diff --git a/changelog.d/be-reference-documents.added.md b/changelog.d/be-reference-documents.added.md new file mode 100644 index 0000000000..9fe9c01160 --- /dev/null +++ b/changelog.d/be-reference-documents.added.md @@ -0,0 +1 @@ +Add Belgium's calibration, pre-calibration and holdout reference documents, generated by `tools/generate_be_target_references.py` from a pinned Chronicle `be` feed (`chronicle_feed.json`). References carry selectors only. Demography targets Statbel's 1 January 2026 population by region, sex and age. Statbel A.1's eight broad stand-in income bands (the d1952 measure), B.4's joint and individual declarations, ONSS contributions and FPB benefit and mixed-income aggregates roll 2023 to 2025 facts to 2026 by declared FPB June 2026 ratio pairs. Commune population is the pre-calibration geography support. Eurostat D51A_C1, NBB and Eurostat household accounts, and FPB's gross wages are holdouts. B.1 assessed tax stays inactive because its tax-definition, income-ranking and policy-year checks fail. Rows without a producer or ruling stay parked with a named reason. `reference_inventory.json` records the stand-in gaps, ageing ratios, B.1 checks and every exclusion, and `reference_aging.json` holds G8-r2 diagnostic factors from RSZ wage totals. The catalog declares two euro money columns. Belgium stays inactive, and every method-card choice remains proposed pending d1902. diff --git a/packages/microcosm-build/src/microcosm/build/be/chronicle_feed.json b/packages/microcosm-build/src/microcosm/build/be/chronicle_feed.json new file mode 100644 index 0000000000..5ef7bb2e50 --- /dev/null +++ b/packages/microcosm-build/src/microcosm/build/be/chronicle_feed.json @@ -0,0 +1,16 @@ +{ + "version": 1, + "country": "be", + "scope": "be_calibration", + "source_repo": "PolicyEngine/chronicle", + "source_commit": "2c7e8357f1dcb9af2337c10d6cf4cbd82b1e55ef", + "build": "build-bundle --suite be -> build-consumer-artifact", + "artifact_schema_version": "policyengine_ledger.consumer_artifact.v2", + "consumer_fact_schema_versions": [ + "chronicle.consumer_fact.v4" + ], + "consumer_fact_schema_sha256": "d953306d6f01fbc64db4372d0262d3012ee590269f8a25b276b18dca0626c6a0", + "fact_row_count": 87112, + "facts_sha256": "e01a463065a81ba60139a24a605e52797442504478be60970e0ff66f9d3c6b95", + "manifest_sha256": "7839792643a6a32a1784328644df16c250e8d4ba08287c455983a6e7ceebb34c" +} diff --git a/packages/microcosm-build/src/microcosm/build/be/country_package.json b/packages/microcosm-build/src/microcosm/build/be/country_package.json index c02792bf68..9590487c51 100644 --- a/packages/microcosm-build/src/microcosm/build/be/country_package.json +++ b/packages/microcosm-build/src/microcosm/build/be/country_package.json @@ -32,6 +32,11 @@ "kind": "vintages", "schema_id": "vintages.schema.json" }, + { + "path": "chronicle_feed.json", + "kind": "legacy_json", + "schema_id": "legacy_json" + }, { "path": "gates.json", "kind": "legacy_json", @@ -42,6 +47,36 @@ "kind": "legacy_json", "schema_id": "legacy_json" }, + { + "path": "holdout_references.json", + "kind": "legacy_json", + "schema_id": "legacy_json" + }, + { + "path": "precal_references.json", + "kind": "legacy_json", + "schema_id": "legacy_json" + }, + { + "path": "reference_aging.json", + "kind": "legacy_json", + "schema_id": "legacy_json" + }, + { + "path": "reference_intervals.json", + "kind": "legacy_json", + "schema_id": "legacy_json" + }, + { + "path": "reference_inventory.json", + "kind": "legacy_json", + "schema_id": "legacy_json" + }, + { + "path": "reference_profiles.json", + "kind": "legacy_json", + "schema_id": "legacy_json" + }, { "path": "release_contract.json", "kind": "legacy_json", diff --git a/packages/microcosm-build/src/microcosm/build/be/holdout_references.json b/packages/microcosm-build/src/microcosm/build/be/holdout_references.json new file mode 100644 index 0000000000..7aa6e4ade2 --- /dev/null +++ b/packages/microcosm-build/src/microcosm/build/be/holdout_references.json @@ -0,0 +1,716 @@ +{ + "country": "be", + "schema_version": 2, + "reference_set": "holdout", + "description": "Belgian held-out references: compared with the model, never fitted. No calibration-side node may read this resource. Every row is parked until its measure has a producer; JRC's EUROMOD-BE statistics are deferred while d1822 is open.", + "allowed_value_operations": [ + "rolled_forward_by_ratio" + ], + "hierarchy": { + "providers": { + "eurostat": { + "label": "Eurostat" + }, + "fpb": { + "label": "Federal Planning Bureau" + }, + "nbb": { + "label": "National Bank of Belgium" + } + }, + "categories": { + "eurostat.household_accounts": { + "provider_id": "eurostat", + "label": "Household accounts" + }, + "eurostat.income_tax": { + "provider_id": "eurostat", + "label": "Income tax revenue" + }, + "fpb.household_account": { + "provider_id": "fpb", + "label": "Household account" + }, + "nbb.national_accounts": { + "provider_id": "nbb", + "label": "National accounts" + } + }, + "target_labels": { + "eurostat_d51a_c1_individual_income_tax": "Eurostat D51A_C1 taxes on individual or household income, 2025, rolled to 2026", + "eurostat_household_current_taxes_paid": "Eurostat household current taxes on income and wealth paid (D5), 2024, rolled to 2026", + "eurostat_household_gross_disposable_income": "Eurostat household and NPISH gross disposable income (B6G), 2024, rolled to 2026", + "eurostat_household_social_benefits_received": "Eurostat household social benefits received (D62), 2024, rolled to 2026", + "eurostat_household_social_contributions_paid": "Eurostat household social contributions paid (D61), 2024, rolled to 2026", + "fpb_gross_wages_and_salaries": "FPB gross wages and salaries (salaires bruts), 2025, rolled to 2026", + "nbb_household_gross_disposable_income": "NBB household gross disposable income (B6G), 2024, rolled to 2026" + } + }, + "target_references": [ + { + "name": "eurostat_d51a_c1_individual_income_tax", + "ledger_selector": { + "source_name": "eurostat", + "source_measure_id": "revenue", + "source_concept": "eurostat.gov_10a_taxag.value", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "eurostat.gov_10a_taxag.cy2025.income_tax_revenue_by_taxpayer.country", + "dimensions": [ + "freq", + "geo", + "na_item", + "sector", + "time", + "unit" + ], + "dimension_values": { + "freq": "A", + "geo": "BE", + "na_item": "D51A_C1", + "sector": "S13", + "time": 2025, + "unit": "MIO_EUR" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:e3c28f2774b8452eeb2acd91", + "assertion": "observation" + }, + "entity": "person", + "measure": "belgium_pit_federal_and_local_tax_before_withholding", + "period": 2026, + "family": "income_tax", + "category_id": "eurostat.income_tax", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "eurostat_d51a_c1_individual_income_tax", + "activation_status": "requires_holdout_measure", + "criticality": "diagnostic", + "measure_kind": "rules_output", + "publisher": "Eurostat", + "target_role": "validation", + "reference_set": "holdout", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "parking_reason": "Held out of calibration; compared, never fitted. Accrual national-accounts revenue held out against assessed tax (BE-MC5). W3: needs a pinned rulespec-be binding for be/statutes/income_tax/individual/final_tax.yaml on the transported frame, the S5 pre-calibration allowlist entry for it, and B4's euro conversion of the donor inputs it reads.", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t17_direct_taxes_households", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2025", + "target_period": "2026", + "holdout_use": "validation_comparator" + }, + "notes": "Held out of calibration; compared, never fitted. Accrual national-accounts revenue held out against assessed tax (BE-MC5). W3: needs a pinned rulespec-be binding for be/statutes/income_tax/individual/final_tax.yaml on the transported frame, the S5 pre-calibration allowlist entry for it, and B4's euro conversion of the donor inputs it reads.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base" + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t17.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.general_government_account.direct_taxes_households", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:09dcccdb13ecc60173a18079", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t17.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2025.general_government_account.direct_taxes_households", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:ebae7d68bab03979e30b2b5e", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "nbb_household_gross_disposable_income", + "ledger_selector": { + "source_name": "nbb_national_accounts", + "source_measure_id": "household_disposable_income", + "source_concept": "nbb.household_income_accounts.gross_disposable_income", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2024, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "nbb.national_accounts.cy2024.household_disposable_income.country", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:5e83461cf5b9b1d0292c4c7e", + "assertion": "observation" + }, + "entity": "household", + "measure": "household_gross_disposable_income_eur", + "period": 2026, + "family": "national_accounts", + "category_id": "nbb.national_accounts", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "nbb_household_gross_disposable_income", + "activation_status": "requires_holdout_measure", + "criticality": "diagnostic", + "measure_kind": "prepared_column", + "publisher": "National Bank of Belgium", + "target_role": "validation", + "reference_set": "holdout", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "parking_reason": "Held out of calibration; compared, never fitted. No producer: rulespec-be's disposable-income policy is a narrow worker bridge, not integrated disposable income.", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t06_net_national_disposable_income", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2024", + "target_period": "2026", + "holdout_use": "validation_comparator" + }, + "notes": "Held out of calibration; compared, never fitted. No producer: rulespec-be's disposable-income policy is a narrow worker bridge, not integrated disposable income.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base" + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t06.published_cell", + "entity_name": "institutional_sector", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.national_income_account.net_national_disposable_income", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:63c570cc58902f2813b3bde9", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t06.published_cell", + "entity_name": "institutional_sector", + "period_type": "calendar_year", + "period_value": 2024, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2024.national_income_account.net_national_disposable_income", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:5148b5898c391c11ff484930", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "eurostat_household_gross_disposable_income", + "ledger_selector": { + "source_name": "eurostat", + "source_measure_id": "amount", + "source_concept": "eurostat.nasa_10_nf_tr.non_financial_transaction_amount", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2024, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "eurostat.nasa_10_nf_tr.cy2024.household_non_financial_transactions.received.be", + "dimensions": [ + "direct", + "freq", + "geo", + "na_item", + "sector", + "time", + "unit" + ], + "dimension_values": { + "direct": "RECV", + "freq": "A", + "geo": "BE", + "na_item": "B6G", + "sector": "S14_S15", + "time": 2024, + "unit": "CP_MEUR" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:1c1549bca1f666dae3f1c6fe", + "assertion": "observation" + }, + "entity": "household", + "measure": "household_gross_disposable_income_eur", + "period": 2026, + "family": "household_accounts", + "category_id": "eurostat.household_accounts", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "eurostat_household_gross_disposable_income", + "activation_status": "requires_holdout_measure", + "criticality": "diagnostic", + "measure_kind": "prepared_column", + "publisher": "Eurostat", + "target_role": "validation", + "reference_set": "holdout", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "parking_reason": "Held out of calibration; compared, never fitted. No producer, as for NBB's B6G. Eurostat's S14_S15 sector adds non-profit institutions to NBB's household figure.", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t06_net_national_disposable_income", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2024", + "target_period": "2026", + "holdout_use": "validation_comparator" + }, + "notes": "Held out of calibration; compared, never fitted. No producer, as for NBB's B6G. Eurostat's S14_S15 sector adds non-profit institutions to NBB's household figure.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base" + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t06.published_cell", + "entity_name": "institutional_sector", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.national_income_account.net_national_disposable_income", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:63c570cc58902f2813b3bde9", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t06.published_cell", + "entity_name": "institutional_sector", + "period_type": "calendar_year", + "period_value": 2024, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2024.national_income_account.net_national_disposable_income", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:5148b5898c391c11ff484930", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "eurostat_household_social_benefits_received", + "ledger_selector": { + "source_name": "eurostat", + "source_measure_id": "amount", + "source_concept": "eurostat.nasa_10_nf_tr.non_financial_transaction_amount", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2024, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "eurostat.nasa_10_nf_tr.cy2024.household_non_financial_transactions.received.be", + "dimensions": [ + "direct", + "freq", + "geo", + "na_item", + "sector", + "time", + "unit" + ], + "dimension_values": { + "direct": "RECV", + "freq": "A", + "geo": "BE", + "na_item": "D62", + "sector": "S14_S15", + "time": 2024, + "unit": "CP_MEUR" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:8c7c28463b5421308945c344", + "assertion": "observation" + }, + "entity": "household", + "measure": "household_social_benefits_received_eur", + "period": 2026, + "family": "household_accounts", + "category_id": "eurostat.household_accounts", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "eurostat_household_social_benefits_received", + "activation_status": "requires_holdout_measure", + "criticality": "diagnostic", + "measure_kind": "prepared_column", + "publisher": "Eurostat", + "target_role": "validation", + "reference_set": "holdout", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "parking_reason": "Held out of calibration; compared, never fitted. No producer: pensions (d1902), child benefits (not modelled at level) and unemployment receipts (W3) are missing.", + "ageing_target_equals": "FPB's 2026 projection of the pair's row: the base equals its denominator", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t11_social_benefits", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2024", + "target_period": "2026", + "holdout_use": "validation_comparator" + }, + "notes": "Held out of calibration; compared, never fitted. No producer: pensions (d1902), child benefits (not modelled at level) and unemployment receipts (W3) are missing.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base" + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.household_account.social_benefits", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:bf52974b05acf19d1d3ccb28", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2024, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2024.household_account.social_benefits", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:e87808ae0b585214ec608b92", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "eurostat_household_social_contributions_paid", + "ledger_selector": { + "source_name": "eurostat", + "source_measure_id": "amount", + "source_concept": "eurostat.nasa_10_nf_tr.non_financial_transaction_amount", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2024, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "eurostat.nasa_10_nf_tr.cy2024.household_non_financial_transactions.paid.be", + "dimensions": [ + "direct", + "freq", + "geo", + "na_item", + "sector", + "time", + "unit" + ], + "dimension_values": { + "direct": "PAID", + "freq": "A", + "geo": "BE", + "na_item": "D61", + "sector": "S14_S15", + "time": 2024, + "unit": "CP_MEUR" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:627f1716ff45e9ac8e2ffd22", + "assertion": "observation" + }, + "entity": "household", + "measure": "household_social_contributions_paid_eur", + "period": 2026, + "family": "household_accounts", + "category_id": "eurostat.household_accounts", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "eurostat_household_social_contributions_paid", + "activation_status": "requires_holdout_measure", + "criticality": "diagnostic", + "measure_kind": "prepared_column", + "publisher": "Eurostat", + "target_role": "validation", + "reference_set": "holdout", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "parking_reason": "Held out of calibration; compared, never fitted. No producer: employer and self-employed contributions are not bound (W3).", + "ageing_target_equals": "FPB's 2026 projection of the pair's row: the base equals its denominator", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t11_social_contributions", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2024", + "target_period": "2026", + "holdout_use": "validation_comparator" + }, + "notes": "Held out of calibration; compared, never fitted. No producer: employer and self-employed contributions are not bound (W3).", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base" + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.household_account.social_contributions", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:4c597d6ad755576b4e1faf01", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2024, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2024.household_account.social_contributions", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:deed6d1fc86e5e7032cbfa5e", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "eurostat_household_current_taxes_paid", + "ledger_selector": { + "source_name": "eurostat", + "source_measure_id": "amount", + "source_concept": "eurostat.nasa_10_nf_tr.non_financial_transaction_amount", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2024, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "eurostat.nasa_10_nf_tr.cy2024.household_non_financial_transactions.paid.be", + "dimensions": [ + "direct", + "freq", + "geo", + "na_item", + "sector", + "time", + "unit" + ], + "dimension_values": { + "direct": "PAID", + "freq": "A", + "geo": "BE", + "na_item": "D5", + "sector": "S14_S15", + "time": 2024, + "unit": "CP_MEUR" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:05ca22b4bedd957b4d655ff6", + "assertion": "observation" + }, + "entity": "household", + "measure": "household_current_taxes_on_income_paid_eur", + "period": 2026, + "family": "household_accounts", + "category_id": "eurostat.household_accounts", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "eurostat_household_current_taxes_paid", + "activation_status": "requires_holdout_measure", + "criticality": "diagnostic", + "measure_kind": "prepared_column", + "publisher": "Eurostat", + "target_role": "validation", + "reference_set": "holdout", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "parking_reason": "Held out of calibration; compared, never fitted. No producer: needs the PIT binding (W3) aggregated to households.", + "ageing_target_equals": "FPB's 2026 projection of the pair's row: the base equals its denominator", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t11_current_taxes_on_income_and_wealth", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2024", + "target_period": "2026", + "holdout_use": "validation_comparator" + }, + "notes": "Held out of calibration; compared, never fitted. No producer: needs the PIT binding (W3) aggregated to households.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base" + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.household_account.current_taxes_on_income_and_wealth", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:67bb0b178a502334a5798bfa", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2024, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2024.household_account.current_taxes_on_income_and_wealth", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:d3638106fd28d6f6d119c0d5", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "fpb_gross_wages_and_salaries", + "ledger_selector": { + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2025.household_account.gross_wages_and_salaries", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:1b99b4161fa76ca1069ad5e7", + "assertion": "observation" + }, + "entity": "person", + "measure": "employment_income", + "period": 2026, + "family": "household_accounts", + "category_id": "fpb.household_account", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "fpb_gross_wages_and_salaries", + "activation_status": "requires_holdout_measure", + "criticality": "diagnostic", + "measure_kind": "transported_input", + "publisher": "Federal Planning Bureau", + "target_role": "validation", + "reference_set": "holdout", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "parking_reason": "Held out of calibration; compared, never fitted. The card's wage-headline comparator (BE-MC5): gross wages, not compensation including employer contributions. The euro wage column has no producer until B4's currency bridge.", + "ageing_target_equals": "FPB's 2026 projection of the base's own row", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t11_gross_wages_and_salaries", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2025", + "target_period": "2026", + "holdout_use": "validation_comparator" + }, + "notes": "Held out of calibration; compared, never fitted. The card's wage-headline comparator (BE-MC5): gross wages, not compensation including employer contributions. The euro wage column has no producer until B4's currency bridge.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base" + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.household_account.gross_wages_and_salaries", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:f17958efe84e42471bf68f80", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2025.household_account.gross_wages_and_salaries", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:1b99b4161fa76ca1069ad5e7", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + } + ], + "target_profile": { + "schema_version": 1, + "hierarchy_reconciliations": [] + } +} diff --git a/packages/microcosm-build/src/microcosm/build/be/precal_references.json b/packages/microcosm-build/src/microcosm/build/be/precal_references.json new file mode 100644 index 0000000000..4c9a895a55 --- /dev/null +++ b/packages/microcosm-build/src/microcosm/build/be/precal_references.json @@ -0,0 +1,21501 @@ +{ + "country": "be", + "schema_version": 2, + "reference_set": "precal", + "description": "Belgian pre-calibration references: Statbel commune population on 1 January 2025 as the atomic geography support mass, unaged (support shares). Identity only; no observation is carried.", + "allowed_value_operations": [ + "identity" + ], + "hierarchy": { + "providers": { + "statbel": { + "label": "Statbel" + } + }, + "categories": { + "statbel.geography_support": { + "provider_id": "statbel", + "label": "Geography support" + } + }, + "target_labels": { + "statbel_population_by_commune": "Statbel resident population by NIS 2025 commune, 1 January 2025 (atomic geography support)" + } + }, + "target_references": [ + { + "name": "statbel_population_by_commune__nis11001", + "ledger_selector": { + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "commune", + "geography_id": "11001", + "geography_vintage": "nis_2025", + "record_set_id": "statbel.population_structure.cy2025.people.by_commune_nis2025.total", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:f835115b964f486edb03713c" + }, + "entity": "person", + "measure": "people", + "period": 2025, + "family": "geography_support", + "category_id": "statbel.geography_support", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_population_by_commune", + "activation_status": "active", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "pre_calibration", + "reference_set": "precal", + "method_card_row": "geography_spine", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "nis_2025", + "geography_vintage_authority": "vintage:be_nis_2025", + "precal_use": "atomic_geography_support", + "ageing": "none: support shares at 1 January 2025" + } + }, + { + "name": "statbel_population_by_commune__nis11002", + "ledger_selector": { + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "commune", + "geography_id": "11002", + "geography_vintage": "nis_2025", + "record_set_id": "statbel.population_structure.cy2025.people.by_commune_nis2025.total", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:2ba2424c10ef64feaf16d030" + }, + "entity": "person", + "measure": "people", + "period": 2025, + "family": "geography_support", + "category_id": "statbel.geography_support", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_population_by_commune", + "activation_status": "active", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "pre_calibration", + "reference_set": "precal", + "method_card_row": "geography_spine", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "nis_2025", + "geography_vintage_authority": "vintage:be_nis_2025", + "precal_use": "atomic_geography_support", + "ageing": "none: support shares at 1 January 2025" + } + }, + { + "name": "statbel_population_by_commune__nis11004", + "ledger_selector": { + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "commune", + "geography_id": "11004", + "geography_vintage": "nis_2025", + "record_set_id": "statbel.population_structure.cy2025.people.by_commune_nis2025.total", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:1c156d0b0bfc79da703fa489" + }, + "entity": "person", + "measure": "people", + "period": 2025, + "family": "geography_support", + "category_id": "statbel.geography_support", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_population_by_commune", + "activation_status": "active", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "pre_calibration", + "reference_set": "precal", + "method_card_row": "geography_spine", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "nis_2025", + "geography_vintage_authority": "vintage:be_nis_2025", + "precal_use": "atomic_geography_support", + "ageing": "none: support shares at 1 January 2025" + } + }, + { + "name": "statbel_population_by_commune__nis11005", + "ledger_selector": { + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "commune", + "geography_id": "11005", + "geography_vintage": "nis_2025", + "record_set_id": "statbel.population_structure.cy2025.people.by_commune_nis2025.total", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:ed6bf439079a3a43301b05ef" + }, + "entity": "person", + "measure": "people", + "period": 2025, + "family": "geography_support", + "category_id": "statbel.geography_support", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_population_by_commune", + "activation_status": "active", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "pre_calibration", + "reference_set": "precal", + "method_card_row": "geography_spine", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "nis_2025", + "geography_vintage_authority": "vintage:be_nis_2025", + "precal_use": "atomic_geography_support", + "ageing": "none: support shares at 1 January 2025" + } + }, + { + "name": "statbel_population_by_commune__nis11008", + "ledger_selector": { + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "commune", + "geography_id": "11008", + "geography_vintage": "nis_2025", + "record_set_id": "statbel.population_structure.cy2025.people.by_commune_nis2025.total", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:24f980b6aeca203045018aad" + }, + "entity": "person", + "measure": "people", + "period": 2025, + "family": "geography_support", + "category_id": "statbel.geography_support", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_population_by_commune", + "activation_status": "active", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "pre_calibration", + "reference_set": "precal", + "method_card_row": "geography_spine", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "nis_2025", + "geography_vintage_authority": "vintage:be_nis_2025", + "precal_use": "atomic_geography_support", + "ageing": "none: support shares at 1 January 2025" + } + }, + { + "name": "statbel_population_by_commune__nis11009", + "ledger_selector": { + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "commune", + "geography_id": "11009", + "geography_vintage": "nis_2025", + "record_set_id": "statbel.population_structure.cy2025.people.by_commune_nis2025.total", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:3d2995f8041fc351e1b93796" + }, + "entity": "person", + "measure": "people", + "period": 2025, + "family": "geography_support", + "category_id": "statbel.geography_support", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_population_by_commune", + "activation_status": "active", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "pre_calibration", + "reference_set": "precal", + "method_card_row": "geography_spine", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "nis_2025", + "geography_vintage_authority": "vintage:be_nis_2025", + "precal_use": "atomic_geography_support", + "ageing": "none: support shares at 1 January 2025" + } + }, + { + "name": "statbel_population_by_commune__nis11013", + "ledger_selector": { + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "commune", + "geography_id": "11013", + 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pre-publication raw data, landing page updated 22/10/2026. The 2024–2025 figures are not described as final. RSZ-registered employment in Belgium; includes inbound cross-border workers, excludes posted workers and self-employed people. Administrative employment population differs from Statbel fiscal declarations.", + "source_period_label": "2024", + "start_date": "2024-01-01" + }, + "weight": "1", + "sequence": 0 + } + ], + "target_schedule": [ + { + "selector": { + "source_name": "rsz_annual_wages_key_figures", + "source_measure_id": "ordinary_remuneration", + "source_concept": "rsz.annual_wages.ordinary_remuneration", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "rsz.annual_wages.year2025.ordinary_remuneration", + "dimensions": [ + "rsz.annual_worker_type_sex" + ], + "dimension_values": { + "rsz.annual_worker_type_sex": "total" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:3c1a0cfec5e2740c02758f98", + "assertion": "observation" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:3c1a0cfec5e2740c02758f98", + "decimal_operand": "171074878.6", + "numeric_token_proof": { + "numeric_representation": "binary_float_with_lexical_token", + "lexical_token": "171074878.6", + "recovered_decimal": "171074878.6", + "decimal_values_equal": true + }, + "validation": { + "unit": "EUR_thousands", + "source_sha256": "7f97f510d332a0966b1afba110ce448f4a4a83d9d58fd5c3bb4d8d36d1aeca97", + "source_vintage": "rsz_raw_wages_prepublication_2026_10_22", + "entity_role": "employee", + "provenance_class": "administrative", + "assertion": "observation", + "period_coverage": { + "start_date": "2025-01-01", + "end_date": "2025-12-31" + }, + "source_column_id": "ordinary_remuneration" + }, + "period": { + "type": "calendar_year", + "value": 2025 + }, + "source": { + "extracted_at": "2026-10-24", + "extraction_method": "CellSelectorSpec and SourceRecordSpec resolved from cells", + "method_notes": "Each fact carries source_record_id, source_cell_keys, and source_row_keys when available.", + "raw_r2_bucket": "ledger-raw", + "raw_r2_key": "raw/belgium/rsz-annual-wages-key-figures-2020-2025/2025/7f97f510d332a0966b1afba110ce448f4a4a83d9d58fd5c3bb4d8d36d1aeca97/annual_wages_key_figures_2020_2025.csv", + "raw_r2_uri": "r2://ledger-raw/raw/belgium/rsz-annual-wages-key-figures-2020-2025/2025/7f97f510d332a0966b1afba110ce448f4a4a83d9d58fd5c3bb4d8d36d1aeca97/annual_wages_key_figures_2020_2025.csv", + "source_file": "annual_wages_key_figures_2020_2025.csv", + "source_name": "rsz_annual_wages_key_figures", + "source_sha256": "7f97f510d332a0966b1afba110ce448f4a4a83d9d58fd5c3bb4d8d36d1aeca97", + "source_size_bytes": 68891, + "source_table": "Lonen en bezoldigde prestaties, Kerncijfers-Chiffres Clés, 2020–2025", + "url": "https://www.rsz.be/file/6103c41969844d308979992d7f84d51e59927e1e/c4c5776181e3dd24273ecb6b9486065cb468fadb/ruwedata-donneesbrutes-periods-wages.xlsx", + "vintage": "rsz_raw_wages_prepublication_2026_10_22" + }, + "unit": "EUR_thousands", + "assertion": "observation", + "provenance_class": "administrative", + "entity_role": "employee", + "period_coverage": { + "basis": "calendar", + "end_date": "2025-12-31", + "notes": "Calendar-year remuneration or paid days/hours; pre-publication raw data, landing page updated 22/10/2026. The 2024–2025 figures are not described as final. RSZ-registered employment in Belgium; includes inbound cross-border workers, excludes posted workers and self-employed people. Administrative employment population differs from Statbel fiscal declarations.", + "source_period_label": "2025", + "start_date": "2025-01-01" + }, + "status": "observed", + "sequence": 0, + "weight": "1", + "projection_offset": 0 + } + ], + "subperiods_per_year": 1, + "projection_policy": "observed_preferred_latest_contiguous", + "denominator_mean": { + "numerator": 165739460, + "denominator": 1 + }, + "growth": null, + "root_bounds": { + "lower": { + "numerator": 1, + "denominator": 1 + }, + "upper": { + "numerator": 1, + "denominator": 1 + }, + "exact": true, + "decimal_places": 14, + "degree": 1, + "radicand": { + "numerator": 1, + "denominator": 1 + } + }, + "numerator_mean_bounds": { + "lower": { + "numerator": 855374393, + "denominator": 5 + }, + "upper": { + "numerator": 855374393, + "denominator": 5 + } + }, + "unrounded_factor_bounds": { + "lower": { + "numerator": 855374393, + "denominator": 828697300 + }, + "upper": { + "numerator": 855374393, + "denominator": 828697300 + } + }, + "rounding": { + "digits": 6, + "mode": "nearest_half_even" + }, + "operational_factor": { + "numerator": 1032192, + "denominator": 1000000 + }, + "validity": { + "declared_on": "2026-11-01", + "valid_from": "2026-11-01", + "valid_until": "2027-06-30", + "as_of": "2026-11-01" + }, + "evidence": [ + "RSZ/ONSS annual wages key figures (Kerncijfers), ordinary remuneration, all employees, calendar years; pre-publication raw data, 2024-2025 not final", + "Diagnostic cross-check of the observed segment of FPB wage-driven ratio pairs; never a profile or money normalization input" + ], + "decision_references": [ + "BE-MC0 (proposed pending d1902): targets rolled to 2026 by FPB June 2026 ratio pairs", + "G8-r2 factor resolver: projected_period_average_ratio@1" + ], + "receipt_sha256": "1fa388f0c5b6d3ad8e01f7a0c3355155e5aacc84b710ee4f49b137a2b98d2b9c" + } + } + ] +} diff --git a/packages/microcosm-build/src/microcosm/build/be/reference_intervals.json b/packages/microcosm-build/src/microcosm/build/be/reference_intervals.json new file mode 100644 index 0000000000..bf5081a8b8 --- /dev/null +++ b/packages/microcosm-build/src/microcosm/build/be/reference_intervals.json @@ -0,0 +1,92 @@ +{ + "schema_version": 1, + "country": "be", + "description": "Generated by tools/generate_be_target_references.py from the class bounds Chronicle publishes on Statbel A.1 (universe constraints), checked to tile A.1's positive range without gaps.", + "disclosure": "Statbel's labels ('Minder dan 1', '1-2', '100 en meer') do not state a closure; Chronicle's A.1 universe constraints do: 0 < t < 1,000, then lower <= t < upper, and t >= 100,000 for the open top class. The table follows them: left-closed positive bands, a nil band for t == 0 (Statbel counts zero-income declarations outside A.1, and no reference fits the nil band, because the proxy's zeros are not Statbel's zeros), negative proxy income floored to zero, integer cents. Cuts are income-year-2023 euros and are not aged: no shared operation scales them by a declared annual ratio pair, so the A.1 references stay parked (BE-MC5, d1952; proposed pending d1902).", + "tables": [ + { + "id": "statbel_a1_standin_bands_iy2023", + "entity": "tax_unit", + "currency": "EUR", + "input_unit": "integer_cent", + "income_column": "statbel_net_taxable_income_proxy_v1_cents", + "universe_column": "statbel_net_taxable_income_proxy_v1_universe_status", + "source_period": 2023, + "target_period": 2026, + "positive_band_closure": "left", + "nil_band": "present", + "negative_income_policy": "floor_zero", + "first_lower_cut_cents": 0, + "source_locator": "Chronicle statbel.fiscal_income_distribution.a1.by_income_class_eur1000.v1, Belgium, taxable income classes", + "description": "The eight d1952 stand-in bands of total net taxable income, income year 2023, each an exact sum of A.1 EUR 1,000 classes.", + "diagnostics": { + "boundary_window_cents": 100, + "alternative_positive_band_closure": "right" + }, + "bands": [ + { + "id": "nil", + "kind": "nil", + "indicator": "statbel_a1_standin_nil_indicator", + "source_label": "zero total net taxable income (outside A.1)" + }, + { + "id": "under_10k", + "kind": "positive", + "upper_cent": 1000000, + "indicator": "statbel_a1_standin_band_under_10k_indicator", + "source_label": "A.1 classes class_under_1 to class_9_10" + }, + { + "id": "10k_20k", + "kind": "positive", + "upper_cent": 2000000, + "indicator": "statbel_a1_standin_band_10k_20k_indicator", + "source_label": "A.1 classes class_10_11 to class_19_20" + }, + { + "id": "20k_30k", + "kind": "positive", + "upper_cent": 3000000, + "indicator": "statbel_a1_standin_band_20k_30k_indicator", + "source_label": "A.1 classes class_20_21 to class_29_30" + }, + { + "id": "30k_40k", + "kind": "positive", + "upper_cent": 4000000, + "indicator": "statbel_a1_standin_band_30k_40k_indicator", + "source_label": "A.1 classes class_30_31 to class_39_40" + }, + { + "id": "40k_50k", + "kind": "positive", + "upper_cent": 5000000, + "indicator": "statbel_a1_standin_band_40k_50k_indicator", + "source_label": "A.1 classes class_40_41 to class_49_50" + }, + { + "id": "50k_75k", + "kind": "positive", + "upper_cent": 7500000, + "indicator": "statbel_a1_standin_band_50k_75k_indicator", + "source_label": "A.1 classes class_50_51 to class_74_75" + }, + { + "id": "75k_100k", + "kind": "positive", + "upper_cent": 10000000, + "indicator": "statbel_a1_standin_band_75k_100k_indicator", + "source_label": "A.1 classes class_75_76 to class_99_100" + }, + { + "id": "100k_plus", + "kind": "positive", + "upper_cent": null, + "indicator": "statbel_a1_standin_band_100k_plus_indicator", + "source_label": "A.1 classes class_100_plus to class_100_plus" + } + ] + } + ] +} diff --git a/packages/microcosm-build/src/microcosm/build/be/reference_inventory.json b/packages/microcosm-build/src/microcosm/build/be/reference_inventory.json new file mode 100644 index 0000000000..52b6fe3a97 --- /dev/null +++ b/packages/microcosm-build/src/microcosm/build/be/reference_inventory.json @@ -0,0 +1,13120 @@ +{ + "schema_version": 1, + "country": "be", + "generated_by": "tools/generate_be_target_references.py", + "feed_identity": { + "version": 1, + "country": "be", + "scope": "be_calibration", + "source_repo": "PolicyEngine/chronicle", + "source_commit": "2c7e8357f1dcb9af2337c10d6cf4cbd82b1e55ef", + "build": "build-bundle --suite be -> build-consumer-artifact", + "artifact_schema_version": "policyengine_ledger.consumer_artifact.v2", + "consumer_fact_schema_versions": [ + "chronicle.consumer_fact.v4" + ], + "consumer_fact_schema_sha256": "d953306d6f01fbc64db4372d0262d3012ee590269f8a25b276b18dca0626c6a0", + "fact_row_count": 87112, + "facts_sha256": "e01a463065a81ba60139a24a605e52797442504478be60970e0ff66f9d3c6b95", + "manifest_sha256": "7839792643a6a32a1784328644df16c250e8d4ba08287c455983a6e7ceebb34c" + }, + "policy_year": 2026, + "method_card_status": "BE-MC0, BE-MC3 to BE-MC6 proposed pending d1902; nothing publishes a number", + "reference_counts": { + "target_references.json": { + "total": 60, + "by_family": { + "demography": 18, + "fiscal_income": 18, + "income_tax": 19, + "social_security": 1, + "caseloads": 1, + "benefit_expenditure": 2, + "self_employment": 1 + }, + "by_contract": { + "statbel_population_by_region_sex_age": 18, + "statbel_a1_standin_declarations_by_band": 8, + "statbel_a1_standin_taxable_income_by_band": 8, + "statbel_b4_declarations_by_type": 2, + "statbel_b1_enrolled_tax_by_rank_group": 19, + "onss_worker_personal_contributions": 1, + "onem_complete_unemployment_recipients": 1, + "fpb_unemployment_benefit_expenditure": 1, + "fpb_grapa_expenditure": 1, + "fpb_net_mixed_income": 1 + }, + "by_activation_status": { + "active": 18, + "requires_prerequisites": 16, + "requires_declared_tax_units": 2, + "inactive_pending_b1_checks": 19, + "requires_rules_binding": 1, + "requires_ageing_ruling_and_receipt_binding": 1, + "requires_receipt_contract_and_rules_binding": 1, + "requires_pension_route_d1902": 1, + "requires_currency_bridge_b4": 1 + } + }, + "precal_references.json": { + "total": 565, + "by_family": { + "geography_support": 565 + }, + "by_contract": { + "statbel_population_by_commune": 565 + }, + "by_activation_status": { + "active": 565 + } + }, + "holdout_references.json": { + "total": 7, + "by_family": { + "income_tax": 1, + "national_accounts": 1, + "household_accounts": 5 + }, + "by_contract": { + "eurostat_d51a_c1_individual_income_tax": 1, + "nbb_household_gross_disposable_income": 1, + "eurostat_household_gross_disposable_income": 1, + "eurostat_household_social_benefits_received": 1, + "eurostat_household_social_contributions_paid": 1, + "eurostat_household_current_taxes_paid": 1, + "fpb_gross_wages_and_salaries": 1 + }, + "by_activation_status": { + "requires_holdout_measure": 7 + } + } + }, + "regions": [ + "BE1", + "BE2", + "BE3" + ], + "age_bands": [ + "0_17", + "18_64", + "65_plus" + ], + "standin_bands": [ + { + "id": "under_10k", + "lower_eur_iy2023": 0, + "upper_eur_iy2023": 10000, + "a1_classes": [ + "class_under_1", + "class_1_2", + "class_2_3", + "class_3_4", + "class_4_5", + "class_5_6", + "class_6_7", + "class_7_8", + "class_8_9", + "class_9_10" + ] + }, + { + "id": "10k_20k", + "lower_eur_iy2023": 10000, + "upper_eur_iy2023": 20000, + "a1_classes": [ + "class_10_11", + "class_11_12", + "class_12_13", + "class_13_14", + "class_14_15", + "class_15_16", + "class_16_17", + "class_17_18", + "class_18_19", + "class_19_20" + ] + }, + { + "id": "20k_30k", + "lower_eur_iy2023": 20000, + "upper_eur_iy2023": 30000, + "a1_classes": [ + "class_20_21", + "class_21_22", + "class_22_23", + "class_23_24", + "class_24_25", + "class_25_26", + "class_26_27", + "class_27_28", + "class_28_29", + "class_29_30" + ] + }, + { + "id": "30k_40k", + "lower_eur_iy2023": 30000, + "upper_eur_iy2023": 40000, + "a1_classes": [ + "class_30_31", + "class_31_32", + "class_32_33", + "class_33_34", + "class_34_35", + "class_35_36", + "class_36_37", + "class_37_38", + "class_38_39", + "class_39_40" + ] + }, + { + "id": "40k_50k", + "lower_eur_iy2023": 40000, + "upper_eur_iy2023": 50000, + "a1_classes": [ + "class_40_41", + "class_41_42", + "class_42_43", + "class_43_44", + "class_44_45", + "class_45_46", + "class_46_47", + "class_47_48", + "class_48_49", + "class_49_50" + ] + }, + { + "id": "50k_75k", + "lower_eur_iy2023": 50000, + "upper_eur_iy2023": 75000, + "a1_classes": [ + "class_50_51", + "class_51_52", + "class_52_53", + "class_53_54", + "class_54_55", + "class_55_56", + "class_56_57", + "class_57_58", + "class_58_59", + "class_59_60", + "class_60_61", + "class_61_62", + "class_62_63", + "class_63_64", + "class_64_65", + "class_65_66", + "class_66_67", + "class_67_68", + "class_68_69", + "class_69_70", + "class_70_71", + "class_71_72", + "class_72_73", + "class_73_74", + "class_74_75" + ] + }, + { + "id": "75k_100k", + "lower_eur_iy2023": 75000, + "upper_eur_iy2023": 100000, + "a1_classes": [ + "class_75_76", + "class_76_77", + "class_77_78", + "class_78_79", + "class_79_80", + "class_80_81", + "class_81_82", + "class_82_83", + "class_83_84", + "class_84_85", + "class_85_86", + "class_86_87", + "class_87_88", + "class_88_89", + "class_89_90", + "class_90_91", + "class_91_92", + "class_92_93", + "class_93_94", + "class_94_95", + "class_95_96", + "class_96_97", + "class_97_98", + "class_98_99", + "class_99_100" + ] + }, + { + "id": "100k_plus", + "lower_eur_iy2023": 100000, + "upper_eur_iy2023": null, + "a1_classes": [ + "class_100_plus" + ] + } + ], + "standin_band_reason": "Fixed before any candidate (d1952): EUR 10,000 steps over the dense middle, wider steps above EUR 50,000, A.1's open top class whole; every edge is an A.1 class edge; eight bands, sixteen constraints.", + "standin_gaps": { + "measure": "statbel_net_taxable_income_proxy_v1", + "unit": "tax declaration (S2-d tax_unit); joint declarations count once", + "in_measure": "net professional income, rule-computed from transported gross amounts", + "published_gaps": "Components of Statbel's total net taxable income left out of the stand-in, as shares of it (method card BE-MC5; d1952). Within bands they can be larger than nationally.", + "national": { + "band": "all", + "declarations_iy2023": 6846186.0, + "taxable_income_eur_iy2023": 274707991587.37, + "component_shares_of_taxable_income": { + "professional_income": 0.9804992672847079, + "immovable_property_income": 0.014947349534038036, + "capital_and_movable_property_income": 0.005510746189298706, + "miscellaneous_income": 0.001157214923974624, + "deductible_expenditures": 0.0021145779320557163 + }, + "omitted_share_gross": 0.023729888579367083, + "omitted_share_net": 0.01950073271529207, + "identity_residual_eur": -0.01 + }, + "bands": [ + { + "band": "under_10k", + "declarations_iy2023": 937036.0, + "taxable_income_eur_iy2023": 3070063069.25, + "component_shares_of_taxable_income": { + "professional_income": 0.9595986159951101, + "immovable_property_income": 0.02519848271029131, + "capital_and_movable_property_income": 0.0033038102837665345, + "miscellaneous_income": 0.0159551657197604, + "deductible_expenditures": 0.004056074708928392 + }, + "omitted_share_gross": 0.04851353342274664, + "omitted_share_net": 0.040401384004889906, + "identity_residual_eur": 0.0 + }, + { + "band": "10k_20k", + "declarations_iy2023": 838884.0, + "taxable_income_eur_iy2023": 13708204696.7, + "component_shares_of_taxable_income": { + "professional_income": 0.9912500478513517, + "immovable_property_income": 0.009116430572420925, + "capital_and_movable_property_income": 0.0017326149270091968, + "miscellaneous_income": 0.0025143532623420313, + "deductible_expenditures": 0.004613446613123918 + }, + "omitted_share_gross": 0.01797684537489607, + "omitted_share_net": 0.008749952148648266, + "identity_residual_eur": 0.0 + }, + { + "band": "20k_30k", + "declarations_iy2023": 1634125.0, + "taxable_income_eur_iy2023": 40205856133.07, + "component_shares_of_taxable_income": { + "professional_income": 0.9913302376500499, + "immovable_property_income": 0.009227389444764247, + "capital_and_movable_property_income": 0.0012725470541072963, + "miscellaneous_income": 0.0008747289975271217, + "deductible_expenditures": 0.0027049031464485805 + }, + "omitted_share_gross": 0.014079568642847245, + "omitted_share_net": 0.008669762349950094, + "identity_residual_eur": 0.0 + }, + { + "band": "30k_40k", + "declarations_iy2023": 1013263.0, + "taxable_income_eur_iy2023": 35099727677.01, + "component_shares_of_taxable_income": { + "professional_income": 0.9857787374909764, + "immovable_property_income": 0.014128450381534244, + "capital_and_movable_property_income": 0.00203641256558287, + "miscellaneous_income": 0.0006833036894388543, + "deductible_expenditures": 0.0026269041275323777 + }, + "omitted_share_gross": 0.019475070764088345, + "omitted_share_net": 0.014221262509023558, + "identity_residual_eur": 0.0 + }, + { + "band": "40k_50k", + "declarations_iy2023": 716476.0, + "taxable_income_eur_iy2023": 32003198754.01, + "component_shares_of_taxable_income": { + 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Ressources", + "numerator_selector": { + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.household_account.total_resources", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:96551e39b8ae3a2a4d4fbba5" + }, + "denominator_selector": { + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2023.household_account.total_resources", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:782bd24d9f5d7ce79feadabf" + }, + "numerator": 571010000000.0, + "denominator": 518286000000.0, + "ratio": 1.1017276175702218, + "base_period": 2023, + "target_period": 2026, + "numerator_assertion": "source_projection", + "denominator_assertion": "observation", + "reason": "Net professional income mixes wages, replacement incomes, pensions and profits; the household account's total resources is the one FPB row spanning them (August's resource alignment).", + "status": "proposed (BE-MC0, pending d1902); series choice is a B3 finding", + "used_by": [ + "statbel_a1_standin_taxable_income__100k_plus", + "statbel_a1_standin_taxable_income__10k_20k", + "statbel_a1_standin_taxable_income__20k_30k", + "statbel_a1_standin_taxable_income__30k_40k", + "statbel_a1_standin_taxable_income__40k_50k", + "statbel_a1_standin_taxable_income__50k_75k", + "statbel_a1_standin_taxable_income__75k_100k", + "statbel_a1_standin_taxable_income__under_10k" + ], + "observed_segment_to_2025": 1.0691336443585202, + "projected_step_2025_to_2026": 1.0304863413322458 + }, + { + "id": "fpb_t17_direct_taxes_households", + "use": "holdout", + "fpb_row": "general_government_account.direct_taxes_households", + "record_set_spec_id": "fpb.economic_outlook_2026_2031.general_government_account.direct_taxes_households.country.v1", + "source_row_id": "direct_taxes_households", + "row_label": "- Ménages", + "numerator_selector": { + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t17.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.general_government_account.direct_taxes_households", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:09dcccdb13ecc60173a18079" + }, + "denominator_selector": { + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t17.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2025.general_government_account.direct_taxes_households", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:ebae7d68bab03979e30b2b5e" + }, + "numerator": 81561000000.0, + "denominator": 77771000000.0, + "ratio": 1.0487328181455813, + "base_period": 2025, + "target_period": 2026, + "numerator_assertion": "source_projection", + "denominator_assertion": "observation", + "reason": "Government direct taxes on households, the FPB counterpart of D51A_C1.", + "status": "proposed (BE-MC0, pending d1902); series choice is a B3 finding", + "used_by": [ + "eurostat_d51a_c1_individual_income_tax" + ] + }, + { + "id": "fpb_t24_federal_cash_income_guarantee_for_older_people", + "use": "calibration", + "fpb_row": "social_benefits_detail.federal_government_cash_income_guarantee_for_older_people", + "record_set_spec_id": "fpb.economic_outlook_2026_2031.social_benefits_detail.federal_government_cash_income_guarantee_for_older_people.country.v1", + "source_row_id": "federal_government_cash_income_guarantee_for_older_people", + "row_label": "4. Garantie de revenus aux personnes âgées", + "numerator_selector": { + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t24.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.social_benefits_detail.federal_government_cash_income_guarantee_for_older_people", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:13ee4f4b5a469ddeb487eafc" + }, + "denominator_selector": { + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t24.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2025.social_benefits_detail.federal_government_cash_income_guarantee_for_older_people", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:776e68a9e93ca03151c53baf" + }, + "numerator": 1034000000.0, + "denominator": 1025000000.0, + "ratio": 1.008780487804878, + "base_period": 2025, + "target_period": 2026, + "numerator_assertion": "source_projection", + "denominator_assertion": "observation", + "reason": "The target's own series (GRAPA).", + "status": "proposed (BE-MC0, pending d1902); series choice is a B3 finding", + "used_by": [ + "fpb_grapa_expenditure" + ] + }, + { + "id": "fpb_t24_social_security_cash_unemployment", + "use": "calibration", + "fpb_row": "social_benefits_detail.social_security_cash_unemployment", + "record_set_spec_id": "fpb.economic_outlook_2026_2031.social_benefits_detail.social_security_cash_unemployment.country.v1", + "source_row_id": "social_security_cash_unemployment", + "row_label": "a. Chômage", + "numerator_selector": { + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t24.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.social_benefits_detail.social_security_cash_unemployment", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:61a041fd9dff09745593e4da" + }, + "denominator_selector": { + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t24.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2025.social_benefits_detail.social_security_cash_unemployment", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:45ad11668f4cf559bb3c388f" + }, + "numerator": 4255000000.0, + "denominator": 5602000000.0, + "ratio": 0.7595501606569083, + "base_period": 2025, + "target_period": 2026, + "numerator_assertion": "source_projection", + "denominator_assertion": "observation", + "reason": "The target's own series, FPB T24 line a., rolled by its 2026/2025 step. unemployment_series_choice in the inventory compares it with the larger line 4.", + "status": "proposed (BE-MC0, pending d1902); series choice is a B3 finding", + "used_by": [ + "fpb_unemployment_benefit_expenditure" + ] + } + ], + "rsz_wage_cross_checks": [ + { + "factor_id": "rsz_ordinary_remuneration_cy2023_to_cy2025_observed", + "rsz_observed_factor": 1.063921, + "fpb_gross_wages_observed_ratio": 1.0642338220849668, + "use": "diagnostic only" + }, + { + "factor_id": "rsz_ordinary_remuneration_cy2024_to_cy2025_observed", + "rsz_observed_factor": 1.032192, + "fpb_gross_wages_observed_ratio": 1.0319934442828398, + "use": "diagnostic only" + } + ], + "b4_identity": { + "joint": 2215303.0, + "individual": 4630883.0, + "a1_declarations": 6846186.0, + "closes_exactly": true, + "use": "A.1 band counts and B.4 type counts share fpb_t07_total_population, so the identity survives ageing." + }, + "destination_mass": { + "commune_sum_2025": 11825551.0, + "nuts1_sum_2025": 11825551.0, + "nuts1_sum_2026": 11867634.0, + "commune_minus_nuts1_2025": 0.0, + "create_mass_reference": "Not in B3. CREATE needs exactly one unfiltered national person count. The suite has no national Statbel population fact, and a national row composed from the 565 communes refuses: the shared composed-geography path labels only UK areas. W3 chooses between a shared Belgian geography label (NZ hub) and FPB's annual-average population." + }, + "b1_checks": { + "verdict": "B.1 stays inactive: no check passes completely from the documents.", + "asserted_evidence": { + "b1_total_matches_spf_total": true, + "b1_deciles_sum_to_total": true, + "top_percentiles_sum_to_decile_10": true, + "decile_bounds_strictly_increase": true, + "percentile_bounds_strictly_increase": true, + "decile_9_bound_below_percentile_91_bound": true, + "b1_and_a1_taxable_income_totals_match": true, + "chronicle_states_zero_income_exclusion": true + }, + "tax_definition": { + "evidence": { + "b1_total_enrolled_tax_eur": 62840116133.93, + "spf_finances_total_taxes_eur": 62840116133.99, + "difference_eur": -0.06, + "b1_deciles_sum_minus_total_eur": 0.0, + "top_percentiles_sum_minus_decile_10_eur": 0.0, + "negative_deciles": [ + "decile_01", + "decile_02" + ] + }, + "passed": [ + "B.1's total enrolled tax equals the total taxes in Chronicle's spf-finances-pit-2023 package to EUR 0.06. That fact carries Statbel's concept and evidence URL, so the match reads one administrative total twice and corroborates nothing independently.", + "B.1's deciles sum to its total, and percentiles 91-100 sum to decile 10, within EUR 0.10." + ], + "missing": [ + "rulespec-be's candidate output belgium_pit_federal_and_local_tax_before_withholding (final_tax.yaml at 530849e) adds article 134 federal tax and the articles 465-466 local additions but not regional_surcharge.yaml's regional additional tax. No document in the suite says whether Statbel's total taxes include the regional additional tax.", + "B.1 counts declarations (joint = one); every rulespec-be PIT output is per Person, and the couple pipeline needs relation bindings (S2-d) that are not built.", + "That output is also the D51A_C1 holdout's measure: a B.1 producer must be a separately bound declaration-level measure, because S5 refuses a pre-calibration stage whose module produces a holdout measure." + ], + "result": "fail" + }, + "income_ranking": { + "evidence": { + "decile_upper_bounds_strictly_increase": true, + "percentile_upper_bounds_strictly_increase": true, + "decile_9_bound_below_percentile_91_bound": true, + "b1_minus_a1_total_taxable_income_eur": 0.02, + "decile_taxable_income_shares_sum": 1.0, + "chronicle_concept_note": "B.1 excludes declarations with zero total net taxable income; Statbel reports those declarations separately in A.1 Home. B.1 total enrolled tax; low-decile cells are negative because of refundable credits." + }, + "passed": [ + "Chronicle's B.1 facts state that B.1 excludes zero-income declarations, as A.1 does; B.1's and A.1's taxable-income totals agree to EUR 0.02, and the published bounds increase." + ], + "missing": [ + "The stand-in ranks declarations by net professional income only; 42,007 declarations with taxable but no professional income, and every pensioner while pensions are unmodelled (d1902), would rank differently from Statbel's total net taxable income.", + "B.1 publishes no declaration counts by decile; classifying model declarations needs either model-side ranking or the published bounds, and the bounds are income-year-2023 euros that need the same unavailable cut ageing as A.1." + ], + "result": "fail" + }, + "policy_year": { + "evidence": { + "b1_legal_vintage": "income_year_2023_assessment_year_2024", + "model_policy_year": 2026, + "rulespec_be_final_tax_effective_from": "2025-01-01", + "negative_deciles": [ + "decile_01", + "decile_02" + ] + }, + "passed": [], + "missing": [ + "B.1 is assessed under income-year-2023 law; the model applies 2026 law (BE-MC0). rulespec-be defines its PIT outputs from 2025-01-01 (its article 134 module states income year 2025 parameters), so B.1's own year cannot be reproduced, and no document bridges 2023 to 2026 tax law: ageing a 2023 tax mass by an FPB ratio would mix growth with law changes.", + "Deciles 1 and 2 are negative (refundable credits) and rolled_forward_by_ratio refuses a negative base, so the declared ageing route cannot carry them to 2026." + ], + "result": "fail" + } + }, + "unemployment_series_choice": { + "lines_2025": { + "chosen": { + "row": "social_security_cash_unemployment", + "label": "a. Chômage", + "eur": 5602000000.0 + }, + "alternative": { + "row": "social_security_cash_unemployment_total", + "label": "4. Chômage", + "eur": 6510000000.0 + }, + "company_supplement": { + "row": "social_security_cash_unemployment_with_company_supplement", + "label": "c. Allocations de chômage avec complément d'entreprise", + "eur": 167000000.0 + }, + "career_breaks": { + "row": "social_security_cash_career_breaks_and_time_credit", + "label": "d. Interruptions de carrière et crédit-temps", + "eur": 740000000.0 + } + }, + "choice": "The target takes line a. Line 4 also holds benefits with a company supplement and career breaks and time credit, about 14% of the level. This row choice is proposed with d1902.", + "open_question": "No document in the suite says whether line a. includes temporary unemployment, which the ordinary-benefit output does not compute." + }, + "geography_vintage_bindings": [ + { + "layer": "nuts1", + "chronicle_vintage": "NUTS_2024", + "typed_authority": "vintage:be_nuts1_2025", + "relation": "crosswalk", + "basis": "Chronicle labels Statbel's regions NUTS_2024. The typed nuts1 layer records no code list, so the mapping rests on destination_mass: the three regions' 2025 population equals the 565 communes' sum. A package test holds every nuts1 row to this binding. This choice is proposed with d1902." + }, + { + "layer": "commune", + "chronicle_vintage": "nis_2025", + "typed_authority": "vintage:be_nis_2025", + "relation": "exact_alias", + "basis": "nis_2025 is an exact typed alias of vintage:be_nis_2025." + } + ], + "holdout_information_overlaps": [ + "The tests check separation at the fact and measure level; holdouts still share information with calibration through economics, not facts:", + "FPB gross wages (wage-headline holdout): ONSS's calibrated worker contributions scale with wages.", + "Eurostat D62 social benefits received contain the calibrated unemployment and GRAPA aggregates.", + "Eurostat D61 social contributions paid contain the calibrated ONSS worker contributions.", + "Eurostat D51A_C1 and D5 measure the same personal income tax that B.1 would calibrate once active.", + "The A.1 stand-in is 98% net professional income, and its amount pair, FPB T11 total resources, contains gross wages, the wage holdout's own series." + ], + "grammar_gaps": [ + "A national row composed from commune facts refuses for Belgium: the composed-geography path labels only UK areas (ledger_targets._geography_fallback_label), so CREATE's single national mass reference cannot be the commune sum.", + "A schema-2 target_profile requires period_match_policy 'exact', which refuses rolled_forward_by_ratio; the documents keep B1's schema-2 hierarchy catalogs with a schema-1 target_profile (NZ's documents use the same schema-1 profile, with inline hierarchies).", + "No shared operation ages interval cuts by a declared annual ratio pair: scale_money_and_intervals needs a G8-r2 factor and singleton identity money rows, and G8-r2's projected_period_average_ratio cannot project an annual series past its last observation.", + "G8-r2's resolver needs dated period_coverage on every operand; Chronicle's FPB, Statbel NUTS1, NBB, ONSS, ONEM and most Eurostat facts carry none.", + "rolled_forward_by_ratio refuses a negative base, so signed targets (B.1 low deciles) cannot be aged by it.", + "rolled_forward_by_ratio's series key treats every FPB annex row of one table as one series (same concept, entity, geography and empty dimensions); the generator and tests enforce row identity themselves.", + "The typed vintage alias set admits only a layer's full id, its country-shortened id and its authority value, so Chronicle's NUTS_2024 label cannot be an alias of vintage:be_nuts1_2025; geography_vintage_bindings carries the mapping instead.", + "The schema-1 target_profile drops B1's required_families, basis_periods, tolerance tiers and subnational vintage rule. Package tests restore required families, the vintage rule and each row's periods. Caseload tolerance moves from B1's 15% to BE-MC6's 5%, and the ONSS contribution row moves from B1's standard_admin_release 10% to 5%." + ], + "exclusions": [ + { + "id": "jrc_euromod_be_statistics", + "reason": "jrc-euromod-be-baseline-statistics-2025 is outside the Chronicle be suite while d1822 (move it to the scorecard, its only consumer) is open; no reference selects JRC. August took two calibration rows from it: the unemployment recipient count, now read from ONEM/RVA's own 2024 count (a different concept, parked), and the RIS amount and recipient count, for which the suite holds no source, so no RIS reference exists." + }, + { + "id": "ris_amount_and_recipients", + "reason": "August's RIS amount and count came from JRC; the suite holds no RIS administrative source, so the gap is named, not filled." + }, + { + "id": "legal_pensions", + "reason": "FPB pension amounts and SFPD beneficiary counts and bands: legal pensions are not modelled until d1902 settles BE-MC3's pension route; the SFPD bands are B4's quantile-map surface." + }, + { + "id": "family_allowances", + "reason": "FPB family allowances and Opgroeien/Ostbelgien caseloads: child benefits are reported as not modelled at level until indexed amounts are encoded (BE-MC0)." + }, + { + "id": "rsz_wage_classes", + "reason": "RSZ daily-wage classes (B2f) are B4's wage quantile-map input under d1902, not a reference." + }, + { + "id": "usd_eur_rate", + "reason": "Eurostat ert_bil_eur_a is B4's currency-bridge input (BE-MC3), not a reference." + }, + { + "id": "regional_a1_and_b1", + "reason": "National bands only: the short list d1952 asks for; v0.5.1's 606 regional A.1 rows failed to fit." + }, + { + "id": "a1_component_tables", + "reason": "Professional, property, movable, miscellaneous and deduction tables are gap diagnostics in this inventory, not fitted rows." + }, + { + "id": "a1_and_b1_totals", + "reason": "Published totals duplicate the band and decile partitions; B.1's taxable-income masses duplicate A.1." + }, + { + "id": "zero_income_declarations", + "reason": "Statbel's 523,770 zero-income declarations are a diagnostic; the proxy's zeros differ, so the nil band is not fitted." + }, + { + "id": "b3_b5_tables", + "reason": "B.3 professional-category and B.5 dependant tables are outside the card's targets; v0.5.1's wage-only B.3 proxy destroyed weights." + }, + { + "id": "b4_age_and_decile_cells", + "reason": "Only the all-age joint and individual totals are targets (BE-MC4); age and decile cells would multiply weak cells." + }, + { + "id": "statbel_commune_fiscal_income", + "reason": "Commune fiscal income is a diagnostic surface for a later commune spine gate, not a B3 reference." + }, + { + "id": "spf_finances_pit_total", + "reason": "SPF Finances' total taxes equal B.1's total: one administrative total, read twice. The tax-definition check records it, and no row targets it." + }, + { + "id": "spf_municipal_surcharge_rates", + "reason": "Communal surcharge rates are W3 rule inputs, not references." + }, + { + "id": "statbel_population_2025_nuts1", + "reason": "Statbel's 1 January 2026 cells are the target-year observation; the 2025 cells would duplicate them." + }, + { + "id": "movable_income", + "reason": "Movable income stays out of the stand-in (art. 313 CIR 92 withholding dispensation) and out of the targets until the investment-income match check (d1952 build item 5)." + }, + { + "id": "eurostat_d11_wages", + "reason": "Eurostat D11 duplicates FPB's gross wages, the card's wage-headline comparator." + }, + { + "id": "eurostat_b3g_mixed_income", + "reason": "Mixed income is a calibration aggregate (FPB net mixed income), so it cannot also be held out." + }, + { + "id": "eurostat_survey_and_social_protection", + "reason": "Eurostat ilc_* survey aggregates and spr_exp_func expenditure are excluded: surveys are validation-only and outside the card's holdouts, and ESSPROS overlaps FPB's T24 rows." + }, + { + "id": "fpb_projections_as_direct_targets", + "reason": "No reference takes an FPB projection as its base: every base is an observation. 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"97b1ac33a58e0609903deb84d521bee5e583b7a7dcc445055f235f273008f640", + "base_facts": [ + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:1c1549bca1f666dae3f1c6fe" + } + ], + "operand_facts": [ + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:5148b5898c391c11ff484930" + }, + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:63c570cc58902f2813b3bde9" + } + ], + "semantic_facts": [ + { + "semantic_fact_key": "ledger.semantic_fact.v2:04dc8b1eec58416095149f14" + }, + { + "semantic_fact_key": "ledger.semantic_fact.v2:0a84547fbe77c1fcb8b894e2" + }, + { + "semantic_fact_key": "ledger.semantic_fact.v2:8d8897e73ef895c8e8167308" + } + ] + }, + { + "name": "eurostat_household_social_benefits_received", + "reference_set": "holdout", + "selector_sha256": "90a4a4f5341352071e84d04c69ead1dd5c26a8eb0361f91b34f14203cb451777", + "base_facts": [ + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:8c7c28463b5421308945c344" + } + ], + "operand_facts": [ + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:bf52974b05acf19d1d3ccb28" + }, + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:e87808ae0b585214ec608b92" + } + ], + "semantic_facts": [ + { + "semantic_fact_key": "ledger.semantic_fact.v2:1638c151c2262f1ce0191094" + }, + { + "semantic_fact_key": "ledger.semantic_fact.v2:60776b4f41217b1852f17c91" + }, + { + "semantic_fact_key": "ledger.semantic_fact.v2:64a3983fff87ee9f42466ac6" + } + ] + }, + { + "name": "eurostat_household_social_contributions_paid", + "reference_set": "holdout", + "selector_sha256": "3e292559ff7720db6d917612b9d4b6eff5095bee53ca1d9248691bcfa0e6b200", + "base_facts": [ + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:627f1716ff45e9ac8e2ffd22" + } + ], + "operand_facts": [ + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:4c597d6ad755576b4e1faf01" + }, + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:deed6d1fc86e5e7032cbfa5e" + } + ], + "semantic_facts": [ + { + "semantic_fact_key": "ledger.semantic_fact.v2:20f87b9a4118de41a2f856f3" + }, + { + "semantic_fact_key": "ledger.semantic_fact.v2:9583978946413377f5caa2c5" + }, + { + "semantic_fact_key": "ledger.semantic_fact.v2:a0277e7955859433c07df1ce" + } + ] + }, + { + "name": "eurostat_household_current_taxes_paid", + "reference_set": "holdout", + "selector_sha256": "38a4d2a3a2276d345195600da54e1a809c9602360c08137f7b0cb56be354264f", + "base_facts": [ + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:05ca22b4bedd957b4d655ff6" + } + ], + "operand_facts": [ + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:67bb0b178a502334a5798bfa" + }, + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:d3638106fd28d6f6d119c0d5" + } + ], + "semantic_facts": [ + { + "semantic_fact_key": "ledger.semantic_fact.v2:196625a11847843058001006" + }, + { + "semantic_fact_key": "ledger.semantic_fact.v2:37c2a59a25a6c6332b0bfce8" + }, + { + "semantic_fact_key": "ledger.semantic_fact.v2:ed20bbda07448b57ac2a7926" + } + ] + }, + { + "name": "fpb_gross_wages_and_salaries", + "reference_set": "holdout", + "selector_sha256": "4d9a02dbf906f65fabaefb636892ab35a81263d399078d77726ec9675dd6f79c", + "base_facts": [ + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:1b99b4161fa76ca1069ad5e7" + } + ], + "operand_facts": [ + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:1b99b4161fa76ca1069ad5e7" + }, + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:f17958efe84e42471bf68f80" + } + ], + "semantic_facts": [ + { + "semantic_fact_key": "ledger.semantic_fact.v2:9a10c918fc42ebf78196db46" + }, + { + "semantic_fact_key": "ledger.semantic_fact.v2:acfb4cabda91df16d75eb910" + } + ] + }, + { + "name": "factor:rsz_ordinary_remuneration_cy2023_to_cy2025_observed", + "reference_set": "factor_context", + "selector_sha256": "ce4e2924e7e83ed992e881b2156398e5ec9f0ee9f8d437dbd8682231c3b5a8ad", + "base_facts": [], + "operand_facts": [ + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:2c0d2f4c10c54cee45e5777b" + }, + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:3c1a0cfec5e2740c02758f98" + } + ], + "semantic_facts": [ + { + "semantic_fact_key": "ledger.semantic_fact.v2:14dba4cf6712222563513d5d" + }, + { + "semantic_fact_key": "ledger.semantic_fact.v2:7bf0f7a2df4fce129ca59e5a" + } + ] + }, + { + "name": "factor:rsz_ordinary_remuneration_cy2024_to_cy2025_observed", + "reference_set": "factor_context", + "selector_sha256": "bbe980d704b65ae19cee79684083d75bfc8aa7af8c1cc261a6a025bb42a87a78", + "base_facts": [], + "operand_facts": [ + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:3c1a0cfec5e2740c02758f98" + }, + { + "aggregate_fact_key": "ledger.aggregate_fact.v2:fff2864b2ff60754bce8bfcf" + } + ], + "semantic_facts": [ + { + "semantic_fact_key": "ledger.semantic_fact.v2:7bf0f7a2df4fce129ca59e5a" + }, + { + "semantic_fact_key": "ledger.semantic_fact.v2:c3b7497e94ea33df32f56635" + } + ] + } + ] +} diff --git a/packages/microcosm-build/src/microcosm/build/be/reference_profiles.json b/packages/microcosm-build/src/microcosm/build/be/reference_profiles.json new file mode 100644 index 0000000000..1230d93cfb --- /dev/null +++ b/packages/microcosm-build/src/microcosm/build/be/reference_profiles.json @@ -0,0 +1,16 @@ +{ + "schema_version": 1, + "factor_context_resource": "reference_aging.json", + "interval_resource": "reference_intervals.json", + "dimensions": { + "aging_index": { + "default": "central", + "profiles": { + "central": { + "deferred": true, + "notes": "Declared but not executable: ageing the A.1 stand-in band cuts to 2026 needs a shared operation that scales interval cuts by a declared annual ratio pair, and reference_aging.json holds no profile_input factor for it. The profile is deferred, so the resolver applies no transformation and the A.1 rows keep both prerequisites." + } + } + } + } +} diff --git a/packages/microcosm-build/src/microcosm/build/be/source_stages.json b/packages/microcosm-build/src/microcosm/build/be/source_stages.json index 3682568a6c..ad91ae7bfa 100644 --- a/packages/microcosm-build/src/microcosm/build/be/source_stages.json +++ b/packages/microcosm-build/src/microcosm/build/be/source_stages.json @@ -1,7 +1,7 @@ { "version": 1, "country": "be", - "policy": "Belgium transports the immutable public Microcosm US Build P support artifact into a synthetic Belgian population (BE-MC2). Donor records remain US support records and retain their support-stratum provenance; Belgian geography is assigned, never source-observed. Destination calibration uses Belgian administrative and national-accounts targets from sums of Chronicle facts; surveys are validation-only. The Chronicle consumer artifact and rulespec-be tree are declared unpinned placeholders, so this package remains inactive. Executable Python belongs in shared runtimes; publication remains private pending Max's decision in release_contract.json.", + "policy": "Belgium transports the immutable public Microcosm US Build P support artifact into a synthetic Belgian population (BE-MC2). Donor records remain US support records and retain their support-stratum provenance; Belgian geography is assigned, never source-observed. Destination calibration uses Belgian administrative and national-accounts targets from sums of Chronicle facts; surveys are validation-only. chronicle_feed.json pins the Chronicle consumer artifact (B3); the rulespec-be tree remains a declared unpinned placeholder, so this package remains inactive. Executable Python belongs in shared runtimes; publication remains private pending Max's decision in release_contract.json.", "stages": [ { "stage": "load_populace_us_support_pool", @@ -29,7 +29,7 @@ }, { "kind": "public_aggregate_reference", - "role": "destination_chronicle_consumer_artifact_unpinned", + "role": "destination_chronicle_consumer_artifact", "resource": "chronicle_feed.json", "format": "json", "runtime_sha256_required": true @@ -66,7 +66,7 @@ "household_weight", "age" ], - "notes": "The first artifact copies the authenticated donor pin from build/nz/source_stages.json exactly. Shared transport must preserve donor entity ids, membership, typed household design weights and support strata, retain US donor provenance, and bridge donor mass to a Chronicle-supplied Belgian population total with a conservation receipt. The next two artifacts are declared placeholders for a PolicyEngine/chronicle consumer artifact and the TheAxiomFoundation/rulespec-be tree, respectively. Their referenced resources and exact facts/manifest hashes and RuleSpec commit/tree hashes are not authored or pinned here; neither reference permits execution or a latest/main fallback. Later work must supply those pins, source materialization, unit construction, engine bindings and an executable graph. Monetary conversion and quantile mapping are later declarations; monetary catalog columns wait for the shared EUR unit (PLAN S3)." + "notes": "The first artifact copies the authenticated donor pin from build/nz/source_stages.json exactly. Shared transport must preserve donor entity ids, membership, typed household design weights and support strata, retain US donor provenance, and bridge donor mass to a Chronicle-supplied Belgian population total with a conservation receipt. The second artifact names chronicle_feed.json, which pins the PolicyEngine/chronicle consumer artifact by its facts, manifest and schema hashes (B3); the third is a declared placeholder for the TheAxiomFoundation/rulespec-be tree, whose RuleSpec commit and tree hashes are not authored here. Neither reference permits a latest/main fallback. Later work must supply the RuleSpec pins, source materialization, unit construction, engine bindings and an executable graph. Monetary conversion and quantile mapping are later declarations (B4); the catalog's money columns use the shared eur unit." } ] } diff --git a/packages/microcosm-build/src/microcosm/build/be/spec/bundle.yaml b/packages/microcosm-build/src/microcosm/build/be/spec/bundle.yaml index 0b16e17b89..598dbf0fa5 100644 --- a/packages/microcosm-build/src/microcosm/build/be/spec/bundle.yaml +++ b/packages/microcosm-build/src/microcosm/build/be/spec/bundle.yaml @@ -5,10 +5,10 @@ dataset_run: target_period: 2026 status: Inactive Belgian donor-transport specification. Donor period 2024 uses the exact US Build P artifact NZ pins (BE-MC2); target and policy period 2026 is the BE-MC0 proposal - pending Max's ruling d1902. Geography uses NIS 2025 communes. Destination Chronicle consumer-artifact - and rulespec-be tree pins remain declared placeholders in spec/sources.yaml. Earlier-period - target_references.json is inactive groundwork awaiting B3 and explicit ageing; those source - periods do not redefine the target year. Shared EUR catalog support (PLAN S3), unit construction, - pinned engine bindings, active separated references, executable geography support, graph, - receipt contract and release qualification remain later work. Publication remains private - and Max's decision. + pending Max's ruling d1902. Geography uses NIS 2025 communes. chronicle_feed.json pins the + Chronicle consumer artifact; the rulespec-be tree pin remains a declared placeholder in + spec/sources.yaml. B3's separated calibration, pre-calibration and holdout references carry + selectors only, roll 2023-2025 facts to 2026 by declared FPB ratio pairs, and stay parked + where a producer or ruling is missing. Unit construction, pinned engine bindings, executable + geography support, graph, receipt contract and release qualification remain later work. + Publication remains private and Max's decision. diff --git a/packages/microcosm-build/src/microcosm/build/be/spec/catalogs.yaml b/packages/microcosm-build/src/microcosm/build/be/spec/catalogs.yaml index 42a883fdd8..13292b56dd 100644 --- a/packages/microcosm-build/src/microcosm/build/be/spec/catalogs.yaml +++ b/packages/microcosm-build/src/microcosm/build/be/spec/catalogs.yaml @@ -10,9 +10,8 @@ columns: domain: frame_identity public_stability: internal docs: - description: Non-monetary catalog only. Monetary columns arrive with the Belgian target - references, in the shared eur unit; no USD or placeholder money unit is used for - Belgian amounts. + description: Monetary columns use the shared eur unit; no USD or placeholder money unit + is used for Belgian amounts. - key: household.household_weight contract: entity: household @@ -163,3 +162,32 @@ columns: nullable: false domain: target_assigned_geography public_stability: internal +- key: person.employment_income + contract: + entity: person + dtype: float64 + unit: eur + definition_period: year + vintage: vintage:be_target_2026 + nullable: false + domain: donor_transported_money + public_stability: internal + docs: + description: Donor wages and salaries in euros of the 2026 policy year, converted once + from USD at the ECB annual reference rate for the donor year and then uprated (BE-MC3, + proposed pending d1902). No producer until B4's currency bridge. The FPB gross-wage + holdout in holdout_references.json measures it. +- key: person.nonfarm_self_employment_income + contract: + entity: person + dtype: float64 + unit: eur + definition_period: year + vintage: vintage:be_target_2026 + nullable: false + domain: donor_transported_money + public_stability: internal + docs: + description: Donor non-farm self-employment profit in euros of the 2026 policy year, with + FX and uprating only (BE-MC3, proposed pending d1902). No producer until B4's currency + bridge. The FPB net mixed income reference in target_references.json measures it. diff --git a/packages/microcosm-build/src/microcosm/build/be/spec/sources.yaml b/packages/microcosm-build/src/microcosm/build/be/spec/sources.yaml index f575dd0420..b9092edd21 100644 --- a/packages/microcosm-build/src/microcosm/build/be/spec/sources.yaml +++ b/packages/microcosm-build/src/microcosm/build/be/spec/sources.yaml @@ -1,8 +1,8 @@ sources: - id: be_populace_us_support_contract role: be_populace_us_support_pool - sha256: c94df32e544b74e7e6a70ae587345c757d9773035fceafc98660f4ab52d09d2c - byte_size: 3747 + sha256: 3d0a362345894dc6ea230ebed7fec7ff99a972879dc60c06001635c1b4a1ec47 + byte_size: 3774 loader: kernel:load_populace_us_support_pool vintages: - vintage:be_support_pool_2024_buildp @@ -36,14 +36,14 @@ sources: stage_manifest: version: 1 country: be - policy: Belgium transports the immutable public Microcosm US Build P support artifact into - a synthetic Belgian population (BE-MC2). Donor records remain US support records and retain + policy: Belgium transports the immutable public Microcosm US Build P support artifact into a + synthetic Belgian population (BE-MC2). Donor records remain US support records and retain their support-stratum provenance; Belgian geography is assigned, never source-observed. Destination calibration uses Belgian administrative and national-accounts targets from - sums of Chronicle facts; surveys are validation-only. The Chronicle consumer artifact - and rulespec-be tree are declared unpinned placeholders, so this package remains inactive. - Executable Python belongs in shared runtimes; publication remains private pending Max's - decision in release_contract.json. + sums of Chronicle facts; surveys are validation-only. chronicle_feed.json pins the + Chronicle consumer artifact (B3); the rulespec-be tree remains a declared unpinned + placeholder, so this package remains inactive. Executable Python belongs in shared + runtimes; publication remains private pending Max's decision in release_contract.json. stages: - stage: load_populace_us_support_pool survey: Microcosm US Build P support population (US donor support records) @@ -67,7 +67,7 @@ stages: pointer on 2026-08-29. Execution must verify both SHA-256 and byte size before reading; main/latest fallback is forbidden. - kind: public_aggregate_reference - role: destination_chronicle_consumer_artifact_unpinned + role: destination_chronicle_consumer_artifact resource: chronicle_feed.json format: json runtime_sha256_required: true @@ -94,14 +94,15 @@ stages: nonnegative_outputs: - household_weight - age - notes: The first artifact copies the authenticated donor pin from build/nz/source_stages.json - exactly. Shared transport must preserve donor entity ids, membership, typed household - design weights and support strata, retain US donor provenance, and bridge donor mass to - a Chronicle-supplied Belgian population total with a conservation receipt. The next two - artifacts are declared placeholders for a PolicyEngine/chronicle consumer artifact and - the TheAxiomFoundation/rulespec-be tree, respectively. Their referenced resources and - exact facts/manifest hashes and RuleSpec commit/tree hashes are not authored or pinned - here; neither reference permits execution or a latest/main fallback. Later work must supply - those pins, source materialization, unit construction, engine bindings and an executable - graph. Monetary conversion and quantile mapping are later declarations; monetary catalog - columns wait for the shared EUR unit (PLAN S3). + notes: The first artifact copies the authenticated donor pin from + build/nz/source_stages.json exactly. Shared transport must preserve donor entity ids, + membership, typed household design weights and support strata, retain US donor provenance, + and bridge donor mass to a Chronicle-supplied Belgian population total with a conservation + receipt. The second artifact names chronicle_feed.json, which pins the + PolicyEngine/chronicle consumer artifact by its facts, manifest and schema hashes (B3); + the third is a declared placeholder for the TheAxiomFoundation/rulespec-be tree, whose + RuleSpec commit and tree hashes are not authored here. Neither reference permits a + latest/main fallback. Later work must supply the RuleSpec pins, source materialization, + unit construction, engine bindings and an executable graph. Monetary conversion and + quantile mapping are later declarations (B4); the catalog's money columns use the shared + eur unit. diff --git a/packages/microcosm-build/src/microcosm/build/be/target_references.json b/packages/microcosm-build/src/microcosm/build/be/target_references.json index 5f4b0408ea..762f2bd860 100644 --- a/packages/microcosm-build/src/microcosm/build/be/target_references.json +++ b/packages/microcosm-build/src/microcosm/build/be/target_references.json @@ -1,278 +1,4218 @@ { "country": "be", - "description": "Belgian calibration and validation schema groundwork, by reference only. Values and source projections would resolve from Chronicle consumer facts at build time, but the current Chronicle Belgian catalog does not satisfy this full selector and period surface. Criticality tiers, relative tolerances, and target_role are validated declaration metadata only: this package does not yet wire them into runtime calibration objectives or release gates. Multi-cell series remain non-executable until Chronicle fanout produces cell-pinned references. No external-oracle implementation from #264 is included. The file never copies a target value from Chronicle, a survey publication, or a validation oracle. These earlier-period declarations remain inactive groundwork; B3 must replace them with reviewed transport references and explicit ageing to the proposed 2026 policy year. Their source periods are not donor or target-period authorities.", + "schema_version": 2, + "reference_set": "calibration", + "description": "Belgian calibration references (reference set calibration), generated by tools/generate_be_target_references.py from the pinned Chronicle be feed. Selectors only: no observation is carried. Demography targets Statbel's 1 January 2026 population directly; every other row rolls a 2023-2025 fact to 2026 by a declared FPB June 2026 ratio pair or stays parked with a named reason. Method-card choices are proposed pending d1902. Belgium stays inactive.", "allowed_value_operations": [ - "identity" + "identity", + "rolled_forward_by_ratio" ], + "hierarchy": { + "providers": { + "fpb": { + "label": "Federal Planning Bureau" + }, + "onem": { + "label": "National Employment Office" + }, + "onss": { + "label": "National Social Security Office" + }, + "statbel": { + "label": "Statbel" + } + }, + "categories": { + "fpb.benefit_expenditure": { + "provider_id": "fpb", + "label": "Benefit expenditure" + }, + "fpb.self_employment": { + "provider_id": "fpb", + "label": "Self-employment income" + }, + "onem.caseloads": { + "provider_id": "onem", + "label": "Benefit caseloads" + }, + "onss.social_security": { + "provider_id": "onss", + "label": "Social security contributions" + }, + "statbel.demography": { + "provider_id": "statbel", + "label": "Demography" + }, + "statbel.fiscal_income": { + "provider_id": "statbel", + "label": "Fiscal income" + }, + "statbel.income_tax": { + "provider_id": "statbel", + "label": "Assessed income tax" + } + }, + "target_labels": { + "fpb_grapa_expenditure": "FPB income guarantee for older people (GRAPA), 2025, rolled to 2026 (parked)", + "fpb_net_mixed_income": "FPB household net mixed income, 2025, rolled to 2026 (parked)", + "fpb_unemployment_benefit_expenditure": "FPB social-security unemployment benefits, 2025, rolled to 2026 (parked)", + "onem_complete_unemployment_recipients": "ONEM/RVA complete-unemployment benefit recipients, 2024 monthly average (parked, unaged)", + "onss_worker_personal_contributions": "ONSS/RSZ worker-borne personal contributions, 2024, rolled to 2026 (parked)", + "statbel_a1_standin_declarations_by_band": "Stand-in income (d1952): Statbel A.1 declarations by broad band of total net taxable income, rolled to 2026 (parked)", + "statbel_a1_standin_taxable_income_by_band": "Stand-in income (d1952): Statbel A.1 total net taxable income by broad band, rolled to 2026 (parked)", + "statbel_b1_enrolled_tax_by_rank_group": "Statbel B.1 total enrolled tax by decile 1-9 and top percentiles 91-100, income year 2023 (inactive: checks failed)", + "statbel_b4_declarations_by_type": "Statbel B.4 joint and individual declarations (all ages, deciles 1-10 summed), rolled to 2026 (parked)", + "statbel_population_by_region_sex_age": "Statbel resident population on 1 January 2026 by region, sex and age band" + } + }, "target_references": [ { - "name": "statbel_population_by_age_sex_region", + "name": "statbel_population_by_region_sex_age__be1__male__a0_17", "ledger_selector": { "source_name": "statbel_population_structure", "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", "period_type": "calendar_year", + "period_value": 2026, "geography_level": "nuts1", - "geography_vintage": "nuts1_2025" + "geography_id": "BE1", + "geography_vintage": "NUTS_2024", + "record_set_id": "statbel.population_structure.cy2026.people.by_nuts1_age_sex", + "dimensions": [ + "person.age_band", + "person.sex" + ], + "dimension_values": { + "person.age_band": "0_17", + "person.sex": "male" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:120cd8981baad80a656e1b30" }, "entity": "person", "measure": "people", - "period": 2023, + "period": 2026, "family": "demography", - "assertion_policy": "allow_source_projection", - "period_match_policy": "exact", + "category_id": "statbel.demography", + "assertion_policy": "observed_only", "metadata": { - "activation_status": "requires_harvested_cell_references", - "basis_period": "population_reference_2023", + "contract_target_id": "statbel_population_by_region_sex_age", + "activation_status": "active", "criticality": "release_blocking", - "criticality_tier": "demography_release", - "geography_vintage": "nuts1_2025", + "measure_kind": "prepared_column", "publisher": "Statbel", - "series": "Structure of the population: age band by sex by region", - "target_role": "calibration" + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC6", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "NUTS_2024", + "geography_vintage_authority": "vintage:be_nuts1_2025", + "fit_tolerance": "0.02", + "ageing": "none: observation for the target year", + "source_snapshot": "1 January 2026 resident population", + "target_period": "2026" }, - "notes": "Non-executable series placeholder for an age-band x sex x NUTS1 count surface. Chronicle must fan this into dimension- and geography-pinned scalar references before compilation. The selector uses the typed NUTS1-2025 authority alias; a differently-vintaged source requires an explicit Chronicle projection/crosswalk. An observation for another year may enter only as a Chronicle source_projection whose fact period is the declared 2023 reference year.", - "category_id": "statbel.demography" + "filter": "population_region_be1_male_age_0_17_indicator", + "period_match_policy": "exact" }, { - "name": "statbel_fiscal_income_by_commune", + "name": "statbel_population_by_region_sex_age__be1__male__a18_64", "ledger_selector": { - "source_name": "statbel_fiscal_income", - "source_measure_id": "taxable_income", - "period_type": "tax_year", - "geography_level": "commune", - "geography_vintage": "nis_2025" + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "nuts1", + "geography_id": "BE1", + "geography_vintage": "NUTS_2024", + "record_set_id": "statbel.population_structure.cy2026.people.by_nuts1_age_sex", + "dimensions": [ + "person.age_band", + "person.sex" + ], + "dimension_values": { + "person.age_band": "18_64", + "person.sex": "male" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:4f3a6c98b66da2c0df41224b" }, - "entity": "household", - "measure": "belgium_pit_taxable_income", - "period": 2022, - "family": "fiscal_income", - "assertion_policy": "allow_source_projection", - "period_match_policy": "exact", + "entity": "person", + "measure": "people", + "period": 2026, + "family": "demography", + "category_id": "statbel.demography", + "assertion_policy": "observed_only", "metadata": { - "activation_status": "requires_harvested_cell_references", - "basis_period": "assessment_income_year_2022", - "criticality": "diagnostic", - "criticality_tier": "commune_diagnostic", - "geography_vintage": "nis_2025", - "nis_vintage": "2025", + "contract_target_id": "statbel_population_by_region_sex_age", + "activation_status": "active", + "criticality": "release_blocking", + "measure_kind": "prepared_column", "publisher": "Statbel", - "series": "Fiscal statistics of income: total net taxable income by municipality", - "target_role": "calibration" + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC6", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "NUTS_2024", + "geography_vintage_authority": "vintage:be_nuts1_2025", + "fit_tolerance": "0.02", + "ageing": "none: observation for the target year", + "source_snapshot": "1 January 2026 resident population", + "target_period": "2026" }, - "notes": "Non-executable series placeholder for commune fiscal-income cells; Chronicle must fan it into one commune-pinned scalar reference per selected cell before compilation. The eventual open commune series is diagnostic until the synthetic spine demonstrates adequate support. The selector binds the typed nis_2025 alias to the spine's 2025 NIS code set, and another code set must be projected and crosswalked in Chronicle rather than partially joined.", - "category_id": "statbel.fiscal_income" + "filter": "population_region_be1_male_age_18_64_indicator", + "period_match_policy": "exact" }, { - "name": "spf_finances_pit_total", + "name": "statbel_population_by_region_sex_age__be1__male__a65_plus", "ledger_selector": { - "source_name": "spf_finances_pit", - "source_measure_id": "tax_before_withholding", - "period_type": "tax_year", - "geography_level": "country" + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "nuts1", + "geography_id": "BE1", + "geography_vintage": "NUTS_2024", + "record_set_id": "statbel.population_structure.cy2026.people.by_nuts1_age_sex", + "dimensions": [ + "person.age_band", + "person.sex" + ], + "dimension_values": { + "person.age_band": "65_plus", + "person.sex": "male" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:04cad2d2d74601f480a04878" }, "entity": "person", - "measure": "belgium_pit_federal_and_local_tax_before_withholding", - "period": 2022, - "family": "income_tax", - "assertion_policy": "allow_source_projection", - "period_match_policy": "exact", + "measure": "people", + "period": 2026, + "family": "demography", + "category_id": "statbel.demography", + "assertion_policy": "observed_only", "metadata": { - "basis_period": "assessment_income_year_2022", + "contract_target_id": "statbel_population_by_region_sex_age", + "activation_status": "active", "criticality": "release_blocking", - "criticality_tier": "core_fiscal_release", - "publisher": "SPF Finances / Statbel", - "series": "Personal income tax: assessed total", - "target_role": "calibration" + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC6", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "NUTS_2024", + "geography_vintage_authority": "vintage:be_nuts1_2025", + "fit_tolerance": "0.02", + "ageing": "none: observation for the target year", + "source_snapshot": "1 January 2026 resident population", + "target_period": "2026" }, - "notes": "National assessed PIT is compared with the Axiom-computed federal and local liability on the 2022 income-year basis. Assessment-year facts must identify the represented income year in Chronicle; a period mismatch is a projection, never a silent relabeling.", - "category_id": "spf_finances.income_tax" + "filter": "population_region_be1_male_age_65_plus_indicator", + "period_match_policy": "exact" }, { - "name": "onss_employee_contribution_total", + "name": "statbel_population_by_region_sex_age__be1__female__a0_17", "ledger_selector": { - "source_name": "onss_contributions", - "source_measure_id": "worker_article_17_uncapped_component_contribution", + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", "period_type": "calendar_year", - "geography_level": "country" + "period_value": 2026, + "geography_level": "nuts1", + "geography_id": "BE1", + "geography_vintage": "NUTS_2024", + "record_set_id": "statbel.population_structure.cy2026.people.by_nuts1_age_sex", + "dimensions": [ + "person.age_band", + "person.sex" + ], + "dimension_values": { + "person.age_band": "0_17", + "person.sex": "female" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:5bd4d90dbf75fa183b749e89" }, "entity": "person", - "measure": "belgium_worker_article_17_uncapped_component_contribution", - "period": 2022, - "family": "social_security", - "assertion_policy": "allow_source_projection", - "period_match_policy": "exact", + "measure": "people", + "period": 2026, + "family": "demography", + "category_id": "statbel.demography", + "assertion_policy": "observed_only", "metadata": { - "basis_period": "calendar_year_2022", + "contract_target_id": "statbel_population_by_region_sex_age", + "activation_status": "active", "criticality": "release_blocking", - "criticality_tier": "standard_admin_release", - "publisher": "ONSS/RSZ", - "series": "Employee social-security contributions", - "target_role": "calibration" + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC6", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "NUTS_2024", + "geography_vintage_authority": "vintage:be_nuts1_2025", + "fit_tolerance": "0.02", + "ageing": "none: observation for the target year", + "source_snapshot": "1 January 2026 resident population", + "target_period": "2026" }, - "notes": "Worker-side contributions on the encoded slice. Employer-side and capped-regime totals can enter as distinct references when both the engine concepts and Ledger selectors exist.", - "category_id": "onss.social_security" + "filter": "population_region_be1_female_age_0_17_indicator", + "period_match_policy": "exact" }, { - "name": "onem_unemployment_caseload", + "name": "statbel_population_by_region_sex_age__be1__female__a18_64", "ledger_selector": { - "source_name": "onem_rva_unemployment", - "source_measure_id": "receives_unemployment_benefit", + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", "period_type": "calendar_year", - "geography_level": "country" + "period_value": 2026, + "geography_level": "nuts1", + "geography_id": "BE1", + "geography_vintage": "NUTS_2024", + "record_set_id": "statbel.population_structure.cy2026.people.by_nuts1_age_sex", + "dimensions": [ + "person.age_band", + "person.sex" + ], + "dimension_values": { + "person.age_band": "18_64", + "person.sex": "female" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:31103ab0dcc5bb5bd663c6a3" }, "entity": "person", - "measure": "receives_unemployment_benefit", - "period": 2022, - "family": "caseloads", - "assertion_policy": "allow_source_projection", - "period_match_policy": "exact", + "measure": "people", + "period": 2026, + "family": "demography", + "category_id": "statbel.demography", + "assertion_policy": "observed_only", "metadata": { - "basis_period": "calendar_year_2022", + "contract_target_id": "statbel_population_by_region_sex_age", + "activation_status": "active", "criticality": "release_blocking", - "criticality_tier": "caseload_release", - "publisher": "ONEM/RVA", - "series": "Unemployment benefit recipients", - "target_role": "calibration" + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC6", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "NUTS_2024", + "geography_vintage_authority": "vintage:be_nuts1_2025", + "fit_tolerance": "0.02", + "ageing": "none: observation for the target year", + "source_snapshot": "1 January 2026 resident population", + "target_period": "2026" }, - "notes": "The initial caseload family uses the calendar-year recipient count. Pension and regional child-benefit caseload references can join this family when their Chronicle packages and model mappings land.", - "category_id": "onem.caseloads" + "filter": "population_region_be1_female_age_18_64_indicator", + "period_match_policy": "exact" }, { - "name": "nbb_household_disposable_income", + "name": "statbel_population_by_region_sex_age__be1__female__a65_plus", "ledger_selector": { - "source_name": "nbb_national_accounts", - "source_measure_id": "household_disposable_income", + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", "period_type": "calendar_year", - "geography_level": "country" + "period_value": 2026, + "geography_level": "nuts1", + "geography_id": "BE1", + "geography_vintage": "NUTS_2024", + "record_set_id": "statbel.population_structure.cy2026.people.by_nuts1_age_sex", + "dimensions": [ + "person.age_band", + "person.sex" + ], + "dimension_values": { + "person.age_band": "65_plus", + "person.sex": "female" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:633f2cac5dcab7a455322cf0" }, - "entity": "household", - "measure": "household_disposable_income", - "period": 2022, - "family": "national_accounts", - "assertion_policy": "allow_source_projection", - "period_match_policy": "exact", + "entity": "person", + "measure": "people", + "period": 2026, + "family": "demography", + "category_id": "statbel.demography", + "assertion_policy": "observed_only", "metadata": { - "basis_period": "calendar_year_2022", - "criticality": "diagnostic", - "criticality_tier": "validation_only", - "publisher": "NBB", - "series": "Household-sector disposable income (national accounts)", - "target_role": "validation" - }, - "notes": "Validation-tier level anchor only. The macro-realism gate may use it as a broad band, but neither the exact NBB level nor any survey- or EUROMOD-derived quantity enters the calibration objective.", - "category_id": "nbb.national_accounts" - } - ], - "target_profile": { - "schema_version": 2, - "required_families": [ - "demography", - "fiscal_income", - "income_tax", - "social_security", - "caseloads" - ], - "criticality_tiers": { - "demography_release": { + "contract_target_id": "statbel_population_by_region_sex_age", + "activation_status": "active", "criticality": "release_blocking", - "relative_tolerance": 0.02, - "description": "Population-structure cells: plus or minus 2 percent." + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC6", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "NUTS_2024", + "geography_vintage_authority": "vintage:be_nuts1_2025", + "fit_tolerance": "0.02", + "ageing": "none: observation for the target year", + "source_snapshot": "1 January 2026 resident population", + "target_period": "2026" + }, + "filter": "population_region_be1_female_age_65_plus_indicator", + "period_match_policy": "exact" + }, + { + "name": "statbel_population_by_region_sex_age__be2__male__a0_17", + "ledger_selector": { + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "nuts1", + "geography_id": "BE2", + "geography_vintage": "NUTS_2024", + "record_set_id": "statbel.population_structure.cy2026.people.by_nuts1_age_sex", + "dimensions": [ + "person.age_band", + "person.sex" + ], + "dimension_values": { + "person.age_band": "0_17", + "person.sex": "male" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:b73dde1c55bf24c4e9826526" }, - "core_fiscal_release": { + "entity": "person", + "measure": "people", + "period": 2026, + "family": "demography", + "category_id": "statbel.demography", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_population_by_region_sex_age", + "activation_status": "active", "criticality": "release_blocking", - "relative_tolerance": 0.05, - "description": "Core fiscal totals, including assessed PIT: plus or minus 5 percent." + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC6", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "NUTS_2024", + "geography_vintage_authority": "vintage:be_nuts1_2025", + "fit_tolerance": "0.02", + "ageing": "none: observation for the target year", + "source_snapshot": "1 January 2026 resident population", + "target_period": "2026" + }, + "filter": "population_region_be2_male_age_0_17_indicator", + "period_match_policy": "exact" + }, + { + "name": "statbel_population_by_region_sex_age__be2__male__a18_64", + "ledger_selector": { + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "nuts1", + "geography_id": "BE2", + "geography_vintage": "NUTS_2024", + "record_set_id": "statbel.population_structure.cy2026.people.by_nuts1_age_sex", + "dimensions": [ + "person.age_band", + "person.sex" + ], + "dimension_values": { + "person.age_band": "18_64", + "person.sex": "male" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:fac6476a0da56862ec9d981e" }, - "standard_admin_release": { + "entity": "person", + "measure": "people", + "period": 2026, + "family": "demography", + "category_id": "statbel.demography", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_population_by_region_sex_age", + "activation_status": "active", "criticality": "release_blocking", - "relative_tolerance": 0.1, - "description": "Administrative contribution totals: plus or minus 10 percent." + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC6", + "method_card_status": "proposed_pending_d1902", + "geography_vintage": "NUTS_2024", + "geography_vintage_authority": "vintage:be_nuts1_2025", + "fit_tolerance": "0.02", + "ageing": "none: observation for the target year", + "source_snapshot": "1 January 2026 resident population", + "target_period": "2026" + }, + "filter": "population_region_be2_male_age_18_64_indicator", + "period_match_policy": "exact" + }, + { + "name": "statbel_population_by_region_sex_age__be2__male__a65_plus", + "ledger_selector": { + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "source_concept": "statbel.population_structure.population", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "nuts1", + "geography_id": "BE2", + "geography_vintage": "NUTS_2024", + "record_set_id": "statbel.population_structure.cy2026.people.by_nuts1_age_sex", + "dimensions": [ + "person.age_band", + "person.sex" + ], + "dimension_values": { + "person.age_band": "65_plus", + "person.sex": "male" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:3b1fb01f519506661f18756a" }, - "caseload_release": { + "entity": "person", + "measure": "people", + "period": 2026, + "family": "demography", + "category_id": "statbel.demography", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_population_by_region_sex_age", + "activation_status": "active", "criticality": "release_blocking", - "relative_tolerance": 0.15, - "description": "Administrative caseload totals: plus or minus 15 percent." + "measure_kind": "prepared_column", + "publisher": "Statbel", + 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The stand-in is never described as reproducing official taxable income.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base", + "expected_member_count": 25 + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "level_thousand", + "source_concept": "fpb.economic_outlook_2026_2031.t07.published_cell", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.labour_market.levels.total_population", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:d0f703b4cdbc4b51ce2a9674", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "level_thousand", + "source_concept": "fpb.economic_outlook_2026_2031.t07.published_cell", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2023.labour_market.levels.total_population", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:216674c54ce3810c24e7434c", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "statbel_a1_standin_taxable_income__75k_100k", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "taxable_income_eur", + "source_concept": "statbel.fiscal_income.total_net_taxable_income", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.taxable_income.by_income_class_eur1000", + "dimensions": [ + "tax_return.net_taxable_income_class" + ], + "dimension_values": { + "tax_return.net_taxable_income_class": [ + "class_75_76", + "class_76_77", + "class_77_78", + "class_78_79", + "class_79_80", + "class_80_81", + "class_81_82", + "class_82_83", + "class_83_84", + "class_84_85", + "class_85_86", + "class_86_87", + "class_87_88", + "class_88_89", + "class_89_90", + "class_90_91", + "class_91_92", + "class_92_93", + "class_93_94", + "class_94_95", + "class_95_96", + "class_96_97", + "class_97_98", + "class_98_99", + "class_99_100" + ] + }, + "assertion": "observation" + }, + "entity": "tax_unit", + "measure": "statbel_net_taxable_income_proxy_v1_eur", + "period": 2026, + "family": "fiscal_income", + "category_id": "statbel.fiscal_income", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "statbel_a1_standin_taxable_income_by_band", + "activation_status": "requires_prerequisites", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "B4/W3: the d1952 stand-in measurement statbel_net_taxable_income_proxy_v1 (rule-computed net professional income per declaration on the S2-d tax_unit) has no producer, and legal pensions, part of professional income, are not modelled until d1902. The band cuts are income-year-2023 euros: ageing them to 2026 needs a shared operation that scales interval cuts by a declared annual ratio pair. scale_money_and_intervals needs a G8-r2 factor and singleton identity money rows, and G8-r2's resolver needs dated observations through the target period; neither fits FPB's annual 2026 projections or summed bands, so reference_profile:aging_index stays deferred. The stand-in is never described as reproducing official taxable income.", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t11_total_resources", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2023", + "target_period": "2026", + "reference_value_kind": "money", + "required_reference_profile": "aging_index", + "required_measurement_binding": "statbel_net_taxable_income_proxy_v1", + "reference_prerequisites": "[\"reference_profile:aging_index\",\"measurement:statbel_net_taxable_income_proxy_v1\"]", + "interval_table_id": "statbel_a1_standin_bands_iy2023", + "declaration_universe": "filed declarations with positive total net taxable income; zero-income declarations are outside A.1, B.1 and B.4", + "standin_band": "75k_100k", + "standin_band_lower_eur_iy2023": "75000", + "standin_band_upper_eur_iy2023": "100000" + }, + "filter": "statbel_a1_standin_band_75k_100k_indicator", + "notes": "B4/W3: the d1952 stand-in measurement statbel_net_taxable_income_proxy_v1 (rule-computed net professional income per declaration on the S2-d tax_unit) has no producer, and legal pensions, part of professional income, are not modelled until d1902. The band cuts are income-year-2023 euros: ageing them to 2026 needs a shared operation that scales interval cuts by a declared annual ratio pair. scale_money_and_intervals needs a G8-r2 factor and singleton identity money rows, and G8-r2's resolver needs dated observations through the target period; neither fits FPB's annual 2026 projections or summed bands, so reference_profile:aging_index stays deferred. The stand-in is never described as reproducing official taxable income.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base", + "expected_member_count": 25 + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.household_account.total_resources", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:96551e39b8ae3a2a4d4fbba5", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2023.household_account.total_resources", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:782bd24d9f5d7ce79feadabf", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "statbel_a1_standin_declarations__100k_plus", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "declarations", + "source_concept": "statbel.fiscal_income.taxable_income.declaration_count", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.taxable_income.by_income_class_eur1000", + "dimensions": [ + "tax_return.net_taxable_income_class" + ], + "dimension_values": { + "tax_return.net_taxable_income_class": [ + "class_100_plus" + ] + }, + "assertion": "observation" + }, + "entity": "tax_unit", + "measure": "tax_units", + "period": 2026, + "family": "fiscal_income", + "category_id": "statbel.fiscal_income", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "statbel_a1_standin_declarations_by_band", + "activation_status": "requires_prerequisites", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "B4/W3: the d1952 stand-in measurement statbel_net_taxable_income_proxy_v1 (rule-computed net professional income per declaration on the S2-d tax_unit) has no producer, and legal pensions, part of professional income, are not modelled until d1902. 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The stand-in is never described as reproducing official taxable income.", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t07_total_population", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2023", + "target_period": "2026", + "reference_value_kind": "count", + "required_reference_profile": "aging_index", + "required_measurement_binding": "statbel_net_taxable_income_proxy_v1", + "reference_prerequisites": "[\"reference_profile:aging_index\",\"measurement:statbel_net_taxable_income_proxy_v1\"]", + "interval_table_id": "statbel_a1_standin_bands_iy2023", + "declaration_universe": "filed declarations with positive total net taxable income; zero-income declarations are outside A.1, B.1 and B.4", + "standin_band": "100k_plus", + "standin_band_lower_eur_iy2023": "100000", + "standin_band_upper_eur_iy2023": "open" + }, + "filter": "statbel_a1_standin_band_100k_plus_indicator", + "notes": "B4/W3: the d1952 stand-in measurement statbel_net_taxable_income_proxy_v1 (rule-computed net professional income per declaration on the S2-d tax_unit) has no producer, and legal pensions, part of professional income, are not modelled until d1902. 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The stand-in is never described as reproducing official taxable income.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base", + "expected_member_count": 1 + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "level_thousand", + "source_concept": "fpb.economic_outlook_2026_2031.t07.published_cell", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.labour_market.levels.total_population", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:d0f703b4cdbc4b51ce2a9674", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "level_thousand", + "source_concept": "fpb.economic_outlook_2026_2031.t07.published_cell", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2023.labour_market.levels.total_population", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:216674c54ce3810c24e7434c", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "statbel_a1_standin_taxable_income__100k_plus", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "taxable_income_eur", + "source_concept": "statbel.fiscal_income.total_net_taxable_income", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.taxable_income.by_income_class_eur1000", + "dimensions": [ + "tax_return.net_taxable_income_class" + ], + "dimension_values": { + "tax_return.net_taxable_income_class": [ + "class_100_plus" + ] + }, + "assertion": "observation" + }, + "entity": "tax_unit", + "measure": "statbel_net_taxable_income_proxy_v1_eur", + "period": 2026, + "family": "fiscal_income", + "category_id": "statbel.fiscal_income", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "statbel_a1_standin_taxable_income_by_band", + "activation_status": "requires_prerequisites", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "B4/W3: the d1952 stand-in measurement statbel_net_taxable_income_proxy_v1 (rule-computed net professional income per declaration on the S2-d tax_unit) has no producer, and legal pensions, part of professional income, are not modelled until d1902. 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The stand-in is never described as reproducing official taxable income.", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t11_total_resources", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2023", + "target_period": "2026", + "reference_value_kind": "money", + "required_reference_profile": "aging_index", + "required_measurement_binding": "statbel_net_taxable_income_proxy_v1", + "reference_prerequisites": "[\"reference_profile:aging_index\",\"measurement:statbel_net_taxable_income_proxy_v1\"]", + "interval_table_id": "statbel_a1_standin_bands_iy2023", + "declaration_universe": "filed declarations with positive total net taxable income; zero-income declarations are outside A.1, B.1 and B.4", + "standin_band": "100k_plus", + "standin_band_lower_eur_iy2023": "100000", + "standin_band_upper_eur_iy2023": "open" + }, + "filter": "statbel_a1_standin_band_100k_plus_indicator", + "notes": "B4/W3: the d1952 stand-in measurement statbel_net_taxable_income_proxy_v1 (rule-computed net professional income per declaration on the S2-d tax_unit) has no producer, and legal pensions, part of professional income, are not modelled until d1902. 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The stand-in is never described as reproducing official taxable income.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base", + "expected_member_count": 1 + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.household_account.total_resources", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:96551e39b8ae3a2a4d4fbba5", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2023.household_account.total_resources", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:782bd24d9f5d7ce79feadabf", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "statbel_b4_declarations__joint", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "declarations", + "source_concept": "statbel.fiscal_income_distribution.b4.declaration_count", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.declaration_type_age.by_decile", + "dimensions": [ + "tax_return.age_band", + "tax_return.decile", + "tax_return.declaration_type" + ], + "dimension_values": { + "tax_return.age_band": "all", + "tax_return.decile": [ + 1, + 2, + 3, + 4, + 5, + 6, + 7, + 8, + 9, + 10 + ], + "tax_return.declaration_type": "joint" + }, + "assertion": "observation" + }, + "entity": "tax_unit", + "measure": "tax_units", + "period": 2026, + "family": "fiscal_income", + "category_id": "statbel.fiscal_income", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "statbel_b4_declarations_by_type", + "activation_status": "requires_declared_tax_units", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC4", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "S1/S2-d: the declared tax-unit partition and the BE-MC4 legal-status proxy (partner pointers calibrated to these counts) are not built; joint and individual declaration indicators have no producer. B.4, like A.1, counts only declarations with positive total net taxable income (Statbel's 523,770 zero-income declarations of income year 2023 are outside it), so the indicators must count the same declared filing universe as the A.1 bands (d1952 build item 2), or the target overshoots by up to 7%.", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t07_total_population", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2023", + "target_period": "2026", + "reference_value_kind": "count", + "declaration_universe": "filed declarations with positive total net taxable income; zero-income declarations are outside A.1, B.1 and B.4" + }, + "filter": "joint_declaration_indicator", + "notes": "S1/S2-d: the declared tax-unit partition and the BE-MC4 legal-status proxy (partner pointers calibrated to these counts) are not built; joint and individual declaration indicators have no producer. B.4, like A.1, counts only declarations with positive total net taxable income (Statbel's 523,770 zero-income declarations of income year 2023 are outside it), so the indicators must count the same declared filing universe as the A.1 bands (d1952 build item 2), or the target overshoots by up to 7%.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base", + "expected_member_count": 10 + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "level_thousand", + "source_concept": "fpb.economic_outlook_2026_2031.t07.published_cell", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.labour_market.levels.total_population", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:d0f703b4cdbc4b51ce2a9674", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "level_thousand", + "source_concept": "fpb.economic_outlook_2026_2031.t07.published_cell", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2023.labour_market.levels.total_population", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:216674c54ce3810c24e7434c", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "statbel_b4_declarations__individual", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "declarations", + "source_concept": "statbel.fiscal_income_distribution.b4.declaration_count", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.declaration_type_age.by_decile", + "dimensions": [ + "tax_return.age_band", + "tax_return.decile", + "tax_return.declaration_type" + ], + "dimension_values": { + "tax_return.age_band": "all", + "tax_return.decile": [ + 1, + 2, + 3, + 4, + 5, + 6, + 7, + 8, + 9, + 10 + ], + "tax_return.declaration_type": "individual" + }, + "assertion": "observation" + }, + "entity": "tax_unit", + "measure": "tax_units", + "period": 2026, + "family": "fiscal_income", + "category_id": "statbel.fiscal_income", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "statbel_b4_declarations_by_type", + "activation_status": "requires_declared_tax_units", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC4", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "S1/S2-d: the declared tax-unit partition and the BE-MC4 legal-status proxy (partner pointers calibrated to these counts) are not built; joint and individual declaration indicators have no producer. B.4, like A.1, counts only declarations with positive total net taxable income (Statbel's 523,770 zero-income declarations of income year 2023 are outside it), so the indicators must count the same declared filing universe as the A.1 bands (d1952 build item 2), or the target overshoots by up to 7%.", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t07_total_population", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2023", + "target_period": "2026", + "reference_value_kind": "count", + "declaration_universe": "filed declarations with positive total net taxable income; zero-income declarations are outside A.1, B.1 and B.4" + }, + "filter": "individual_declaration_indicator", + "notes": "S1/S2-d: the declared tax-unit partition and the BE-MC4 legal-status proxy (partner pointers calibrated to these counts) are not built; joint and individual declaration indicators have no producer. B.4, like A.1, counts only declarations with positive total net taxable income (Statbel's 523,770 zero-income declarations of income year 2023 are outside it), so the indicators must count the same declared filing universe as the A.1 bands (d1952 build item 2), or the target overshoots by up to 7%.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base", + "expected_member_count": 10 + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "level_thousand", + "source_concept": "fpb.economic_outlook_2026_2031.t07.published_cell", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.labour_market.levels.total_population", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:d0f703b4cdbc4b51ce2a9674", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "level_thousand", + "source_concept": "fpb.economic_outlook_2026_2031.t07.published_cell", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2023.labour_market.levels.total_population", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:216674c54ce3810c24e7434c", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "statbel_b1_enrolled_tax__decile_01", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "total_tax_eur", + "source_concept": "statbel.fiscal_income_distribution.b1.total_tax", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.by_decile.decile_values", + "dimensions": [ + "tax_return.rank_group" + ], + "dimension_values": { + "tax_return.rank_group": "decile_01" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:0b2b5e737d0305a356532b3b" + }, + "entity": "tax_unit", + "measure": "statbel_b1_enrolled_tax_proxy_v1_eur", + "period": 2023, + "family": "income_tax", + "category_id": "statbel.income_tax", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_b1_enrolled_tax_by_rank_group", + "activation_status": "inactive_pending_b1_checks", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "ageing": "none declared: B.1 checks failed", + "reference_value_kind": "money", + "source_period": "2023" + }, + "filter": "statbel_b1_rank_group_decile_01_indicator", + "notes": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "signed": true, + "period_match_policy": "exact" + }, + { + "name": "statbel_b1_enrolled_tax__decile_02", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "total_tax_eur", + "source_concept": "statbel.fiscal_income_distribution.b1.total_tax", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.by_decile.decile_values", + "dimensions": [ + "tax_return.rank_group" + ], + "dimension_values": { + "tax_return.rank_group": "decile_02" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:c6ca78a1c708058c93a0f976" + }, + "entity": "tax_unit", + "measure": "statbel_b1_enrolled_tax_proxy_v1_eur", + "period": 2023, + "family": "income_tax", + "category_id": "statbel.income_tax", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_b1_enrolled_tax_by_rank_group", + "activation_status": "inactive_pending_b1_checks", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "ageing": "none declared: B.1 checks failed", + "reference_value_kind": "money", + "source_period": "2023" + }, + "filter": "statbel_b1_rank_group_decile_02_indicator", + "notes": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "signed": true, + "period_match_policy": "exact" + }, + { + "name": "statbel_b1_enrolled_tax__decile_03", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "total_tax_eur", + "source_concept": "statbel.fiscal_income_distribution.b1.total_tax", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.by_decile.decile_values", + "dimensions": [ + "tax_return.rank_group" + ], + "dimension_values": { + "tax_return.rank_group": "decile_03" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:109397450babe832524a5c97" + }, + "entity": "tax_unit", + "measure": "statbel_b1_enrolled_tax_proxy_v1_eur", + "period": 2023, + "family": "income_tax", + "category_id": "statbel.income_tax", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_b1_enrolled_tax_by_rank_group", + "activation_status": "inactive_pending_b1_checks", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "ageing": "none declared: B.1 checks failed", + "reference_value_kind": "money", + "source_period": "2023" + }, + "filter": "statbel_b1_rank_group_decile_03_indicator", + "notes": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "signed": true, + "period_match_policy": "exact" + }, + { + "name": "statbel_b1_enrolled_tax__decile_04", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "total_tax_eur", + "source_concept": "statbel.fiscal_income_distribution.b1.total_tax", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.by_decile.decile_values", + "dimensions": [ + "tax_return.rank_group" + ], + "dimension_values": { + "tax_return.rank_group": "decile_04" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:af9649af17a29cc5dd903c59" + }, + "entity": "tax_unit", + "measure": "statbel_b1_enrolled_tax_proxy_v1_eur", + "period": 2023, + "family": "income_tax", + "category_id": "statbel.income_tax", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_b1_enrolled_tax_by_rank_group", + "activation_status": "inactive_pending_b1_checks", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "ageing": "none declared: B.1 checks failed", + "reference_value_kind": "money", + "source_period": "2023" + }, + "filter": "statbel_b1_rank_group_decile_04_indicator", + "notes": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "signed": true, + "period_match_policy": "exact" + }, + { + "name": "statbel_b1_enrolled_tax__decile_05", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "total_tax_eur", + "source_concept": "statbel.fiscal_income_distribution.b1.total_tax", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.by_decile.decile_values", + "dimensions": [ + "tax_return.rank_group" + ], + "dimension_values": { + "tax_return.rank_group": "decile_05" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:7a4e850043abefabfa3ed8b0" + }, + "entity": "tax_unit", + "measure": "statbel_b1_enrolled_tax_proxy_v1_eur", + "period": 2023, + "family": "income_tax", + "category_id": "statbel.income_tax", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_b1_enrolled_tax_by_rank_group", + "activation_status": "inactive_pending_b1_checks", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "ageing": "none declared: B.1 checks failed", + "reference_value_kind": "money", + "source_period": "2023" + }, + "filter": "statbel_b1_rank_group_decile_05_indicator", + "notes": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "signed": true, + "period_match_policy": "exact" + }, + { + "name": "statbel_b1_enrolled_tax__decile_06", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "total_tax_eur", + "source_concept": "statbel.fiscal_income_distribution.b1.total_tax", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.by_decile.decile_values", + "dimensions": [ + "tax_return.rank_group" + ], + "dimension_values": { + "tax_return.rank_group": "decile_06" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:72b19dd783c1bc3da72aae0d" + }, + "entity": "tax_unit", + "measure": "statbel_b1_enrolled_tax_proxy_v1_eur", + "period": 2023, + "family": "income_tax", + "category_id": "statbel.income_tax", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_b1_enrolled_tax_by_rank_group", + "activation_status": "inactive_pending_b1_checks", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "ageing": "none declared: B.1 checks failed", + "reference_value_kind": "money", + "source_period": "2023" + }, + "filter": "statbel_b1_rank_group_decile_06_indicator", + "notes": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "signed": true, + "period_match_policy": "exact" + }, + { + "name": "statbel_b1_enrolled_tax__decile_07", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "total_tax_eur", + "source_concept": "statbel.fiscal_income_distribution.b1.total_tax", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.by_decile.decile_values", + "dimensions": [ + "tax_return.rank_group" + ], + "dimension_values": { + "tax_return.rank_group": "decile_07" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:076e8b7e6856e7e8a9c7352d" + }, + "entity": "tax_unit", + "measure": "statbel_b1_enrolled_tax_proxy_v1_eur", + "period": 2023, + "family": "income_tax", + "category_id": "statbel.income_tax", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_b1_enrolled_tax_by_rank_group", + "activation_status": "inactive_pending_b1_checks", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "ageing": "none declared: B.1 checks failed", + "reference_value_kind": "money", + "source_period": "2023" + }, + "filter": "statbel_b1_rank_group_decile_07_indicator", + "notes": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. 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All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "signed": true, + "period_match_policy": "exact" + }, + { + "name": "statbel_b1_enrolled_tax__percentile_099", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "total_tax_eur", + "source_concept": "statbel.fiscal_income_distribution.b1.total_tax", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.by_decile.top_decile_percentile_values", + "dimensions": [ + "tax_return.rank_group" + ], + "dimension_values": { + "tax_return.rank_group": "percentile_099" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:707eddca745f7611662f6d46" + }, + "entity": "tax_unit", + "measure": "statbel_b1_enrolled_tax_proxy_v1_eur", + "period": 2023, + "family": "income_tax", + "category_id": "statbel.income_tax", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_b1_enrolled_tax_by_rank_group", + "activation_status": "inactive_pending_b1_checks", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "ageing": "none declared: B.1 checks failed", + "reference_value_kind": "money", + "source_period": "2023" + }, + "filter": "statbel_b1_rank_group_percentile_099_indicator", + "notes": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "signed": true, + "period_match_policy": "exact" + }, + { + "name": "statbel_b1_enrolled_tax__percentile_100", + "ledger_selector": { + "source_name": "statbel_fiscal_income_distribution", + "source_measure_id": "total_tax_eur", + "source_concept": "statbel.fiscal_income_distribution.b1.total_tax", + "entity_name": "return", + "period_type": "tax_year", + "period_value": 2023, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "statbel.fiscal_income_distribution.income_year2023.by_decile.top_decile_percentile_values", + "dimensions": [ + "tax_return.rank_group" + ], + "dimension_values": { + "tax_return.rank_group": "percentile_100" + }, + "aggregate_fact_key": "ledger.aggregate_fact.v2:fefd7bd484d320ad42b5f7fe" + }, + "entity": "tax_unit", + "measure": "statbel_b1_enrolled_tax_proxy_v1_eur", + "period": 2023, + "family": "income_tax", + "category_id": "statbel.income_tax", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "statbel_b1_enrolled_tax_by_rank_group", + "activation_status": "inactive_pending_b1_checks", + "criticality": "release_blocking", + "measure_kind": "prepared_column", + "publisher": "Statbel", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC5", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "ageing": "none declared: B.1 checks failed", + "reference_value_kind": "money", + "source_period": "2023" + }, + "filter": "statbel_b1_rank_group_percentile_100_indicator", + "notes": "BE-MC5 activates B.1 only after its tax definition, income ranking and policy year are checked. All three checks fail or cannot be completed from the documents (reference_inventory.json b1_checks), so B.1 stays inactive and unaged at its source period.", + "signed": true, + "period_match_policy": "exact" + }, + { + "name": "onss_worker_personal_contributions", + "ledger_selector": { + "source_name": "onss_contributions", + "source_measure_id": "worker_article_17_uncapped_component_contribution", + "source_concept": "onss.declared_contributions.personal_social_security_contributions_worker_borne", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2024, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "onss.contributions.cy2024.worker_personal_contributions.country", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:b6355af1bd917ae71a7df3ae", + "assertion": "observation" + }, + "entity": "person", + "measure": "belgium_worker_article_17_uncapped_component_contribution", + "period": 2026, + "family": "social_security", + "category_id": "onss.social_security", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "onss_worker_personal_contributions", + "activation_status": "requires_rules_binding", + "criticality": "release_blocking", + "measure_kind": "rules_output", + "publisher": "National Social Security Office", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC6", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "W3: needs a pinned rulespec-be binding for be/statutes/social_security/workers/contribution_rates.yaml on the transported frame, the S5 pre-calibration allowlist entry for it, and B4's euro conversion of the donor inputs it reads.", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t11_actual_social_contributions", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2024", + "target_period": "2026" + }, + "notes": "W3: needs a pinned rulespec-be binding for be/statutes/social_security/workers/contribution_rates.yaml on the transported frame, the S5 pre-calibration allowlist entry for it, and B4's euro conversion of the donor inputs it reads.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base" + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.household_account.actual_social_contributions", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:a66b02d02ed92c58e542e7ed", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2024, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2024.household_account.actual_social_contributions", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:3f953c8cbe00192899c93c3b", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "onem_complete_unemployment_recipients", + "ledger_selector": { + "source_name": "onem_rva_unemployment", + "source_measure_id": "receives_unemployment_benefit", + "source_concept": "onem_rva.complete_unemployment.monthly_average_recipients", + "entity_name": "person", + "period_type": "calendar_year", + "period_value": 2024, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "onem_rva.unemployment.cy2024.complete_unemployment.country", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:466ad99667f2d50f94a42726" + }, + "entity": "person", + "measure": "receives_unemployment_benefit", + "period": 2024, + "family": "caseloads", + "category_id": "onem.caseloads", + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": "onem_complete_unemployment_recipients", + "activation_status": "requires_ageing_ruling_and_receipt_binding", + "criticality": "release_blocking", + "measure_kind": "receipt_flag", + "publisher": "National Employment Office", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC6", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "No declared ageing pair: FPB publishes jobseeker levels (BFP unemployment, +0.6% 2026/2025), not benefit recipients, and its unemployment benefit spending falls 24% in 2026, so the two series point opposite ways and neither ages a recipient count. Kept unaged at its 2024 source period. Also needs W3's receipt contract for unemployment.", + "ageing": "none declared: no recipient series" + }, + "notes": "No declared ageing pair: FPB publishes jobseeker levels (BFP unemployment, +0.6% 2026/2025), not benefit recipients, and its unemployment benefit spending falls 24% in 2026, so the two series point opposite ways and neither ages a recipient count. Kept unaged at its 2024 source period. Also needs W3's receipt contract for unemployment.", + "period_match_policy": "exact" + }, + { + "name": "fpb_unemployment_benefit_expenditure", + "ledger_selector": { + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t24.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2025.social_benefits_detail.social_security_cash_unemployment", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:45ad11668f4cf559bb3c388f", + "assertion": "observation" + }, + "entity": "household", + "measure": "belgium_unemployment_ordinary_annual_payable_amount", + "period": 2026, + "family": "benefit_expenditure", + "category_id": "fpb.benefit_expenditure", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "fpb_unemployment_benefit_expenditure", + "activation_status": "requires_receipt_contract_and_rules_binding", + "criticality": "release_blocking", + "measure_kind": "rules_output", + "publisher": "Federal Planning Bureau", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC6", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "W3: needs a pinned rulespec-be binding for be/regulations/unemployment/pilot_oracle_pipeline.yaml on the transported frame, the S5 pre-calibration allowlist entry for it, and B4's euro conversion of the donor inputs it reads. Unemployment history inputs and W3's receipt contract are also missing.", + "ageing_target_equals": "FPB's 2026 projection of the base's own row", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t24_social_security_cash_unemployment", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2025", + "target_period": "2026" + }, + "notes": "W3: needs a pinned rulespec-be binding for be/regulations/unemployment/pilot_oracle_pipeline.yaml on the transported frame, the S5 pre-calibration allowlist entry for it, and B4's euro conversion of the donor inputs it reads. Unemployment history inputs and W3's receipt contract are also missing.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base" + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t24.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.social_benefits_detail.social_security_cash_unemployment", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:61a041fd9dff09745593e4da", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t24.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2025.social_benefits_detail.social_security_cash_unemployment", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:45ad11668f4cf559bb3c388f", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "fpb_grapa_expenditure", + "ledger_selector": { + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t24.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2025.social_benefits_detail.federal_government_cash_income_guarantee_for_older_people", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:776e68a9e93ca03151c53baf", + "assertion": "observation" + }, + "entity": "person", + "measure": "belgium_grapa_income_guarantee_for_elderly_annual_amount", + "period": 2026, + "family": "benefit_expenditure", + "category_id": "fpb.benefit_expenditure", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "fpb_grapa_expenditure", + "activation_status": "requires_pension_route_d1902", + "criticality": "release_blocking", + "measure_kind": "rules_output", + "publisher": "Federal Planning Bureau", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC6", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "GRAPA is means-tested on pension income, and legal pensions are not modelled until d1902 settles BE-MC3's pension route. W3: needs a pinned rulespec-be binding for be/statutes/income_guarantee_for_elderly/payable_amount.yaml on the transported frame, the S5 pre-calibration allowlist entry for it, and B4's euro conversion of the donor inputs it reads.", + "ageing_target_equals": "FPB's 2026 projection of the base's own row", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t24_federal_cash_income_guarantee_for_older_people", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2025", + "target_period": "2026" + }, + "notes": "GRAPA is means-tested on pension income, and legal pensions are not modelled until d1902 settles BE-MC3's pension route. W3: needs a pinned rulespec-be binding for be/statutes/income_guarantee_for_elderly/payable_amount.yaml on the transported frame, the S5 pre-calibration allowlist entry for it, and B4's euro conversion of the donor inputs it reads.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base" + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t24.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.social_benefits_detail.federal_government_cash_income_guarantee_for_older_people", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:13ee4f4b5a469ddeb487eafc", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t24.published_cell", + "entity_name": "government", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2025.social_benefits_detail.federal_government_cash_income_guarantee_for_older_people", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:776e68a9e93ca03151c53baf", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + }, + { + "name": "fpb_net_mixed_income", + "ledger_selector": { + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2025.household_account.net_mixed_income", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:0db8ec51ab64a7f7519fc5d4", + "assertion": "observation" + }, + "entity": "person", + "measure": "nonfarm_self_employment_income", + "period": 2026, + "family": "self_employment", + "category_id": "fpb.self_employment", + "assertion_policy": "allow_source_projection", + "metadata": { + "contract_target_id": "fpb_net_mixed_income", + "activation_status": "requires_currency_bridge_b4", + "criticality": "release_blocking", + "measure_kind": "transported_input", + "publisher": "Federal Planning Bureau", + "target_role": "calibration", + "reference_set": "calibration", + "method_card_row": "BE-MC3", + "method_card_status": "proposed_pending_d1902", + "fit_tolerance": "0.05", + "parking_reason": "B4: BE-MC3 gives self-employment income FX and uprating only, then calibrates its aggregate; the euro column has no producer until B4's currency bridge. FPB's net mixed income also covers farm income, which the donor carries separately.", + "ageing_target_equals": "FPB's 2026 projection of the base's own row", + "ageing": "rolled_forward_by_ratio", + "ageing_pair": "fpb_t11_net_mixed_income", + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": "2025", + "target_period": "2026" + }, + "notes": "B4: BE-MC3 gives self-employment income FX and uprating only, then calibrates its aggregate; the euro column has no producer until B4's currency bridge. FPB's net mixed income also covers farm income, which the donor carries separately.", + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + { + "role": "base" + }, + { + "role": "numerator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2026, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2026.household_account.net_mixed_income", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:82a8d913db8aa3594a182492", + "assertion": "source_projection" + }, + { + "role": "denominator", + "source_name": "fpb_economic_outlook", + "source_measure_id": "amount_meur", + "source_concept": "fpb.economic_outlook_2026_2031.t11.published_cell", + "entity_name": "household", + "period_type": "calendar_year", + "period_value": 2025, + "geography_level": "country", + "geography_id": "BE", + "geography_vintage": "current", + "record_set_id": "fpb.economic_outlook_2026_2031.cy2025.household_account.net_mixed_income", + "dimensions": [], + "aggregate_fact_key": "ledger.aggregate_fact.v2:0db8ec51ab64a7f7519fc5d4", + "assertion": "observation" + } + ], + "period_match_policy": "latest_not_after" + } + ], + "target_profile": { + "schema_version": 1, + "hierarchy_reconciliations": [] } } diff --git a/packages/microcosm-build/tests/engine_free/shared/test_be_target_references.py b/packages/microcosm-build/tests/engine_free/shared/test_be_target_references.py new file mode 100644 index 0000000000..cc45cb43e4 --- /dev/null +++ b/packages/microcosm-build/tests/engine_free/shared/test_be_target_references.py @@ -0,0 +1,1777 @@ +"""Belgian reference documents: separation, ageing pairs, bands and a pinned-feed audit. + +The static tests read the committed documents. The feed audit needs the +Chronicle ``be`` consumer artifact, which CI does not hold: set +``BE_CHRONICLE_ARTIFACT`` to its directory to run it, as for NZ. +""" + +from __future__ import annotations + +import copy +import functools +import json +import math +import os +import re +from fractions import Fraction +from pathlib import Path +from unittest import mock + +import pytest +from hypothesis import HealthCheck, example, given, settings +from hypothesis import strategies as st + +from microcosm.build.country_spec import ( + _carried_value_keys, + _typed_geography_vintage_aliases, + load_country_spec, +) +from microcosm.build.ledger_artifact import ( + ChronicleFeedPinMismatchError, + chronicle_feed_identity, + load_ledger_consumer_artifact, +) +from microcosm.build.ledger_targets import ( + compile_ledger_target_references, + fact_matches_selector, + reference_fact_selectors, +) +from microcosm.build.reference_factors import ( + replay_reference_factor, + validate_factor_context, +) +from microcosm.build.reference_intervals import ( + BELOW_FIRST_CUT, + classify_records, + interval_table, + validate_interval_document, +) +from microcosm.build.reference_profiles import ( + REFERENCE_DOCUMENT_KEYS, + reference_document_sha256, + resolve_reference_profiles, + validate_reference_resolution, +) +from microcosm.build.transport.compose import ( + load_transport_spec, + validate_transport_activation, +) +from microcosm.build.transport.target_kernels import parse_reference_document +from test_support.paths import paths_for +from tools import generate_be_target_references as generator + +_SPEC = paths_for("microcosm-build").package / "src/microcosm/build/be" +SETS = { + "calibration": "target_references.json", + "precal": "precal_references.json", + "holdout": "holdout_references.json", +} +# The committed selectors' fields. The shared vocabulary admits more, including +# other fact keys that neither the pin check nor the cell check reads. +_SELECTOR_FIELDS = frozenset( + { + "aggregate_fact_key", + "assertion", + "dimension_values", + "dimensions", + "entity_name", + "geography_id", + "geography_level", + "geography_vintage", + "period_type", + "period_value", + "record_set_id", + "source_concept", + "source_measure_id", + "source_name", + } +) +GENERATED = ( + *SETS.values(), + "reference_aging.json", + "reference_intervals.json", + "reference_inventory.json", + "reference_profiles.json", +) +BELGIAN_LEVELS = {"country": {"BE"}, "nuts1": {"BE1", "BE2", "BE3"}} +# B1's schema-2 profile required these; schema 1 can't, so this package test does. +REQUIRED_FAMILIES = { + "demography", + "fiscal_income", + "income_tax", + "social_security", + "caseloads", +} +# Rows whose Eurostat base equals the pair's denominator without being its fact. +BASES_EQUAL_TO_DENOMINATOR = { + "eurostat_household_current_taxes_paid", + "eurostat_household_social_benefits_received", + "eurostat_household_social_contributions_paid", +} +A1_CLASSES = [ + (0, 1000, "class_under_1"), + *( + (1000 * low, 1000 * (low + 1), f"class_{low}_{low + 1}") + for low in range(1, 100) + ), + (100_000, None, "class_100_plus"), +] + + +def _document(name): + return json.loads((_SPEC / name).read_text()) + + +def _documents(): + return {reference_set: _document(name) for reference_set, name in SETS.items()} + + +def _rows(reference_set="calibration"): + return _document(SETS[reference_set])["target_references"] + + +def _parsed(rows, hierarchy): + return parse_reference_document( + { + "country": "be", + "schema_version": 2, + "hierarchy": hierarchy, + "target_references": rows, + }, + country="be", + ) + + +def _selectors(row): + """The base selector (with any geography overlay), then each operand.""" + + base = dict(row["ledger_selector"]) + operands = row.get("value_operands", []) + for operand in operands: + if operand.get("role") == "base": + base.update( + { + key: value + for key, value in operand.items() + if key in {"geography_level", "geography_id"} + } + ) + yield base + for operand in operands: + if operand.get("role") != "base": + yield {key: value for key, value in operand.items() if key != "role"} + + +def _row_cells(row): + """One identity per cell a row reads, whether pinned by key or by roster. + + A pinned selector also names its record set, measure, geography and + dimension values, so pinned and roster cells share one identity and a + holdout pinning a fact that calibration reads through a roster collides. + """ + + cells = set() + for selector in _selectors(row): + pins = dict(selector.get("dimension_values", {})) + rosters = [key for key, value in pins.items() if isinstance(value, list)] + members = pins[rosters[0]] if rosters else [None] + areas = selector["geography_id"] + for area in areas if isinstance(areas, list) else [areas]: + for member in members: + if rosters: + pins[rosters[0]] = member + cells.add( + ( + selector["record_set_id"], + selector["source_measure_id"], + area, + json.dumps(pins, sort_keys=True), + ) + ) + return cells + + +def _separation_violations(documents): + """Every way a row could sit in two sets or a holdout could feed calibration.""" + + violations = [] + names, bases, reads, measures = {}, {}, {}, {} + for reference_set, document in documents.items(): + for row in document["target_references"]: + if row["metadata"]["reference_set"] != reference_set: + violations.append(("misfiled", row["name"])) + names.setdefault(row["name"], set()).add(reference_set) + base = { + cell for cell in _row_cells({"ledger_selector": row["ledger_selector"]}) + } + for cell in base: + bases.setdefault(cell, set()).add(reference_set) + for cell in _row_cells(row): + reads.setdefault(cell, set()).add(reference_set) + measures.setdefault(row["measure"], set()).add(reference_set) + violations += [("name", name) for name, sets in names.items() if len(sets) > 1] + violations += [("base", cell) for cell, sets in bases.items() if len(sets) > 1] + violations += [ + ("holdout_read", cell) + for cell, sets in reads.items() + if "holdout" in sets and len(sets) > 1 + ] + violations += [ + ("holdout_measure", measure) + for measure, sets in measures.items() + if "holdout" in sets and len(sets) > 1 + ] + return violations + + +def _reads(): + return _document("reference_inventory.json")["resolved_reads"] + + +def _keys(facts): + return [key for fact in facts for key in fact.values()] + + +def _unpinned(row): + """Whether a row's selectors read through a spelling no check here can see. + + The pin check reads aggregate keys and the cell check reads measures and + dimension values literally, but the resolver skips an empty field, admits + other fact keys and checks only the pins a selector names. So each selector + keeps to the committed fields, leaves none empty, pins every dimension it + declares with at most one roster, and pins an aggregate key or, for a base + selector, a roster. The feed audit stays the proof: these shapes catch hand + edits, and a roster's members bind to no listed key without the artifact. + """ + + for index, selector in enumerate(_selectors(row)): + pins = selector.get("dimension_values") or {} + rosters = [value for value in pins.values() if isinstance(value, list)] + members = [ + member + for value in pins.values() + for member in (value if isinstance(value, list) else [value]) + ] + if ( + set(selector) - _SELECTOR_FIELDS + or any(value is None or value == "" for value in selector.values()) + or not isinstance(selector.get("dimensions"), list) + or set(pins) != set(selector["dimensions"]) + or len(rosters) > 1 + or not all(rosters) + or not all(isinstance(item, str | int) and item != "" for item in members) + or not (selector.get("aggregate_fact_key") or (index == 0 and rosters)) + ): + return True + return False + + +def _pin_violations(documents, factors, listed): + """Each selector must pin what its resolved-read entry lists, under its set. + + A digest ties an entry to its selectors but not to the keys it lists, so a + selector rewritten with a recomputed digest would keep its old keys. Roster + selectors name no key, and only the feed audit proves what they resolve to. + """ + + violations = [] + for reference_set, document in documents.items(): + for row in document["target_references"]: + if _unpinned(row): + violations.append(("unpinned", row["name"])) + entry = listed.get(row["name"]) + if entry is None: + continue + if entry["reference_set"] != reference_set: + violations.append(("relabelled", row["name"])) + base = row["ledger_selector"].get("aggregate_fact_key") + operands = { + operand["aggregate_fact_key"] + for operand in row.get("value_operands", []) + if "aggregate_fact_key" in operand + } + if ( + base is not None and _keys(entry["base_facts"]) != [base] + ) or not operands <= set(_keys(entry["operand_facts"])): + violations.append(("pin", row["name"])) + for factor in factors["factors"]: + declaration = factor["declaration"] + name = f"factor:{declaration['id']}" + pins = { + slot["selector"]["aggregate_fact_key"] + for schedule in ("source_schedule", "target_schedule") + for slot in declaration[schedule] + } + if name not in listed: + continue + if pins != set(_keys(listed[name]["operand_facts"])): + violations.append(("pin", name)) + if listed[name]["reference_set"] != "factor_context": + violations.append(("relabelled", name)) + return violations + + +def _read_violations(documents, factors, reads): + """Disjointness on the listed feed keys, for every selector as committed. + + A digest ties each listed entry to its row's exact selectors, so a selector + respelled to dodge the cell check fails here. The pin check ties each pinned + key and each row's set to its entry and refuses a spelling these checks can't + read, and the feed audit proves every listed key. Partition totals count as + read, because a holdout on a band set's total shares its information. + """ + + listed = {entry["name"]: entry for entry in reads} + violations = _pin_violations(documents, factors, listed) + expected = { + row["name"]: generator.selector_digest(row) + for document in documents.values() + for row in document["target_references"] + } | { + f"factor:{entry['declaration']['id']}": generator.factor_digest( + entry["declaration"] + ) + for entry in factors["factors"] + } + violations += [("unlisted", name) for name in expected.keys() - listed.keys()] + violations += [("unlisted", name) for name in listed.keys() - expected.keys()] + violations += [ + ("digest", name) + for name in expected.keys() & listed.keys() + if listed[name]["selector_sha256"] != expected[name] + ] + facts, semantic, bases = {}, {}, {} + for entry in reads: + reference_set = entry["reference_set"] + for key in _keys(entry["base_facts"]): + bases.setdefault(key, set()).add(reference_set) + facts.setdefault(key, set()).add(reference_set) + for key in _keys(entry["operand_facts"]): + facts.setdefault(key, set()).add(reference_set) + total = entry.get("partition_total") + for key in _keys([*entry["semantic_facts"], *([total] if total else [])]): + semantic.setdefault(key, set()).add(reference_set) + violations += [("shared_base", key) for key, sets in bases.items() if len(sets) > 1] + violations += [ + (kind, key) + for kind, index in (("holdout_fact", facts), ("holdout_semantic", semantic)) + for key, sets in index.items() + if "holdout" in sets and len(sets) > 1 + ] + return violations + + +def _vintage_violations(rows, layers): + """Each subnational row must map its vintage to its layer's typed authority.""" + + violations = [] + for row in rows: + selector, metadata = row["ledger_selector"], row["metadata"] + level = selector["geography_level"] + if level == "country": + continue + vintage, _ = generator.GEOGRAPHY_VINTAGES.get(level, (None, None)) + if ( + selector["geography_vintage"] != vintage + or metadata.get("geography_vintage") != vintage + or metadata.get("geography_vintage_authority") != layers.get(level) + ): + violations.append(row["name"]) + return violations + + +def _money_context_violations(package): + """One factor context must serve references and money, as #1436 can't check. + + Run entry validates each money node's context on its own, so two contexts + could carry one factor id under different declarations. A non-diagnostic + factor may live only in reference_profiles.factor_context_resource, and + every money.normalize@1 node, in the graph or in entitlement rows, must + select that resource. + """ + + context = json.loads((package / "reference_profiles.json").read_text())[ + "factor_context_resource" + ] + stem = context.removesuffix(".json") + + def nodes(value): + if isinstance(value, dict): + if value.get("kernel") == "money.normalize@1": + yield value + value = list(value.values()) + if isinstance(value, list): + for item in value: + yield from nodes(item) + + violations = [] + for path in sorted(package.glob("*.json")): + document = json.loads(path.read_text()) + factors = document.get("factors") if isinstance(document, dict) else None + if path.name != context and isinstance(factors, list): + violations += [ + ("stray_factor", path.name) + for entry in factors + if entry["declaration"]["purpose"] != "diagnostic" + ] + for node in nodes(document): + selection = node.get("params", {}).get("factor_context") + resource = selection.get("resource") if isinstance(selection, dict) else "" + if str(resource).removesuffix(".json") != stem: + violations.append(("money_context", path.name)) + return violations + + +@functools.cache +def _rolled_rows(): + """Every rolled row across the three sets, as JSON text to copy per example.""" + + return tuple( + json.dumps(row) + for reference_set in SETS + for row in _rows(reference_set) + if row.get("value_operation") == "rolled_forward_by_ratio" + ) + + +def _year_free(record_set_id): + return re.sub(r"\.cy\d{4}\.", ".cy*.", record_set_id) + + +def _pair_violations(row): + """A rolled row's operands must be one FPB row at the declared periods.""" + + if row.get("value_operation") != "rolled_forward_by_ratio": + return [] + base, numerator, denominator = row["value_operands"] + problems = [] + if [base["role"], numerator["role"], denominator["role"]] != [ + "base", + "numerator", + "denominator", + ]: + problems.append("roles") + for key in ( + "source_name", + "source_measure_id", + "source_concept", + "entity_name", + "geography_level", + "geography_id", + "dimensions", + ): + if numerator.get(key) != denominator.get(key): + problems.append(key) + if _year_free(numerator["record_set_id"]) != _year_free( + denominator["record_set_id"] + ): + problems.append("row") + pair = generator.AGEING_PAIRS.get(row["metadata"].get("ageing_pair")) + if pair is None: + problems.append("undeclared_pair") + else: + expected = f"{generator.FPB}cy*.{pair['row']}" + if _year_free(numerator["record_set_id"]) != expected: + problems.append("pair_row") + if set(pair["operands"]) != { + numerator["period_value"], + denominator["period_value"], + }: + problems.append("pair_periods") + if ( + numerator["period_value"] != row["period"] + or numerator["assertion"] != "source_projection" + ): + problems.append("numerator_period") + if ( + denominator["period_value"] != row["ledger_selector"]["period_value"] + or denominator["assertion"] != "observation" + or str(denominator["period_value"]) != row["metadata"]["source_period"] + or str(row["period"]) != row["metadata"]["target_period"] + ): + problems.append("denominator_period") + return problems + + +def _belgian_selector(selector): + level, area = selector["geography_level"], selector["geography_id"] + if level == "commune": + areas = area if isinstance(area, list) else [area] + return all(re.fullmatch(r"[1-9][0-9]{4}", code) for code in areas) + return area in BELGIAN_LEVELS.get(level, set()) + + +def test_documents_are_value_free_uniquely_named_and_registered(): + package = _document("country_package.json") + declared = {row["path"] for row in package["resources"]} + assert {"chronicle_feed.json", *GENERATED} <= declared + spec = load_country_spec(_SPEC) + assert {"chronicle_feed.json", *GENERATED} <= set(spec.resources) + for name in GENERATED: + payload = _document(name) + if name not in {"reference_aging.json", "reference_inventory.json"}: + # Factor receipts and the inventory record evidence; references, + # intervals and profiles carry no observation at any depth. + assert not _carried_value_keys(payload), name + if name in SETS.values(): + rows = payload["target_references"] + assert len({row["name"] for row in rows}) == len(rows) + assert payload["schema_version"] == 2 + assert payload["target_profile"] == { + "schema_version": 1, + "hierarchy_reconciliations": [], + } + for row in rows: + if row["metadata"]["activation_status"] != "active": + assert row["metadata"]["parking_reason"].strip(), row["name"] + assert row["metadata"]["method_card_status"] == ( + "proposed_pending_d1902" + ) + + +def test_counts_by_family_and_reference_set(): + inventory = _document("reference_inventory.json")["reference_counts"] + assert {name: counts["total"] for name, counts in inventory.items()} == { + "target_references.json": 60, + "precal_references.json": 565, + "holdout_references.json": 7, + } + assert inventory["target_references.json"]["by_family"] == { + "demography": 18, + "fiscal_income": 18, + "income_tax": 19, + "social_security": 1, + "caseloads": 1, + "benefit_expenditure": 2, + "self_employment": 1, + } + for reference_set, name in SETS.items(): + rows = _rows(reference_set) + assert inventory[name]["total"] == len(rows) + active = { + reference_set: sum( + row["metadata"]["activation_status"] == "active" + for row in _rows(reference_set) + ) + for reference_set in SETS + } + assert active == {"calibration": 18, "precal": 565, "holdout": 0} + + +def test_reference_sets_are_separated(): + assert _separation_violations(_documents()) == [] + holdout = _rows("holdout") + assert {row["metadata"]["target_role"] for row in holdout} == {"validation"} + assert {row["metadata"]["target_role"] for row in _rows("precal")} == { + "pre_calibration" + } + + +@pytest.mark.parametrize( + ("mutant", "kind"), + [ + ("calibration_row_in_holdout", "name"), + ("precal_row_in_calibration", "base"), + ("holdout_reads_calibration_operand", "holdout_read"), + ("holdout_measures_calibration_column", "holdout_measure"), + ("calibration_reuses_holdout_column_on_another_entity", "holdout_measure"), + ("holdout_base_is_calibration_fact", "holdout_read"), + ("holdout_pins_a_class_calibration_reads_by_roster", "holdout_read"), + ], +) +def test_separation_mutants_are_caught(mutant, kind): + documents = copy.deepcopy(_documents()) + calibration = documents["calibration"]["target_references"] + holdout = documents["holdout"]["target_references"] + if mutant == "calibration_row_in_holdout": + row = copy.deepcopy(calibration[0]) + row["metadata"]["reference_set"] = "holdout" + holdout.append(row) + elif mutant == "precal_row_in_calibration": + row = copy.deepcopy(documents["precal"]["target_references"][0]) + row["name"] += "__copy" + row["metadata"]["reference_set"] = "calibration" + calibration.append(row) + elif mutant == "holdout_reads_calibration_operand": + donor = next( + row + for row in calibration + if row["metadata"].get("ageing_pair") == "fpb_t11_total_resources" + ) + holdout[0]["value_operands"][1] = copy.deepcopy(donor["value_operands"][1]) + elif mutant == "holdout_measures_calibration_column": + holdout[0]["entity"], holdout[0]["measure"] = "tax_unit", "tax_units" + elif mutant == "calibration_reuses_holdout_column_on_another_entity": + donor = next( + row for row in calibration if row["entity"] != holdout[0]["entity"] + ) + donor["measure"] = holdout[0]["measure"] + elif mutant == "holdout_pins_a_class_calibration_reads_by_roster": + band = next( + row + for row in calibration + if row["name"] == "statbel_a1_standin_declarations__10k_20k" + ) + selector = copy.deepcopy(band["ledger_selector"]) + selector["dimension_values"] = {generator.A1_CLASS: "class_12_13"} + selector["aggregate_fact_key"] = "ledger.aggregate_fact.v2:pinned-class" + holdout[0]["ledger_selector"] = selector + else: + donor = next( + row + for row in calibration + if row["name"] == "onss_worker_personal_contributions" + ) + holdout[0]["ledger_selector"] = copy.deepcopy(donor["ledger_selector"]) + assert kind in {violation[0] for violation in _separation_violations(documents)} + + +def test_resolved_reads_bind_every_selector_and_stay_disjoint(): + assert ( + _read_violations(_documents(), _document("reference_aging.json"), _reads()) + == [] + ) + + +@pytest.mark.parametrize( + ("mutant", "kind"), + [ + ("respelled_selector", "digest"), + ("recomputed_digest_on_a_rewritten_base", "pin"), + ("recomputed_digest_on_a_rewritten_operand", "pin"), + ("factor_entry_keeps_an_old_key", "pin"), + ("relabelled_entry", "relabelled"), + ("relabelled_factor_entry", "relabelled"), + ("dropped_entry", "unlisted"), + ("holdout_reads_a_band_class", "holdout_fact"), + ("holdout_reads_a_factor_operand", "holdout_fact"), + ("holdout_on_a_partition_total", "holdout_semantic"), + ("calibration_base_in_precal", "shared_base"), + ], +) +def test_read_mutants_are_caught(mutant, kind): + documents, reads = copy.deepcopy(_documents()), copy.deepcopy(_reads()) + entries = {entry["name"]: entry for entry in reads} + holdout = next(entry for entry in reads if entry["reference_set"] == "holdout") + band = entries["statbel_a1_standin_taxable_income__10k_20k"] + row = documents["holdout"]["target_references"][0] + if mutant.startswith(("respelled", "recomputed")): + # A band row's selector with the class named only by its aggregate key: + # the cell check sees a new cell, yet the selector still reads the class. + donor = next( + row + for row in documents["calibration"]["target_references"] + if row["name"] == band["name"] + ) + selector = copy.deepcopy(donor["ledger_selector"]) + del selector["dimension_values"] + selector["aggregate_fact_key"] = _keys(band["base_facts"])[2] + if mutant == "recomputed_digest_on_a_rewritten_operand": + operand = row["value_operands"][1] + row["value_operands"][1] = {"role": operand["role"], **selector} + else: + row["ledger_selector"] = selector + assert _separation_violations(documents) == [] + if mutant != "respelled_selector": + entries[row["name"]]["selector_sha256"] = generator.selector_digest(row) + elif mutant == "factor_entry_keeps_an_old_key": + factor = next( + entry for entry in reads if entry["reference_set"] == "factor_context" + ) + factor["operand_facts"][0] = {"aggregate_fact_key": "stale"} + elif mutant == "relabelled_entry": + entries[row["name"]]["reference_set"] = "calibration" + elif mutant == "relabelled_factor_entry": + factor = next( + entry for entry in reads if entry["reference_set"] == "factor_context" + ) + factor["reference_set"] = "calibration" + elif mutant == "dropped_entry": + reads.remove(holdout) + elif mutant == "holdout_reads_a_band_class": + holdout["base_facts"].append(band["base_facts"][0]) + elif mutant == "holdout_reads_a_factor_operand": + factor = next( + entry for entry in reads if entry["reference_set"] == "factor_context" + ) + holdout["operand_facts"].append(factor["operand_facts"][0]) + elif mutant == "holdout_on_a_partition_total": + holdout["semantic_facts"].append(band["partition_total"]) + else: + precal = next(entry for entry in reads if entry["reference_set"] == "precal") + precal["base_facts"].append(band["base_facts"][0]) + assert kind in { + violation[0] + for violation in _read_violations( + documents, _document("reference_aging.json"), reads + ) + } + + +@pytest.mark.parametrize("target", ["base", "operand"]) +@pytest.mark.parametrize( + "spelling", + [ + {"semantic_fact_key": "key"}, + {"legacy_fact_key": "key"}, + {"source_record_id": "key"}, + {"layout_groupby_value_id": "key"}, + {"dimensions": {generator.A1_CLASS: "class_12_13"}}, + {"aggregate_fact_key": None, "source_measure_id": None}, + {"aggregate_fact_key": ""}, + { + "dimensions": [generator.A1_CLASS], + "dimension_values": {generator.A1_CLASS: ["class_12_13"]}, + "source_measure_id": None, + }, + { + "dimensions": [generator.A1_CLASS], + "dimension_values": {generator.A1_CLASS: ["class_12_13"]}, + "source_measure_id": "", + }, + { + "dimensions": [generator.A1_CLASS], + "dimension_values": {generator.A1_CLASS: ["class_12_13"]}, + "semantic_fact_key": "key", + }, + {}, + {"dimensions": {"a": "x"}, "dimension_values": {"a": ["x"]}}, + {"dimensions": ["a", "b"], "dimension_values": {"a": ["x"]}}, + {"dimensions": ["a", "b"], "dimension_values": {"a": ["x"], "b": ["y"]}}, + {"dimensions": ["a"], "dimension_values": {"a": []}}, + {"dimensions": ["a"], "dimension_values": {"a": [None]}}, + {"dimensions": ["a"], "dimension_values": {"a": [""]}}, + {"dimensions": ["a"], "dimension_values": {"a": [[]]}}, + {"dimensions": ["a"], "dimension_values": {"a": ["x", None]}}, + {"dimensions": ["a", "b"], "dimension_values": {"a": ["x"], "b": None}}, + {"dimensions": ["a", "b"], "dimension_values": {"a": ["x"], "b": ""}}, + {"dimensions": ["a", "b"], "dimension_values": {"a": ["x"], "b": []}}, + ], +) +def test_spellings_the_checks_cannot_read_refuse(spelling, target): + """A selector can name a fact in ways neither the key nor cell check sees.""" + + documents, reads = copy.deepcopy(_documents()), copy.deepcopy(_reads()) + row = documents["holdout"]["target_references"][0] + selector = row["ledger_selector"] + if target == "operand": + selector = row["value_operands"][1] + del selector["aggregate_fact_key"] + selector.update(spelling) + next(entry for entry in reads if entry["name"] == row["name"])[ + "selector_sha256" + ] = generator.selector_digest(row) + violations = _read_violations(documents, _document("reference_aging.json"), reads) + assert ("unpinned", row["name"]) in violations + assert ("digest", row["name"]) not in violations + + +def test_an_operand_needs_a_key_even_with_a_roster(): + """Only a base selector may read a roster; an operand reads one fact.""" + + row = copy.deepcopy(_rows("holdout")[0]) + operand = row["value_operands"][1] + del operand["aggregate_fact_key"] + operand["dimensions"] = [generator.A1_CLASS] + operand["dimension_values"] = {generator.A1_CLASS: ["class_12_13"]} + assert _unpinned(row) + assert not _unpinned(_rows("holdout")[0]) + + +@functools.cache +def _typed_layers(): + resolved = load_country_spec(_SPEC).resolved_spec + assignment = resolved.domain("geography").to_wire()["assignment"] + return json.dumps(assignment["layer_vintages"]) + + +def test_subnational_rows_map_their_vintage_to_the_typed_layer(): + layers = json.loads(_typed_layers()) + for reference_set in SETS: + assert _vintage_violations(_rows(reference_set), layers) == [] + aliases = _typed_geography_vintage_aliases( + load_country_spec(_SPEC).resolved_spec, country="be" + ) + bindings = _document("reference_inventory.json")["geography_vintage_bindings"] + assert {row["layer"] for row in bindings} == set(generator.GEOGRAPHY_VINTAGES) + for binding in bindings: + layer = binding["layer"] + assert binding["typed_authority"] == layers[layer] + assert (binding["chronicle_vintage"], binding["typed_authority"]) == ( + generator.GEOGRAPHY_VINTAGES[layer] + ) + exact = binding["chronicle_vintage"] in aliases[layer] + assert binding["relation"] == ("exact_alias" if exact else "crosswalk") + + +@pytest.mark.parametrize( + ("reference_set", "change"), + [ + ("calibration", {"selector": "NUTS_2021"}), + ("calibration", {"metadata": "NUTS_2021"}), + ("calibration", {"metadata": None}), + ("calibration", {"authority": "vintage:be_province_2025"}), + ("calibration", {"authority": None}), + ("precal", {"selector": "nis_2024"}), + ], +) +def test_vintage_mutants_refuse(reference_set, change): + rows = copy.deepcopy(_rows(reference_set)[:1]) + selector, metadata = rows[0]["ledger_selector"], rows[0]["metadata"] + for field, value in change.items(): + if field == "selector": + selector["geography_vintage"] = value + else: + key = { + "metadata": "geography_vintage", + "authority": "geography_vintage_authority", + }[field] + if value is None: + del metadata[key] + else: + metadata[key] = value + assert _vintage_violations(rows, json.loads(_typed_layers())) == [rows[0]["name"]] + + +def test_an_unreviewed_vintage_label_refuses_generation(): + fact = { + "aggregate_fact_key": "ledger.aggregate_fact.v2:synthetic", + "geography": {"level": "nuts1", "id": "BE1", "vintage": "NUTS_2027"}, + } + with pytest.raises(ValueError, match="reviewed mapping"): + generator._vintage_authority(fact) + + +def test_calibration_keeps_every_family_b1_required(): + assert REQUIRED_FAMILIES <= {row["family"] for row in _rows()} + + +def test_belgian_selectors_never_name_german_or_french_rows(): + for reference_set in SETS: + for row in _rows(reference_set): + for selector in _selectors(row): + assert _belgian_selector(selector), (row["name"], selector) + assert not str(selector.get("geography_id")).startswith(("DE", "FR")) + mutant = copy.deepcopy(_rows("holdout")[0]["ledger_selector"]) + mutant["geography_id"] = "DE" + assert not _belgian_selector(mutant) + for level, area in (("country", "DE"), ("country", "FR"), ("nuts1", "FR1")): + fact = { + "aggregate_fact_key": "ledger.aggregate_fact.v2:synthetic", + "geography": {"level": level, "id": area}, + } + with pytest.raises(ValueError, match="Belgian selectors read Belgian facts"): + generator._belgian(fact) + + +def test_every_rolled_row_uses_one_declared_fpb_row_at_its_periods(): + rolled = [ + row + for reference_set in SETS + for row in _rows(reference_set) + if row.get("value_operation") == "rolled_forward_by_ratio" + ] + assert len(rolled) == 22 + 7 + for row in rolled: + assert _pair_violations(row) == [], row["name"] + assert row["period"] == 2026 + assert row["period_match_policy"] == "latest_not_after" + assert row["assertion_policy"] == "allow_source_projection" + for row in _rows(): + if row.get("value_operation", "identity") == "identity": + assert row["period"] == row["ledger_selector"]["period_value"] + assert row["period_match_policy"] == "exact" + pairs = {row["metadata"]["ageing_pair"] for row in rolled} + assert pairs == set(generator.AGEING_PAIRS) + + +_FPB_ROWS = sorted({pair["row"] for pair in generator.AGEING_PAIRS.values()}) + + +@settings(max_examples=100, deadline=None, suppress_health_check=[HealthCheck.too_slow]) +@given( + index=st.integers(min_value=0, max_value=30), + other_row=st.sampled_from( + [*_FPB_ROWS, "labour_market.levels.working_age_population"] + ), + other_year=st.sampled_from([2022, 2023, 2024, 2025, 2026, 2027]), + field=st.sampled_from(["row", "numerator_year", "denominator_year", "concept"]), +) +def test_ratio_pairs_share_one_row_and_their_declared_periods( + index, other_row, other_year, field +): + rolled = _rolled_rows() + row = json.loads(rolled[index % len(rolled)]) + assert _pair_violations(row) == [] + numerator, denominator = row["value_operands"][1:] + changed = False + if field == "row": + current = _year_free(denominator["record_set_id"]) + target = f"{generator.FPB}cy*.{other_row}" + changed = current != target + denominator["record_set_id"] = target.replace( + "cy*", f"cy{denominator['period_value']}" + ) + elif field == "numerator_year": + changed = other_year != numerator["period_value"] + numerator["period_value"] = other_year + numerator["record_set_id"] = re.sub( + r"\.cy\d{4}\.", f".cy{other_year}.", numerator["record_set_id"] + ) + elif field == "denominator_year": + changed = other_year != denominator["period_value"] + denominator["period_value"] = other_year + denominator["record_set_id"] = re.sub( + r"\.cy\d{4}\.", f".cy{other_year}.", denominator["record_set_id"] + ) + else: + changed = True + denominator["source_concept"] += ".other" + assert bool(_pair_violations(row)) == changed + + +@functools.cache +def _hierarchy(reference_set): + return json.dumps(_document(SETS[reference_set])["hierarchy"]) + + +def _synthetic_fact(selector, value, member=None): + """A minimal fact matching one selector; a resolver probe, not a Belgian value.""" + + dimensions = dict(selector.get("dimension_values", {})) + key = selector.get("aggregate_fact_key") + if member is not None: + dimensions[member[0]] = member[1] + key = f"synthetic:{selector['record_set_id']}:{member[1]}" + return { + "aggregate_fact_key": key, + "observed_measure": { + name: selector[name] + for name in ("source_name", "source_measure_id", "source_concept") + } + | {"unit": "count"}, + "entity": {"name": selector["entity_name"]}, + "period": {"type": selector["period_type"], "value": selector["period_value"]}, + "geography": { + "level": selector["geography_level"], + "id": selector["geography_id"], + "vintage": selector["geography_vintage"], + "name": "Belgium", + }, + "layout": {"record_set_id": selector["record_set_id"]}, + "dimensions": dimensions, + "dimension_labels": {name: name for name in dimensions}, + "dimension_value_labels": { + name: {str(item): str(item)} for name, item in dimensions.items() + }, + "assertion": selector["assertion"], + "value": value, + "aggregation": {"method": "sum"}, + "label": "Synthetic resolver probe", + } + + +def _synthetic_roll(row, draw): + """Facts for one rolled row and the independently computed exact target.""" + + selector = row["ledger_selector"] + numerator_selector, denominator_selector = ( + {key: value for key, value in operand.items() if key != "role"} + for operand in row["value_operands"][1:] + ) + amount = st.integers(min_value=1, max_value=10**12) + denominator = draw(amount) + # The shared operation refuses ratios outside (0.5, 2]: stay inside. + numerator = draw( + st.integers( + min_value=denominator * 6 // 10 + 1, max_value=denominator * 19 // 10 + ) + ) + rosters = [ + (key, value) + for key, value in selector.get("dimension_values", {}).items() + if isinstance(value, list) + ] + facts = [] + if rosters: + dimension, members = rosters[0] + bases = [draw(amount) for _ in members] + facts += [ + _synthetic_fact(selector, value, (dimension, member)) + for value, member in zip(bases, members, strict=True) + ] + elif selector["aggregate_fact_key"] == denominator_selector["aggregate_fact_key"]: + bases = [denominator] + else: + bases = [draw(amount)] + facts.append(_synthetic_fact(selector, bases[0])) + facts.append(_synthetic_fact(numerator_selector, numerator)) + facts.append(_synthetic_fact(denominator_selector, denominator)) + return facts, Fraction(sum(bases)) * Fraction(numerator, denominator) + + +@settings(max_examples=60, deadline=None, suppress_health_check=[HealthCheck.too_slow]) +@given(index=st.integers(min_value=0, max_value=60), data=st.data()) +def test_shared_compiler_rolls_each_committed_row_as_declared(index, data): + """Differential: the shared resolver against exact base * num / den, in CI.""" + + rolled = _rolled_rows() + row = _executable(json.loads(rolled[index % len(rolled)])) + facts, expected = _synthetic_roll(row, data.draw) + (reference,) = _parsed( + [row], json.loads(_hierarchy(row["metadata"]["reference_set"])) + ) + (spec,) = compile_ledger_target_references(facts, [reference], country="be").specs + assert spec.value == pytest.approx(float(expected), rel=1e-12) + + +@pytest.mark.parametrize( + "name", + ["statbel_a1_standin_declarations__50k_75k", "statbel_b4_declarations__joint"], +) +def test_a_missing_roster_member_refuses_compilation(name): + row = _executable(next(row for row in _rows() if row["name"] == name)) + facts, _ = _synthetic_roll(row, lambda strategy: 1000) + (reference,) = _parsed([row], _document(SETS["calibration"])["hierarchy"]) + with pytest.raises(ValueError, match="base"): + compile_ledger_target_references(facts[1:], [reference], country="be") + + +def test_rows_equal_to_the_fpb_projection_declare_it(): + flagged = set() + for reference_set in SETS: + for row in _rows(reference_set): + if row.get("value_operation") != "rolled_forward_by_ratio": + continue + own = row["ledger_selector"].get("aggregate_fact_key") == row[ + "value_operands" + ][2].get("aggregate_fact_key") + declared = "ageing_target_equals" in row["metadata"] + assert declared == (own or row["name"] in BASES_EQUAL_TO_DENOMINATOR) + flagged |= {row["name"]} if declared else set() + assert len(flagged) == 7 + + +def test_band_edges_strictly_increase_and_partition_the_positive_range(): + document = _document("reference_intervals.json") + tables = validate_interval_document(document) + assert list(tables) == [generator.STANDIN_TABLE] + table = tables[generator.STANDIN_TABLE] + assert table.entity == "tax_unit" + assert table.closure == "left" and table.nil_present + assert table.cuts[0] == 0 + assert all(a < b for a, b in zip(table.cuts, table.cuts[1:], strict=False)) + bands = [band for band in document["tables"][0]["bands"] if band["kind"] != "nil"] + assert [band["id"] for band in bands] == [ + band for band, _, _ in generator.STANDIN_BANDS + ] + assert [band["upper_cent"] for band in bands] == [ + None if upper is None else upper * 100 + for _, _, upper in generator.STANDIN_BANDS + ] + inventory = _document("reference_inventory.json")["standin_bands"] + members = [code for band in inventory for code in band["a1_classes"]] + assert members == [code for _, _, code in A1_CLASSES] + assert len(inventory) == 8 + filters = { + row["filter"] + for row in _rows() + if row["metadata"].get("interval_table_id") == generator.STANDIN_TABLE + } + assert filters == {band["indicator"] for band in bands} + + +@settings(max_examples=200, deadline=None, suppress_health_check=[HealthCheck.too_slow]) +@given(st.integers(min_value=-(10**9), max_value=10**9)) +@example(0) +@example(1) +@example(999_999) +@example(1_000_000) +@example(9_999_999) +@example(10_000_000) +def test_every_amount_lands_in_exactly_one_band(cents): + document = _document("reference_intervals.json") + table = interval_table(document["tables"][0]) + (position,) = classify_records(table, [cents], ["included"]) + floored = max(0, cents) + if floored == 0: + assert position == table.nil_index + return + assert position != BELOW_FIRST_CUT + band = document["tables"][0]["bands"][position] + upper = band["upper_cent"] + lower = table.cuts[table.positive_indices.index(position)] + assert lower <= floored and (upper is None or floored < upper) + + +_EDGES = [lower for lower, _, _ in A1_CLASSES] + + +@settings(max_examples=200, deadline=None, suppress_health_check=[HealthCheck.too_slow]) +@given(st.sets(st.sampled_from(_EDGES[1:]), max_size=20)) +def test_any_band_list_on_class_edges_partitions_a1(cuts): + edges = [0, *sorted(cuts)] + bands = tuple( + (f"b{index}", lower, upper) + for index, (lower, upper) in enumerate( + zip(edges, [*edges[1:], None], strict=True) + ) + ) + with mock.patch.object(generator, "STANDIN_BANDS", bands): + members = generator._band_members(A1_CLASSES) + assert [code for band in members.values() for code in band] == [ + code for _, _, code in A1_CLASSES + ] + for (band, lower, upper), codes in zip(bands, members.values(), strict=True): + spans = [(start, end) for start, end, code in A1_CLASSES if code in codes] + assert spans[0][0] == lower and spans[-1][1] == upper, band + + +@pytest.mark.parametrize( + "bands", + [ + (("a", 0, 10_500), ("b", 10_500, None)), + (("a", 0, 99_999), ("b", 99_999, None)), + # The upper is off an edge, yet the next band restarts on one. + (("a", 0, 10_500), ("b", 10_000, None)), + ], +) +def test_band_edges_off_class_edges_refuse(bands): + with mock.patch.object(generator, "STANDIN_BANDS", bands): + with pytest.raises(ValueError, match="class edge|partition"): + generator._band_members(A1_CLASSES) + + +def test_ageing_factors_are_g8r2_diagnostics_whose_periods_match_declarations(): + context = _document("reference_aging.json") + feed = chronicle_feed_identity(_document("chronicle_feed.json")) + assert context["feed_identity"] == feed + selected = validate_factor_context(context) + assert set(selected) == set(generator.RSZ_FACTORS) + for factor_id, entry in selected.items(): + declaration, receipt = entry["declaration"], entry["receipt"] + assert declaration["purpose"] == "diagnostic" + assert declaration["feed_identity"] == feed + source_year, expected = generator.RSZ_FACTORS[factor_id] + assert declaration["source_period"] == source_year + assert declaration["target_period"] == 2025 + for schedule, period in ( + ("source_schedule", declaration["source_period"]), + ("target_schedule", declaration["target_period"]), + ): + (slot,) = declaration[schedule] + assert slot["selector"]["period_value"] == period + assert slot["validation"]["period_coverage"] == { + "start_date": f"{period}-01-01", + "end_date": f"{period}-12-31", + } + assert receipt["source_period"] == declaration["source_period"] + assert receipt["target_period"] == declaration["target_period"] + assert entry["operational_factor"] == { + "numerator": expected, + "denominator": 1_000_000, + } + + +@settings(max_examples=100, deadline=None, suppress_health_check=[HealthCheck.too_slow]) +@given( + index=st.integers(min_value=0, max_value=40), + shift=st.integers(min_value=-3, max_value=3).filter(bool), + where=st.sampled_from(["source_period", "target_period", "period"]), +) +def test_each_rolled_period_matches_its_declaration(index, shift, where): + rolled = _rolled_rows() + row = json.loads(rolled[index % len(rolled)]) + if where == "period": + row["period"] += shift + else: + row["metadata"][where] = str(int(row["metadata"][where]) + shift) + assert "numerator_period" in _pair_violations(row) or ( + "denominator_period" in _pair_violations(row) + ) + + +def test_every_money_factor_lives_in_the_reference_profile_context(): + assert _money_context_violations(_SPEC) == [] + assert ( + _document("reference_profiles.json")["factor_context_resource"] + == "reference_aging.json" + ) + + +_MONEY_FACTOR = {"factors": [{"declaration": {"purpose": "money_normalization_input"}}]} + + +@pytest.mark.parametrize( + ("files", "expected"), + [ + # A money node on the reference context passes, in either resource. + ( + { + "reference_aging.json": _MONEY_FACTOR, + "transport_graph.json": { + "nodes": [ + { + "kernel": "money.normalize@1", + "params": { + "factor_context": {"resource": "reference_aging.json"} + }, + } + ] + }, + }, + [], + ), + ( + { + "entitlement_graph.json": { + "steps": [ + { + "kernel": "money.normalize@1", + "params": { + "factor_context": {"resource": "reference_aging"} + }, + } + ] + } + }, + [], + ), + # A second context, with or without a node that selects it. + ({"money_factor_context.json": _MONEY_FACTOR}, ["stray_factor"]), + ( + { + "money_factor_context.json": _MONEY_FACTOR, + "transport_graph.json": { + "nodes": [ + { + "kernel": "money.normalize@1", + "params": { + "factor_context": { + "resource": "money_factor_context.json" + } + }, + } + ] + }, + }, + ["stray_factor", "money_context"], + ), + ( + { + "entitlement_graph.json": { + "steps": [ + { + "kernel": "money.normalize@1", + "params": {"factor_context": {"resource": "other.json"}}, + } + ] + } + }, + ["money_context"], + ), + ( + {"transport_graph.json": {"nodes": [{"kernel": "money.normalize@1"}]}}, + ["money_context"], + ), + ], +) +def test_money_context_mutants(tmp_path, files, expected): + (tmp_path / "reference_profiles.json").write_text( + (_SPEC / "reference_profiles.json").read_text() + ) + (tmp_path / "reference_aging.json").write_text( + (_SPEC / "reference_aging.json").read_text() + ) + for name, document in files.items(): + (tmp_path / name).write_text(json.dumps(document)) + assert sorted(kind for kind, _ in _money_context_violations(tmp_path)) == sorted( + expected + ) + + +def test_profiles_name_the_factor_context_and_keep_ageing_deferred(): + profiles = _document("reference_profiles.json") + assert profiles["factor_context_resource"] == "reference_aging.json" + assert profiles["interval_resource"] == "reference_intervals.json" + raw = _document("target_references.json") + effective, intervals, receipt = resolve_reference_profiles( + raw, + profiles, + {}, + _document("reference_intervals.json"), + factor_context=_document("reference_aging.json"), + ) + assert receipt["deferred_dimensions"] == ["aging_index"] + assert receipt["transformed_names"] == [] + assert intervals == _document("reference_intervals.json") + assert set(effective) == set(raw) & REFERENCE_DOCUMENT_KEYS + assert effective["target_references"] == raw["target_references"] + assert ( + validate_reference_resolution( + effective, + receipt, + references_sha256=reference_document_sha256(effective), + interval_document=intervals, + ) + == receipt + ) + references = parse_reference_document(effective, country="be") + a1 = [ + reference + for reference in references + if reference.metadata.get("interval_table_id") == generator.STANDIN_TABLE + ] + assert len(a1) == 16 + for reference in a1: + assert json.loads(reference.metadata["reference_prerequisites"]) == [ + "reference_profile:aging_index", + f"measurement:{generator.STANDIN_MEASUREMENT}", + ] + + +def test_only_demography_and_commune_support_are_active(): + active = { + reference_set: { + row["metadata"]["contract_target_id"] + for row in _rows(reference_set) + if row["metadata"]["activation_status"] == "active" + } + for reference_set in SETS + } + assert active == { + "calibration": {"statbel_population_by_region_sex_age"}, + "precal": {"statbel_population_by_commune"}, + "holdout": set(), + } + + +def test_every_parked_row_refuses_direct_compilation(): + for name in SETS.values(): + document = _document(name) + for reference in _parsed(document["target_references"], document["hierarchy"]): + if reference.metadata["activation_status"] != "active": + with pytest.raises( + ValueError, + match="non-executable placeholder|requires reference profile", + ): + compile_ledger_target_references([], [reference], country="be") + + +def test_belgium_still_refuses_to_activate(): + spec = load_transport_spec(_SPEC) + with pytest.raises(ValueError, match="not activated") as error: + validate_transport_activation(spec) + for missing in ("benefit_unit_rule.json", "axiom_rules_bindings.json"): + assert missing in str(error.value) + assert not (_SPEC / "transport_graph.json").exists() + assert not (_SPEC / "receipt_contract.json").exists() + assert not (_SPEC / "currency_bridge.json").exists() + + +def test_b1_stays_inactive_with_named_failed_checks(): + checks = _document("reference_inventory.json")["b1_checks"] + assert { + key: checks[key]["result"] + for key in ("tax_definition", "income_ranking", "policy_year") + } == {"tax_definition": "fail", "income_ranking": "fail", "policy_year": "fail"} + for key in ("tax_definition", "income_ranking", "policy_year"): + assert checks[key]["missing"] + # Every "passed" statement is backed by an assertion the generator makes. + assert checks["asserted_evidence"] and all(checks["asserted_evidence"].values()) + assert checks["tax_definition"]["evidence"]["b1_deciles_sum_minus_total_eur"] == ( + pytest.approx(0, abs=0.1) + ) + assert checks["tax_definition"]["evidence"][ + "top_percentiles_sum_minus_decile_10_eur" + ] == pytest.approx(0, abs=0.1) + b1 = [row for row in _rows() if row["family"] == "income_tax"] + assert len(b1) == 19 + assert {row["metadata"]["activation_status"] for row in b1} == { + "inactive_pending_b1_checks" + } + assert all(row.get("value_operation", "identity") == "identity" for row in b1) + assert all(row["period"] == 2023 and row["signed"] is True for row in b1) + evidence = checks["tax_definition"]["evidence"] + assert abs(evidence["difference_eur"]) < 0.1 + assert evidence["negative_deciles"] == ["decile_01", "decile_02"] + + +def test_standin_gaps_publish_the_card_shares(): + gaps = _document("reference_inventory.json")["standin_gaps"] + shares = gaps["national"]["component_shares_of_taxable_income"] + assert {key: round(value * 100, 2) for key, value in shares.items()} == { + "professional_income": 98.05, + "immovable_property_income": 1.49, + "capital_and_movable_property_income": 0.55, + "miscellaneous_income": 0.12, + "deductible_expenditures": 0.21, + } + assert round(gaps["national"]["omitted_share_gross"] * 100, 2) == 2.37 + assert gaps["declarations_with_taxable_but_no_professional_income"] == 42007 + assert gaps["zero_income_declarations_outside_a1"] == 523770 + assert [band["band"] for band in gaps["bands"]] == [ + band for band, _, _ in generator.STANDIN_BANDS + ] + for band in [gaps["national"], *gaps["bands"]]: + assert abs(band["identity_residual_eur"]) < 0.05 + assert math.isclose( + sum(band["declarations_iy2023"] for band in gaps["bands"]), + gaps["national"]["declarations_iy2023"], + ) + + +def test_a1_band_counts_and_b4_types_share_one_ageing_pair(): + counts = { + row["metadata"]["ageing_pair"] + for row in _rows() + if row["metadata"]["contract_target_id"] + in { + "statbel_a1_standin_declarations_by_band", + "statbel_b4_declarations_by_type", + } + } + assert counts == {"fpb_t07_total_population"} + identity = _document("reference_inventory.json")["b4_identity"] + assert identity["closes_exactly"] is True + assert identity["joint"] + identity["individual"] == identity["a1_declarations"] + + +def test_jrc_is_deferred_and_august_gaps_are_named(): + for reference_set in SETS: + for row in _rows(reference_set): + for selector in _selectors(row): + assert "jrc" not in selector["source_name"] + exclusions = { + row["id"] for row in _document("reference_inventory.json")["exclusions"] + } + assert {"jrc_euromod_be_statistics", "ris_amount_and_recipients"} <= exclusions + onem = next( + row for row in _rows() if row["name"] == "onem_complete_unemployment_recipients" + ) + assert onem["metadata"]["activation_status"].startswith("requires_ageing_ruling") + + +def test_unemployment_choice_names_the_larger_line(): + choice = _document("reference_inventory.json")["unemployment_series_choice"] + lines = {key: row["eur"] for key, row in choice["lines_2025"].items()} + assert choice["lines_2025"]["chosen"]["label"] == "a. Chômage" + assert choice["lines_2025"]["alternative"]["label"] == "4. Chômage" + assert lines["alternative"] == pytest.approx( + lines["chosen"] + lines["company_supplement"] + lines["career_breaks"], + abs=2e6, + ) + + +def test_inventory_feed_identity_is_the_pin(): + assert _document("reference_inventory.json")["feed_identity"] == _document( + "chronicle_feed.json" + ) + + +@pytest.fixture(scope="module") +def artifact(): + path = os.environ.get("BE_CHRONICLE_ARTIFACT") + if not path: + pytest.skip("BE_CHRONICLE_ARTIFACT is unset; Belgian feed audit unavailable") + return load_ledger_consumer_artifact( + Path(path), feed_pin=_document("chronicle_feed.json"), lexical_floats=True + ) + + +@pytest.fixture(scope="module") +def by_record_set(artifact): + index = {} + for fact in artifact.facts: + index.setdefault(fact.get("layout", {}).get("record_set_id"), []).append(fact) + return index + + +def _matched(selector, by_record_set): + pool = by_record_set.get(selector.get("record_set_id"), []) + return [fact for fact in pool if fact_matches_selector(fact, selector)] + + +def _executable(row): + row = copy.deepcopy(row) + row["metadata"]["activation_status"] = "active" + for key in ("required_reference_profile", "reference_prerequisites"): + row["metadata"].pop(key, None) + return row + + +def test_generation_reproduces_committed_resources_with_exact_feed_identity(artifact): + generated = generator.build_reference_documents(artifact) + assert set(generated) == set(GENERATED) + for filename, document in generated.items(): + assert generator._encode(document) == (_SPEC / filename).read_text(), filename + assert artifact.fact_row_count == _document("chronicle_feed.json")["fact_row_count"] + + +def test_check_mode_passes_and_refuses_a_stale_copy(artifact, tmp_path, monkeypatch): + monkeypatch.setattr( + generator, "load_ledger_consumer_artifact", lambda *args, **kwargs: artifact + ) + monkeypatch.setattr( + "sys.argv", ["generate", "--artifact", "unused", "--check", "--out", str(_SPEC)] + ) + generator.main() + for name in ("chronicle_feed.json", *GENERATED): + (tmp_path / name).write_text((_SPEC / name).read_text()) + stale = _document("holdout_references.json") + stale["description"] += " (edited)" + (tmp_path / "holdout_references.json").write_text(generator._encode(stale)) + monkeypatch.setattr( + "sys.argv", + ["generate", "--artifact", "unused", "--check", "--out", str(tmp_path)], + ) + with pytest.raises(SystemExit, match="Stale generated resource"): + generator.main() + + +def test_every_selector_resolves_to_one_fact_or_its_declared_set( + artifact, by_record_set +): + for name in SETS.values(): + document = _document(name) + for row in document["target_references"]: + base = _matched(row["ledger_selector"], by_record_set) + pins = row["ledger_selector"].get("dimension_values", {}) + rosters = [value for value in pins.values() if isinstance(value, list)] + expected = len(rosters[0]) if rosters else 1 + assert len(base) == expected, row["name"] + for operand in row.get("value_operands", [])[1:]: + selector = {k: v for k, v in operand.items() if k != "role"} + assert len(_matched(selector, by_record_set)) == 1, row["name"] + assert all(generator._belgian(fact) for fact in base) + (reference,) = _parsed([_executable(row)], document["hierarchy"]) + needed = {} + for selector in reference_fact_selectors(reference): + for fact in _matched(selector, by_record_set): + needed[fact["aggregate_fact_key"]] = fact + (spec,) = compile_ledger_target_references( + needed.values(), [reference], country="be" + ).specs + if row.get("value_operation") == "rolled_forward_by_ratio": + assert spec.metadata["ledger_value_base_cells"] == str(expected) + numerator = _matched( + {k: v for k, v in row["value_operands"][1].items() if k != "role"}, + by_record_set, + )[0] + denominator = _matched( + {k: v for k, v in row["value_operands"][2].items() if k != "role"}, + by_record_set, + )[0] + total = math.fsum(float(fact["value"]) for fact in base) + assert spec.value == pytest.approx( + total * float(numerator["value"]) / float(denominator["value"]), + rel=1e-12, + ) + else: + assert spec.value == float(base[0]["value"]) + + +def test_german_and_french_rows_are_refused_and_never_selected(artifact, by_record_set): + foreign = [ + fact + for fact in artifact.facts + if fact["geography"]["level"] == "country" + and fact["geography"]["id"] in {"DE", "FR"} + ] + assert len(foreign) == 72 + for fact in foreign: + with pytest.raises(ValueError, match="Belgian selectors read Belgian facts"): + generator._selector(fact) + keys = {fact["aggregate_fact_key"] for fact in foreign} + for reference_set in SETS: + for row in _rows(reference_set): + for selector in _selectors(row): + assert ( + not { + fact["aggregate_fact_key"] + for fact in _matched(selector, by_record_set) + } + & keys + ) + + +def test_resolved_sets_share_no_fact_and_holdouts_read_none(artifact, by_record_set): + reads = {} + for reference_set in SETS: + for row in _rows(reference_set): + keys = { + fact["aggregate_fact_key"] + for selector in _selectors(row) + for fact in _matched(selector, by_record_set) + } + for key in keys: + reads.setdefault(key, set()).add(reference_set) + assert not [ + key for key, sets in reads.items() if "holdout" in sets and len(sets) > 1 + ] + bases = {} + for reference_set in SETS: + for row in _rows(reference_set): + for fact in _matched(row["ledger_selector"], by_record_set): + bases.setdefault(fact["aggregate_fact_key"], set()).add(reference_set) + assert all(len(sets) == 1 for sets in bases.values()) + + +def test_resolved_reads_list_what_each_selector_resolves_to(artifact, by_record_set): + listed = {entry["name"]: entry for entry in _reads()} + for reference_set in SETS: + for row in _rows(reference_set): + entry = listed[row["name"]] + selectors = list(_selectors(row)) + base = _matched(selectors[0], by_record_set) + operands = [ + fact + for selector in selectors[1:] + for fact in _matched(selector, by_record_set) + ] + assert _keys(entry["base_facts"]) == sorted( + {fact["aggregate_fact_key"] for fact in base} + ) + assert _keys(entry["operand_facts"]) == sorted( + {fact["aggregate_fact_key"] for fact in operands} + ) + assert _keys(entry["semantic_facts"]) == sorted( + {fact["semantic_fact_key"] for fact in [*base, *operands]} + ) + + +def test_a_holdout_on_b1s_income_total_collides_with_a1s_bands(artifact): + """B.1 and A.1 print one semantic total, which the bands add up to.""" + + inventory = generator.Inventory(artifact.facts) + total = inventory.one( + spec=generator.B1_VALUES, + measure="taxable_income_eur", + geography="BE", + dimensions={"tax_return.rank_group": "all"}, + ) + documents = copy.deepcopy(_documents()) + row = documents["holdout"]["target_references"][0] + row["ledger_selector"] = generator._selector(total) + del row["value_operands"] + named = {name: documents[key] for key, name in SETS.items()} + context = _document("reference_aging.json") + reads = generator.resolved_reads( + inventory, {**named, "reference_aging.json": context} + ) + assert ("holdout_semantic", total["semantic_fact_key"]) in _read_violations( + documents, context, reads + ) + + +def test_projection_flags_match_the_feed(artifact, by_record_set): + for reference_set in SETS: + for row in _rows(reference_set): + if row.get("value_operation") != "rolled_forward_by_ratio": + continue + selectors = list(_selectors(row)) + base = _matched(selectors[0], by_record_set) + (denominator,) = _matched(selectors[2], by_record_set) + equal = len(base) == 1 and generator._value(base[0]) == generator._value( + denominator + ) + assert ("ageing_target_equals" in row["metadata"]) == equal, row["name"] + + +def test_a_changed_b1_fact_refuses_generation(artifact): + facts = list(artifact.facts) + index = next( + position + for position, fact in enumerate(facts) + if fact["layout"].get("record_set_spec_id") + == "spf_finances.pit.tax_before_withholding.country.v1" + ) + facts[index] = {**facts[index], "value": 1.0} + with pytest.raises(ValueError, match="Reviewed B.1 evidence changed"): + generator._b1_checks(generator.Inventory(facts)) + + +def test_shared_series_check_accepts_a_mismatched_fpb_row_that_ours_refuses( + artifact, by_record_set +): + """Documents a shared limitation: every T07 row shares one series key.""" + + row = copy.deepcopy( + next(row for row in _rows() if row["name"] == "statbel_b4_declarations__joint") + ) + working_age = next( + fact + for fact in by_record_set[ + f"{generator.FPB}cy2023.labour_market.levels.working_age_population" + ] + ) + row["value_operands"][2] = { + "role": "denominator", + **generator._selector(working_age), + "assertion": "observation", + } + assert "row" in _pair_violations(row) + (reference,) = _parsed( + [_executable(row)], _document("target_references.json")["hierarchy"] + ) + needed = { + fact["aggregate_fact_key"]: fact + for selector in reference_fact_selectors(reference) + for fact in _matched(selector, by_record_set) + } + compile_ledger_target_references(needed.values(), [reference], country="be") + + +def test_factor_receipts_replay_against_the_feed(artifact): + context = _document("reference_aging.json") + for entry in context["factors"]: + replay_reference_factor( + entry["declaration"], + artifact.facts, + context["feed_identity"], + entry["operational_factor"], + entry["receipt"], + ) + + +@pytest.mark.parametrize( + ("field", "altered"), + [ + ("facts_sha256", "0" * 64), + ("manifest_sha256", "0" * 64), + ("fact_row_count", 87111), + ("consumer_fact_schema_versions", ["wrong"]), + ("consumer_fact_schema_sha256", "0" * 64), + ("artifact_schema_version", "wrong"), + ], +) +def test_changed_feed_identity_refuses_authoring(artifact, field, altered, tmp_path): + pin = _document("chronicle_feed.json") + pin[field] = altered + (tmp_path / "chronicle_feed.json").write_text(json.dumps(pin)) + with pytest.raises(ChronicleFeedPinMismatchError): + generator.build_reference_documents(artifact, package_dir=tmp_path) + + +@pytest.mark.parametrize( + ("table", "key", "period"), + [ + ("AGEING_PAIRS", "fpb_t11_total_resources", 2026), + ("AGEING_PAIRS", "fpb_t07_total_population", 2023), + ("RSZ_OPERANDS", None, 2025), + ], +) +def test_a_changed_reviewed_operand_refuses_generation(artifact, table, key, period): + if table == "AGEING_PAIRS": + pairs = copy.deepcopy(generator.AGEING_PAIRS) + pairs[key]["operands"][period] = str( + Fraction(pairs[key]["operands"][period]) + 1 + ) + patch = mock.patch.object(generator, "AGEING_PAIRS", pairs) + message = "Reviewed FPB operand" + else: + operands = {**generator.RSZ_OPERANDS, period: "1"} + patch = mock.patch.object(generator, "RSZ_OPERANDS", operands) + message = "Reviewed RSZ operand" + with patch, pytest.raises(ValueError, match=message): + generator.build_reference_documents(artifact) 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 079c9da968..63c919ddf0 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 @@ -17,6 +17,7 @@ from pathlib import Path import pytest +import yaml from microcosm.build import ( CountryResourceRow, @@ -77,6 +78,18 @@ def _nested_mapping_keys(value: object) -> set[str]: return set() +# B1's schema-2 target document, kept so the schema-2 target-profile contract +# (typed vintage aliases, exact periods) stays exercised on Belgian geography +# after B3 moved the packaged references to a schema-1 profile. +BE_SCHEMA2_TARGETS = _TEST_PATHS.tests / "fixtures/be_schema2_target_references.json" + + +def _be_package_with_schema2_profile(package_dir: Path) -> Path: + shutil.copytree(COUNTRY_PACKAGE_ROOT / "be", package_dir) + shutil.copyfile(BE_SCHEMA2_TARGETS, package_dir / "target_references.json") + return package_dir + + def _armenia_scalar_ledger_fact( reference, ordinal: int, @@ -510,7 +523,14 @@ def test_loads_with_every_declared_resource(self, spec) -> None: "spec/vintages.yaml", "source_stages.json", "geography_spine.json", + "chronicle_feed.json", "target_references.json", + "precal_references.json", + "holdout_references.json", + "reference_aging.json", + "reference_intervals.json", + "reference_inventory.json", + "reference_profiles.json", "gates.json", "release_contract.json", } @@ -545,7 +565,7 @@ def test_source_stage_pins_the_us_donor_support_contract(self, spec) -> None: assert [(row["kind"], row["role"]) for row in stage.artifacts[1:]] == [ ( "public_aggregate_reference", - "destination_chronicle_consumer_artifact_unpinned", + "destination_chronicle_consumer_artifact", ), ("public_parameter_reference", "rulespec_be_tree_unpinned"), ] @@ -607,160 +627,201 @@ def test_observed_region_geography_compatibility_still_requires_preservation( load_country_spec(package_dir) def test_targets_arrive_by_reference_with_no_values(self, spec) -> None: - names = {reference.name for reference in spec.target_references} - assert { - "statbel_population_by_age_sex_region", - "statbel_fiscal_income_by_commune", - "spf_finances_pit_total", - "onss_employee_contribution_total", - "onem_unemployment_caseload", - "nbb_household_disposable_income", - } <= names - by_name = {reference.name: reference for reference in spec.target_references} - commune = by_name["statbel_fiscal_income_by_commune"] - assert commune.metadata["nis_vintage"] == "2025" - assert commune.metadata["geography_vintage"] == "nis_2025" - assert commune.ledger_selector["geography_vintage"] == "nis_2025" - assert commune.metadata["criticality"] == "diagnostic" assert { - by_name[name].metadata["activation_status"] - for name in { - "statbel_population_by_age_sex_region", - "statbel_fiscal_income_by_commune", - } - } == {"requires_harvested_cell_references"} - - payload = json.loads( - (COUNTRY_PACKAGE_ROOT / "be/target_references.json").read_text( - encoding="utf-8" + reference.metadata["contract_target_id"] + for reference in spec.target_references + } == { + "statbel_population_by_region_sex_age", + "statbel_a1_standin_declarations_by_band", + "statbel_a1_standin_taxable_income_by_band", + "statbel_b4_declarations_by_type", + "statbel_b1_enrolled_tax_by_rank_group", + "onss_worker_personal_contributions", + "onem_complete_unemployment_recipients", + "fpb_unemployment_benefit_expenditure", + "fpb_grapa_expenditure", + "fpb_net_mixed_income", + } + for name in ( + "target_references.json", + "precal_references.json", + "holdout_references.json", + "reference_intervals.json", + "reference_profiles.json", + ): + payload = json.loads( + (COUNTRY_PACKAGE_ROOT / "be" / name).read_text(encoding="utf-8") ) - ) - assert FORBIDDEN_TARGET_VALUE_KEYS.isdisjoint( - _nested_mapping_keys(payload["target_references"]) - ) + assert FORBIDDEN_TARGET_VALUE_KEYS.isdisjoint( + _nested_mapping_keys(payload) + ), name def test_target_selectors_declare_the_intended_chronicle_vocabulary( self, spec ) -> None: - references = {reference.name: reference for reference in spec.target_references} + statbel = "statbel_fiscal_income_distribution" + rolled = "rolled_forward_by_ratio" expected = { - "statbel_population_by_age_sex_region": ( + "statbel_population_by_region_sex_age": ( "statbel_population_structure", "people", "calendar_year", - 2023, + 2026, "nuts1", - "nuts1_2025", + "identity", ), - "statbel_fiscal_income_by_commune": ( - "statbel_fiscal_income", - "taxable_income", + "statbel_a1_standin_declarations_by_band": ( + statbel, + "declarations", "tax_year", - 2022, - "commune", - "nis_2025", + 2023, + "country", + rolled, ), - "spf_finances_pit_total": ( - "spf_finances_pit", - "tax_before_withholding", + "statbel_a1_standin_taxable_income_by_band": ( + statbel, + "taxable_income_eur", "tax_year", - 2022, + 2023, + "country", + rolled, + ), + "statbel_b4_declarations_by_type": ( + statbel, + "declarations", + "tax_year", + 2023, + "country", + rolled, + ), + "statbel_b1_enrolled_tax_by_rank_group": ( + statbel, + "total_tax_eur", + "tax_year", + 2023, "country", - None, + "identity", ), - "onss_employee_contribution_total": ( + "onss_worker_personal_contributions": ( "onss_contributions", "worker_article_17_uncapped_component_contribution", "calendar_year", - 2022, + 2024, "country", - None, + rolled, ), - "onem_unemployment_caseload": ( + "onem_complete_unemployment_recipients": ( "onem_rva_unemployment", "receives_unemployment_benefit", "calendar_year", - 2022, + 2024, "country", - None, - ), - "nbb_household_disposable_income": ( - "nbb_national_accounts", - "household_disposable_income", - "calendar_year", - 2022, - "country", - None, + "identity", ), + **{ + contract: ( + "fpb_economic_outlook", + "amount_meur", + "calendar_year", + 2025, + "country", + rolled, + ) + for contract in ( + "fpb_unemployment_benefit_expenditure", + "fpb_grapa_expenditure", + "fpb_net_mixed_income", + ) + }, } - - for name, ( - source_name, - source_measure_id, - period_type, - period, - geography_level, - geography_vintage, - ) in expected.items(): - reference = references[name] - assert reference.ledger_selector["source_name"] == source_name - assert reference.ledger_selector["source_measure_id"] == source_measure_id - assert reference.ledger_selector["period_type"] == period_type - assert reference.period == period - assert reference.period_match_policy == "exact" - assert reference.assertion_policy == "allow_source_projection" - assert reference.ledger_selector["geography_level"] == geography_level - assert ( - reference.ledger_selector.get("geography_vintage") == geography_vintage + for reference in spec.target_references: + ( + source_name, + source_measure_id, + period_type, + source_period, + geography_level, + operation, + ) = expected[reference.metadata["contract_target_id"]] + selector = reference.ledger_selector + assert selector["source_name"] == source_name + assert selector["source_measure_id"] == source_measure_id + assert selector["period_type"] == period_type + assert selector["period_value"] == source_period + assert selector["geography_level"] == geography_level + assert reference.value_operation == operation + if operation == rolled: + assert reference.period == 2026 + assert reference.period_match_policy == "latest_not_after" + assert reference.assertion_policy == "allow_source_projection" + else: + # Identity rows never relabel a period: the 2026 cells are + # 2026 observations, and parked rows keep source periods. + assert reference.period == source_period + assert reference.period_match_policy == "exact" + assert reference.assertion_policy == "observed_only" + + def test_target_profile_is_schema_one_with_schema_two_hierarchies( + self, spec + ) -> None: + # A schema-2 target profile requires exact period matching, which + # refuses rolled_forward_by_ratio; NZ uses the same schema-1 profile. + assert dict(spec.target_profile) == { + "schema_version": 1, + "hierarchy_reconciliations": (), + } + payload = json.loads( + (COUNTRY_PACKAGE_ROOT / "be/target_references.json").read_text( + encoding="utf-8" ) - - def test_target_profile_declares_tiers_and_income_basis(self, spec) -> None: - profile = spec.target_profile - assert profile["schema_version"] == 2 - assert tuple(profile["required_families"]) == ( - "demography", - "fiscal_income", - "income_tax", - "social_security", - "caseloads", - ) - tiers = profile["criticality_tiers"] - assert tiers["core_fiscal_release"]["relative_tolerance"] == 0.05 - assert tiers["caseload_release"]["relative_tolerance"] == 0.15 - assert tiers["validation_only"]["relative_tolerance"] is None - - income_basis = profile["basis_periods"]["assessment_income_year_2022"] - assert income_basis["period"] == 2022 - assert income_basis["fact_period_type"] == "tax_year" - assert "survey_year" not in income_basis - assert "income_reference_offset_years" not in income_basis - assert income_basis["mismatch_policy"] == "requires_source_projection" - - references = {reference.name: reference for reference in spec.target_references} - assert ( - references["nbb_household_disposable_income"].metadata["target_role"] - == "validation" ) + assert payload["schema_version"] == 2 + assert set(payload["hierarchy"]) == { + "providers", + "categories", + "target_labels", + } + tolerances = { + reference.family: reference.metadata["fit_tolerance"] + for reference in spec.target_references + } + assert tolerances.pop("demography") == "0.02" + assert set(tolerances.values()) == {"0.05"} assert { - reference.family - for reference in references.values() - if reference.metadata["target_role"] == "calibration" - } >= set(profile["required_families"]) + reference.metadata["target_role"] for reference in spec.target_references + } == {"calibration"} + assert { + reference.metadata["method_card_status"] + for reference in spec.target_references + } == {"proposed_pending_d1902"} - def test_target_profile_tiers_and_roles_are_declaration_only(self, spec) -> None: + def test_target_tolerances_and_roles_are_declaration_only(self, spec) -> None: assert all(reference.tolerance is None for reference in spec.target_references) description = json.loads( (COUNTRY_PACKAGE_ROOT / "be/target_references.json").read_text( encoding="utf-8" ) )["description"] - assert "validated declaration metadata only" in description - assert "does not yet wire them into runtime calibration" in description - assert "current Chronicle Belgian catalog does not satisfy" in description - assert "#264" in description + assert "Selectors only" in description + assert "proposed pending d1902" in description + assert "Belgium stays inactive" in description assert "Declaration-only intended Belgian gate posture" in spec.gates.policy assert "not implemented here" in spec.gates.policy + def test_parked_references_refuse_direct_compilation(self, spec) -> None: + parked = [ + reference + for reference in spec.target_references + if reference.metadata["activation_status"] != "active" + ] + assert len(parked) == 42 + for reference in parked: + with pytest.raises( + ValueError, + match="non-executable placeholder|requires reference profile", + ): + compile_ledger_target_references([], [reference], country="be") + @pytest.mark.parametrize( ("reference_name", "aliases"), [ @@ -774,12 +835,13 @@ def test_target_profile_tiers_and_roles_are_declaration_only(self, spec) -> None ), ], ) - def test_subnational_targets_accept_only_declared_typed_vintage_aliases( + def test_schema2_subnational_targets_accept_only_declared_typed_vintage_aliases( self, tmp_path, reference_name, aliases ) -> None: for index, alias in enumerate(aliases): - package_dir = tmp_path / f"case-{index}" / "be" - shutil.copytree(COUNTRY_PACKAGE_ROOT / "be", package_dir) + package_dir = _be_package_with_schema2_profile( + tmp_path / f"case-{index}" / "be" + ) target_path = package_dir / "target_references.json" payload = json.loads(target_path.read_text(encoding="utf-8")) reference = next( @@ -804,11 +866,10 @@ def test_subnational_targets_accept_only_declared_typed_vintage_aliases( ("statbel_fiscal_income_by_commune", "nis_2024"), ], ) - def test_subnational_targets_refuse_vintages_outside_typed_registry( + def test_schema2_subnational_targets_refuse_vintages_outside_typed_registry( self, tmp_path, reference_name, invalid_vintage ) -> None: - package_dir = tmp_path / "be" - shutil.copytree(COUNTRY_PACKAGE_ROOT / "be", package_dir) + package_dir = _be_package_with_schema2_profile(tmp_path / "be") target_path = package_dir / "target_references.json" payload = json.loads(target_path.read_text(encoding="utf-8")) reference = next( @@ -821,11 +882,10 @@ def test_subnational_targets_refuse_vintages_outside_typed_registry( with pytest.raises(ValueError, match="not an exact typed authority alias"): load_country_spec(package_dir) - def test_subnational_target_requires_a_typed_geography_layer( + def test_schema2_subnational_target_requires_a_typed_geography_layer( self, tmp_path ) -> None: - package_dir = tmp_path / "be" - shutil.copytree(COUNTRY_PACKAGE_ROOT / "be", package_dir) + package_dir = _be_package_with_schema2_profile(tmp_path / "be") target_path = package_dir / "target_references.json" payload = json.loads(target_path.read_text(encoding="utf-8")) reference = payload["target_references"][0] @@ -842,11 +902,12 @@ def test_subnational_target_requires_a_typed_geography_layer( "statbel_fiscal_income_by_commune", ], ) - def test_multicell_be_placeholders_cannot_compile_before_fanout( - self, spec, reference_name + def test_schema2_multicell_placeholders_cannot_compile_before_fanout( + self, tmp_path, reference_name ) -> None: + loaded = load_country_spec(_be_package_with_schema2_profile(tmp_path / "be")) reference = next( - row for row in spec.target_references if row.name == reference_name + row for row in loaded.target_references if row.name == reference_name ) with pytest.raises(ValueError, match="non-executable placeholder"): @@ -2513,8 +2574,7 @@ def test_schema2_period_contract_preserves_valid_aliases_and_opaque_labels( def test_schema2_be_geography_vintage_contract_survives_identifier_resolution( tmp_path, identifier_field, fact_vintage ) -> None: - package_dir = tmp_path / "be" - shutil.copytree(COUNTRY_PACKAGE_ROOT / "be", package_dir) + package_dir = _be_package_with_schema2_profile(tmp_path / "be") target_path = package_dir / "target_references.json" payload = json.loads(target_path.read_text(encoding="utf-8")) raw_reference = next( @@ -2594,12 +2654,20 @@ def units(spec) -> dict[str, str]: shipped = units(load_bundle(country)) changed = units(load_bundle(_package_with_catalog_unit(tmp_path, country, unit))) - - assert unit not in shipped.values() - assert [key for key in shipped if shipped[key] != changed[key]] == [ - key for key in changed if changed[key] == unit - ] - assert list(changed.values()).count(unit) == 1 + # The helper edits the first authored count column; bind the compiled + # change to that source key, so a wrong-row edit cannot pass. + authored = yaml.safe_load( + (COUNTRY_PACKAGE_ROOT / country / "spec/catalogs.yaml").read_text( + encoding="utf-8" + ) + )["columns"] + edited = next(row["key"] for row in authored if row["contract"]["unit"] == "count") + + # Belgium ships euro money columns (B3); New Zealand ships none yet. + assert list(shipped.values()).count(unit) == {"be": 2, "nz": 0}[country] + assert [key for key in shipped if shipped[key] != changed[key]] == [edited] + assert (shipped[edited], changed[edited]) == ("count", unit) + assert list(changed.values()).count(unit) == list(shipped.values()).count(unit) + 1 @pytest.mark.parametrize("unit", ["EUR", "NZD", "euro", "eur_cents"]) diff --git a/packages/microcosm-build/tests/engine_free/shared/test_ledger_artifact.py b/packages/microcosm-build/tests/engine_free/shared/test_ledger_artifact.py index 2c59d73e20..79a1caafb4 100644 --- a/packages/microcosm-build/tests/engine_free/shared/test_ledger_artifact.py +++ b/packages/microcosm-build/tests/engine_free/shared/test_ledger_artifact.py @@ -150,6 +150,7 @@ def test_lexical_float_opt_in_is_limited_to_factor_consumers(): assert opt_ins == { "packages/microcosm-build/src/microcosm/build/transport/money_kernels.py", "packages/microcosm-build/src/microcosm/build/transport/target_kernels.py", + "tools/generate_be_target_references.py", "tools/generate_nz_reference_aging.py", } diff --git a/packages/microcosm-build/tests/engine_free/shared/test_spec_engine_country_bundles.py b/packages/microcosm-build/tests/engine_free/shared/test_spec_engine_country_bundles.py index 5b4c45ee6c..61d8fd4d31 100644 --- a/packages/microcosm-build/tests/engine_free/shared/test_spec_engine_country_bundles.py +++ b/packages/microcosm-build/tests/engine_free/shared/test_spec_engine_country_bundles.py @@ -36,6 +36,8 @@ "person.commune_nis", "person.community_code", "person.donor_country_code", + "person.employment_income", + "person.nonfarm_self_employment_income", "person.person_household_id", "person.person_id", "person.province_nis", @@ -217,8 +219,15 @@ def test_be_generation_zero_views_still_come_from_the_country_spec_seam() -> Non assert not spec.release_contract.licence_restricted assert spec.release_contract.public_artifacts == () assert {row.path for row in spec.resource_rows if row.kind == "legacy_json"} == { + "chronicle_feed.json", "gates.json", "geography_spine.json", + "holdout_references.json", + "precal_references.json", + "reference_aging.json", + "reference_intervals.json", + "reference_inventory.json", + "reference_profiles.json", "release_contract.json", "source_stages.json", "target_references.json", diff --git a/packages/microcosm-build/tests/engine_free/shared/test_transport_reference_selection.py b/packages/microcosm-build/tests/engine_free/shared/test_transport_reference_selection.py index 6f97aa9c78..c7c5312ec4 100644 --- a/packages/microcosm-build/tests/engine_free/shared/test_transport_reference_selection.py +++ b/packages/microcosm-build/tests/engine_free/shared/test_transport_reference_selection.py @@ -577,17 +577,31 @@ def test_legacy_selection_path_changed_mutant_frozen_surface_params_and_keys( reference = next( row for row in document["target_references"] - if row["name"] == "spf_finances_pit_total" + if row["name"] == "statbel_population_by_region_sex_age__be1__male__a0_17" ) document["target_references"] = [reference] + selector = reference["ledger_selector"] fact = toy_fact(reference["name"], 3, entity=reference["entity"]) - fact["period"] = {"type": "tax_year", "value": reference["period"]} - fact["geography"]["id"] = country.upper() + fact["aggregate_fact_key"] = selector["aggregate_fact_key"] + fact["period"] = { + "type": selector["period_type"], + "value": selector["period_value"], + } + fact["geography"].update( + level=selector["geography_level"], + id=selector["geography_id"], + vintage=selector["geography_vintage"], + ) for section in ("source", "observed_measure"): - fact[section]["source_name"] = reference["ledger_selector"]["source_name"] - fact["observed_measure"]["source_measure_id"] = reference["ledger_selector"][ - "source_measure_id" - ] + fact[section]["source_name"] = selector["source_name"] + fact["observed_measure"]["source_measure_id"] = selector["source_measure_id"] + fact["observed_measure"]["source_concept"] = selector["source_concept"] + fact["layout"] = {"record_set_id": selector["record_set_id"]} + fact["dimensions"] = dict(selector["dimension_values"]) + fact["dimension_labels"] = {name: name for name in fact["dimensions"]} + fact["dimension_value_labels"] = { + name: {value: value} for name, value in fact["dimensions"].items() + } spec["resources"]["target_references"] = document facts = write_facts(tmp_path / "facts.jsonl", [fact]) legacy_targets = _legacy( diff --git a/packages/microcosm-build/tests/fixtures/be_schema2_target_references.json b/packages/microcosm-build/tests/fixtures/be_schema2_target_references.json new file mode 100644 index 0000000000..5f4b0408ea --- /dev/null +++ b/packages/microcosm-build/tests/fixtures/be_schema2_target_references.json @@ -0,0 +1,278 @@ +{ + "country": "be", + "description": "Belgian calibration and validation schema groundwork, by reference only. Values and source projections would resolve from Chronicle consumer facts at build time, but the current Chronicle Belgian catalog does not satisfy this full selector and period surface. Criticality tiers, relative tolerances, and target_role are validated declaration metadata only: this package does not yet wire them into runtime calibration objectives or release gates. Multi-cell series remain non-executable until Chronicle fanout produces cell-pinned references. No external-oracle implementation from #264 is included. The file never copies a target value from Chronicle, a survey publication, or a validation oracle. These earlier-period declarations remain inactive groundwork; B3 must replace them with reviewed transport references and explicit ageing to the proposed 2026 policy year. Their source periods are not donor or target-period authorities.", + "allowed_value_operations": [ + "identity" + ], + "target_references": [ + { + "name": "statbel_population_by_age_sex_region", + "ledger_selector": { + "source_name": "statbel_population_structure", + "source_measure_id": "people", + "period_type": "calendar_year", + "geography_level": "nuts1", + "geography_vintage": "nuts1_2025" + }, + "entity": "person", + "measure": "people", + "period": 2023, + "family": "demography", + "assertion_policy": "allow_source_projection", + "period_match_policy": "exact", + "metadata": { + "activation_status": "requires_harvested_cell_references", + "basis_period": "population_reference_2023", + "criticality": "release_blocking", + "criticality_tier": "demography_release", + "geography_vintage": "nuts1_2025", + "publisher": "Statbel", + "series": "Structure of the population: age band by sex by region", + "target_role": "calibration" + }, + "notes": "Non-executable series placeholder for an age-band x sex x NUTS1 count surface. Chronicle must fan this into dimension- and geography-pinned scalar references before compilation. The selector uses the typed NUTS1-2025 authority alias; a differently-vintaged source requires an explicit Chronicle projection/crosswalk. An observation for another year may enter only as a Chronicle source_projection whose fact period is the declared 2023 reference year.", + "category_id": "statbel.demography" + }, + { + "name": "statbel_fiscal_income_by_commune", + "ledger_selector": { + "source_name": "statbel_fiscal_income", + "source_measure_id": "taxable_income", + "period_type": "tax_year", + "geography_level": "commune", + "geography_vintage": "nis_2025" + }, + "entity": "household", + "measure": "belgium_pit_taxable_income", + "period": 2022, + "family": "fiscal_income", + "assertion_policy": "allow_source_projection", + "period_match_policy": "exact", + "metadata": { + "activation_status": "requires_harvested_cell_references", + "basis_period": "assessment_income_year_2022", + "criticality": "diagnostic", + "criticality_tier": "commune_diagnostic", + "geography_vintage": "nis_2025", + "nis_vintage": "2025", + "publisher": "Statbel", + "series": "Fiscal statistics of income: total net taxable income by municipality", + "target_role": "calibration" + }, + "notes": "Non-executable series placeholder for commune fiscal-income cells; Chronicle must fan it into one commune-pinned scalar reference per selected cell before compilation. The eventual open commune series is diagnostic until the synthetic spine demonstrates adequate support. The selector binds the typed nis_2025 alias to the spine's 2025 NIS code set, and another code set must be projected and crosswalked in Chronicle rather than partially joined.", + "category_id": "statbel.fiscal_income" + }, + { + "name": "spf_finances_pit_total", + "ledger_selector": { + "source_name": "spf_finances_pit", + "source_measure_id": "tax_before_withholding", + "period_type": "tax_year", + "geography_level": "country" + }, + "entity": "person", + "measure": "belgium_pit_federal_and_local_tax_before_withholding", + "period": 2022, + "family": "income_tax", + "assertion_policy": "allow_source_projection", + "period_match_policy": "exact", + "metadata": { + "basis_period": "assessment_income_year_2022", + "criticality": "release_blocking", + "criticality_tier": "core_fiscal_release", + "publisher": "SPF Finances / Statbel", + "series": "Personal income tax: assessed total", + "target_role": "calibration" + }, + "notes": "National assessed PIT is compared with the Axiom-computed federal and local liability on the 2022 income-year basis. Assessment-year facts must identify the represented income year in Chronicle; a period mismatch is a projection, never a silent relabeling.", + "category_id": "spf_finances.income_tax" + }, + { + "name": "onss_employee_contribution_total", + "ledger_selector": { + "source_name": "onss_contributions", + "source_measure_id": "worker_article_17_uncapped_component_contribution", + "period_type": "calendar_year", + "geography_level": "country" + }, + "entity": "person", + "measure": "belgium_worker_article_17_uncapped_component_contribution", + "period": 2022, + "family": "social_security", + "assertion_policy": "allow_source_projection", + "period_match_policy": "exact", + "metadata": { + "basis_period": "calendar_year_2022", + "criticality": "release_blocking", + "criticality_tier": "standard_admin_release", + "publisher": "ONSS/RSZ", + "series": "Employee social-security contributions", + "target_role": "calibration" + }, + "notes": "Worker-side contributions on the encoded slice. Employer-side and capped-regime totals can enter as distinct references when both the engine concepts and Ledger selectors exist.", + "category_id": "onss.social_security" + }, + { + "name": "onem_unemployment_caseload", + "ledger_selector": { + "source_name": "onem_rva_unemployment", + "source_measure_id": "receives_unemployment_benefit", + "period_type": "calendar_year", + "geography_level": "country" + }, + "entity": "person", + "measure": "receives_unemployment_benefit", + "period": 2022, + "family": "caseloads", + "assertion_policy": "allow_source_projection", + "period_match_policy": "exact", + "metadata": { + "basis_period": "calendar_year_2022", + "criticality": "release_blocking", + "criticality_tier": "caseload_release", + "publisher": "ONEM/RVA", + "series": "Unemployment benefit recipients", + "target_role": "calibration" + }, + "notes": "The initial caseload family uses the calendar-year recipient count. Pension and regional child-benefit caseload references can join this family when their Chronicle packages and model mappings land.", + "category_id": "onem.caseloads" + }, + { + "name": "nbb_household_disposable_income", + "ledger_selector": { + "source_name": "nbb_national_accounts", + "source_measure_id": "household_disposable_income", + "period_type": "calendar_year", + "geography_level": "country" + }, + "entity": "household", + "measure": "household_disposable_income", + "period": 2022, + "family": "national_accounts", + "assertion_policy": "allow_source_projection", + "period_match_policy": "exact", + "metadata": { + "basis_period": "calendar_year_2022", + "criticality": "diagnostic", + "criticality_tier": "validation_only", + "publisher": "NBB", + "series": "Household-sector disposable income (national accounts)", + "target_role": "validation" + }, + "notes": "Validation-tier level anchor only. The macro-realism gate may use it as a broad band, but neither the exact NBB level nor any survey- or EUROMOD-derived quantity enters the calibration objective.", + "category_id": "nbb.national_accounts" + } + ], + "target_profile": { + "schema_version": 2, + "required_families": [ + "demography", + "fiscal_income", + "income_tax", + "social_security", + "caseloads" + ], + "criticality_tiers": { + "demography_release": { + "criticality": "release_blocking", + "relative_tolerance": 0.02, + "description": "Population-structure cells: plus or minus 2 percent." + }, + "core_fiscal_release": { + "criticality": "release_blocking", + "relative_tolerance": 0.05, + "description": "Core fiscal totals, including assessed PIT: plus or minus 5 percent." + }, + "standard_admin_release": { + "criticality": "release_blocking", + "relative_tolerance": 0.1, + "description": "Administrative contribution totals: plus or minus 10 percent." + }, + "caseload_release": { + "criticality": "release_blocking", + "relative_tolerance": 0.15, + "description": "Administrative caseload totals: plus or minus 15 percent." + }, + "commune_diagnostic": { + "criticality": "diagnostic", + "relative_tolerance": 0.1, + "description": "Commune fiscal-income cells: plus or minus 10 percent, reported but not release-blocking." + }, + "validation_only": { + "criticality": "diagnostic", + "relative_tolerance": null, + "description": "Validation oracle only; no calibration tolerance." + } + }, + "basis_periods": { + "population_reference_2023": { + "period": 2023, + "basis": "reference_date", + "fact_period_type": "calendar_year", + "mismatch_policy": "requires_source_projection", + "description": "Earlier-period population-stock reference, retained as inactive groundwork pending the B3 transport reference rewrite." + }, + "assessment_income_year_2022": { + "period": 2022, + "basis": "income_year", + "fact_period_type": "tax_year", + "mismatch_policy": "requires_source_projection", + "description": "Earlier assessed fiscal reference binds the represented 2022 income year; retained as inactive groundwork pending B3, never silently relabelled to 2026." + }, + "calendar_year_2022": { + "period": 2022, + "basis": "calendar_year", + "fact_period_type": "calendar_year", + "mismatch_policy": "requires_source_projection", + "description": "Calendar-year administrative or national-accounts fact aligned to the 2022 income reference year." + } + }, + "hierarchy_reconciliations": [] + }, + "schema_version": 2, + "hierarchy": { + "providers": { + "statbel": { + "label": "Statbel" + }, + "spf_finances": { + "label": "FPS Finance" + }, + "onss": { + "label": "National Social Security Office" + }, + "onem": { + "label": "National Employment Office" + }, + "nbb": { + "label": "National Bank of Belgium" + } + }, + "categories": { + "statbel.demography": { + "provider_id": "statbel", + "label": "Demography" + }, + "statbel.fiscal_income": { + "provider_id": "statbel", + "label": "Fiscal income" + }, + "spf_finances.income_tax": { + "provider_id": "spf_finances", + "label": "Personal income tax" + }, + "onss.social_security": { + "provider_id": "onss", + "label": "Social security contributions" + }, + "onem.caseloads": { + "provider_id": "onem", + "label": "Benefit caseloads" + }, + "nbb.national_accounts": { + "provider_id": "nbb", + "label": "National accounts" + } + } + } +} diff --git a/packages/microcosm-build/tests/golden/be_country_spec.json b/packages/microcosm-build/tests/golden/be_country_spec.json index 23441d0a8a..96047f95be 100644 --- a/packages/microcosm-build/tests/golden/be_country_spec.json +++ b/packages/microcosm-build/tests/golden/be_country_spec.json @@ -1,6 +1,6 @@ { "country": "be", - "fingerprint": "842b6a2d7d99b60216951ab17486724a7d65866864c32c90ad11085a34c92a5d", + "fingerprint": "e4ac1c718e9dfcc120302584eda17ada620580e808d7a73aabe0fa691efee386", "gate_ids": [ "calibration_per_family_fit", "national_and_nuts1_admin_aggregates", @@ -28,18 +28,25 @@ "staging_repo": "policyengine/populace-be-staging" }, "resource_hashes": { - "country_package.json": "1dff9052dbdcdbceeb077d1212008226cf783aa5d33cbda52d07437aef69d30b", + "chronicle_feed.json": "71f3967cefa12d8ad6c4b955547bfc37e33183ee839b3edf3a43e0cb72559030", + "country_package.json": "d6ec55828ac4fe5b4754b0727c0630f7720ad1aff0624d076c55ba8ed68dcfe1", "gates.json": "85c07f713168058a081b40cf94da6a33035108ba7807e04818486032fb2ad580", "geography_spine.json": "090b83a4fa511e691b8f1486bc4188e4170cf9d4a1239e7418d33d5020ceca50", + "holdout_references.json": "c9d32204b4c6364a95fcab066cbbc8b1b99dd49ef608e72c99009f01c7d1c942", + "precal_references.json": "acd7904779b34bca841686fa6000c5cb57db9a031638e021f59ba348f771de63", + "reference_aging.json": "e1eb7a4e5abc6aad77b822bf91b09ad1de0a22d349ee39b63b8bb787bd036404", + "reference_intervals.json": "5c13dc32257d9d3c9b5cbbd14b79c229bbeb7037671778fdb8b09042693bb562", + "reference_inventory.json": "4f19968e175ed87dc985b6b6a5ec55e384f2d7c807922996950db35006a54444", + "reference_profiles.json": "1f7eb7f7a5bde2484b423e12835c9ef5eb8351599c29d836e35a910897ead52a", "release_contract.json": "916d8cba095d05ee5bc0c3d1b8e165eb1cf22867b91f0adac01533448b394730", - "source_stages.json": "c94df32e544b74e7e6a70ae587345c757d9773035fceafc98660f4ab52d09d2c", - "spec/bundle.yaml": "6ef6efbdc1db9765a8d0acaf86c6f2a507d442f425c8fa4900c8350469935451", - "spec/catalogs.yaml": "4234b7c97481cfe677a4d67098b17cece20a8ac805f0d803ace13b20a8eacdd0", + "source_stages.json": "3d0a362345894dc6ea230ebed7fec7ff99a972879dc60c06001635c1b4a1ec47", + "spec/bundle.yaml": "8ac8b75f61f78f67946828863962c9096f8f98ab12b1a44e40e09b5f6cac67eb", + "spec/catalogs.yaml": "46c4ba309e52e5e8afc0612e4d9f85bab703389c9292fc72fbf44370cfbdea1a", "spec/geography.yaml": "99e29bce429e30e6accc471db7cf66a44ecfbc7bc0fd9f0b9caeaa8785fcb7a2", - "spec/sources.yaml": "3fdd8943b0404784880d9b42db05c832744cc79d57d7c73de660fc6a7b89b63c", + "spec/sources.yaml": "24ea9b8c9aac32175d1c75156af5549a05bb3f155fbb23968235f3ead2cbefda", "spec/spine.yaml": "981be4881954d7696fbabf1bc989f619577b6e5600262f1a9c20915461808d41", "spec/vintages.yaml": "1a10d5aedd24cdb2fc9544c7a0d444df0b06d4b089dcb769bf0a7de9218df696", - "target_references.json": "656f41b7c0005519a14411ca488acdf46cc3b739d58531a9f0802b98ccffd526" + "target_references.json": "38178a5015b520061542c471cec70ac34702deccb29b586f6a59045656789465" }, "resources": [ "spec/bundle.yaml", @@ -48,8 +55,15 @@ "spec/sources.yaml", "spec/spine.yaml", "spec/vintages.yaml", + "chronicle_feed.json", "gates.json", "geography_spine.json", + "holdout_references.json", + "precal_references.json", + "reference_aging.json", + "reference_intervals.json", + "reference_inventory.json", + "reference_profiles.json", "release_contract.json", "source_stages.json", "target_references.json" @@ -58,11 +72,65 @@ "load_populace_us_support_pool" ], "target_reference_names": [ - "statbel_population_by_age_sex_region", - "statbel_fiscal_income_by_commune", - "spf_finances_pit_total", - "onss_employee_contribution_total", - "onem_unemployment_caseload", - "nbb_household_disposable_income" + "statbel_population_by_region_sex_age__be1__male__a0_17", + "statbel_population_by_region_sex_age__be1__male__a18_64", + "statbel_population_by_region_sex_age__be1__male__a65_plus", + "statbel_population_by_region_sex_age__be1__female__a0_17", + "statbel_population_by_region_sex_age__be1__female__a18_64", + "statbel_population_by_region_sex_age__be1__female__a65_plus", + "statbel_population_by_region_sex_age__be2__male__a0_17", + "statbel_population_by_region_sex_age__be2__male__a18_64", + "statbel_population_by_region_sex_age__be2__male__a65_plus", + "statbel_population_by_region_sex_age__be2__female__a0_17", + "statbel_population_by_region_sex_age__be2__female__a18_64", + "statbel_population_by_region_sex_age__be2__female__a65_plus", + "statbel_population_by_region_sex_age__be3__male__a0_17", + "statbel_population_by_region_sex_age__be3__male__a18_64", + "statbel_population_by_region_sex_age__be3__male__a65_plus", + "statbel_population_by_region_sex_age__be3__female__a0_17", + "statbel_population_by_region_sex_age__be3__female__a18_64", + "statbel_population_by_region_sex_age__be3__female__a65_plus", + "statbel_a1_standin_declarations__under_10k", + "statbel_a1_standin_taxable_income__under_10k", + "statbel_a1_standin_declarations__10k_20k", + "statbel_a1_standin_taxable_income__10k_20k", + "statbel_a1_standin_declarations__20k_30k", + "statbel_a1_standin_taxable_income__20k_30k", + "statbel_a1_standin_declarations__30k_40k", + "statbel_a1_standin_taxable_income__30k_40k", + "statbel_a1_standin_declarations__40k_50k", + "statbel_a1_standin_taxable_income__40k_50k", + "statbel_a1_standin_declarations__50k_75k", + "statbel_a1_standin_taxable_income__50k_75k", + "statbel_a1_standin_declarations__75k_100k", + "statbel_a1_standin_taxable_income__75k_100k", + "statbel_a1_standin_declarations__100k_plus", + "statbel_a1_standin_taxable_income__100k_plus", + "statbel_b4_declarations__joint", + "statbel_b4_declarations__individual", + "statbel_b1_enrolled_tax__decile_01", + "statbel_b1_enrolled_tax__decile_02", + "statbel_b1_enrolled_tax__decile_03", + "statbel_b1_enrolled_tax__decile_04", + "statbel_b1_enrolled_tax__decile_05", + "statbel_b1_enrolled_tax__decile_06", + "statbel_b1_enrolled_tax__decile_07", + "statbel_b1_enrolled_tax__decile_08", + "statbel_b1_enrolled_tax__decile_09", + "statbel_b1_enrolled_tax__percentile_091", + "statbel_b1_enrolled_tax__percentile_092", + "statbel_b1_enrolled_tax__percentile_093", + "statbel_b1_enrolled_tax__percentile_094", + "statbel_b1_enrolled_tax__percentile_095", + "statbel_b1_enrolled_tax__percentile_096", + "statbel_b1_enrolled_tax__percentile_097", + "statbel_b1_enrolled_tax__percentile_098", + "statbel_b1_enrolled_tax__percentile_099", + "statbel_b1_enrolled_tax__percentile_100", + "onss_worker_personal_contributions", + "onem_complete_unemployment_recipients", + "fpb_unemployment_benefit_expenditure", + "fpb_grapa_expenditure", + "fpb_net_mixed_income" ] } diff --git a/tools/generate_be_target_references.py b/tools/generate_be_target_references.py new file mode 100644 index 0000000000..fe419f0c59 --- /dev/null +++ b/tools/generate_be_target_references.py @@ -0,0 +1,2195 @@ +"""Generate Belgium's reviewed reference documents from a pinned Chronicle artifact. + +Run with ``BE_CHRONICLE_ARTIFACT`` or ``--artifact``. References carry selectors +only: observations stay in Chronicle. The separate inventory resource records the +diagnostics the method card asks to publish (ageing ratios, stand-in gaps, the +B.1 checks) and every exclusion. Each choice that shapes numbers is a proposal +of the Belgian method card (BE-MC0 to BE-MC6), pending Max's ruling d1902; +nothing here publishes a number, and Belgium stays inactive. + +``--pin-feed SOURCE_COMMIT`` rewrites ``chronicle_feed.json`` from the loaded +artifact's verified identity before generating; use it only when Chronicle +re-pins (for example once PolicyEngine/chronicle#401 merges). +""" + +from __future__ import annotations + +import argparse +import copy +import hashlib +import json +import os +import re +from collections import Counter +from fractions import Fraction +from pathlib import Path + +from microcosm.build.ledger_artifact import ( + LexicalFloat, + chronicle_feed_identity, + load_ledger_consumer_artifact, + validate_chronicle_feed_pin, +) +from microcosm.build.ledger_targets import fact_matches_selector + +SPEC = ( + Path(__file__).resolve().parents[1] + / "packages/microcosm-build/src/microcosm/build/be" +) +POLICY_YEAR = 2026 +METHOD_CARD_STATUS = "proposed_pending_d1902" +REGIONS = { + "BE1": "Brussels-Capital Region", + "BE2": "Flemish Region", + "BE3": "Walloon Region", +} +AGE_BANDS = ("0_17", "18_64", "65_plus") +SEXES = ("male", "female") +FPB = "fpb.economic_outlook_2026_2031." +STATBEL_POPULATION = "statbel.population_structure.cy{year}.people.by_nuts1_age_sex" +COMMUNE_POPULATION = ( + "statbel.population_structure.cy2025.people.by_commune_nis2025.total" +) +A1 = "statbel.fiscal_income_distribution.income_year2023.{component}.by_income_class_eur1000" +A1_CLASS = "tax_return.net_taxable_income_class" +A1_COMPONENTS = ( + ("professional_income", "professional_income_eur", "in"), + ("immovable_property_income", "immovable_property_income_eur", "gap"), + ( + "capital_and_movable_property_income", + "capital_and_movable_property_income_eur", + "gap", + ), + ("miscellaneous_income", "miscellaneous_income_eur", "gap"), + ("deductible_expenditures", "deductible_expenditures_eur", "gap_subtracted"), +) +B1_VALUES = "statbel.fiscal_income_distribution.b1.decile_values.v1" +B1_PERCENTILES = "statbel.fiscal_income_distribution.b1.top_decile_percentile_values.v1" +B1_BOUNDS = "statbel.fiscal_income_distribution.b1.decile_bounds.v1" +B1_PERCENTILE_BOUNDS = ( + "statbel.fiscal_income_distribution.b1.top_decile_percentile_bounds.v1" +) +B1_GROUPS = ( + *(f"decile_{decile:02d}" for decile in range(1, 10)), + *(f"percentile_{percentile:03d}" for percentile in range(91, 101)), +) +B4 = "statbel.fiscal_income_distribution.b4.declaration_type_age_decile.v1" + +# The d1952 stand-in bands, fixed in advance and before any candidate exists +# (BE-MC5; d1952 option A). Edges are income-year-2023 euros of total net +# taxable income, chosen on A.1's own class edges so every band is an exact sum +# of published EUR 1,000 classes and no cut is interpolated. EUR 10,000 steps +# cover the dense middle of the declaration distribution, which holds B.1's +# deciles 3 to 7 whole (their bounds run from EUR 16,867 to EUR 44,639); above +# EUR 50,000 counts thin, so the steps widen; A.1's open top class (EUR 100,000 +# and more) stays whole. Eight bands give sixteen count and amount +# constraints, the "short list" d1952 asks for, not 101 classes. The +# lowest band is kept so the bands partition A.1's whole positive range and sum +# exactly to B.4's joint plus individual declarations. +STANDIN_BANDS = ( + ("under_10k", 0, 10_000), + ("10k_20k", 10_000, 20_000), + ("20k_30k", 20_000, 30_000), + ("30k_40k", 30_000, 40_000), + ("40k_50k", 40_000, 50_000), + ("50k_75k", 50_000, 75_000), + ("75k_100k", 75_000, 100_000), + ("100k_plus", 100_000, None), +) +STANDIN_MEASUREMENT = "statbel_net_taxable_income_proxy_v1" +STANDIN_MONEY_COLUMN = f"{STANDIN_MEASUREMENT}_eur" +STANDIN_INCOME_COLUMN = f"{STANDIN_MEASUREMENT}_cents" +STANDIN_UNIVERSE_COLUMN = f"{STANDIN_MEASUREMENT}_universe_status" +STANDIN_TABLE = "statbel_a1_standin_bands_iy2023" +STANDIN_REASON = ( + "B4/W3: the d1952 stand-in measurement statbel_net_taxable_income_proxy_v1 " + "(rule-computed net professional income per declaration on the S2-d " + "tax_unit) has no producer, and legal pensions, part of professional " + "income, are not modelled until d1902. The band cuts are income-year-2023 " + "euros: ageing them to 2026 needs a shared operation that scales interval " + "cuts by a declared annual ratio pair. scale_money_and_intervals needs a " + "G8-r2 factor and singleton identity money rows, and G8-r2's resolver needs " + "dated observations through the target period; neither fits FPB's annual " + "2026 projections or summed bands, so reference_profile:aging_index stays " + "deferred. The stand-in is never described as reproducing official " + "taxable income." +) +B4_REASON = ( + "S1/S2-d: the declared tax-unit partition and the BE-MC4 legal-status proxy " + "(partner pointers calibrated to these counts) are not built; joint and " + "individual declaration indicators have no producer. B.4, like A.1, counts " + "only declarations with positive total net taxable income (Statbel's 523,770 " + "zero-income declarations of income year 2023 are outside it), so the " + "indicators must count the same declared filing universe as the A.1 bands " + "(d1952 build item 2), or the target overshoots by up to 7%." +) +DECLARATION_UNIVERSE = ( + "filed declarations with positive total net taxable income; zero-income " + "declarations are outside A.1, B.1 and B.4" +) +B1_REASON = ( + "BE-MC5 activates B.1 only after its tax definition, income ranking and " + "policy year are checked. All three checks fail or cannot be completed from " + "the documents (reference_inventory.json b1_checks), so B.1 stays inactive " + "and unaged at its source period." +) +RULES_REASON = ( + "W3: needs a pinned rulespec-be binding for {module} on the transported " + "frame, the S5 pre-calibration allowlist entry for it, and B4's euro " + "conversion of the donor inputs it reads." +) + +# Declared ratio pairs from the FPB June 2026 outlook. Each pair is one +# published annex row at two periods; its numerator is FPB's 2026 projection +# and its denominator the observed value at the base fact's own period, so +# rolled_forward_by_ratio applies base * numerator / denominator. The reviewed +# lexical tokens are assertions of the feed, never arithmetic inputs. The +# series choice for each pair is a B3 proposal (reported as a finding). +AGEING_PAIRS = { + "fpb_t07_total_population": { + "row": "labour_market.levels.total_population", + "operands": {2023: "11730600", 2026: "11896000"}, + "use": "calibration", + "reason": "Declaration counts follow resident population (August's alignment); A.1 band counts and B.4 type counts share this pair so the bands still sum to B.4's joint plus individual total.", + }, + "fpb_t11_total_resources": { + "row": "household_account.total_resources", + "operands": {2023: "518286000000", 2026: "571010000000"}, + "use": "calibration", + "reason": "Net professional income mixes wages, replacement incomes, pensions and profits; the household account's total resources is the one FPB row spanning them (August's resource alignment).", + }, + "fpb_t11_actual_social_contributions": { + "row": "household_account.actual_social_contributions", + "operands": {2024: "94613000000", 2026: "101300000000"}, + "use": "calibration", + "reason": "Employee personal contributions follow FPB's actual social contributions; gross wages stay free for the wage-headline holdout.", + }, + "fpb_t24_social_security_cash_unemployment": { + "row": "social_benefits_detail.social_security_cash_unemployment", + "operands": {2025: "5602000000", 2026: "4255000000"}, + "use": "calibration", + "reason": "The target's own series, FPB T24 line a., rolled by its 2026/2025 step. unemployment_series_choice in the inventory compares it with the larger line 4.", + }, + "fpb_t24_federal_cash_income_guarantee_for_older_people": { + "row": "social_benefits_detail.federal_government_cash_income_guarantee_for_older_people", + "operands": {2025: "1025000000", 2026: "1034000000"}, + "use": "calibration", + "reason": "The target's own series (GRAPA).", + }, + "fpb_t11_net_mixed_income": { + "row": "household_account.net_mixed_income", + "operands": {2025: "39834000000", 2026: "41044000000"}, + "use": "calibration", + "reason": "The target's own series (BE-MC3 self-employment aggregate).", + }, + "fpb_t17_direct_taxes_households": { + "row": "general_government_account.direct_taxes_households", + "operands": {2025: "77771000000", 2026: "81561000000"}, + "use": "holdout", + "reason": "Government direct taxes on households, the FPB counterpart of D51A_C1.", + }, + "fpb_t06_net_national_disposable_income": { + "row": "national_income_account.net_national_disposable_income", + "operands": {2024: "500699000000", 2026: "534156000000"}, + "use": "holdout", + "reason": "FPB publishes no household disposable income; national net disposable income is the nearest disposable-income row (a proxy).", + }, + "fpb_t11_social_benefits": { + "row": "household_account.social_benefits", + "operands": {2024: "124608000000", 2026: "132674000000"}, + "use": "holdout", + "reason": "The household account row matching Eurostat D62 received.", + }, + "fpb_t11_social_contributions": { + "row": "household_account.social_contributions", + "operands": {2024: "112346000000", 2026: "120094000000"}, + "use": "holdout", + "reason": "The household account row matching Eurostat D61 paid.", + }, + "fpb_t11_current_taxes_on_income_and_wealth": { + "row": "household_account.current_taxes_on_income_and_wealth", + "operands": {2024: "77033000000", 2026: "83113000000"}, + "use": "holdout", + "reason": "The household account row matching Eurostat D5 paid.", + }, + "fpb_t11_gross_wages_and_salaries": { + "row": "household_account.gross_wages_and_salaries", + "operands": {2025: "240536000000", 2026: "247221000000"}, + "use": "holdout", + "reason": "The card's wage-headline comparator (FPB salaires bruts), rolled by its own 2026/2025 step.", + }, +} +# Observed FPB levels the inventory splits each pair at (2025 is the last +# observed year); reviewed like the pair operands. +FPB_OBSERVED_2025 = { + "fpb_t07_total_population": "11850400", + "fpb_t11_total_resources": "554117000000", + "fpb_t11_actual_social_contributions": "98402000000", + "fpb_t06_net_national_disposable_income": "519140000000", + "fpb_t11_social_benefits": "128659000000", + "fpb_t11_social_contributions": "116379000000", + "fpb_t11_current_taxes_on_income_and_wealth": "79273000000", +} +# G8-r2 factors need operands with dated period coverage. FPB's annex facts +# carry none, so the only Belgian operands the resolver can authenticate are +# RSZ's annual wage totals: diagnostic cross-checks of the observed segment of +# the wage-driven pairs, never profile or money-normalization inputs. +# FPB T24 prints unemployment twice. The pair takes line a.; these reviewed 2025 +# levels keep the inventory's comparison with line 4 tied to the feed. +T24_UNEMPLOYMENT_2025 = { + "chosen": ("social_security_cash_unemployment", "5602000000"), + "alternative": ("social_security_cash_unemployment_total", "6510000000"), + "company_supplement": ( + "social_security_cash_unemployment_with_company_supplement", + "167000000", + ), + "career_breaks": ( + "social_security_cash_career_breaks_and_time_credit", + "740000000", + ), +} +RSZ_SOURCE_SHA256 = "7f97f510d332a0966b1afba110ce448f4a4a83d9d58fd5c3bb4d8d36d1aeca97" +RSZ_OPERANDS = {2023: "160796591.5", 2024: "165739460", 2025: "171074878.6"} +RSZ_FACTORS = { + "rsz_ordinary_remuneration_cy2023_to_cy2025_observed": (2023, 1063921), + "rsz_ordinary_remuneration_cy2024_to_cy2025_observed": (2024, 1032192), +} +FACTOR_VALIDITY = { + "declared_on": "2026-11-01", + "valid_from": "2026-11-01", + "valid_until": "2027-06-30", + "as_of": "2026-11-01", +} +# Chronicle labels Statbel's regions NUTS_2024, while the typed geography layer +# names vintage:be_nuts1_2025 and its closed alias set admits no NUTS label. +# Each selector keeps Chronicle's label, and its row names the layer's typed +# authority, so an unreviewed label refuses at generation. +GEOGRAPHY_VINTAGES = { + "nuts1": ("NUTS_2024", "vintage:be_nuts1_2025"), + "commune": ("nis_2025", "vintage:be_nis_2025"), +} +TRANSPORTED_INPUTS = {"employment_income", "nonfarm_self_employment_income"} +PROVIDERS = { + "statbel": "Statbel", + "fpb": "Federal Planning Bureau", + "onss": "National Social Security Office", + "onem": "National Employment Office", + "eurostat": "Eurostat", + "nbb": "National Bank of Belgium", +} +CATEGORIES = { + "statbel.demography": ("statbel", "Demography"), + "statbel.geography_support": ("statbel", "Geography support"), + "statbel.fiscal_income": ("statbel", "Fiscal income"), + "statbel.income_tax": ("statbel", "Assessed income tax"), + "onss.social_security": ("onss", "Social security contributions"), + "onem.caseloads": ("onem", "Benefit caseloads"), + "fpb.benefit_expenditure": ("fpb", "Benefit expenditure"), + "fpb.self_employment": ("fpb", "Self-employment income"), + "fpb.household_account": ("fpb", "Household account"), + "eurostat.income_tax": ("eurostat", "Income tax revenue"), + "eurostat.household_accounts": ("eurostat", "Household accounts"), + "nbb.national_accounts": ("nbb", "National accounts"), +} +DEFERRED_JRC = ( + "jrc-euromod-be-baseline-statistics-2025 is outside the Chronicle be suite " + "while d1822 (move it to the scorecard, its only consumer) is open; no " + "reference selects JRC. August took two calibration rows from it: the " + "unemployment recipient count, now read from ONEM/RVA's own 2024 count " + "(a different concept, parked), and the RIS amount and recipient count, " + "for which the suite holds no source, so no RIS reference exists." +) + + +def _token(value): + if isinstance(value, LexicalFloat): + return value.lexical_token + if isinstance(value, bool) or not isinstance(value, (int, float)): + raise ValueError(f"Non-numeric fact value {value!r}") + return repr(value) if isinstance(value, float) else str(value) + + +def _belgian(fact, communes=None): + """Refuse any fact outside Belgium before a selector can name it.""" + + geography = fact["geography"] + level, area = geography["level"], geography["id"] + if ( + (level == "country" and area == "BE") + or (level == "nuts1" and area in REGIONS) + or ( + level == "commune" + and re.fullmatch(r"[1-9][0-9]{4}", area) + and (communes is None or area in communes) + ) + ): + return fact + raise ValueError( + f"Belgian selectors read Belgian facts only; got {level} {area!r} " + f"({fact['aggregate_fact_key']})." + ) + + +# _selector, Inventory and _typed_equal follow tools/generate_nz_target_references.py +# (copied, not imported: Belgium must not bind to NZ's generator module). +def _selector(fact, *, pin_key=True): + _belgian(fact) + measure, geography = fact["observed_measure"], fact["geography"] + result = { + "source_name": measure["source_name"], + "source_measure_id": measure["source_measure_id"], + "source_concept": measure["source_concept"], + "entity_name": fact["entity"]["name"], + "period_type": fact["period"]["type"], + "period_value": fact["period"]["value"], + "geography_level": geography["level"], + "geography_id": geography["id"], + "geography_vintage": geography["vintage"], + "record_set_id": fact["layout"]["record_set_id"], + "dimensions": list(fact["dimensions"]), + } + if fact["dimensions"]: + result["dimension_values"] = dict(fact["dimensions"]) + if pin_key: + result["aggregate_fact_key"] = fact["aggregate_fact_key"] + return result + + +class Inventory: + def __init__(self, facts): + self.by_record_set, self.by_spec = {}, {} + for fact in facts: + layout = fact.get("layout", {}) + self.by_record_set.setdefault(layout.get("record_set_id"), []).append(fact) + self.by_spec.setdefault(layout.get("record_set_spec_id"), []).append(fact) + + def cells( + self, + record_set=None, + *, + spec=None, + measure=None, + geography=None, + period=None, + dimensions=None, + ): + result = ( + self.by_record_set.get(record_set, []) + if spec is None + else self.by_spec.get(spec, []) + ) + if measure is not None: + result = [ + f + for f in result + if f["observed_measure"]["source_measure_id"] == measure + ] + if geography is not None: + result = [f for f in result if f["geography"]["id"] == geography] + if period is not None: + result = [f for f in result if f["period"]["value"] == period] + if dimensions is not None: + result = [f for f in result if _typed_equal(f["dimensions"], dimensions)] + return result + + def one(self, *args, **kwargs): + matches = self.cells(*args, **kwargs) + if len(matches) != 1: + raise ValueError( + f"Expected one source cell for {args!r} {kwargs!r}; found {len(matches)}" + ) + return _belgian(matches[0]) + + +def _typed_equal(actual, expected): + return actual.keys() == expected.keys() and all( + type(actual[k]) is type(v) and actual[k] == v for k, v in expected.items() + ) + + +def _eurostat(inventory, spec, period, **dimensions): + matches = [ + fact + for fact in inventory.cells(spec=spec, geography="BE", period=period) + if all( + fact["dimensions"].get(key) == value for key, value in dimensions.items() + ) + ] + if len(matches) != 1: + raise ValueError(f"Expected one Eurostat cell {spec} {period} {dimensions}") + return _belgian(matches[0]) + + +def _fpb(inventory, row, period): + fact = inventory.one( + f"{FPB}cy{period}.{row}", geography="BE", dimensions={}, period=period + ) + if fact["observed_measure"]["source_name"] != "fpb_economic_outlook": + raise ValueError(f"FPB row {row} is not an FPB outlook fact") + return fact + + +def _pair(inventory, pair_id, base_period): + """Return the reviewed numerator/denominator facts of one declared pair.""" + + pair = AGEING_PAIRS[pair_id] + if set(pair["operands"]) != {base_period, POLICY_YEAR}: + raise ValueError(f"{pair_id} is declared for {sorted(pair['operands'])}") + numerator = _fpb(inventory, pair["row"], POLICY_YEAR) + denominator = _fpb(inventory, pair["row"], base_period) + for fact, period, assertion in ( + (numerator, POLICY_YEAR, "source_projection"), + (denominator, base_period, "observation"), + ): + if ( + _token(fact["value"]) != pair["operands"][period] + or fact["assertion"] != assertion + ): + raise ValueError(f"Reviewed FPB operand {pair_id} {period} changed") + if ( + numerator["layout"]["record_set_spec_id"] + != denominator["layout"]["record_set_spec_id"] + or numerator["layout"]["source_row_id"] + != denominator["layout"]["source_row_id"] + or numerator["observed_measure"]["source_concept"] + != denominator["observed_measure"]["source_concept"] + ): + raise ValueError(f"{pair_id} numerator and denominator are not one row") + return numerator, denominator + + +def _operand(role, fact): + selector = _selector(fact) + selector["assertion"] = fact["assertion"] + return {"role": role, **selector} + + +def _roll(reference, pair_id, numerator, denominator, *, base_fact=None, members=None): + base = {"role": "base"} + selector = reference["ledger_selector"] + selector["assertion"] = "observation" + if members is not None: + dimension, values = members + base["expected_member_count"] = len(values) + selector.pop("aggregate_fact_key") + selector["dimension_values"][dimension] = list(values) + reference.update( + { + "value_operation": "rolled_forward_by_ratio", + "value_operands": [ + base, + _operand("numerator", numerator), + _operand("denominator", denominator), + ], + "period": POLICY_YEAR, + "period_match_policy": "latest_not_after", + "assertion_policy": "allow_source_projection", + } + ) + if base_fact is not None and _value(base_fact) == _value(denominator): + # A base equal to the denominator makes the target FPB's 2026 + # projection of the row: declared, not hidden. + reference["metadata"]["ageing_target_equals"] = ( + "FPB's 2026 projection of the base's own row" + if base_fact["aggregate_fact_key"] == denominator["aggregate_fact_key"] + else "FPB's 2026 projection of the pair's row: the base equals its denominator" + ) + reference["metadata"].update( + { + "ageing": "rolled_forward_by_ratio", + "ageing_pair": pair_id, + "ageing_source": "FPB Economic Outlook 2026-2031, June 2026 annex", + "source_period": str(denominator["period"]["value"]), + "target_period": str(POLICY_YEAR), + } + ) + + +def _vintage_authority(fact): + """Return a subnational fact's typed authority; refuse an unreviewed label.""" + + geography = fact["geography"] + if geography["level"] == "country": + return None + vintage, authority = GEOGRAPHY_VINTAGES[geography["level"]] + if geography["vintage"] != vintage: + raise ValueError( + f"{geography['level']} fact carries vintage {geography['vintage']!r}; " + f"the reviewed mapping names {vintage!r}." + ) + return authority + + +def _measure_kind(measure): + if measure.startswith("belgium_"): + return "rules_output" + return "transported_input" if measure in TRANSPORTED_INPUTS else "prepared_column" + + +def _reference( + fact, + *, + name, + contract, + category, + entity, + measure, + family, + reference_set, + status, + method_card, + measure_kind, + reason=None, + filter_column=None, + period=None, + tolerance=None, +): + provider = CATEGORIES[category][0] + role = { + "calibration": "calibration", + "precal": "pre_calibration", + "holdout": "validation", + }[reference_set] + result = { + "name": name, + "ledger_selector": _selector(fact), + "entity": entity, + "measure": measure, + "period": fact["period"]["value"] if period is None else period, + "family": family, + "category_id": category, + "assertion_policy": "observed_only", + "metadata": { + "contract_target_id": contract, + "activation_status": status, + "criticality": "release_blocking" + if reference_set != "holdout" + else "diagnostic", + "measure_kind": measure_kind, + "publisher": PROVIDERS[provider], + "target_role": role, + "reference_set": reference_set, + "method_card_row": method_card, + "method_card_status": METHOD_CARD_STATUS, + }, + } + authority = _vintage_authority(fact) + if authority is not None: + result["metadata"].update( + geography_vintage=fact["geography"]["vintage"], + geography_vintage_authority=authority, + ) + if tolerance is not None: + result["metadata"]["fit_tolerance"] = tolerance + if filter_column is not None: + result["filter"] = filter_column + if reason: + result["metadata"]["parking_reason"] = reason + result["notes"] = reason + return result + + +def _hierarchy(rows, labels): + used = sorted({row["category_id"] for row in rows}) + return { + "providers": { + provider: {"label": PROVIDERS[provider]} + for provider in sorted({CATEGORIES[category][0] for category in used}) + }, + "categories": { + category: { + "provider_id": CATEGORIES[category][0], + "label": CATEGORIES[category][1], + } + for category in used + }, + "target_labels": { + contract: labels[contract] + for contract in sorted( + {row["metadata"]["contract_target_id"] for row in rows} + ) + }, + } + + +def _a1_classes(inventory): + """Read A.1's EUR 1,000 classes and their bounds from Chronicle's constraints.""" + + facts = inventory.cells( + A1.format(component="taxable_income"), measure="declarations", geography="BE" + ) + classes = [] + for fact in facts: + code = fact["dimensions"][A1_CLASS] + if code == "all": + continue + bounds = {"lower": None, "upper": None} + for row in fact["universe_constraints"]["constraints"]: + if row["variable"] != "tax_return.net_taxable_income": + continue + if row.get("unit") != "eur": + raise ValueError(f"A.1 class {code} bound is not in euros") + if row["operator"] in {">", ">="}: + bounds["lower"] = (row["value"], row["operator"]) + elif row["operator"] == "<": + bounds["upper"] = row["value"] + else: + raise ValueError(f"A.1 class {code} has operator {row['operator']}") + classes.append((bounds["lower"], bounds["upper"], code)) + classes.sort(key=lambda row: row[0][0]) + previous = None + for index, ((lower, operator), upper, code) in enumerate(classes): + if index == 0: + if (lower, operator) != (0, ">"): + raise ValueError("A.1's first class must exclude zero income") + elif (lower, operator) != (previous, ">="): + raise ValueError(f"A.1 class {code} leaves a gap or overlap") + previous = upper + if classes[-1][1] is not None or len(classes) != 101: + raise ValueError("A.1 must hold 101 classes ending in an open top class") + return [(lower, upper, code) for (lower, _), upper, code in classes] + + +def _band_members(classes): + members = {} + ends = {code: end for _, end, code in classes} + for band, lower, upper in STANDIN_BANDS: + inside = [ + code + for start, end, code in classes + if start >= lower and (upper is None or (end is not None and end <= upper)) + ] + edges = [start for start, _, code in classes if code in inside] + if not inside or edges[0] != lower or ends[inside[-1]] != upper: + raise ValueError(f"Band {band} does not sit on A.1 class edges") + members[band] = inside + flat = [code for band in members for code in members[band]] + if flat != [code for _, _, code in classes]: + raise ValueError("Stand-in bands must partition A.1's positive classes") + return members + + +def calibration_references(inventory, pairs, members): + rows, labels = [], {} + for region in REGIONS: + for sex in SEXES: + for band in AGE_BANDS: + fact = inventory.one( + STATBEL_POPULATION.format(year=POLICY_YEAR), + geography=region, + dimensions={"person.age_band": band, "person.sex": sex}, + ) + code = region.lower() + rows.append( + _reference( + fact, + name=f"statbel_population_by_region_sex_age__{code}__{sex}__a{band}", + contract="statbel_population_by_region_sex_age", + category="statbel.demography", + entity="person", + measure="people", + family="demography", + reference_set="calibration", + status="active", + method_card="BE-MC6", + measure_kind="prepared_column", + filter_column=f"population_region_{code}_{sex}_age_{band}_indicator", + tolerance="0.02", + ) + ) + rows[-1]["period_match_policy"] = "exact" + rows[-1]["metadata"].update( + { + "ageing": "none: observation for the target year", + "source_snapshot": "1 January 2026 resident population", + "target_period": str(POLICY_YEAR), + } + ) + labels["statbel_population_by_region_sex_age"] = ( + "Statbel resident population on 1 January 2026 by region, sex and age band" + ) + count_num, count_den = pairs["fpb_t07_total_population"] + money_num, money_den = pairs["fpb_t11_total_resources"] + for band, lower, upper in STANDIN_BANDS: + anchor = inventory.one( + A1.format(component="taxable_income"), + measure="declarations", + geography="BE", + dimensions={A1_CLASS: members[band][0]}, + ) + money_anchor = inventory.one( + A1.format(component="taxable_income"), + measure="taxable_income_eur", + geography="BE", + dimensions={A1_CLASS: members[band][0]}, + ) + for kind, fact, contract, measure, numerator, denominator, pair_id in ( + ( + "count", + anchor, + "statbel_a1_standin_declarations_by_band", + "tax_units", + count_num, + count_den, + "fpb_t07_total_population", + ), + ( + "money", + money_anchor, + "statbel_a1_standin_taxable_income_by_band", + STANDIN_MONEY_COLUMN, + money_num, + money_den, + "fpb_t11_total_resources", + ), + ): + row = _reference( + fact, + name=f"{contract.removesuffix('_by_band')}__{band}", + contract=contract, + category="statbel.fiscal_income", + entity="tax_unit", + measure=measure, + family="fiscal_income", + reference_set="calibration", + status="requires_prerequisites", + method_card="BE-MC5", + measure_kind="prepared_column", + reason=STANDIN_REASON, + filter_column=f"statbel_a1_standin_band_{band}_indicator", + tolerance="0.05", + ) + _roll( + row, pair_id, numerator, denominator, members=(A1_CLASS, members[band]) + ) + row["metadata"].update( + { + "reference_value_kind": kind, + "required_reference_profile": "aging_index", + "required_measurement_binding": STANDIN_MEASUREMENT, + "reference_prerequisites": json.dumps( + [ + "reference_profile:aging_index", + f"measurement:{STANDIN_MEASUREMENT}", + ], + separators=(",", ":"), + ), + "interval_table_id": STANDIN_TABLE, + "declaration_universe": DECLARATION_UNIVERSE, + "standin_band": band, + "standin_band_lower_eur_iy2023": str(lower), + "standin_band_upper_eur_iy2023": "open" + if upper is None + else str(upper), + } + ) + rows.append(row) + labels["statbel_a1_standin_declarations_by_band"] = ( + "Stand-in income (d1952): Statbel A.1 declarations by broad band of total " + "net taxable income, rolled to 2026 (parked)" + ) + labels["statbel_a1_standin_taxable_income_by_band"] = ( + "Stand-in income (d1952): Statbel A.1 total net taxable income by broad " + "band, rolled to 2026 (parked)" + ) + for declaration_type in ("joint", "individual"): + fact = inventory.one( + spec=B4, + measure="declarations", + geography="BE", + dimensions={ + "tax_return.age_band": "all", + "tax_return.decile": 1, + "tax_return.declaration_type": declaration_type, + }, + ) + row = _reference( + fact, + name=f"statbel_b4_declarations__{declaration_type}", + contract="statbel_b4_declarations_by_type", + category="statbel.fiscal_income", + entity="tax_unit", + measure="tax_units", + family="fiscal_income", + reference_set="calibration", + status="requires_declared_tax_units", + method_card="BE-MC4", + measure_kind="prepared_column", + reason=B4_REASON, + filter_column=f"{declaration_type}_declaration_indicator", + tolerance="0.05", + ) + _roll( + row, + "fpb_t07_total_population", + count_num, + count_den, + members=("tax_return.decile", list(range(1, 11))), + ) + row["metadata"].update( + reference_value_kind="count", declaration_universe=DECLARATION_UNIVERSE + ) + rows.append(row) + labels["statbel_b4_declarations_by_type"] = ( + "Statbel B.4 joint and individual declarations (all ages, deciles 1-10 " + "summed), rolled to 2026 (parked)" + ) + for group in B1_GROUPS: + fact = inventory.one( + spec=B1_VALUES if group.startswith("decile") else B1_PERCENTILES, + measure="total_tax_eur", + geography="BE", + dimensions={"tax_return.rank_group": group}, + ) + row = _reference( + fact, + name=f"statbel_b1_enrolled_tax__{group}", + contract="statbel_b1_enrolled_tax_by_rank_group", + category="statbel.income_tax", + entity="tax_unit", + measure="statbel_b1_enrolled_tax_proxy_v1_eur", + family="income_tax", + reference_set="calibration", + status="inactive_pending_b1_checks", + method_card="BE-MC5", + measure_kind="prepared_column", + reason=B1_REASON, + filter_column=f"statbel_b1_rank_group_{group}_indicator", + tolerance="0.05", + ) + row["signed"] = True + row["period_match_policy"] = "exact" + row["metadata"].update( + { + "ageing": "none declared: B.1 checks failed", + "reference_value_kind": "money", + "source_period": "2023", + } + ) + rows.append(row) + labels["statbel_b1_enrolled_tax_by_rank_group"] = ( + "Statbel B.1 total enrolled tax by decile 1-9 and top percentiles 91-100, " + "income year 2023 (inactive: checks failed)" + ) + onss = inventory.one( + spec="onss.contributions.worker_personal_contributions.country.v1", + geography="BE", + ) + row = _reference( + onss, + name="onss_worker_personal_contributions", + contract="onss_worker_personal_contributions", + category="onss.social_security", + entity="person", + measure="belgium_worker_article_17_uncapped_component_contribution", + family="social_security", + reference_set="calibration", + status="requires_rules_binding", + method_card="BE-MC6", + measure_kind="rules_output", + reason=RULES_REASON.format( + module="be/statutes/social_security/workers/contribution_rates.yaml" + ), + tolerance="0.05", + ) + _roll( + row, + "fpb_t11_actual_social_contributions", + *pairs["fpb_t11_actual_social_contributions"], + base_fact=onss, + ) + rows.append(row) + labels["onss_worker_personal_contributions"] = ( + "ONSS/RSZ worker-borne personal contributions, 2024, rolled to 2026 (parked)" + ) + onem = inventory.one( + spec="onem_rva.unemployment.complete_unemployment.country.v1", geography="BE" + ) + rows.append( + _reference( + onem, + name="onem_complete_unemployment_recipients", + contract="onem_complete_unemployment_recipients", + category="onem.caseloads", + entity="person", + measure="receives_unemployment_benefit", + family="caseloads", + reference_set="calibration", + status="requires_ageing_ruling_and_receipt_binding", + method_card="BE-MC6", + measure_kind="receipt_flag", + reason=( + "No declared ageing pair: FPB publishes jobseeker levels (BFP " + "unemployment, +0.6% 2026/2025), not benefit recipients, and its " + "unemployment benefit spending falls 24% in 2026, so the two " + "series point opposite ways and neither ages a recipient count. " + "Kept unaged at its 2024 source period. Also needs W3's receipt " + "contract for unemployment." + ), + tolerance="0.05", + ) + ) + rows[-1]["period_match_policy"] = "exact" + rows[-1]["metadata"]["ageing"] = "none declared: no recipient series" + labels["onem_complete_unemployment_recipients"] = ( + "ONEM/RVA complete-unemployment benefit recipients, 2024 monthly average " + "(parked, unaged)" + ) + for ( + name, + pair_id, + category, + entity, + measure, + family, + status, + method_card, + reason, + label, + ) in ( + ( + "fpb_unemployment_benefit_expenditure", + "fpb_t24_social_security_cash_unemployment", + "fpb.benefit_expenditure", + "household", + "belgium_unemployment_ordinary_annual_payable_amount", + "benefit_expenditure", + "requires_receipt_contract_and_rules_binding", + "BE-MC6", + RULES_REASON.format( + module="be/regulations/unemployment/pilot_oracle_pipeline.yaml" + ) + + " Unemployment history inputs and W3's receipt contract are also missing.", + "FPB social-security unemployment benefits, 2025, rolled to 2026 (parked)", + ), + ( + "fpb_grapa_expenditure", + "fpb_t24_federal_cash_income_guarantee_for_older_people", + "fpb.benefit_expenditure", + "person", + "belgium_grapa_income_guarantee_for_elderly_annual_amount", + "benefit_expenditure", + "requires_pension_route_d1902", + "BE-MC6", + "GRAPA is means-tested on pension income, and legal pensions are not " + "modelled until d1902 settles BE-MC3's pension route. " + + RULES_REASON.format( + module="be/statutes/income_guarantee_for_elderly/payable_amount.yaml" + ), + "FPB income guarantee for older people (GRAPA), 2025, rolled to 2026 (parked)", + ), + ( + "fpb_net_mixed_income", + "fpb_t11_net_mixed_income", + "fpb.self_employment", + "person", + "nonfarm_self_employment_income", + "self_employment", + "requires_currency_bridge_b4", + "BE-MC3", + "B4: BE-MC3 gives self-employment income FX and uprating only, then " + "calibrates its aggregate; the euro column has no producer until " + "B4's currency bridge. FPB's net mixed income also covers farm " + "income, which the donor carries separately.", + "FPB household net mixed income, 2025, rolled to 2026 (parked)", + ), + ): + numerator, denominator = pairs[pair_id] + fact = denominator + row = _reference( + fact, + name=name, + contract=name, + category=category, + entity=entity, + measure=measure, + family=family, + reference_set="calibration", + status=status, + method_card=method_card, + measure_kind=_measure_kind(measure), + reason=reason, + tolerance="0.05", + ) + _roll(row, pair_id, numerator, denominator, base_fact=fact) + rows.append(row) + labels[name] = label + return rows, labels + + +def precal_references(communes): + rows = [] + for code in sorted(communes): + fact = _belgian(communes[code], communes) + row = _reference( + fact, + name=f"statbel_population_by_commune__nis{code}", + contract="statbel_population_by_commune", + category="statbel.geography_support", + entity="person", + measure="people", + family="geography_support", + reference_set="precal", + status="active", + method_card="geography_spine", + measure_kind="prepared_column", + ) + row["metadata"].update( + { + "precal_use": "atomic_geography_support", + "ageing": "none: support shares at 1 January 2025", + } + ) + rows.append(row) + labels = { + "statbel_population_by_commune": "Statbel resident population by NIS 2025 commune, 1 January 2025 (atomic geography support)", + } + return rows, labels + + +def holdout_references(inventory, pairs): + rows, labels = [], {} + d51 = _eurostat( + inventory, + "eurostat.gov_10a_taxag.income_tax_revenue_by_taxpayer.country.v1", + 2025, + na_item="D51A_C1", + sector="S13", + ) + nbb = inventory.one( + spec="nbb.national_accounts.household_disposable_income.country.v1", + geography="BE", + ) + wages = pairs["fpb_t11_gross_wages_and_salaries"][1] + + def nasa(item, direction): + return _eurostat( + inventory, + "eurostat.nasa_10_nf_tr.household_non_financial_transactions.direction.country.v1", + 2024, + na_item=item, + direct=direction, + sector="S14_S15", + ) + + declarations = ( + ( + d51, + "eurostat_d51a_c1_individual_income_tax", + "fpb_t17_direct_taxes_households", + "eurostat.income_tax", + "person", + "belgium_pit_federal_and_local_tax_before_withholding", + "income_tax", + "Eurostat D51A_C1 taxes on individual or household income, 2025, rolled to 2026", + "Accrual national-accounts revenue held out against assessed tax (BE-MC5). " + + RULES_REASON.format( + module="be/statutes/income_tax/individual/final_tax.yaml" + ), + ), + ( + nbb, + "nbb_household_gross_disposable_income", + "fpb_t06_net_national_disposable_income", + "nbb.national_accounts", + "household", + "household_gross_disposable_income_eur", + "national_accounts", + "NBB household gross disposable income (B6G), 2024, rolled to 2026", + "No producer: rulespec-be's disposable-income policy is a narrow worker bridge, not integrated disposable income.", + ), + ( + nasa("B6G", "RECV"), + "eurostat_household_gross_disposable_income", + "fpb_t06_net_national_disposable_income", + "eurostat.household_accounts", + "household", + "household_gross_disposable_income_eur", + "household_accounts", + "Eurostat household and NPISH gross disposable income (B6G), 2024, rolled to 2026", + "No producer, as for NBB's B6G. Eurostat's S14_S15 sector adds non-profit institutions to NBB's household figure.", + ), + ( + nasa("D62", "RECV"), + "eurostat_household_social_benefits_received", + "fpb_t11_social_benefits", + "eurostat.household_accounts", + "household", + "household_social_benefits_received_eur", + "household_accounts", + "Eurostat household social benefits received (D62), 2024, rolled to 2026", + "No producer: pensions (d1902), child benefits (not modelled at level) and unemployment receipts (W3) are missing.", + ), + ( + nasa("D61", "PAID"), + "eurostat_household_social_contributions_paid", + "fpb_t11_social_contributions", + "eurostat.household_accounts", + "household", + "household_social_contributions_paid_eur", + "household_accounts", + "Eurostat household social contributions paid (D61), 2024, rolled to 2026", + "No producer: employer and self-employed contributions are not bound (W3).", + ), + ( + nasa("D5", "PAID"), + "eurostat_household_current_taxes_paid", + "fpb_t11_current_taxes_on_income_and_wealth", + "eurostat.household_accounts", + "household", + "household_current_taxes_on_income_paid_eur", + "household_accounts", + "Eurostat household current taxes on income and wealth paid (D5), 2024, rolled to 2026", + "No producer: needs the PIT binding (W3) aggregated to households.", + ), + ( + wages, + "fpb_gross_wages_and_salaries", + "fpb_t11_gross_wages_and_salaries", + "fpb.household_account", + "person", + "employment_income", + "household_accounts", + "FPB gross wages and salaries (salaires bruts), 2025, rolled to 2026", + "The card's wage-headline comparator (BE-MC5): gross wages, not compensation including employer contributions. The euro wage column has no producer until B4's currency bridge.", + ), + ) + for ( + fact, + name, + pair_id, + category, + entity, + measure, + family, + label, + reason, + ) in declarations: + row = _reference( + fact, + name=name, + contract=name, + category=category, + entity=entity, + measure=measure, + family=family, + reference_set="holdout", + status="requires_holdout_measure", + method_card="BE-MC5", + measure_kind=_measure_kind(measure), + reason="Held out of calibration; compared, never fitted. " + reason, + ) + _roll(row, pair_id, *pairs[pair_id], base_fact=fact) + row["metadata"]["holdout_use"] = "validation_comparator" + rows.append(row) + labels[name] = label + return rows, labels + + +def _interval_document(classes, members): + bands = [] + bands.append( + { + "id": "nil", + "kind": "nil", + "indicator": "statbel_a1_standin_nil_indicator", + "source_label": "zero total net taxable income (outside A.1)", + } + ) + edges = {code: (lower, upper) for lower, upper, code in classes} + for band, lower, upper in STANDIN_BANDS: + if edges[members[band][0]][0] != lower or ( + edges[members[band][-1]][1] != upper + ): + raise ValueError(f"Band {band} edges differ from its member classes") + bands.append( + { + "id": band, + "kind": "positive", + "upper_cent": None if upper is None else upper * 100, + "indicator": f"statbel_a1_standin_band_{band}_indicator", + "source_label": f"A.1 classes {members[band][0]} to {members[band][-1]}", + } + ) + return { + "schema_version": 1, + "country": "be", + "description": "Generated by tools/generate_be_target_references.py from the class bounds Chronicle publishes on Statbel A.1 (universe constraints), checked to tile A.1's positive range without gaps.", + "disclosure": ( + "Statbel's labels ('Minder dan 1', '1-2', '100 en meer') do not state a " + "closure; Chronicle's A.1 universe constraints do: 0 < t < 1,000, then " + "lower <= t < upper, and t >= 100,000 for the open top class. The " + "table follows them: left-closed positive bands, a nil band for " + "t == 0 (Statbel counts zero-income declarations outside A.1, and " + "no reference fits the nil band, because the proxy's zeros are not " + "Statbel's zeros), negative proxy income floored to zero, integer " + "cents. Cuts are income-year-2023 euros and are not aged: no shared " + "operation scales them by a declared annual ratio pair, so the A.1 " + "references stay parked (BE-MC5, d1952; proposed pending d1902)." + ), + "tables": [ + { + "id": STANDIN_TABLE, + "entity": "tax_unit", + "currency": "EUR", + "input_unit": "integer_cent", + "income_column": STANDIN_INCOME_COLUMN, + "universe_column": STANDIN_UNIVERSE_COLUMN, + "source_period": 2023, + "target_period": POLICY_YEAR, + "positive_band_closure": "left", + "nil_band": "present", + "negative_income_policy": "floor_zero", + "first_lower_cut_cents": 0, + "source_locator": "Chronicle statbel.fiscal_income_distribution.a1.by_income_class_eur1000.v1, Belgium, taxable income classes", + "description": "The eight d1952 stand-in bands of total net taxable income, income year 2023, each an exact sum of A.1 EUR 1,000 classes.", + "diagnostics": { + "boundary_window_cents": 100, + "alternative_positive_band_closure": "right", + }, + "bands": bands, + } + ], + } + + +def _reference_profiles(): + return { + "schema_version": 1, + "factor_context_resource": "reference_aging.json", + "interval_resource": "reference_intervals.json", + "dimensions": { + "aging_index": { + "default": "central", + "profiles": { + "central": { + "deferred": True, + "notes": ( + "Declared but not executable: ageing the A.1 stand-in " + "band cuts to 2026 needs a shared operation that scales " + "interval cuts by a declared annual ratio pair, and " + "reference_aging.json holds no profile_input factor for " + "it. The profile is deferred, so the resolver applies " + "no transformation and the A.1 rows keep both " + "prerequisites." + ), + } + }, + } + }, + } + + +def _factor_validation(fact): + return { + "unit": fact["observed_measure"]["unit"], + "source_sha256": fact["source"]["source_sha256"], + "source_vintage": fact["source"]["vintage"], + "entity_role": fact["entity"]["role"], + "provenance_class": fact["provenance_class"], + "assertion": fact["assertion"], + "period_coverage": { + key: fact["period_coverage"][key] for key in ("start_date", "end_date") + }, + "source_column_id": fact["layout"]["source_column_id"], + } + + +def _rsz(inventory, year): + fact = inventory.one( + f"rsz.annual_wages.year{year}.ordinary_remuneration", + geography="BE", + dimensions={"rsz.annual_worker_type_sex": "total"}, + ) + if ( + _token(fact["value"]) != RSZ_OPERANDS[year] + or fact["source"]["source_sha256"] != RSZ_SOURCE_SHA256 + or fact["assertion"] != "observation" + ): + raise ValueError(f"Reviewed RSZ operand changed for {year}") + return fact + + +def build_aging_declarations(inventory, feed_identity): + """Declare the G8-r2 factors whose operands carry dated coverage.""" + + declarations = [] + target = _rsz(inventory, 2025) + for factor_id, (source_year, expected) in RSZ_FACTORS.items(): + source = _rsz(inventory, source_year) + + def slot(fact, *, is_target=False): + row = { + "selector": {**_selector(fact), "assertion": "observation"}, + "validation": _factor_validation(fact), + "weight": "1", + "sequence": 0, + } + if is_target: + row["projection_offset"] = 0 + return row + + declarations.append( + { + "schema_version": 1, + "id": factor_id, + "operation": "projected_period_average_ratio", + "operation_version": 1, + "purpose": "diagnostic", + "feed_identity": copy.deepcopy(feed_identity), + "source_period": source_year, + "target_period": 2025, + "source_schedule": [slot(source)], + "target_schedule": [slot(target, is_target=True)], + "growth": None, + "subperiods_per_year": 1, + "projection_policy": "observed_preferred_latest_contiguous", + "rounding": {"digits": 6, "mode": "nearest_half_even"}, + "expected_operational_factor": { + "numerator": expected, + "denominator": 1000000, + }, + "validity": dict(FACTOR_VALIDITY), + "evidence": [ + "RSZ/ONSS annual wages key figures (Kerncijfers), ordinary " + "remuneration, all employees, calendar years; pre-publication " + "raw data, 2024-2025 not final", + "Diagnostic cross-check of the observed segment of FPB " + "wage-driven ratio pairs; never a profile or money " + "normalization input", + ], + "decision_references": [ + "BE-MC0 (proposed pending d1902): targets rolled to 2026 by FPB June 2026 ratio pairs", + "G8-r2 factor resolver: projected_period_average_ratio@1", + ], + } + ) + return declarations + + +def build_reference_aging(inventory, feed_identity): + from microcosm.build.reference_factors import resolve_reference_factor + + factors = [] + for declaration in build_aging_declarations(inventory, feed_identity): + factor, receipt = resolve_reference_factor( + declaration, + [fact for rows in inventory.by_spec.values() for fact in rows], + feed_identity, + ) + factors.append( + { + "declaration": declaration, + "operational_factor": factor, + "receipt": receipt, + } + ) + return {"schema_version": 1, "feed_identity": feed_identity, "factors": factors} + + +def _value(fact): + return Fraction(_token(fact["value"])) + + +def _share(part, whole): + return float(part / whole) + + +def _standin_gaps(inventory, members): + def component(name, measure, codes): + return sum( + ( + _value( + inventory.one( + A1.format(component=name), + measure=measure, + geography="BE", + dimensions={A1_CLASS: code}, + ) + ) + for code in codes + ), + Fraction(), + ) + + def row(codes, label): + total = component("taxable_income", "taxable_income_eur", codes) + declarations = component("taxable_income", "declarations", codes) + shares = { + name: _share(component(name, measure, codes), total) + for name, measure, _ in A1_COMPONENTS + } + identity = component("professional_income", "professional_income_eur", codes) + for name, measure, role in A1_COMPONENTS[1:]: + value = component(name, measure, codes) + identity += -value if role == "gap_subtracted" else value + return { + "band": label, + "declarations_iy2023": float(declarations), + "taxable_income_eur_iy2023": float(total), + "component_shares_of_taxable_income": shares, + "omitted_share_gross": sum( + shares[name] for name, _, role in A1_COMPONENTS if role != "in" + ), + "omitted_share_net": 1 - shares["professional_income"], + "identity_residual_eur": float(identity - total), + } + + national = row(["all"], "all") + bands = [row(members[band], band) for band, _, _ in STANDIN_BANDS] + professional = _value( + inventory.one( + A1.format(component="professional_income"), + measure="declarations", + geography="BE", + dimensions={A1_CLASS: "all"}, + ) + ) + zero = _value( + inventory.one( + "statbel.fiscal_income_distribution.income_year2023.zero_income_declarations", + geography="BE", + ) + ) + return { + "measure": STANDIN_MEASUREMENT, + "unit": "tax declaration (S2-d tax_unit); joint declarations count once", + "in_measure": "net professional income, rule-computed from transported gross amounts", + "published_gaps": "Components of Statbel's total net taxable income left out of the stand-in, as shares of it (method card BE-MC5; d1952). Within bands they can be larger than nationally.", + "national": national, + "bands": bands, + "declarations_with_taxable_but_no_professional_income": float( + Fraction(national["declarations_iy2023"]) - professional + ), + "zero_income_declarations_outside_a1": float(zero), + "zero_handling": "The proxy's zeros (no professional income, or losses floored to zero) are not Statbel's zero-income declarations; the nil band is not fitted.", + "stress_test": "Declared, not executable in B3: rerun with unemployment and sickness benefits left out of the measure (d1952); a measurement variant owed by B4/W3.", + "pension_gap": "Legal pensions are part of net professional income but are not modelled until d1902 settles BE-MC3's pension route, so the proxy cannot yet represent pensioner declarations.", + } + + +def _b1_checks(inventory): + """Run the three BE-MC5 checks the artifact allows; B.1 activates only if all pass.""" + + def b1(spec, measure, group): + return _value( + inventory.one( + spec=spec, + measure=measure, + geography="BE", + dimensions={"tax_return.rank_group": group}, + ) + ) + + total_tax = b1(B1_VALUES, "total_tax_eur", "all") + spf = _value( + inventory.one( + spec="spf_finances.pit.tax_before_withholding.country.v1", geography="BE" + ) + ) + deciles = [f"decile_{decile:02d}" for decile in range(1, 11)] + decile_tax = sum((b1(B1_VALUES, "total_tax_eur", g) for g in deciles), Fraction()) + percentile_tax = sum( + ( + b1(B1_PERCENTILES, "total_tax_eur", f"percentile_{p:03d}") + for p in range(91, 101) + ), + Fraction(), + ) + negative = [g for g in deciles if b1(B1_VALUES, "total_tax_eur", g) < 0] + bounds = [b1(B1_BOUNDS, "upper_bound_eur", f"decile_{d:02d}") for d in range(1, 10)] + top_bounds = [ + b1(B1_PERCENTILE_BOUNDS, "upper_bound_eur", f"percentile_{p:03d}") + for p in range(91, 100) + ] + b1_income = b1(B1_VALUES, "taxable_income_eur", "all") + a1_income = _value( + inventory.one( + A1.format(component="taxable_income"), + measure="taxable_income_eur", + geography="BE", + dimensions={A1_CLASS: "all"}, + ) + ) + shares = sum( + (b1(B1_VALUES, "taxable_income_share", g) for g in deciles), Fraction() + ) + decile_10 = b1(B1_VALUES, "total_tax_eur", "decile_10") + note = inventory.one( + spec=B1_VALUES, + measure="total_tax_eur", + geography="BE", + dimensions={"tax_return.rank_group": "all"}, + )["concept_alignment"]["evidence_notes"] + cent = Fraction(1, 10) + asserted = { + "b1_total_matches_spf_total": abs(total_tax - spf) <= cent, + "b1_deciles_sum_to_total": abs(decile_tax - total_tax) <= cent, + "top_percentiles_sum_to_decile_10": abs(percentile_tax - decile_10) <= cent, + "decile_bounds_strictly_increase": all( + a < b for a, b in zip(bounds, bounds[1:], strict=False) + ), + "percentile_bounds_strictly_increase": all( + a < b for a, b in zip(top_bounds, top_bounds[1:], strict=False) + ), + "decile_9_bound_below_percentile_91_bound": bounds[-1] < top_bounds[0], + "b1_and_a1_taxable_income_totals_match": abs(b1_income - a1_income) <= cent, + "chronicle_states_zero_income_exclusion": ( + "excludes declarations with zero total net taxable income" in note + ), + } + if not all(asserted.values()): + raise ValueError(f"Reviewed B.1 evidence changed: {asserted}") + checks = { + "tax_definition": { + "evidence": { + "b1_total_enrolled_tax_eur": float(total_tax), + "spf_finances_total_taxes_eur": float(spf), + "difference_eur": float(total_tax - spf), + "b1_deciles_sum_minus_total_eur": float(decile_tax - total_tax), + "top_percentiles_sum_minus_decile_10_eur": float( + percentile_tax - decile_10 + ), + "negative_deciles": negative, + }, + "passed": [ + "B.1's total enrolled tax equals the total taxes in Chronicle's spf-finances-pit-2023 package to EUR 0.06. That fact carries Statbel's concept and evidence URL, so the match reads one administrative total twice and corroborates nothing independently.", + "B.1's deciles sum to its total, and percentiles 91-100 sum to decile 10, within EUR 0.10.", + ], + "missing": [ + "rulespec-be's candidate output belgium_pit_federal_and_local_tax_before_withholding (final_tax.yaml at 530849e) adds article 134 federal tax and the articles 465-466 local additions but not regional_surcharge.yaml's regional additional tax. No document in the suite says whether Statbel's total taxes include the regional additional tax.", + "B.1 counts declarations (joint = one); every rulespec-be PIT output is per Person, and the couple pipeline needs relation bindings (S2-d) that are not built.", + "That output is also the D51A_C1 holdout's measure: a B.1 producer must be a separately bound declaration-level measure, because S5 refuses a pre-calibration stage whose module produces a holdout measure.", + ], + }, + "income_ranking": { + "evidence": { + "decile_upper_bounds_strictly_increase": asserted[ + "decile_bounds_strictly_increase" + ], + "percentile_upper_bounds_strictly_increase": asserted[ + "percentile_bounds_strictly_increase" + ], + "decile_9_bound_below_percentile_91_bound": asserted[ + "decile_9_bound_below_percentile_91_bound" + ], + "b1_minus_a1_total_taxable_income_eur": float(b1_income - a1_income), + "decile_taxable_income_shares_sum": float(shares), + "chronicle_concept_note": note, + }, + "passed": [ + "Chronicle's B.1 facts state that B.1 excludes zero-income declarations, as A.1 does; B.1's and A.1's taxable-income totals agree to EUR 0.02, and the published bounds increase.", + ], + "missing": [ + "The stand-in ranks declarations by net professional income only; 42,007 declarations with taxable but no professional income, and every pensioner while pensions are unmodelled (d1902), would rank differently from Statbel's total net taxable income.", + "B.1 publishes no declaration counts by decile; classifying model declarations needs either model-side ranking or the published bounds, and the bounds are income-year-2023 euros that need the same unavailable cut ageing as A.1.", + ], + }, + "policy_year": { + "evidence": { + "b1_legal_vintage": "income_year_2023_assessment_year_2024", + "model_policy_year": POLICY_YEAR, + "rulespec_be_final_tax_effective_from": "2025-01-01", + "negative_deciles": negative, + }, + "passed": [], + "missing": [ + "B.1 is assessed under income-year-2023 law; the model applies 2026 law (BE-MC0). rulespec-be defines its PIT outputs from 2025-01-01 (its article 134 module states income year 2025 parameters), so B.1's own year cannot be reproduced, and no document bridges 2023 to 2026 tax law: ageing a 2023 tax mass by an FPB ratio would mix growth with law changes.", + "Deciles 1 and 2 are negative (refundable credits) and rolled_forward_by_ratio refuses a negative base, so the declared ageing route cannot carry them to 2026.", + ], + }, + } + for check in checks.values(): + check["result"] = "fail" if check["missing"] else "pass" + passing = all(check["result"] == "pass" for check in checks.values()) + return { + "verdict": "B.1 may activate." + if passing + else "B.1 stays inactive: no check passes completely from the documents.", + "asserted_evidence": asserted, + **checks, + } + + +def _digest(payload): + encoded = json.dumps( + payload, ensure_ascii=False, separators=(",", ":"), sort_keys=True + ) + return hashlib.sha256(encoded.encode()).hexdigest() + + +def selector_digest(row): + """Digest everything a reference row selects, however it is spelled.""" + + return _digest( + {key: row[key] for key in ("ledger_selector", "value_operands") if key in row} + ) + + +def factor_digest(declaration): + """Digest the selectors of one factor declaration's two schedules.""" + + return _digest( + [ + slot["selector"] + for schedule in ("source_schedule", "target_schedule") + for slot in declaration[schedule] + ] + ) + + +def _matching(inventory, selector): + pool = inventory.by_record_set.get(selector["record_set_id"], []) + return [fact for fact in pool if fact_matches_selector(fact, selector)] + + +def _partition_total(inventory, row): + """Return the published total a row's bands or rank groups add up to.""" + + if row["metadata"].get("interval_table_id") == STANDIN_TABLE: + return inventory.one( + A1.format(component="taxable_income"), + measure=row["ledger_selector"]["source_measure_id"], + geography="BE", + dimensions={A1_CLASS: "all"}, + ) + if row["metadata"]["contract_target_id"] == "statbel_b1_enrolled_tax_by_rank_group": + return inventory.one( + spec=B1_VALUES, + measure="total_tax_eur", + geography="BE", + dimensions={"tax_return.rank_group": "all"}, + ) + return None + + +def _keyed(facts, field): + """List distinct keys under the field name package scans admit as fact keys.""" + + return [{field: key} for key in sorted({fact[field] for fact in facts})] + + +def _resolved_row(inventory, row, reference_set): + base = _matching(inventory, row["ledger_selector"]) + operands = [ + fact + for operand in row.get("value_operands", []) + if operand.get("role") != "base" + for fact in _matching( + inventory, {key: value for key, value in operand.items() if key != "role"} + ) + ] + entry = { + "name": row["name"], + "reference_set": reference_set, + "selector_sha256": selector_digest(row), + "base_facts": _keyed(base, "aggregate_fact_key"), + "operand_facts": _keyed(operands, "aggregate_fact_key"), + "semantic_facts": _keyed([*base, *operands], "semantic_fact_key"), + } + total = _partition_total(inventory, row) + if total is not None: + entry["partition_total"] = {"semantic_fact_key": total["semantic_fact_key"]} + return entry + + +def _resolved_factor(inventory, declaration): + facts = [ + fact + for schedule in ("source_schedule", "target_schedule") + for slot in declaration[schedule] + for fact in _matching(inventory, slot["selector"]) + ] + return { + "name": f"factor:{declaration['id']}", + "reference_set": "factor_context", + "selector_sha256": factor_digest(declaration), + "base_facts": [], + "operand_facts": _keyed(facts, "aggregate_fact_key"), + "semantic_facts": _keyed(facts, "semantic_fact_key"), + } + + +def resolved_reads(inventory, documents): + """Bind each row and factor to the facts its selectors resolve to in the feed. + + CI holds no artifact, so it checks each digest against the committed row, each + pinned key against its entry and the listed keys for disjointness. The feed + audit proves every listed key, roster selectors included. + """ + + rows = [ + _resolved_row(inventory, row, document["reference_set"]) + for filename in ( + "target_references.json", + "precal_references.json", + "holdout_references.json", + ) + for document in (documents[filename],) + for row in document["target_references"] + ] + factors = [ + _resolved_factor(inventory, entry["declaration"]) + for entry in documents["reference_aging.json"]["factors"] + ] + return [*rows, *factors] + + +def _unemployment_series_choice(inventory): + lines = { + key: _fpb(inventory, f"social_benefits_detail.{row}", 2025) + for key, (row, _) in T24_UNEMPLOYMENT_2025.items() + } + for key, (_, token) in T24_UNEMPLOYMENT_2025.items(): + if _token(lines[key]["value"]) != token: + raise ValueError(f"Reviewed FPB T24 level {key} changed") + return { + "lines_2025": { + key: { + "row": fact["layout"]["source_row_id"], + "label": fact["layout"]["groupby_value_label"], + "eur": float(_value(fact)), + } + for key, fact in lines.items() + }, + "choice": ( + "The target takes line a. Line 4 also holds benefits with a company " + "supplement and career breaks and time credit, about 14% of the level. " + "This row choice is proposed with d1902." + ), + "open_question": ( + "No document in the suite says whether line a. includes temporary " + "unemployment, which the ordinary-benefit output does not compute." + ), + } + + +def _ageing_receipts(pairs, documents): + used = {} + for filename in ( + "target_references.json", + "precal_references.json", + "holdout_references.json", + ): + for row in documents[filename]["target_references"]: + pair = row["metadata"].get("ageing_pair") + if pair: + used.setdefault(pair, []).append(row["name"]) + receipts = [] + for pair_id, (numerator, denominator) in sorted(pairs.items()): + num, den = _value(numerator), _value(denominator) + receipt = { + "id": pair_id, + "use": AGEING_PAIRS[pair_id]["use"], + "fpb_row": AGEING_PAIRS[pair_id]["row"], + "record_set_spec_id": numerator["layout"]["record_set_spec_id"], + "source_row_id": numerator["layout"]["source_row_id"], + "row_label": numerator["layout"]["groupby_value_label"], + "numerator_selector": _selector(numerator), + "denominator_selector": _selector(denominator), + "numerator": float(num), + "denominator": float(den), + "ratio": float(num / den), + "base_period": denominator["period"]["value"], + "target_period": POLICY_YEAR, + "numerator_assertion": numerator["assertion"], + "denominator_assertion": denominator["assertion"], + "reason": AGEING_PAIRS[pair_id]["reason"], + "status": "proposed (BE-MC0, pending d1902); series choice is a B3 finding", + "used_by": sorted(used.get(pair_id, [])), + } + if pair_id in FPB_OBSERVED_2025: + observed = Fraction(FPB_OBSERVED_2025[pair_id]) + receipt.update( + observed_segment_to_2025=float(observed / den), + projected_step_2025_to_2026=float(num / observed), + ) + receipts.append(receipt) + return receipts + + +def build_reference_documents(artifact, *, package_dir=SPEC): + """Return generated file-name/document pairs; verify the full feed identity first.""" + + package_dir = Path(package_dir) + feed_pin = json.loads((package_dir / "chronicle_feed.json").read_text()) + validate_chronicle_feed_pin(artifact, feed_pin) + feed_identity = chronicle_feed_identity(feed_pin) + inventory = Inventory(artifact.facts) + pairs = {} + for pair_id, pair in AGEING_PAIRS.items(): + base = min(pair["operands"]) + pairs[pair_id] = _pair(inventory, pair_id, base) + for pair_id, token in FPB_OBSERVED_2025.items(): + if ( + _token(_fpb(inventory, AGEING_PAIRS[pair_id]["row"], 2025)["value"]) + != token + ): + raise ValueError(f"Reviewed FPB 2025 level {pair_id} changed") + classes = _a1_classes(inventory) + members = _band_members(classes) + communes = { + fact["geography"]["id"]: fact for fact in inventory.cells(COMMUNE_POPULATION) + } + if len(communes) != 565 or any( + fact["geography"]["vintage"] != "nis_2025" for fact in communes.values() + ): + raise ValueError("Expected the 565 NIS 2025 communes") + targets, target_labels = calibration_references(inventory, pairs, members) + precal, precal_labels = precal_references(communes) + holdouts, holdout_labels = holdout_references(inventory, pairs) + documents = {} + description = { + "calibration": "Belgian calibration references (reference set calibration), generated by tools/generate_be_target_references.py from the pinned Chronicle be feed. Selectors only: no observation is carried. Demography targets Statbel's 1 January 2026 population directly; every other row rolls a 2023-2025 fact to 2026 by a declared FPB June 2026 ratio pair or stays parked with a named reason. Method-card choices are proposed pending d1902. Belgium stays inactive.", + "precal": "Belgian pre-calibration references: Statbel commune population on 1 January 2025 as the atomic geography support mass, unaged (support shares). Identity only; no observation is carried.", + "holdout": "Belgian held-out references: compared with the model, never fitted. No calibration-side node may read this resource. Every row is parked until its measure has a producer; JRC's EUROMOD-BE statistics are deferred while d1822 is open.", + } + for reference_set, rows, labels, filename, operations in ( + ( + "calibration", + targets, + target_labels, + "target_references.json", + ["identity", "rolled_forward_by_ratio"], + ), + ("precal", precal, precal_labels, "precal_references.json", ["identity"]), + ( + "holdout", + holdouts, + holdout_labels, + "holdout_references.json", + ["rolled_forward_by_ratio"], + ), + ): + documents[filename] = { + "country": "be", + "schema_version": 2, + "reference_set": reference_set, + "description": description[reference_set], + "allowed_value_operations": operations, + "hierarchy": _hierarchy(rows, labels), + "target_references": rows, + "target_profile": {"schema_version": 1, "hierarchy_reconciliations": []}, + } + documents["reference_intervals.json"] = _interval_document(classes, members) + documents["reference_profiles.json"] = _reference_profiles() + documents["reference_aging.json"] = build_reference_aging(inventory, feed_identity) + documents["reference_inventory.json"] = _inventory( + inventory, pairs, documents, feed_pin, members, communes + ) + return documents + + +def _inventory(inventory, pairs, documents, feed_pin, members, communes): + counts = {} + for filename in ( + "target_references.json", + "precal_references.json", + "holdout_references.json", + ): + rows = documents[filename]["target_references"] + counts[filename] = { + "total": len(rows), + "by_family": dict(Counter(row["family"] for row in rows)), + "by_contract": dict( + Counter(row["metadata"]["contract_target_id"] for row in rows) + ), + "by_activation_status": dict( + Counter(row["metadata"]["activation_status"] for row in rows) + ), + } + nuts = { + year: sum( + ( + _value(fact) + for fact in inventory.cells(STATBEL_POPULATION.format(year=year)) + ), + Fraction(), + ) + for year in (2025, POLICY_YEAR) + } + commune_total = sum((_value(fact) for fact in communes.values()), Fraction()) + b4 = { + kind: sum( + ( + _value( + inventory.one( + spec=B4, + measure="declarations", + geography="BE", + dimensions={ + "tax_return.age_band": "all", + "tax_return.decile": decile, + "tax_return.declaration_type": kind, + }, + ) + ) + for decile in range(1, 11) + ), + Fraction(), + ) + for kind in ("joint", "individual") + } + a1_total = _value( + inventory.one( + A1.format(component="taxable_income"), + measure="declarations", + geography="BE", + dimensions={A1_CLASS: "all"}, + ) + ) + aging = documents["reference_aging.json"] + rsz = { + entry["declaration"]["id"]: entry["operational_factor"]["numerator"] + / entry["operational_factor"]["denominator"] + for entry in aging["factors"] + } + wage_pair = { + year: Fraction(token) + for year, token in ( + (2023, "226018000000"), + (2024, "233079000000"), + (2025, "240536000000"), + ) + } + for year, token in wage_pair.items(): + if ( + _value(_fpb(inventory, "household_account.gross_wages_and_salaries", year)) + != token + ): + raise ValueError("Reviewed FPB gross wages changed") + excluded = [ + ("jrc_euromod_be_statistics", DEFERRED_JRC), + ( + "ris_amount_and_recipients", + "August's RIS amount and count came from JRC; the suite holds no RIS administrative source, so the gap is named, not filled.", + ), + ( + "legal_pensions", + "FPB pension amounts and SFPD beneficiary counts and bands: legal pensions are not modelled until d1902 settles BE-MC3's pension route; the SFPD bands are B4's quantile-map surface.", + ), + ( + "family_allowances", + "FPB family allowances and Opgroeien/Ostbelgien caseloads: child benefits are reported as not modelled at level until indexed amounts are encoded (BE-MC0).", + ), + ( + "rsz_wage_classes", + "RSZ daily-wage classes (B2f) are B4's wage quantile-map input under d1902, not a reference.", + ), + ( + "usd_eur_rate", + "Eurostat ert_bil_eur_a is B4's currency-bridge input (BE-MC3), not a reference.", + ), + ( + "regional_a1_and_b1", + "National bands only: the short list d1952 asks for; v0.5.1's 606 regional A.1 rows failed to fit.", + ), + ( + "a1_component_tables", + "Professional, property, movable, miscellaneous and deduction tables are gap diagnostics in this inventory, not fitted rows.", + ), + ( + "a1_and_b1_totals", + "Published totals duplicate the band and decile partitions; B.1's taxable-income masses duplicate A.1.", + ), + ( + "zero_income_declarations", + "Statbel's 523,770 zero-income declarations are a diagnostic; the proxy's zeros differ, so the nil band is not fitted.", + ), + ( + "b3_b5_tables", + "B.3 professional-category and B.5 dependant tables are outside the card's targets; v0.5.1's wage-only B.3 proxy destroyed weights.", + ), + ( + "b4_age_and_decile_cells", + "Only the all-age joint and individual totals are targets (BE-MC4); age and decile cells would multiply weak cells.", + ), + ( + "statbel_commune_fiscal_income", + "Commune fiscal income is a diagnostic surface for a later commune spine gate, not a B3 reference.", + ), + ( + "spf_finances_pit_total", + "SPF Finances' total taxes equal B.1's total: one administrative total, read twice. The tax-definition check records it, and no row targets it.", + ), + ( + "spf_municipal_surcharge_rates", + "Communal surcharge rates are W3 rule inputs, not references.", + ), + ( + "statbel_population_2025_nuts1", + "Statbel's 1 January 2026 cells are the target-year observation; the 2025 cells would duplicate them.", + ), + ( + "movable_income", + "Movable income stays out of the stand-in (art. 313 CIR 92 withholding dispensation) and out of the targets until the investment-income match check (d1952 build item 5).", + ), + ( + "eurostat_d11_wages", + "Eurostat D11 duplicates FPB's gross wages, the card's wage-headline comparator.", + ), + ( + "eurostat_b3g_mixed_income", + "Mixed income is a calibration aggregate (FPB net mixed income), so it cannot also be held out.", + ), + ( + "eurostat_survey_and_social_protection", + "Eurostat ilc_* survey aggregates and spr_exp_func expenditure are excluded: surveys are validation-only and outside the card's holdouts, and ESSPROS overlaps FPB's T24 rows.", + ), + ( + "fpb_projections_as_direct_targets", + "No reference takes an FPB projection as its base: every base is an observation. Seven rolled rows still equal FPB's 2026 projection, because each base equals its pair's denominator: unemployment benefits, GRAPA and net mixed income in calibration, and gross wages and the Eurostat D61, D62 and D5 rows in the holdouts. Those rows say so in ageing_target_equals.", + ), + ( + "german_and_french_rows", + "Four Eurostat members carry DE and FR rows (72 of 87,112); the generator refuses any non-Belgian fact before it can name one.", + ), + ] + return { + "schema_version": 1, + "country": "be", + "generated_by": "tools/generate_be_target_references.py", + "feed_identity": feed_pin, + "policy_year": POLICY_YEAR, + "method_card_status": "BE-MC0, BE-MC3 to BE-MC6 proposed pending d1902; nothing publishes a number", + "reference_counts": counts, + "regions": list(REGIONS), + "age_bands": list(AGE_BANDS), + "standin_bands": [ + { + "id": band, + "lower_eur_iy2023": lower, + "upper_eur_iy2023": upper, + "a1_classes": members[band], + } + for band, lower, upper in STANDIN_BANDS + ], + "standin_band_reason": ( + "Fixed before any candidate (d1952): EUR 10,000 steps over the dense " + "middle, wider steps above EUR 50,000, A.1's open top class whole; " + "every edge is an A.1 class edge; eight bands, sixteen constraints." + ), + "standin_gaps": _standin_gaps(inventory, members), + "ageing_pairs": _ageing_receipts(pairs, documents), + "rsz_wage_cross_checks": [ + { + "factor_id": factor_id, + "rsz_observed_factor": factor, + "fpb_gross_wages_observed_ratio": float( + wage_pair[2025] / wage_pair[RSZ_FACTORS[factor_id][0]] + ), + "use": "diagnostic only", + } + for factor_id, factor in rsz.items() + ], + "b4_identity": { + "joint": float(b4["joint"]), + "individual": float(b4["individual"]), + "a1_declarations": float(a1_total), + "closes_exactly": b4["joint"] + b4["individual"] == a1_total, + "use": "A.1 band counts and B.4 type counts share fpb_t07_total_population, so the identity survives ageing.", + }, + "destination_mass": { + "commune_sum_2025": float(commune_total), + "nuts1_sum_2025": float(nuts[2025]), + "nuts1_sum_2026": float(nuts[POLICY_YEAR]), + "commune_minus_nuts1_2025": float(commune_total - nuts[2025]), + "create_mass_reference": "Not in B3. CREATE needs exactly one unfiltered national person count. The suite has no national Statbel population fact, and a national row composed from the 565 communes refuses: the shared composed-geography path labels only UK areas. W3 chooses between a shared Belgian geography label (NZ hub) and FPB's annual-average population.", + }, + "b1_checks": _b1_checks(inventory), + "unemployment_series_choice": _unemployment_series_choice(inventory), + "geography_vintage_bindings": [ + { + "layer": "nuts1", + "chronicle_vintage": GEOGRAPHY_VINTAGES["nuts1"][0], + "typed_authority": GEOGRAPHY_VINTAGES["nuts1"][1], + "relation": "crosswalk", + "basis": "Chronicle labels Statbel's regions NUTS_2024. The typed nuts1 layer records no code list, so the mapping rests on destination_mass: the three regions' 2025 population equals the 565 communes' sum. A package test holds every nuts1 row to this binding. This choice is proposed with d1902.", + }, + { + "layer": "commune", + "chronicle_vintage": GEOGRAPHY_VINTAGES["commune"][0], + "typed_authority": GEOGRAPHY_VINTAGES["commune"][1], + "relation": "exact_alias", + "basis": "nis_2025 is an exact typed alias of vintage:be_nis_2025.", + }, + ], + "holdout_information_overlaps": [ + "The tests check separation at the fact and measure level; holdouts still share information with calibration through economics, not facts:", + "FPB gross wages (wage-headline holdout): ONSS's calibrated worker contributions scale with wages.", + "Eurostat D62 social benefits received contain the calibrated unemployment and GRAPA aggregates.", + "Eurostat D61 social contributions paid contain the calibrated ONSS worker contributions.", + "Eurostat D51A_C1 and D5 measure the same personal income tax that B.1 would calibrate once active.", + "The A.1 stand-in is 98% net professional income, and its amount pair, FPB T11 total resources, contains gross wages, the wage holdout's own series.", + ], + "grammar_gaps": [ + "A national row composed from commune facts refuses for Belgium: the composed-geography path labels only UK areas (ledger_targets._geography_fallback_label), so CREATE's single national mass reference cannot be the commune sum.", + "A schema-2 target_profile requires period_match_policy 'exact', which refuses rolled_forward_by_ratio; the documents keep B1's schema-2 hierarchy catalogs with a schema-1 target_profile (NZ's documents use the same schema-1 profile, with inline hierarchies).", + "No shared operation ages interval cuts by a declared annual ratio pair: scale_money_and_intervals needs a G8-r2 factor and singleton identity money rows, and G8-r2's projected_period_average_ratio cannot project an annual series past its last observation.", + "G8-r2's resolver needs dated period_coverage on every operand; Chronicle's FPB, Statbel NUTS1, NBB, ONSS, ONEM and most Eurostat facts carry none.", + "rolled_forward_by_ratio refuses a negative base, so signed targets (B.1 low deciles) cannot be aged by it.", + "rolled_forward_by_ratio's series key treats every FPB annex row of one table as one series (same concept, entity, geography and empty dimensions); the generator and tests enforce row identity themselves.", + "The typed vintage alias set admits only a layer's full id, its country-shortened id and its authority value, so Chronicle's NUTS_2024 label cannot be an alias of vintage:be_nuts1_2025; geography_vintage_bindings carries the mapping instead.", + "The schema-1 target_profile drops B1's required_families, basis_periods, tolerance tiers and subnational vintage rule. Package tests restore required families, the vintage rule and each row's periods. Caseload tolerance moves from B1's 15% to BE-MC6's 5%, and the ONSS contribution row moves from B1's standard_admin_release 10% to 5%.", + ], + "exclusions": [{"id": name, "reason": reason} for name, reason in excluded], + "resolved_reads": resolved_reads(inventory, documents), + } + + +def pin_feed(artifact, source_commit): + """Return a feed pin for a reviewed artifact; identities are the loader's own.""" + + manifest = artifact.manifest or {} + return { + "version": 1, + "country": "be", + "scope": "be_calibration", + "source_repo": "PolicyEngine/chronicle", + "source_commit": source_commit, + "build": "build-bundle --suite be -> build-consumer-artifact", + "artifact_schema_version": artifact.schema_version, + "consumer_fact_schema_versions": list(artifact.fact_schema_versions), + "consumer_fact_schema_sha256": manifest.get("consumer_fact_schema_sha256"), + "fact_row_count": artifact.fact_row_count, + "facts_sha256": artifact.facts_sha256, + "manifest_sha256": artifact.manifest_sha256, + } + + +def _encode(document): + return json.dumps(document, ensure_ascii=False, indent=2) + "\n" + + +def main(): + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--artifact", default=os.environ.get("BE_CHRONICLE_ARTIFACT")) + parser.add_argument("--out", type=Path, default=SPEC) + parser.add_argument("--check", action="store_true") + parser.add_argument("--pin-feed", metavar="SOURCE_COMMIT") + args = parser.parse_args() + if not args.artifact: + parser.error("--artifact or BE_CHRONICLE_ARTIFACT is required") + if args.check and args.pin_feed: + parser.error("--check and --pin-feed are exclusive") + artifact = load_ledger_consumer_artifact(args.artifact, lexical_floats=True) + if args.pin_feed: + (args.out / "chronicle_feed.json").write_text( + _encode(pin_feed(artifact, args.pin_feed)) + ) + documents = build_reference_documents(artifact, package_dir=args.out) + stale = [] + for filename, document in documents.items(): + encoded = _encode(document) + destination = args.out / filename + if args.check: + if not destination.exists() or destination.read_text() != encoded: + stale.append(str(destination)) + else: + destination.write_text(encoded) + if stale: + raise SystemExit(f"Stale generated resource(s): {stale}") + + +if __name__ == "__main__": + main()