Merge pull request #880 from PolicyEngine/fix/879-private-school-vat

Implement private school VAT

changelog_entry.yaml

@@ -0,0 +1,4 @@
+- bump: patch
+  changes:
+    added:
+    - Private school VAT calculation

policyengine_uk/data/datasets/frs/enhanced_frs.py

@@ -5,6 +5,7 @@
 from ..utils import STORAGE_FOLDER
 from .frs import FRS_2019_20
 from .calibration.calibrated_frs import CalibratedSPIEnhancedPooledFRS_2019_21
+from .stacked_frs import StackedFRS
 import yaml
 import copy
 
@@ -137,10 +138,41 @@ def generate(self):
         self.save_dataset(data)
 
 
-EnhancedFRS = ImputationExtendedFRS.from_dataset(
+ImputedCalibratedFRS = ImputationExtendedFRS.from_dataset(
     CalibratedSPIEnhancedPooledFRS_2019_21,
-    "enhanced_frs",
-    "Enhanced FRS",
+    "imputed_calibrated_frs",
+    "Imputed-Calibrated FRS",
     new_num_years=7,
-    new_url="release://policyengine/non-public-microdata/uk-2024-march-efo/enhanced_frs.h5",
 )
+
+
+class EnhancedFRS(Dataset):
+    name = "enhanced_frs"
+    label = "Enhanced FRS"
+    file_path = STORAGE_FOLDER / "enhanced_frs.h5"
+    data_format = Dataset.TIME_PERIOD_ARRAYS
+    num_years = 7
+    time_period = 2021
+    count_copies = 4
+    url = "release://policyengine/non-public-microdata/uk-2024-march-efo/enhanced_frs.h5"
+
+    def generate(self):
+        from policyengine_uk.tools.stack_datasets import stack_datasets
+
+        data = ImputedCalibratedFRS().load_dataset()
+
+        copies = []
+        for _ in range(self.count_copies):
+            copies.append(copy.deepcopy(data))
+
+        for time_period in data["household_weight"]:
+            original_weights = data["household_weight"][time_period].copy()
+            for dataset in [data] + copies:
+                dataset["household_weight"][time_period] = original_weights / (
+                    self.count_copies + 1
+                )
+
+        for dataset in copies:
+            data = stack_datasets(data, dataset)
+
+        self.save_dataset(data)

policyengine_uk/parameters/calibration/demographics/people/total_private_school_students.yaml

@@ -0,0 +1,17 @@
+description: Total number of private school students
+value: 
+  2015-01-01: 583_029
+  2016-01-01: 583_268
+  2017-01-01: 581_873
+  2018-01-01: 580_480
+  2019-01-01: 576_857
+  2020-01-01: 569_366
+  2021-01-01: 581_427
+  2022-01-01: 591_954
+  2023-01-01: 593_486
+metadata:
+  unit: person
+  label: total number of private school students
+  reference:
+    - title: School characteristics for Academy, Independent, Independent school, LA Maintained, Non-maintained special school and 5 other filters in England between 2015/16 and 2023/24
+      href: https://explore-education-statistics.service.gov.uk/data-tables/fast-track/27e148e3-2581-4bc3-b0bc-08dc6f35f09f

policyengine_uk/parameters/gov/contrib/labour/private_school_vat.yaml

@@ -0,0 +1,6 @@
+description: VAT rate applied to private schools.
+values:
+  2000-01-01: 0
+metadata:
+  unit: /1
+  label: private school VAT rate

policyengine_uk/parameters/gov/simulation/private_school_vat/private_school_attendance_rate.yaml

@@ -0,0 +1,49 @@
+description: Rate at which households enroll children in private schools, by percentile.
+0:
+  2000-01-01: 0
+5:
+  2000-01-01: 0.025
+10:
+  2000-01-01: 0.0125
+15:
+  2000-01-01: 0.01
+20:
+  2000-01-01: 0.005
+25:
+  2000-01-01: 0.008
+30:
+  2000-01-01: 0.01
+35:
+  2000-01-01: 0.015
+40:
+  2000-01-01: 0.01
+45:
+  2000-01-01: 0.0175
+50:
+  2000-01-01: 0.025
+55:
+  2000-01-01: 0.0175
+60:
+  2000-01-01: 0.0175
+65:
+  2000-01-01: 0.025
+70:
+  2000-01-01: 0.03
+75:
+  2000-01-01: 0.025
+80:
+  2000-01-01: 0.05
+85:
+  2000-01-01: 0.06
+90:
+  2000-01-01: 0.0875
+95:
+  2000-01-01: 0.13
+100:
+  2000-01-01: 0.47
+metadata:
+  unit: /1
+  label: percentage of students in private school, by household net income percentile
+  reference:
+  - title: Income, housing wealth, and private school access in Britain
+    href: https://www.tandfonline.com/doi/full/10.1080/09645292.2021.1874878

policyengine_uk/parameters/gov/simulation/private_school_vat/private_school_fees.yaml

@@ -0,0 +1,10 @@
+description: Mean annual private school fee
+values:
+  2022-01-01: 15_200
+metadata:
+  unit: currency-GBP
+  label: mean annual private school fee
+  reference:
+    - title: Tax, private school fees and state school spending
+      href: https://ifs.org.uk/publications/tax-private-school-fees-and-state-school-spending
+  uprating: calibration.uprating.CPI

policyengine_uk/parameters/gov/simulation/private_school_vat/private_school_vat_basis.yaml

@@ -0,0 +1,13 @@
+description: Effective percentage of private school tuition subject to VAT
+# Per IFS article
+# (https://ifs.org.uk/publications/tax-private-school-fees-and-state-school-spending),
+# about 25% of private school costs would be
+# effectively VAT-free
+values: 
+  0000-01-01: 0.75
+metadata:
+  unit: /1
+  label: private school tuition VAT basis
+  reference:
+    - title: Tax, private school fees and state school spending
+      href: https://ifs.org.uk/publications/tax-private-school-fees-and-state-school-spending

policyengine_uk/reforms/policyengine/budget_change.py

@@ -341,6 +341,7 @@ class household_tax(Variable):
         "capital_gains_tax",
         "corporate_incident_tax_revenue_change",
         "consumer_incident_tax_revenue_change",
+        "private_school_vat",
     ]
 
     def formula(household, period, parameters):

policyengine_uk/tests/policy/baseline/demographic/poverty.yaml

@@ -5,6 +5,7 @@
     age: 35
     household_gross_income: 0
     is_household_head: true
+    household_weight: 1
   output:
     poverty_gap_bhc: 220 * 52
     in_poverty_bhc: true

policyengine_uk/variables/contrib/labour/private_school_vat.py

@@ -0,0 +1,93 @@
+from policyengine_uk.model_api import *
+from policyengine_uk.variables.gov.hmrc.tax import household_tax
+
+
+class attends_private_school(Variable):
+    label = "attends private school"
+    entity = Person
+    definition_period = YEAR
+    value_type = bool
+
+    def formula(person, period, parameters):
+        household = person.household
+        # To ensure that our model matches
+        # total number of students actually enrolled
+
+        ps_vat_params = parameters(period).gov.simulation.private_school_vat
+        private_school_attendance_rate = (
+            ps_vat_params.private_school_attendance_rate
+        )
+
+        person = household.members
+
+        is_child = person("is_child", period)
+
+        taxes = household.sum(
+            person("income_tax", period) + person("national_insurance", period)
+        )
+
+        net_income = (
+            household("household_market_income", period)
+            + household("household_benefits", period)
+            - taxes
+        )
+
+        household_weight = household("household_weight", period)
+        weighted_income = MicroSeries(net_income, weights=household_weight)
+        percentile = (
+            weighted_income.percentile_rank()
+            .clip(0, 100)
+            .values.astype(numpy.int64)
+        )
+        STUDENT_POPULATION_ADJUSTMENT_FACTOR = 1.1
+
+        p_attends_private_school = (
+            np.array(
+                [
+                    interpolate_percentile(private_school_attendance_rate, p)
+                    for p in percentile
+                ]
+            )
+            * STUDENT_POPULATION_ADJUSTMENT_FACTOR
+            * is_child
+        )
+
+        return random(person) < p_attends_private_school
+
+
+class private_school_vat(Variable):
+    label = "private school VAT"
+    entity = Household
+    definition_period = YEAR
+    value_type = float
+    unit = "currency-GBP"
+
+    def formula(household, period, parameters):
+        num_children = add(household, period, ["attends_private_school"])
+
+        ps_vat_params = parameters(period).gov.simulation.private_school_vat
+        private_school_vat_basis = ps_vat_params.private_school_vat_basis
+        avg_yearly_private_school_cost = ps_vat_params.private_school_fees
+
+        private_school_vat_rate = parameters(
+            period
+        ).gov.contrib.labour.private_school_vat
+
+        return (
+            num_children
+            * avg_yearly_private_school_cost
+            * private_school_vat_rate
+            * private_school_vat_basis
+        )
+
+
+def interpolate_percentile(param, percentile):
+    if str(percentile) in param:
+        return param[str(percentile)]
+    else:
+        idx = percentile - (percentile % 5)
+        p1 = idx
+        p2 = idx + 5
+        v1 = param[str(idx)]
+        v2 = param[str(idx + 5)]
+        return v1 + (v2 - v1) * (percentile - p1) / (p2 - p1)

policyengine_uk/variables/gov/hmrc/tax.py

@@ -36,6 +36,7 @@ class household_tax(Variable):
         "carbon_tax",
         "vat_change",
         "capital_gains_tax",
+        "private_school_vat",
     ]
 
     def formula(household, period, parameters):