total": 7477198.497754444, "table8a_taxpayers_total": 26.82145317410489, - "table8b_all_gains": 36909134.810149446, + "table8b_all_gains": 37385992.48877222, "table8b_all_taxpayers": 26.82145317410489, - "table8b_individuals_gains": 36909134.810149446, + "table8b_individuals_gains": 37385992.48877222, "table8b_individuals_taxpayers": 26.82145317410489 } 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 80ecf64e5f..86a442c812 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 @@ -2249,8 +2249,8 @@ "locator": "pension.tab", "role": "frs_table", "runtime_sha256_required": true, - "sha256": "7090be19cac198c6fc4545266764d267f9e39073b83c5411d0615eda2ac47e9c", - "size_bytes": 3597, + "sha256": "79ba6767e1300e1bb5d3de808706cb4ee1d86e4694a26e9fd94958e821858f33", + "size_bytes": 3875, "table": "pension", "vintage": "synthetic-h2" } @@ -2268,6 +2268,7 @@ "loss_relief", "ni_class_4_losses_brought_forward", "private_pension_income", + "annuity_and_trust_income", "individual_savings_account_interest_income", "savings_interest_income", "dividend_income", @@ -2365,6 +2366,7 @@ "loss_relief", "ni_class_4_losses_brought_forward", "private_pension_income", + "annuity_and_trust_income", "individual_savings_account_interest_income", "savings_interest_income", "dividend_income", @@ -3061,7 +3063,7 @@ "hmrc_spi_total_investment_income", "hmrc_spi_assessable_income" ], - "notes": "Runs the SPI-trained income QRFs on the raw-spine support channel, drawing for its claimants and partners aged 16 and over so dependants aged 16 to 19 keep their FRS twin's values (uk-data#504, microcosm#1095), initializes FRS charity columns to zero, trains FRS-only stage 2 on the FRS rows' reported values, flags the rows it drew (person_is_spi_income_recipient) so later stages tell tape-concept rows from FRS-concept ones without re-deriving the recipient rule (microcosm#840), leaves every FRS-channel income as reported (no base-channel redraw of dividends; uk-data#498, microcosm#1095), and emits a sidecar-only 208-fact replay report for the spine path. Stage 2 also draws trading_loss, the year's trading loss the tape does not carry, from the FRS rows (uk-data#528), and a drawn row whose self_employment_income is positive keeps no loss, so profit and loss never both hold an amount, as on the FRS rows (microcosm#1095). The chain draws self_employment_income net of the tape's losses brought forward (LOSSBF), as the tape holds profits, and last of all, so no earlier draw moves, the year's profit before them and the losses. After the FRS-only fill and the HMRC aggregates the stage moves the losses out of the profit into loss_relief and ni_class_4_losses_brought_forward, the inputs policyengine-uk relieves them against (income tax under ITA 2007 s.83, Class 4 under SSCBA 1992 Sch 2 para 3), so Universal Credit, HBAI and market income read the year's profit; where the drawn net profit is positive the losses are its gap to the year's profit and where it is zero they are at least that profit, so the profit after the relief is the drawn net profit on every row, which the HMRC aggregates and the HMRC self-employment rows read (uk-data#528, microcosm#1095). The engine carries both losses into each projected year at their nominal value while the profit grows with its index. Stage 2 draws the six owner-manager inputs last, the five flags as 0 or 1 and then the income share, so each follows the drawn incomes; the root stage's rules then hold on the drawn rows (an owner works in the company, its other inputs need an owner, and a company carries on a trade or a property business, never both), since the tape carries no director answers (microcosm#1095). A drawn row's annual income descriptors follow its drawn incomes. The tape records the tax year's income, so its pay, profit and private pension shares are 1, and its contributory benefits, stage-2 draws on the current concept with no spell of their own, take share 1 too. It keeps its twin's other-spell pay only where it drew no pay, and its twin's ceased self-employment only where it drew no profit, since the bridge draws a record without pay for a twin who left a job in the year. An undrawn copy keeps its twin's descriptors with its twin's incomes.", + "notes": "Runs the SPI-trained income QRFs on the raw-spine support channel, drawing for its claimants and partners aged 16 and over so dependants aged 16 to 19 keep their FRS twin's values (uk-data#504, microcosm#1095), initializes FRS charity columns to zero, trains FRS-only stage 2 on the FRS rows' reported values, flags the rows it drew (person_is_spi_income_recipient) so later stages tell tape-concept rows from FRS-concept ones without re-deriving the recipient rule (microcosm#840), leaves every FRS-channel income as reported (no base-channel redraw of dividends; uk-data#498, microcosm#1095), and emits a sidecar-only 208-fact replay report for the spine path. Stage 2 also draws trading_loss, the year's trading loss the tape does not carry, from the FRS rows (uk-data#528), and a drawn row whose self_employment_income is positive keeps no loss, so profit and loss never both hold an amount, as on the FRS rows (microcosm#1095). The chain draws self_employment_income net of the tape's losses brought forward (LOSSBF), as the tape holds profits, and last of all, so no earlier draw moves, the year's profit before them and the losses. After the FRS-only fill and the HMRC aggregates the stage moves the losses out of the profit into loss_relief and ni_class_4_losses_brought_forward, the inputs policyengine-uk relieves them against (income tax under ITA 2007 s.83, Class 4 under SSCBA 1992 Sch 2 para 3), so Universal Credit, HBAI and market income read the year's profit; where the drawn net profit is positive the losses are its gap to the year's profit and where it is zero they are at least that profit, so the profit after the relief is the drawn net profit on every row, which the HMRC aggregates and the HMRC self-employment rows read (uk-data#528, microcosm#1095). The engine carries both losses into each projected year at their nominal value while the profit grows with its index. Stage 2 draws the six owner-manager inputs last, the five flags as 0 or 1 and then the income share, so each follows the drawn incomes; the root stage's rules then hold on the drawn rows (an owner works in the company, its other inputs need an owner, and a company carries on a trade or a property business, never both), since the tape carries no director answers (microcosm#1095). A drawn row's annual income descriptors follow its drawn incomes. The tape records the tax year's income, so its pay, profit and private pension shares are 1, and its contributory benefits, stage-2 draws on the current concept with no spell of their own, take share 1 too. It keeps its twin's other-spell pay only where it drew no pay, and its twin's ceased self-employment only where it drew no profit, since the bridge draws a record without pay for a twin who left a job in the year. An undrawn copy keeps its twin's descriptors with its twin's incomes. A drawn row's annuity and trust descriptor is zero, since the tape's private pension excludes those payments and books them as other income (microcosm#1428).", "operations": [ { "artifact_roles": [ @@ -3264,7 +3266,7 @@ "hmrc_spi_state_pension_income": "srp_regular_code5", "hmrc_spi_taxable_termination_pay": null, "hmrc_spi_unemployment_benefit_income": "hmrc_spi_unemployment_benefit_income", - "other_investment_income": null, + "other_investment_income": "other_investment_income", "private_pension_income": "private_pension_income", "property_finance_costs": null, "property_income": "property_income", @@ -3862,7 +3864,8 @@ "self_employment_income_annual_share", "self_employment_income_other_spells", "private_pension_income_annual_share", - "contributory_benefits_annual_share" + "contributory_benefits_annual_share", + "annuity_and_trust_income" ], "source": "https://assets.publishing.service.gov.uk/media/69f1f12d2fae53a03709682f/Collated_Tables_3_1_to_3_11_2324.ods", "stage": "hmrc_spi_income_spine", @@ -6788,6 +6791,54 @@ "stage": "student_loans", "survey": "Family Resources Survey 2024-25 and Student Loans Company borrower forecasts for England" }, + "trading_allowance_receipts": { + "artifacts": [], + "grain": "person", + "nonnegative_outputs": [ + "self_employment_gross_receipts" + ], + "notes": "The last spine stage (microcosm#1428). policyengine-uk applies the trading allowance against self_employment_gross_receipts, which neither the FRS nor the SPI tape records; without receipts a rise in the allowance relieves only profits up to the new allowance, in full, and misses its main base, the traders who already claim the GBP 1,000 allowance against larger receipts. Under current law a claimant's receipts are their profit plus GBP 1,000 exactly. Each trader with a positive profit is flagged a claimant at their profit band's rate, drawn on their own person_id: a claimant's receipts are their profit plus GBP 1,000, any other trader's their profit plus GBP 3,000 (expenses at the raised allowance, so the raise does not relieve them; the costing books switchers as behaviour), and a person with no positive profit keeps zero, which the engine reads as unknown. Every trader with a positive profit is treated as filing, as SPI Table 3.10's counts, which bind the frame's traders, are of filers, so a profit of GBP 1,000 or less is now taxed where the engine used to relieve it in full. The rates are calibrated to HMRC's policy paper until HMRC publishes claimant counts. The engine uprates receipts with profit, so a claimant's GBP 1,000 grows with the mixed income index while the allowance is nominal: the raise relieves GBP 1,932 more in 2027-28, falling to GBP 1,758 by 2031-32, 3.4% to 12.1% below GBP 2,000. The other traders' stored GBP 3,000 grows the same way, so an allowance above GBP 3,000 times that index relieves them from the stored expense, not from data: allowances above GBP 3,000 are mis-scored until policyengine-uk#2765 lets the stage store the claim status (microcosm#1439; Mar\u00eda's ruling of 2026-11-01).", + "operations": [ + { + "calibration": "HMRC's policy paper on the Budget 2026 trading allowance raise: about 400,000 taxpayers with a lower bill, by about GBP 380 on average, on the microcosm#1428 national b441bb5a0's final weights at 2028-29 prices, until HMRC publishes claimant counts (Mar\u00eda's choice of 2026-10-31)", + "claimant_bands": [ + { + "rate": 0.64, + "upper_inclusive": 4500 + }, + { + "rate": 0.32, + "upper_inclusive": 9000 + }, + { + "rate": 0 + } + ], + "claimant_expenses": 1000, + "draw": "trading_allowance_claimant", + "kind": "assign_trading_allowance_receipts", + "other_expenses": 3000, + "output": "self_employment_gross_receipts", + "profit": "self_employment_income", + "rule": "a person with a positive self_employment_income claims the allowance where their uniform falls below their profit band's rate; a claimant's receipts are their profit plus claimant_expenses, any other trader's their profit plus other_expenses, and a person with no positive profit keeps zero", + "seed": 0 + }, + { + "declared_factor": 1, + "entity": "household", + "gate_coupling": "The terminal family gate requires a valid mass-conserving MassChangeRecord carrying exactly this stage-specific reason.", + "kind": "record_mass_conservation_receipt", + "reason": "Self-employed gross receipts stored on the source spine: household weights pass through unchanged and total household mass is conserved." + } + ], + "outputs": [ + "self_employment_gross_receipts" + ], + "rewrites": [], + "source": "self_employment_income after the SPI income stage; HMRC's published gainers of the raise to GBP 3,000, about 400,000 taxpayers with a lower bill by about GBP 380 on average", + "stage": "trading_allowance_receipts", + "survey": "The self-employed's own profit on the final spine, and HMRC's policy paper on the Budget 2026 trading allowance raise (calibration)" + }, "uc_capital_coherence": { "artifacts": [], "grain": "benunit", @@ -7135,9 +7186,9 @@ "minimum_pool_sources": 30, "not_drawn": "keeps its stored flag, except a unit keeping income-related ESA, which claims none", "output": "would_claim_uc", - "pooling": "adjacent bands within a family type, lowest first, until the drawn units rest on minimum_pool_sources distinct household_source_id values; a short last pool joins the one before it", + "pooling": "adjacent bands within a family type, lowest first, until the drawn units rest on minimum_pool_sources distinct household_source_id values; a short last pool joins the one before it. Then, lowest first, a pool that cannot meet DWP's count (its undrawn entitled units' expected claims exceed the count, or the count exceeds them plus the weight of every drawn unit) is held at the nearer of those ends and passes its gap to the other pools, nearest first, the one with more room first at equal distance and the lower on a tie, each taking what its room allows; a gap no pool can take leaves the family type unreachable", "population": "uc_age_eligible", - "residual_rate": "(T - F) / D, clipped to [0, 1]; T DWP's calendar-2025 mean count of the pool's bands, D the weight of the pool's drawn units and F the expected claims of its other entitled units, over Great Britain at the stage's household weights; realized by the drawn units claiming in the order of their uniform until their weight is nearest T - F, and applied at that uniform to Northern Ireland's drawn units too", + "residual_rate": "(T - F) / D, clipped to [0, 1]; T DWP's calendar-2025 mean count of the pool's bands after any gaps passed to or from it, D the weight of the pool's drawn units and F the expected claims of its other entitled units, over Great Britain at the stage's household weights; realized by the drawn units claiming in the order of their uniform until their weight is nearest T - F, and applied at that uniform to Northern Ireland's drawn units too", "seed": 0, "solve_scope": "great_britain", "targets": "DWP Stat-Xplore Households on Universal Credit by family type and monthly award band, mean of April to December 2025", diff --git a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/pension.tab b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/pension.tab index 7b8df74533..da8ce3e7ce 100644 --- a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/pension.tab +++ b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/frs_raw/pension.tab @@ -1,136 +1,136 @@ -SERNUM BENUNIT PERSON PENPAY PTAMT PTINC POAMT POINC PENOTH -1 1 1 10.0 2.0 2 3.0 2 0 -2 1 1 10.0 2.0 2 3.0 2 0 -3 1 1 10.0 2.0 2 3.0 2 0 -4 1 1 10.0 2.0 2 3.0 2 0 -5 1 1 10.0 2.0 2 3.0 2 0 -6 1 1 10.0 2.0 2 3.0 2 0 -7 1 1 10.0 2.0 2 3.0 2 0 -8 1 1 10.0 2.0 2 3.0 2 0 -9 1 1 10.0 2.0 2 3.0 2 0 -10 1 1 10.0 2.0 2 3.0 2 0 -11 1 1 10.0 2.0 2 3.0 2 0 -12 1 1 10.0 2.0 2 3.0 2 0 -13 1 1 10.0 2.0 2 3.0 2 0 -14 1 1 10.0 2.0 2 3.0 2 0 -15 1 1 10.0 2.0 2 3.0 2 0 -16 1 1 10.0 2.0 2 3.0 2 0 -17 1 1 10.0 2.0 2 3.0 2 0 -18 1 1 10.0 2.0 2 3.0 2 0 -19 1 1 10.0 2.0 2 3.0 2 0 -20 1 1 10.0 2.0 2 3.0 2 0 -21 1 1 10.0 2.0 2 3.0 2 0 -22 1 1 10.0 2.0 2 3.0 2 0 -23 1 1 10.0 2.0 2 3.0 2 0 -24 1 1 10.0 2.0 2 3.0 2 0 -25 1 1 10.0 2.0 2 3.0 2 0 -26 1 1 10.0 2.0 2 3.0 2 0 -27 1 1 10.0 2.0 2 3.0 2 0 -28 1 1 10.0 2.0 2 3.0 2 0 -29 1 1 10.0 2.0 2 3.0 2 0 -30 1 1 10.0 2.0 2 3.0 2 0 -31 1 1 10.0 2.0 2 3.0 2 0 -32 1 1 10.0 2.0 2 3.0 2 0 -33 1 1 10.0 2.0 2 3.0 2 0 -34 1 1 10.0 2.0 2 3.0 2 0 -35 1 1 10.0 2.0 2 3.0 2 0 -36 1 1 10.0 2.0 2 3.0 2 0 -37 1 1 10.0 2.0 2 3.0 2 0 -38 1 1 10.0 2.0 2 3.0 2 0 -39 1 1 10.0 2.0 2 3.0 2 0 -40 1 1 10.0 2.0 2 3.0 2 0 -41 1 1 10.0 2.0 2 3.0 2 0 -42 1 1 10.0 2.0 2 3.0 2 0 -43 1 1 10.0 2.0 2 3.0 2 0 -44 1 1 10.0 2.0 2 3.0 2 0 -45 1 1 10.0 2.0 2 3.0 2 0 -46 1 1 10.0 2.0 2 3.0 2 0 -47 1 1 10.0 2.0 2 3.0 2 0 -48 1 1 10.0 2.0 2 3.0 2 0 -49 1 1 10.0 2.0 2 3.0 2 0 -50 1 1 10.0 2.0 2 3.0 2 0 -51 1 1 10.0 2.0 2 3.0 2 0 -52 1 1 10.0 2.0 2 3.0 2 0 -53 1 1 10.0 2.0 2 3.0 2 0 -54 1 1 10.0 2.0 2 3.0 2 0 -55 1 1 10.0 2.0 2 3.0 2 0 -56 1 1 10.0 2.0 2 3.0 2 0 -57 1 1 10.0 2.0 2 3.0 2 0 -58 1 1 10.0 2.0 2 3.0 2 0 -59 1 1 10.0 2.0 2 3.0 2 0 -60 1 1 10.0 2.0 2 3.0 2 0 -61 1 1 10.0 2.0 2 3.0 2 0 -62 1 1 10.0 2.0 2 3.0 2 0 -63 1 1 10.0 2.0 2 3.0 2 0 -64 1 1 10.0 2.0 2 3.0 2 0 -65 1 1 10.0 2.0 2 3.0 2 0 -66 1 1 10.0 2.0 2 3.0 2 0 -67 1 1 10.0 2.0 2 3.0 2 0 -68 1 1 10.0 2.0 2 3.0 2 0 -69 1 1 10.0 2.0 2 3.0 2 0 -70 1 1 10.0 2.0 2 3.0 2 0 -71 1 1 10.0 2.0 2 3.0 2 0 -72 1 1 10.0 2.0 2 3.0 2 0 -73 1 1 10.0 2.0 2 3.0 2 0 -74 1 1 10.0 2.0 2 3.0 2 0 -75 1 1 10.0 2.0 2 3.0 2 0 -76 1 1 10.0 2.0 2 3.0 2 0 -77 1 1 10.0 2.0 2 3.0 2 0 -78 1 1 10.0 2.0 2 3.0 2 0 -79 1 1 10.0 2.0 2 3.0 2 0 -80 1 1 10.0 2.0 2 3.0 2 0 -81 1 1 10.0 2.0 2 3.0 2 0 -82 1 1 10.0 2.0 2 3.0 2 0 -83 1 1 10.0 2.0 2 3.0 2 0 -84 1 1 10.0 2.0 2 3.0 2 0 -85 1 1 10.0 2.0 2 3.0 2 0 -86 1 1 10.0 2.0 2 3.0 2 0 -87 1 1 10.0 2.0 2 3.0 2 0 -88 1 1 10.0 2.0 2 3.0 2 0 -89 1 1 10.0 2.0 2 3.0 2 0 -90 1 1 10.0 2.0 2 3.0 2 0 -91 1 1 10.0 2.0 2 3.0 2 0 -92 1 1 10.0 2.0 2 3.0 2 0 -93 1 1 10.0 2.0 2 3.0 2 0 -94 1 1 10.0 2.0 2 3.0 2 0 -95 1 1 10.0 2.0 2 3.0 2 0 -96 1 1 10.0 2.0 2 3.0 2 0 -97 1 1 10.0 2.0 2 3.0 2 0 -98 1 1 10.0 2.0 2 3.0 2 0 -99 1 1 10.0 2.0 2 3.0 2 0 -100 1 1 10.0 2.0 2 3.0 2 0 -101 1 1 10.0 2.0 2 3.0 2 0 -102 1 1 10.0 2.0 2 3.0 2 0 -103 1 1 10.0 2.0 2 3.0 2 0 -104 1 1 10.0 2.0 2 3.0 2 0 -105 1 1 10.0 2.0 2 3.0 2 0 -106 1 1 10.0 2.0 2 3.0 2 0 -107 1 1 10.0 2.0 2 3.0 2 0 -108 1 1 10.0 2.0 2 3.0 2 0 -109 1 1 10.0 2.0 2 3.0 2 0 -110 1 1 10.0 2.0 2 3.0 2 0 -111 1 1 10.0 2.0 2 3.0 2 0 -112 1 1 10.0 2.0 2 3.0 2 0 -113 1 1 10.0 2.0 2 3.0 2 0 -114 1 1 10.0 2.0 2 3.0 2 0 -115 1 1 10.0 2.0 2 3.0 2 0 -116 1 1 10.0 2.0 2 3.0 2 0 -117 1 1 10.0 2.0 2 3.0 2 0 -118 1 1 10.0 2.0 2 3.0 2 0 -119 1 1 10.0 2.0 2 3.0 2 0 -120 1 1 10.0 2.0 2 3.0 2 0 -121 1 1 10.0 2.0 2 3.0 2 0 -122 1 1 10.0 2.0 2 3.0 2 0 -123 1 1 10.0 2.0 2 3.0 2 0 -124 1 1 10.0 2.0 2 3.0 2 0 -125 1 1 10.0 2.0 2 3.0 2 0 -126 1 1 10.0 2.0 2 3.0 2 0 -127 1 1 10.0 2.0 2 3.0 2 0 -128 1 1 10.0 2.0 2 3.0 2 0 -129 1 1 10.0 2.0 2 3.0 2 0 -130 1 1 10.0 2.0 2 3.0 2 0 -131 1 1 10.0 2.0 2 3.0 2 0 -132 1 1 10.0 2.0 2 3.0 2 0 -133 1 1 10.0 2.0 2 3.0 2 0 -134 1 1 10.0 2.0 2 3.0 2 0 -135 1 1 10.0 2.0 2 3.0 2 0 +SERNUM BENUNIT PERSON PENTYPE PENPAY PTAMT PTINC POAMT POINC PENOTH +1 1 1 1 10.0 2.0 2 3.0 2 0 +2 1 1 1 10.0 2.0 2 3.0 2 0 +3 1 1 1 10.0 2.0 2 3.0 2 0 +4 1 1 1 10.0 2.0 2 3.0 2 0 +5 1 1 5 10.0 2.0 2 3.0 2 0 +6 1 1 1 10.0 2.0 2 3.0 2 0 +7 1 1 1 10.0 2.0 2 3.0 2 0 +8 1 1 1 10.0 2.0 2 3.0 2 0 +9 1 1 1 10.0 2.0 2 3.0 2 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2 0 +79 1 1 1 10.0 2.0 2 3.0 2 0 +80 1 1 5 10.0 2.0 2 3.0 2 0 +81 1 1 1 10.0 2.0 2 3.0 2 0 +82 1 1 1 10.0 2.0 2 3.0 2 0 +83 1 1 1 10.0 2.0 2 3.0 2 0 +84 1 1 1 10.0 2.0 2 3.0 2 0 +85 1 1 5 10.0 2.0 2 3.0 2 0 +86 1 1 1 10.0 2.0 2 3.0 2 0 +87 1 1 1 10.0 2.0 2 3.0 2 0 +88 1 1 1 10.0 2.0 2 3.0 2 0 +89 1 1 1 10.0 2.0 2 3.0 2 0 +90 1 1 5 10.0 2.0 2 3.0 2 0 +91 1 1 1 10.0 2.0 2 3.0 2 0 +92 1 1 1 10.0 2.0 2 3.0 2 0 +93 1 1 1 10.0 2.0 2 3.0 2 0 +94 1 1 1 10.0 2.0 2 3.0 2 0 +95 1 1 5 10.0 2.0 2 3.0 2 0 +96 1 1 1 10.0 2.0 2 3.0 2 0 +97 1 1 1 10.0 2.0 2 3.0 2 0 +98 1 1 1 10.0 2.0 2 3.0 2 0 +99 1 1 1 10.0 2.0 2 3.0 2 0 +100 1 1 5 10.0 2.0 2 3.0 2 0 +101 1 1 1 10.0 2.0 2 3.0 2 0 +102 1 1 1 10.0 2.0 2 3.0 2 0 +103 1 1 1 10.0 2.0 2 3.0 2 0 +104 1 1 1 10.0 2.0 2 3.0 2 0 +105 1 1 5 10.0 2.0 2 3.0 2 0 +106 1 1 1 10.0 2.0 2 3.0 2 0 +107 1 1 1 10.0 2.0 2 3.0 2 0 +108 1 1 1 10.0 2.0 2 3.0 2 0 +109 1 1 1 10.0 2.0 2 3.0 2 0 +110 1 1 5 10.0 2.0 2 3.0 2 0 +111 1 1 1 10.0 2.0 2 3.0 2 0 +112 1 1 1 10.0 2.0 2 3.0 2 0 +113 1 1 1 10.0 2.0 2 3.0 2 0 +114 1 1 1 10.0 2.0 2 3.0 2 0 +115 1 1 5 10.0 2.0 2 3.0 2 0 +116 1 1 1 10.0 2.0 2 3.0 2 0 +117 1 1 1 10.0 2.0 2 3.0 2 0 +118 1 1 1 10.0 2.0 2 3.0 2 0 +119 1 1 1 10.0 2.0 2 3.0 2 0 +120 1 1 5 10.0 2.0 2 3.0 2 0 +121 1 1 1 10.0 2.0 2 3.0 2 0 +122 1 1 1 10.0 2.0 2 3.0 2 0 +123 1 1 1 10.0 2.0 2 3.0 2 0 +124 1 1 1 10.0 2.0 2 3.0 2 0 +125 1 1 5 10.0 2.0 2 3.0 2 0 +126 1 1 1 10.0 2.0 2 3.0 2 0 +127 1 1 1 10.0 2.0 2 3.0 2 0 +128 1 1 1 10.0 2.0 2 3.0 2 0 +129 1 1 1 10.0 2.0 2 3.0 2 0 +130 1 1 5 10.0 2.0 2 3.0 2 0 +131 1 1 1 10.0 2.0 2 3.0 2 0 +132 1 1 1 10.0 2.0 2 3.0 2 0 +133 1 1 1 10.0 2.0 2 3.0 2 0 +134 1 1 1 10.0 2.0 2 3.0 2 0 +135 1 1 5 10.0 2.0 2 3.0 2 0 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 6a81e370c6..eb3565845a 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,frs_care_hours_in_household,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,individual_savings_account_interest_income,savings_interest_income,dividend_income,other_investment_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,frs_bonus_amount,property_income,reports_rent_from_other_property,maintenance_income,spousal_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,widowed_parents_allowance_reported,war_widows_pension_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__ -1001,101,1,80,FEMALE,5.9_9999999999921663e+00,SINGLE,1.0_9200000000000000e+03,3.5_0000000000000000e+01,0.0_0000000000000000e+00,True,True,False,False,5.2_5200000000000000e+03,5.2_0000000000000000e+01,0.0_0000000000000000e+00,0.0_0000000000000000e+00,0.0_0000000000000000e+00,7.8_0000000000000000e+02,5.2_0000000000000000e+01,1.3_0000000000000000e+02,0.0_0000000000000000e+00,0.0_0000000000000000e+00,False,False,False,False,False,0.0_0000000000000000e+00,0.0_0000000000000000e+00,1.0_4000000000000000e+02,True,1.0_4000000000000000e+02,7.2_8000000000000000e+02,2.1_3200000000000000e+03,2.0_8000000000000000e+03,2.0_0000000000000000e+01,1.0_4000000000000000e+02,5.2_0000000000000000e+01,2.6_0000000000000000e+01,1.3_0000000000000000e+01,5.0_0000000000000000e+02,5.2_0000000000000000e+01,5.0_0000000000000000e+00,2.6_0000000000000000e+02,0.0_0000000000000000e+00,0.0_0000000000000000e+00,0.0_0000000000000000e+00,3.6_4000000000000000e+02,0.0_0000000000000000e+00,0.0_0000000000000000e+00,0.0_0000000000000000e+00,0.0_0000000000000000e+00,0.0_0000000000000000e+00,0.0_0000000000000000e+00,4.2_5880000000000018e+03,0.0_0000000000000000e+00,0.0_0000000000000000e+00,0.0_0000000000000000e+00,0.0_0000000000000000e+00,0.0_0000000000000000e+00,0.0_0000000000000000e+00,5.2_0000000000000000e+01,0.0_0000000000000000e+00,0.0_0000000000000000e+00,0.0_0000000000000000e+00,0.0_0000000000000000e+00,0.0_0000000000000000e+00,1.0_4000000000000000e+02,1.5_6000000000000000e+02,2.0_8000000000000000e+02,2.6_0000000000000000e+02,True,0.0_0000000000000000e+00,3.1_2000000000000000e+02,0.0_0000000000000000e+00,True,5.2_0000000000000000e+01,1.0_4000000000000000e+02,2.6_0000000000000000e+02,2.0_8000000000000000e+02,1.0_4000000000000000e+02,1.5_6000000000000000e+02,1.0_0000000000000000e+00,1.0_0000000000000000e+00,True,5.2_0000000000000000e+01,0.0_0000000000000000e+00,True,False,False,False,default 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diff --git a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/schema.json b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/schema.json index a755b50aa2..e195432e98 100644 --- a/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/schema.json +++ b/packages/microcosm-graph/tests/fixtures/parity/uk_spine/sources/schema.json @@ -32,6 +32,7 @@ "access_fund": "float64", "afcs_reported": "float64", "age": "int64", + "annuity_and_trust_income": "float64", "attendance_allowance_reported": "float64", "bsp_reported": "float64", "care_hours": "float64", 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 7b0a6001c7..0693e4a0c4 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 @@ 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structural UK stage 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structural UK stage 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UK spine stage 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UK spine stage 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UK FRS and donor fixture/source bundle.","name":"frs"}]} diff --git a/tools/build_uk_release_input_coverage_manifest.py b/tools/build_uk_release_input_coverage_manifest.py index 6b28c6c42a..621bb9c5c6 100644 --- a/tools/build_uk_release_input_coverage_manifest.py +++ b/tools/build_uk_release_input_coverage_manifest.py @@ -932,6 +932,10 @@ def build_manifest( stage_name="isa_subscriptions", candidate_source=candidate_source, ), + "trading_allowance_receipts": _source_stage_family_coverage_contract( + stage_name="trading_allowance_receipts", + candidate_source=candidate_source, + ), "nts_bus_travel": _source_stage_family_coverage_contract( stage_name="nts_bus_travel", candidate_source=candidate_source, diff --git a/tools/graph_uk_spine_fixture.py b/tools/graph_uk_spine_fixture.py index c0465f9fe2..c89625b6dc 100644 --- a/tools/graph_uk_spine_fixture.py +++ b/tools/graph_uk_spine_fixture.py @@ -176,6 +176,9 @@ ) from microcosm.build.uk_runtime.student_loans import UKStudentLoansStageTransform from microcosm.build.uk_runtime.take_up_contract import load_uk_take_up_contract +from microcosm.build.uk_runtime.trading_allowance_receipts import ( + UKTradingAllowanceReceiptsStageTransform, +) from microcosm.build.uk_runtime.uc_capital_coherence import ( UKUCCapitalCoherenceStageTransform, ) @@ -208,7 +211,7 @@ _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 = 50 +UK_FIXTURE_STAGE_COUNT = 51 _QRF_ESTIMATORS = 4 # These are the complete object-string surface observed in the unchanged @@ -730,6 +733,10 @@ def _frs_tables() -> dict[str, pd.DataFrame]: "SERNUM": household_id, "BENUNIT": 1, "PERSON": 1, + # Every fifth household's payment is trust income (PENTYPE 5), + # which stays private pension with its part stored as the + # annuity and trust descriptor (microcosm#1428). + "PENTYPE": 5 if household_id % 5 == 0 else 1, "PENPAY": 10.0, "PTAMT": 2.0, "PTINC": 2, @@ -2149,6 +2156,9 @@ def capture_root(frame: Frame) -> Frame: donor_household=was, donor_person=was_person, ), + "trading_allowance_receipts": UKTradingAllowanceReceiptsStageTransform( + stage=stages["trading_allowance_receipts"] + ), "nts_bus_travel": UKNTSBusTravelStageTransform( stage=stages["nts_bus_travel"], engine=engine,