Add INITIAL non-dom status

changelog_entry.yaml

@@ -0,0 +1,4 @@
+- bump: minor
+  changes:
+    added:
+    - Non-dom status switch.

policyengine_uk/data/datasets/frs/enhanced_frs.py

@@ -153,7 +153,7 @@ class EnhancedFRS(Dataset):
     data_format = Dataset.TIME_PERIOD_ARRAYS
     num_years = 7
     time_period = 2021
-    count_copies = 4
+    count_copies = 9
     url = "release://policyengine/non-public-microdata/uk-2024-march-efo/enhanced_frs.h5"
 
     def generate(self):

policyengine_uk/parameters/gov/hmrc/income_tax/reliefs/non_domiciled_status.yaml

@@ -0,0 +1,6 @@
+description: Whether individuals can claim non-domiciled status for tax purposes.
+values:
+  2000-01-01: true
+metadata:
+  unit: bool
+  label: allow non-domiciled tax status

policyengine_uk/parameters/gov/simulation/non_domiciled_status/proportion_by_income.yaml

@@ -0,0 +1,43 @@
+description: Proportion of non-domiciled people by income band.
+brackets:
+  - threshold:
+      2022-01-01: 0
+    amount:
+      2022-01-01: 0 # Actually 0.03 but 0 to be safe
+  - threshold:
+      2022-01-01: 100_000
+    amount:
+      2022-01-01: 0.052
+  - threshold:
+      2022-01-01: 200_000
+    amount:
+      2022-01-01: 0.134
+  - threshold:
+      2022-01-01: 500_000
+    amount:
+      2022-01-01: 0.211
+  - threshold:
+      2022-01-01: 1_000_000
+    amount:
+      2022-01-01: 0.268
+  - threshold:
+      2022-01-01: 2_000_000
+    amount:
+      2022-01-01: 0.344
+  - threshold:
+      2022-01-01: 5_000_000
+    amount:
+      2022-01-01: 0.414
+  - threshold:
+      2022-01-01: 10_000_000
+    amount:
+      2022-01-01: 0.4
+
+metadata:
+  label: proportion of non-domiciled individuals by income band
+  type: single_amount
+  threshold_unit: currency-GBP
+  amount_unit: /1
+  reference:
+    - title: CAGE Policy Briefing no. 36
+      href: https://warwick.ac.uk/fac/soc/economics/research/centres/cage/manage/publications/bn36.2022.pdf

policyengine_uk/parameters/gov/simulation/non_domiciled_status/total.yaml

@@ -0,0 +1,9 @@
+description: Total number of non-domiciled people.
+values:
+  2022-01-01: 238_000
+metadata:
+  unit: person
+  label: total non-domiciled individuals
+  reference:
+    - title: CAGE Policy Briefing no. 36
+      href: https://warwick.ac.uk/fac/soc/economics/research/centres/cage/manage/publications/bn36.2022.pdf

policyengine_uk/variables/gov/hmrc/income_tax/relief.py

@@ -327,6 +327,10 @@ def formula(person, period, parameters):
             "taxable_dividend_income",
             "taxable_miscellaneous_income",
         ]
+        if not parameters(
+            period
+        ).gov.hmrc.income_tax.reliefs.non_domiciled_status:
+            COMPONENTS.append("worldwide_income")
         if parameters(
             period
         ).gov.contrib.ubi_center.basic_income.interactions.include_in_taxable_income:

policyengine_uk/variables/household/income/worldwide_income.py

@@ -0,0 +1,57 @@
+from policyengine_uk.model_api import *
+
+
+class is_non_domiciled(Variable):
+    label = "non-domiciled"
+    documentation = "Whether the person is non-domiciled for tax purposes."
+    entity = Person
+    definition_period = YEAR
+    value_type = bool
+
+    def formula(person, period, parameters):
+        if not hasattr(person.simulation, "dataset"):
+            return 0
+        if person.simulation.dataset.name != "enhanced_frs":
+            return 0
+        total_income = person("total_income", period)
+        non_dom = parameters(period).gov.simulation.non_domiciled_status
+        weight = person("person_weight", period)
+
+        thresholds = non_dom.proportion_by_income.thresholds
+        shares_of_non_doms = non_dom.proportion_by_income.amounts
+        probabilities = np.zeros_like(total_income)
+        ADJUSTMENT_FACTOR = 1e3
+        for i in range(len(thresholds)):
+            lower = thresholds[i]
+            upper = thresholds[i + 1] if i + 1 < len(thresholds) else np.inf
+            in_range = (total_income >= lower) & (total_income < upper)
+            total_population = weight[in_range].sum()
+            percent_non_dom = where(
+                total_population == 0,
+                0,
+                shares_of_non_doms[i] / total_population,
+            )
+            probability = 1 - (1 - percent_non_dom) ** ADJUSTMENT_FACTOR
+            probabilities[in_range] = probability
+
+        return random(person) < probabilities
+
+
+class worldwide_income(Variable):
+    label = "worldwide income"
+    documentation = "Income not taxed due to non-domiciled status."
+    entity = Person
+    definition_period = YEAR
+    value_type = float
+    unit = GBP
+
+    def formula(person, period, parameters):
+        ADJUSTMENT_FACTOR = 2.7  # Gets 3.2bn from abolishing non-dom status
+        total_income = person("total_income", period)
+        is_non_dom = person("is_non_domiciled", period)
+
+        return where(
+            is_non_dom,
+            total_income * ADJUSTMENT_FACTOR,
+            0,
+        )