Don't attempt to simulate domestic rates

changelog_entry.yaml

@@ -0,0 +1,4 @@
+- bump: patch
+  changes:
+    fixed:
+    - NI domestic rates taken as reported.

policyengine_uk/parameters/gov/economic_assumptions/yoy_growth.yaml

@@ -310,3 +310,20 @@ ofwat:
           href: https://www.ofwat.gov.uk/price-review/
         - title: Ofwat 2025-26 media statement
           href: https://www.ofwat.gov.uk/average-bills-2025-26-press-statement/
+finance_ni:
+  domestic_rates:
+    description: Domestic rates year-on-year growth.
+    values:
+      2024-01-01: 0.050
+      2025-01-01: 0.047
+      2026-01-01: 0.0
+      2027-01-01: 0.0
+      2028-01-01: 0.0
+      2029-01-01: 0.0
+      2020-01-01: 0.0
+    metadata:
+      unit: /1
+      label: domestic rates growth
+      reference:
+        - title: Finance NI (based on outturn)
+          href: https://www.finance-ni.gov.uk/

policyengine_uk/tests/microsimulation/reforms_config.yaml

@@ -16,15 +16,15 @@ reforms:
   parameters:
     gov.hmrc.child_benefit.amount.additional: 25
 - name: Reduce Universal Credit taper rate to 20%
-  expected_impact: -37.7
+  expected_impact: -36.5
   parameters:
     gov.dwp.universal_credit.means_test.reduction_rate: 0.2
 - name: Raise Class 1 main employee NICs rate to 10%
   expected_impact: 12.3
   parameters:
     gov.hmrc.national_insurance.class_1.rates.employee.main: 0.1
 - name: Raise VAT standard rate by 2pp
-  expected_impact: 19.4
+  expected_impact: 18.8
   parameters:
     gov.hmrc.vat.standard_rate: 0.22
 - name: Raise additional rate by 3pp

policyengine_uk/variables/gov/local_authorities/domestic_rates.py

@@ -7,17 +7,3 @@ class domestic_rates(Variable):
     definition_period = YEAR
     value_type = float
     unit = GBP
-
-    def formula(household, period, parameters):
-        rates = parameters(period).gov.local_authorities.domestic_rates.rates
-        local_authority = household("local_authority", period)
-        rate_defined = pd.Series(local_authority.decode_to_str()).isin(
-            rates._children
-        )
-        percent = np.zeros(household.count, dtype=float)
-        if any(rate_defined):
-            percent[rate_defined] = rates[local_authority[rate_defined]]
-            main_residence_value = household("main_residence_value", period)
-            return percent * main_residence_value
-        else:
-            return 0