Add Scotland UC households with youngest child under 1 calibration target

.github/workflows/pull_request.yaml

@@ -24,7 +24,7 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install black
+          pip install black==25.1.0
       - name: Check formatting
         run: black . -l 79 --check
   test:

changelog_entry.yaml

@@ -0,0 +1,4 @@
+- bump: minor
+  changes:
+    added:
+      - Add calibration target for UC households in Scotland with youngest child under 1 (~14k from DWP Stat-Xplore)

policyengine_uk_data/tests/test_scotland_uc_babies.py

@@ -0,0 +1,51 @@
+"""Test Scotland UC households with child under 1 calibration target.
+
+Source: DWP Stat-Xplore, UC Households dataset, November 2023
+https://stat-xplore.dwp.gov.uk/
+Filters: Scotland, Age of Youngest Child = 0
+Result: 13,992 households (~14k)
+"""
+
+import pytest
+
+
+@pytest.mark.xfail(
+    reason="Will pass after recalibration with new scotland_uc_households_child_under_1 target"
+)
+def test_scotland_uc_households_child_under_1(baseline):
+    """Test that UC households in Scotland with child under 1 matches DWP data.
+
+    Target: ~14,000 households (13,992 from Stat-Xplore November 2023)
+    Source: DWP Stat-Xplore UC Households dataset
+    """
+    region = baseline.calculate(
+        "region", map_to="household", period=2025
+    ).values
+    uc = baseline.calculate("universal_credit", period=2025).values
+    household_weight = baseline.calculate(
+        "household_weight", map_to="household", period=2025
+    ).values
+
+    # Check if household has child under 1
+    is_child = baseline.calculate(
+        "is_child", map_to="person", period=2025
+    ).values
+    age = baseline.calculate("age", map_to="person", period=2025).values
+
+    child_under_1 = is_child & (age < 1)
+    has_child_under_1 = (
+        baseline.map_result(child_under_1, "person", "household") > 0
+    )
+
+    scotland_uc_child_under_1 = (
+        (region == "SCOTLAND") & (uc > 0) & has_child_under_1
+    )
+    total = (household_weight * scotland_uc_child_under_1).sum()
+
+    TARGET = 14_000  # DWP Stat-Xplore November 2023: 13,992 rounded to 14k
+    TOLERANCE = 0.15  # 15% tolerance
+
+    assert abs(total / TARGET - 1) < TOLERANCE, (
+        f"Expected ~{TARGET/1000:.0f}k UC households with child under 1 in Scotland, "
+        f"got {total/1000:.0f}k ({total/TARGET*100:.0f}% of target)"
+    )

policyengine_uk_data/utils/loss.py

@@ -536,6 +536,27 @@ def pe_count(*variables):
     target_names.append("sss/scottish_child_payment")
     target_values.append(scp_target)
 
+    # UC households in Scotland with child under 1
+    # Source: DWP Stat-Xplore, UC Households dataset, November 2023
+    # https://stat-xplore.dwp.gov.uk/
+    # Filters: Scotland, Age of Youngest Child = 0
+    # ~14,000 households (13,992 in November 2023)
+    uc_amount = sim.calculate("universal_credit")
+    on_uc_family = uc_amount > 0
+    on_uc_household = household_from_family(on_uc_family) > 0
+
+    child_under_1 = is_child & (age < 1)
+    has_child_under_1 = household_from_person(child_under_1) > 0
+
+    scotland_uc_child_under_1 = (
+        (household_region == "SCOTLAND") & on_uc_household & has_child_under_1
+    )
+    df["dwp/scotland_uc_households_child_under_1"] = (
+        scotland_uc_child_under_1.astype(float)
+    )
+    target_names.append("dwp/scotland_uc_households_child_under_1")
+    target_values.append(14_000)  # 13,992 rounded, November 2023
+
     # Council Tax band counts
 
     ct_data = pd.read_csv(STORAGE_FOLDER / "council_tax_bands_2024.csv")

pyproject.toml

@@ -59,7 +59,7 @@ python_classes = ["Test*"]
 python_functions = ["test_*"]
 markers = [
     "slow: marks tests as slow (deselect with '-m \"not slow\"')",
-    "unit: marks tests as unit tests",  
+    "unit: marks tests as unit tests",
     "integration: marks tests as integration tests",
 ]
 filterwarnings = [