NI validation

.vscode/python.code-snippets

@@ -21,7 +21,7 @@
 				"	entity = ${4:Person}",
 				"	definition_period = ${5:YEAR}",
 				"	value_type = ${6:float}",
-				"	unit = \"${7:currency-GBP}\"",
+				"	unit = ${7:GBP}",
 				"",
 				""
 		 	],

changelog_entry.yaml

@@ -0,0 +1,4 @@
+- bump: minor
+  changes:
+    changed:
+    - Validated and standardised National Insurance variables.

policyengine_uk/data/datasets/__init__.py

@@ -15,6 +15,7 @@
     CalibratedSPIEnhancedPooledFRS_2018_20,
     CalibratedSPIEnhancedPooledFRS_2019_21,
     EnhancedFRS,
+    UKMOD_FRS_2018,
 )
 
 DATASETS = [
@@ -34,4 +35,5 @@
     CalibratedSPIEnhancedPooledFRS_2018_20,
     CalibratedSPIEnhancedPooledFRS_2019_21,
     EnhancedFRS,
+    UKMOD_FRS_2018,
 ]

policyengine_uk/data/datasets/frs/__init__.py

@@ -22,3 +22,4 @@
 )
 from .stacked_frs import StackedFRS, PooledFRS_2018_20, PooledFRS_2019_21
 from .enhanced_frs import EnhancedFRS
+from .ukmod import UKMOD_FRS_2018

policyengine_uk/data/datasets/frs/ukmod.py

@@ -0,0 +1,63 @@
+import pandas as pd
+from policyengine_uk.data.storage import STORAGE_FOLDER
+import numpy as np
+from policyengine_core.data import Dataset
+
+
+class UKMOD_FRS_2018(Dataset):
+    name = "ukmod_frs_2018"
+    label = "UKMOD (2018-19 FRS)"
+    data_format = Dataset.TIME_PERIOD_ARRAYS
+    file_path = STORAGE_FOLDER / "ukmod_frs_2018.h5"
+    time_period = "2018"
+
+    def generate(self):
+        data = {}
+        ukmod_output = pd.read_csv(
+            STORAGE_FOLDER / "uk_2018_std.txt", delimiter="\t"
+        )
+        ukmod_input = pd.read_csv(
+            STORAGE_FOLDER / "uk_2018_a4.txt", delimiter="\t"
+        )
+        output_columns = [
+            column
+            for column in ukmod_output.columns
+            if column not in ukmod_input.columns
+        ]
+        ukmod = pd.merge(
+            ukmod_output[output_columns + ["idperson"]],
+            ukmod_input,
+            on="idperson",
+            how="right",
+        )
+        # Add ID variables first
+        data["person_id"] = ukmod.idperson
+        data["person_benunit_id"] = person_benunit_id = (
+            ukmod.idorigbenunit * 10 + ukmod.idorighh
+        )
+        data["person_household_id"] = person_household_id = (
+            ukmod.idorighh * 100
+        )
+        data["person_state_id"] = np.ones_like(ukmod.idperson)
+
+        data["benunit_id"] = person_benunit_id.unique()
+        data["household_id"] = person_household_id.unique()
+        data["state_id"] = np.array([1])
+
+        data["age"] = ukmod.dag.values
+        data["gender"] = np.where(
+            ukmod.dgn == 0,
+            "FEMALE",
+            "MALE",
+        ).astype("S")
+        data["employment_income"] = ukmod.yem.values * 12
+        data["self_employment_income"] = ukmod.yse.values * 12
+        data["pension_income"] = ukmod.ypp.values * 12
+        data["statutory_sick_pay"] = ukmod.bhlwk.values * 12
+        data["statutory_maternity_pay"] = ukmod.bmact_s.values * 12
+        data["statutory_paternity_pay"] = ukmod.bpact_s.values * 12
+
+        for variable in data:
+            data[variable] = {"2018": data[variable]}
+
+        self.save_dataset(data)

policyengine_uk/data/storage/__init__.py

@@ -0,0 +1,3 @@
+from pathlib import Path
+
+STORAGE_FOLDER = Path(__file__).parent

policyengine_uk/parameters/gov/dwp/state_pension/female_age.yaml

@@ -5,7 +5,7 @@ values:
   2012-01-01: 62
   2014-01-01: 63
   2016-01-01: 64
-  2018-01-01: 65
+  2019-01-01: 65
   2020-01-01: 66
 metadata:
   unit: year

policyengine_uk/parameters/gov/hmrc/national_insurance/class_1/thresholds/secondary_threshold.yaml

@@ -8,7 +8,6 @@ metadata:
   - https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/882271/Table-a4.pdf
   - https://www.gov.uk/government/publications/rates-and-allowances-national-insurance-contributions/rates-and-allowances-national-insurance-contributions
   unit: currency-GBP
-  uprating: gov.benefit_uprating_cpi
 values:
   2015-04-06: 155
   2016-04-06: 155
@@ -24,3 +23,4 @@ values:
         title: The Social Security (Contributions) (Rates, Limits and Thresholds Amendments
           and National Insurance Funds Payments) Regulations 2022(6)
     value: 175
+  2024-01-01: 175

policyengine_uk/tests/microsimulation/test_against_ukmod.py

@@ -0,0 +1,66 @@
+from policyengine_uk import Microsimulation
+from policyengine_uk.data.datasets import UKMOD_FRS_2018
+from policyengine_uk.data.storage import STORAGE_FOLDER
+import pandas as pd
+import numpy as np
+import pytest
+
+SKIP_UKMOD_TESTS = True
+
+if not SKIP_UKMOD_TESTS:
+    ukmod_output = pd.read_csv(
+        STORAGE_FOLDER / "uk_2018_std.txt", delimiter="\t"
+    )
+    ukmod_input = pd.read_csv(
+        STORAGE_FOLDER / "uk_2018_a4.txt", delimiter="\t"
+    )
+    output_columns = [
+        column
+        for column in ukmod_output.columns
+        if column not in ukmod_input.columns
+    ]
+    ukmod = pd.merge(
+        ukmod_output[output_columns + ["idperson"]],
+        ukmod_input,
+        on="idperson",
+        how="right",
+    )
+
+    UKMOD_FRS_2018().generate()
+    sim = Microsimulation(dataset="ukmod_frs_2018")
+
+
+@pytest.mark.skip(reason="UKMOD data not publicly shareable")
+def test_ni_class_1():
+    # NI Class 1 income matches.
+    assert np.allclose(
+        sim.calculate("ni_class_1_income").values,
+        ukmod.il_empniearns.values * 12,
+        atol=1,
+    )
+
+
+@pytest.mark.skip(reason="UKMOD data not publicly shareable")
+def test_ni_class_1_employee():
+    # NI contributions are off by more because the thresholds change mid-year,
+    # and PolicyEngine simulates over the full year while UKMOD simulates one
+    # month.
+    assert np.allclose(
+        sim.calculate("ni_class_1_employee").values,
+        ukmod.tscee_s.values * 12,
+        atol=50,
+    )
+
+
+@pytest.mark.skip(reason="UKMOD data not publicly shareable")
+def test_ni_self_employed():
+    # NI self-employed contributions don't match entirely for people with both
+    # self-employed and employment income. This might be due to a different
+    # interpretation of the rules around capped NI contributions (our Class 4
+    # maximum uses the legislation as a reference).
+
+    error = np.abs(
+        sim.calculate("ni_self_employed").values - ukmod.tscse_s.values * 12
+    )
+
+    assert (error < 50).mean() > 0.99

policyengine_uk/tests/policy/baseline/gov/hmrc/national_insurance/class_1/ni_class_1_employee.yaml

@@ -0,0 +1,22 @@
+- name: NI Class 1 employee contributions - below PT
+  period: 2023
+  input:
+    ni_class_1_income: 11_000
+  output:
+    ni_class_1_employee: 0
+
+- name: NI Class 1 employee contributions - between PT and UEL
+  period: 2023
+  absolute_error_margin: 1
+  input:
+    ni_class_1_income: 30_000
+  output:
+    ni_class_1_employee: (30_000 - 12_570) * 0.12
+
+- name: NI Class 1 employee contributions - above UEL
+  period: 2023
+  absolute_error_margin: 1
+  input:
+    ni_class_1_income: 70000
+  output:
+    ni_class_1_employee: (50_270 - 12_570) * 0.12 + (70_000 - 50_270) * 0.0325

policyengine_uk/tests/policy/baseline/gov/hmrc/national_insurance/class_1/ni_class_1_employee_additional.yaml

@@ -0,0 +1,15 @@
+- name: NI Class 1 employee additional contributions - income below UEL
+  period: 2023
+  absolute_error_margin: 1
+  input:
+    ni_class_1_income: 30_000
+  output:
+    ni_class_1_employee_additional: 0
+
+- name: NI Class 1 employee additional contributions - income above UEL
+  period: 2023
+  absolute_error_margin: 1
+  input:
+    ni_class_1_income: 100_000
+  output:
+    ni_class_1_employee_additional: (100_000 - 50_270) * 0.0325

policyengine_uk/tests/policy/baseline/gov/hmrc/national_insurance/class_1/ni_class_1_employee_primary.yaml

@@ -0,0 +1,7 @@
+- name: £20k income has NI Class 1 liability
+  period: 2023
+  absolute_error_margin: 1
+  input:
+    employment_income: 20_000
+  output:
+    ni_class_1_employee_primary: (20_000 - 12_570) * 0.12

policyengine_uk/tests/policy/baseline/gov/hmrc/national_insurance/class_1/ni_class_1_employer.yaml

@@ -0,0 +1,15 @@
+- name: NI Class 1 employer contributions for low income in 2023
+  period: 2023
+  absolute_error_margin: 0.01
+  input:
+    ni_class_1_income: 8_000  # Annual income below secondary threshold
+  output:
+    ni_class_1_employer: 0.00  # Expected employer contributions
+
+- name: NI Class 1 employer contributions for moderate income in 2023
+  period: 2023
+  absolute_error_margin: 0.01
+  input:
+    ni_class_1_income: 30_000  # Annual income above secondary threshold but below upper limit
+  output:
+    ni_class_1_employer: (30_000 - 175 * 52) * 0.138  # Expected employer contributions

policyengine_uk/tests/policy/baseline/gov/hmrc/national_insurance/class_1/ni_class_1_income.yaml

@@ -0,0 +1,9 @@
+- name: NI Class 1 income sums income components.
+  period: 2023
+  input:
+    employment_income: 1
+    statutory_sick_pay: 2
+    statutory_maternity_pay: 4
+    statutory_paternity_pay: 8
+  output:
+    ni_class_1_income: 15

policyengine_uk/tests/policy/baseline/gov/hmrc/national_insurance/class_1/ni_liable.yaml

@@ -0,0 +1,20 @@
+- name: Child isn't liable for NI.
+  period: 2023
+  input:
+    age: 15
+  output:
+    ni_liable: false
+
+- name: Working-age adult is liable for NI.
+  period: 2023
+  input:
+    age: 35
+  output:
+    ni_liable: true
+
+- name: Retired adult isn't liable for NI.
+  period: 2023
+  input:
+    age: 70
+  output:
+    ni_liable: false

policyengine_uk/tests/policy/baseline/gov/hmrc/national_insurance/class_2/ni_class_2.yaml

@@ -0,0 +1,13 @@
+- name: NI Class 2 - under LPL.
+  period: 2023
+  input:
+    self_employment_income: 5_000
+  output:
+    ni_class_2: 0
+
+- name: NI Class 2 - over LPL.
+  period: 2023
+  input:
+    self_employment_income: 15_000
+  output:
+    ni_class_2: 3.15 * 52

policyengine_uk/tests/policy/baseline/gov/hmrc/national_insurance/class_4/ni_class_4.yaml

@@ -0,0 +1,7 @@
+- name: NI Class 4 - under UPL.
+  period: 2023
+  absolute_error_margin: 1
+  input:
+    self_employment_income: 30_000
+  output:
+    ni_class_4: 1628

policyengine_uk/tests/policy/baseline/gov/hmrc/national_insurance/class_4/ni_class_4_main.yaml

@@ -0,0 +1,7 @@
+- name: NI Class 4 - over UPL has maximum capped.
+  period: 2023
+  absolute_error_margin: 1
+  input:
+    self_employment_income: 100_000
+  output:
+    ni_class_4_main: 3452