Move disability benefit reported amount mapping to UK data (#1656)

* Tighten child and qualifying young person benefit rules

* Move PIP reported amount mapping to data

* Move DLA and Attendance Allowance categories to data

Author: MaxGhenis

docs/book/assumptions/growthfactors.md

@@ -15,7 +15,7 @@ We use the OBR's CPI projections to drive most benefit and consumption variables
 | Growth rate | 10.0% | 5.7% | 2.3% | 3.2% | 1.9% | 2.0% | 2.0% | 2.0% |
 
 We apply CPI to these variables:
-- All reported benefits– `attendance_allowance_reported`, `carers_allowance_reported`, `child_benefit_reported`, `child_tax_credit_reported`, `dla_m_reported`, `dla_sc_reported`, `esa_contrib_reported`, `esa_income_reported`, `housing_benefit_reported`, `iidb_reported`, `incapacity_benefit_reported`, `income_support_reported`, `jsa_contrib_reported`, `jsa_income_reported`, `maternity_allowance_reported`, `pension_credit_reported`, `pip_dl_reported`, `pip_m_reported`, `sda_reported`, `state_pension_reported`, `universal_credit_reported`, `winter_fuel_allowance_reported`, `working_tax_credit_reported`
+- All reported benefits– `carers_allowance_reported`, `child_benefit_reported`, `child_tax_credit_reported`, `esa_contrib_reported`, `esa_income_reported`, `housing_benefit_reported`, `iidb_reported`, `incapacity_benefit_reported`, `income_support_reported`, `jsa_contrib_reported`, `jsa_income_reported`, `maternity_allowance_reported`, `pension_credit_reported`, `sda_reported`, `state_pension_reported`, `universal_credit_reported`, `winter_fuel_allowance_reported`, `working_tax_credit_reported`
 - All consumption categories– `alcohol_and_tobacco_consumption`, `clothing_and_footwear_consumption`, `communication_consumption`, `domestic_energy_consumption`, `education_consumption`, `food_and_non_alcoholic_beverages_consumption`, `health_consumption`, `household_furnishings_consumption`, `housing_water_and_electricity_consumption`, `miscellaneous_consumption`, `recreation_consumption`, `restaurants_and_hotels_consumption`, `transport_consumption`
 - Other variables– `afcs_reported`, `bsp_reported`, `childcare_expenses`, `diesel_spending`, `free_school_fruit_veg`, `free_school_meals`, `free_school_milk`, `maintenance_expenses`, `petrol_spending`, `statutory_maternity_pay`, `statutory_paternity_pay`, `statutory_sick_pay`, `state_pension`
 
@@ -107,4 +107,4 @@ We use ONS population [projections](https://www.ons.gov.uk/peoplepopulationandco
 |-------------|------|------|------|------|------|------|------|------|
 | Growth rate | 0.3% | 1.4% | 1.0% | 1.1% | 0.7% | 0.8% | 0.4% | 0.5% |
 
-We apply this to: `household_weight`
+We apply this to: `household_weight`

policyengine_uk/data/uprating_indices.yaml

@@ -8,7 +8,6 @@ gov.economic_assumptions.yoy_growth.obr.average_earnings:
 gov.economic_assumptions.yoy_growth.obr.consumer_price_index:
 - afcs_reported
 - alcohol_and_tobacco_consumption
-- attendance_allowance_reported
 - bsp_reported
 - carers_allowance_reported
 - child_benefit_reported
@@ -17,8 +16,6 @@ gov.economic_assumptions.yoy_growth.obr.consumer_price_index:
 - clothing_and_footwear_consumption
 - communication_consumption
 - diesel_spending
-- dla_m_reported
-- dla_sc_reported
 - domestic_energy_consumption
 - education_consumption
 - esa_contrib_reported
@@ -41,8 +38,6 @@ gov.economic_assumptions.yoy_growth.obr.consumer_price_index:
 - miscellaneous_consumption
 - pension_credit_reported
 - petrol_spending
-- pip_dl_reported
-- pip_m_reported
 - recreation_consumption
 - restaurants_and_hotels_consumption
 - sda_reported

policyengine_uk/tests/test_deterministic_variables.py

@@ -7,7 +7,7 @@
 """
 
 import pytest
-from policyengine_uk import Simulation
+from policyengine_uk import CountryTaxBenefitSystem, Simulation
 
 
 class TestDefaultValues:
@@ -79,6 +79,77 @@ def test_is_disabled_for_benefits_defaults_false(self):
         result = sim.calculate("is_disabled_for_benefits", 2024)
         assert result[0] == False
 
+    def test_pip_categories_default_to_none(self):
+        sim = Simulation(
+            situation={
+                "people": {"person": {"age": {2024: 30}}},
+                "benunits": {"benunit": {"members": ["person"]}},
+                "households": {"household": {"members": ["person"]}},
+            }
+        )
+
+        assert sim.calculate("pip", 2024)[0] == 0
+
+    def test_pip_categories_can_be_set_directly(self):
+        sim = Simulation(
+            situation={
+                "people": {
+                    "person": {
+                        "age": {2024: 30},
+                        "pip_dl_category": {2024: "ENHANCED"},
+                        "pip_m_category": {2024: "STANDARD"},
+                    }
+                },
+                "benunits": {"benunit": {"members": ["person"]}},
+                "households": {"household": {"members": ["person"]}},
+            }
+        )
+        pip_parameters = sim.tax_benefit_system.parameters(2024).gov.dwp.pip
+        expected = (
+            pip_parameters.daily_living.enhanced + pip_parameters.mobility.standard
+        ) * 52
+
+        assert sim.calculate("pip", 2024)[0] == pytest.approx(expected)
+
+    def test_pip_reported_amounts_are_not_model_inputs(self):
+        system = CountryTaxBenefitSystem()
+
+        assert "pip_dl_reported" not in system.variables
+        assert "pip_m_reported" not in system.variables
+
+    def test_disability_categories_can_be_set_directly(self):
+        sim = Simulation(
+            situation={
+                "people": {
+                    "person": {
+                        "age": {2024: 30},
+                        "dla_sc_category": {2024: "MIDDLE"},
+                        "dla_m_category": {2024: "HIGHER"},
+                        "aa_category": {2024: "LOWER"},
+                    }
+                },
+                "benunits": {"benunit": {"members": ["person"]}},
+                "households": {"household": {"members": ["person"]}},
+            }
+        )
+        parameters = sim.tax_benefit_system.parameters(2024).gov.dwp
+        expected_dla = (
+            parameters.dla.self_care.middle + parameters.dla.mobility.higher
+        ) * 52
+        expected_aa = parameters.attendance_allowance.lower * 52
+
+        assert sim.calculate("dla", 2024)[0] == pytest.approx(expected_dla)
+        assert sim.calculate("attendance_allowance", 2024)[0] == pytest.approx(
+            expected_aa
+        )
+
+    def test_disability_reported_amounts_are_not_model_inputs(self):
+        system = CountryTaxBenefitSystem()
+
+        assert "attendance_allowance_reported" not in system.variables
+        assert "dla_sc_reported" not in system.variables
+        assert "dla_m_reported" not in system.variables
+
     def test_would_claim_marriage_allowance_defaults_true(self):
         sim = Simulation(
             situation={

policyengine_uk/variables/gov/dwp/aa_category.py

@@ -6,23 +6,9 @@
 
 class aa_category(Variable):
     label = "Attendance Allowance category"
+    documentation = "If you receive Attendance Allowance, you will be in one of the following categories: Lower or Higher. If not, select None. Survey reported amounts should be converted to this category in the data pipeline."
     entity = Person
     definition_period = YEAR
     value_type = Enum
     possible_values = LowerOrHigher
     default_value = LowerOrHigher.NONE
-
-    def formula(person, period, parameters):
-        aa = parameters(period).baseline.gov.dwp.attendance_allowance
-        SAFETY_MARGIN = 0.1  # Survey reported values could be slightly below eligible values when they should be above due to data manipulation
-        reported_weekly_aa = (
-            person("attendance_allowance_reported", period) / WEEKS_IN_YEAR
-        )
-        return select(
-            [
-                reported_weekly_aa >= aa.higher * (1 - SAFETY_MARGIN),
-                reported_weekly_aa >= aa.lower * (1 - SAFETY_MARGIN),
-            ],
-            [LowerOrHigher.HIGHER, LowerOrHigher.LOWER],
-            default=LowerOrHigher.NONE,
-        )

policyengine_uk/variables/gov/dwp/attendance_allowance_reported.py

@@ -6,26 +6,9 @@
 
 class dla_m_category(Variable):
     label = "DLA (mobility) category"
-    documentation = "If you receive the mobility component of Disability Living Allowance, you will be in one of the following categories: Lower, Higher. If not, select None."
+    documentation = "If you receive the mobility component of Disability Living Allowance, you will be in one of the following categories: Lower, Higher. If not, select None. Survey reported amounts should be converted to this category in the data pipeline."
     entity = Person
     definition_period = YEAR
     value_type = Enum
     possible_values = LowerOrHigher
     default_value = LowerOrHigher.NONE
-
-    def formula(person, period, parameters):
-        dla_m = parameters(period).baseline.gov.dwp.dla.mobility
-        SAFETY_MARGIN = 0.1  # Survey reported values could be slightly below eligible values when they should be above due to data manipulation
-        reported_weekly_dla_m = person("dla_m_reported", period) / WEEKS_IN_YEAR
-        return select(
-            [
-                reported_weekly_dla_m >= dla_m.higher * (1 - SAFETY_MARGIN),
-                reported_weekly_dla_m >= dla_m.lower * (1 - SAFETY_MARGIN),
-                True,
-            ],
-            [
-                LowerOrHigher.HIGHER,
-                LowerOrHigher.LOWER,
-                LowerOrHigher.NONE,
-            ],
-        )