Add PLA and ADG SLC targets

changelog.d/pla-adg-targets.added.md

@@ -0,0 +1 @@
+Add SLC calibration targets for Parents' Learning Allowance and Adult Dependants' Grant.

policyengine_uk_data/targets/build_loss_matrix.py

@@ -31,8 +31,8 @@
     compute_housing,
     compute_income_band,
     compute_land_value,
-    compute_maintenance_loan,
     compute_regional_land_value,
+    compute_person_support,
     compute_obr_council_tax,
     compute_pip_claimants,
     compute_regional_age,
@@ -321,8 +321,15 @@ def _compute_column(target: Target, ctx: _SimContext, year: int) -> np.ndarray |
     # Student loan plan borrower counts (SLC)
     if name.startswith("slc/student_loan_repayment/"):
         return compute_student_loan_repayment(target, ctx)
-    if name in ("slc/maintenance_loan_recipients", "slc/maintenance_loan_spend"):
-        return compute_maintenance_loan(target, ctx)
+    if name in (
+        "slc/maintenance_loan_recipients",
+        "slc/maintenance_loan_spend",
+        "slc/parents_learning_allowance_recipients",
+        "slc/parents_learning_allowance_spend",
+        "slc/adult_dependants_grant_recipients",
+        "slc/adult_dependants_grant_spend",
+    ):
+        return compute_person_support(target, ctx)
     if name.startswith("slc/plan_") and "above_threshold" in name:
         return compute_student_loan_plan(target, ctx)
     if name.startswith("slc/plan_") and "liable" in name:

policyengine_uk_data/targets/compute/__init__.py

@@ -34,9 +34,9 @@
     compute_ss_ni_relief,
 )
 from policyengine_uk_data.targets.compute.other import (
-    compute_maintenance_loan,
     compute_housing,
     compute_land_value,
+    compute_person_support,
     compute_regional_land_value,
     compute_savings_interest,
     compute_scottish_child_payment,
@@ -54,10 +54,10 @@
     "compute_household_type",
     "compute_housing",
     "compute_land_value",
-    "compute_maintenance_loan",
     "compute_regional_land_value",
     "compute_income_band",
     "compute_obr_council_tax",
+    "compute_person_support",
     "compute_pip_claimants",
     "compute_regional_age",
     "compute_savings_interest",

policyengine_uk_data/targets/compute/other.py

@@ -1,6 +1,7 @@
 """Miscellaneous compute functions (vehicles, housing, savings, SCP, student loans)."""
 
 import numpy as np
+from policyengine_uk_data.targets.schema import Unit
 
 _STUDENT_LOAN_COUNTRIES = {
     "england": "ENGLAND",
@@ -128,11 +129,11 @@ def compute_student_loan_repayment(target, ctx) -> np.ndarray:
     return ctx.household_from_person(repayments * mask)
 
 
-def compute_maintenance_loan(target, ctx) -> np.ndarray:
-    """Compute maintenance-loan recipient-count and spend targets."""
-    maintenance_loan = ctx.pe_person("maintenance_loan")
-    if target.name == "slc/maintenance_loan_recipients":
-        return ctx.household_from_person((maintenance_loan > 0).astype(float))
-    if target.name == "slc/maintenance_loan_spend":
-        return ctx.household_from_person(maintenance_loan)
+def compute_person_support(target, ctx) -> np.ndarray:
+    """Compute recipient-count and spend targets for person-level support variables."""
+    values = ctx.pe_person(target.variable)
+    if target.is_count or target.unit == Unit.COUNT:
+        return ctx.household_from_person((values > 0).astype(float))
+    if target.unit == Unit.GBP:
+        return ctx.household_from_person(values)
     return None

policyengine_uk_data/targets/sources/slc.py

@@ -2,11 +2,13 @@
 
 Borrower counts for England only: Plan 2 and Plan 5.
 
-Two target types are exposed:
+Three target families are exposed:
 - `above_threshold`: borrowers liable to repay and earning above threshold
 - `liable`: all borrowers liable to repay, including below-threshold holders
 - `maintenance_loan`: full-time undergraduate England maintenance-loan
   recipient counts and total amount paid
+- `parents_learning_allowance` and `adult_dependants_grant`: full-time
+  undergraduate England grant recipient counts and amounts awarded
 
 Source: Explore Education Statistics — Student loan forecasts for England,
 Table 6a: Forecast number of student borrowers liable to repay and number
@@ -18,6 +20,11 @@
 England 2025, Table 3A: Maintenance Loans paid to full-time undergraduate
 students. Academic year 20XX/YY maps to calendar year 20XX+1.
 
+Parents' Learning Allowance and Adult Dependants' Grant targets come from
+Student support for higher education in England 2025, Table 4C (i):
+Other targeted support awarded to full-time applicants. Academic year
+20XX/YY maps to calendar year 20XX+1.
+
 Data permalink:
 https://explore-education-statistics.service.gov.uk/data-tables/permalink/6ff75517-7124-487c-cb4e-08de6eccf22d
 """
@@ -37,7 +44,7 @@
     f"https://explore-education-statistics.service.gov.uk"
     f"/data-tables/permalink/{_PERMALINK_ID}"
 )
-_MAINTENANCE_LOAN_URL = (
+_STUDENT_SUPPORT_URL = (
     "https://assets.publishing.service.gov.uk/media/"
     "691d9e662c6b98ecdbc5003f/slcsp052025.xlsx"
 )
@@ -109,6 +116,68 @@
         2025: 8_591_659_718,
     },
 }
+_TARGETED_SUPPORT_TESTING_DATA = {
+    "adult_dependants_grant": {
+        "recipients": {
+            2014: 13_836,
+            2015: 14_420,
+            2016: 13_877,
+            2017: 14_222,
+            2018: 15_410,
+            2019: 16_336,
+            2020: 19_603,
+            2021: 22_453,
+            2022: 23_699,
+            2023: 20_226,
+            2024: 17_960,
+            2025: 18_611,
+        },
+        "amount_paid": {
+            2014: 33_050_091,
+            2015: 34_538_762,
+            2016: 34_065_350,
+            2017: 34_884_056,
+            2018: 38_145_981,
+            2019: 41_154_737,
+            2020: 48_060_995,
+            2021: 56_104_466,
+            2022: 60_506_271,
+            2023: 54_638_997,
+            2024: 51_719_576,
+            2025: 55_364_917,
+        },
+    },
+    "parents_learning_allowance": {
+        "recipients": {
+            2014: 49_219,
+            2015: 49_409,
+            2016: 47_414,
+            2017: 47_772,
+            2018: 52_568,
+            2019: 57_408,
+            2020: 66_407,
+            2021: 76_740,
+            2022: 82_911,
+            2023: 89_283,
+            2024: 95_287,
+            2025: 99_645,
+        },
+        "amount_paid": {
+            2014: 70_524_886,
+            2015: 71_710_128,
+            2016: 70_799_276,
+            2017: 70_955_697,
+            2018: 80_020_029,
+            2019: 90_006_145,
+            2020: 106_581_771,
+            2021: 126_314_502,
+            2022: 139_380_387,
+            2023: 153_266_251,
+            2024: 168_349_637,
+            2025: 181_421_659,
+        },
+    },
+}
 
 
 def get_snapshot_data() -> dict:
@@ -128,6 +197,14 @@ def get_maintenance_loan_snapshot_data() -> dict:
     }
 
 
+def get_targeted_support_snapshot_data() -> dict:
+    """Return the checked-in targeted-support snapshot."""
+    return {
+        product: {key: values.copy() for key, values in product_data.items()}
+        for product, product_data in _TARGETED_SUPPORT_TESTING_DATA.items()
+    }
+
+
 @lru_cache(maxsize=1)
 def _fetch_slc_data() -> dict:
     """Fetch and parse SLC Table 6a data from Explore Education Statistics.
@@ -232,7 +309,7 @@ def _fetch_maintenance_loan_data() -> dict:
     if os.environ.get("TESTING", "0") == "1":
         return get_maintenance_loan_snapshot_data()
 
-    df = pd.read_excel(_MAINTENANCE_LOAN_URL, sheet_name="Table 3A", header=None)
+    df = pd.read_excel(_STUDENT_SUPPORT_URL, sheet_name="Table 3A", header=None)
 
     count_header_row = _find_row(df, "Number of students paid (000s) [27]")
     count_year_row = count_header_row + 1
@@ -266,10 +343,65 @@ def _fetch_maintenance_loan_data() -> dict:
     }
 
 
+def _series_from_row(
+    df: pd.DataFrame, year_row: int, value_row: int, multiplier: int
+) -> dict:
+    year_columns = {}
+    for column, value in df.iloc[year_row].items():
+        if isinstance(value, str) and re.fullmatch(r"\d{4}/\d{2}", value):
+            year_columns[column] = int(value[:4]) + 1
+
+    if not year_columns:
+        raise ValueError("Could not find year columns")
+
+    values = {}
+    for column, year in year_columns.items():
+        raw_value = df.iloc[value_row, column]
+        if pd.notna(raw_value) and raw_value not in (".", "-", ":"):
+            values[year] = int(round(float(raw_value) * multiplier))
+    return values
+
+
+@lru_cache(maxsize=1)
+def _fetch_targeted_support_data() -> dict:
+    """Fetch Adult Dependants' Grant and Parents' Learning Allowance targets."""
+    if os.environ.get("TESTING", "0") == "1":
+        return get_targeted_support_snapshot_data()
+
+    df = pd.read_excel(_STUDENT_SUPPORT_URL, sheet_name="Table 4C (i)(ii)", header=None)
+
+    count_year_row = _find_row(df, "2013/14")
+    amount_year_row = _find_row(df, "2013/14", start=count_year_row + 1)
+    adg_count_row = _find_row(df, "Adult Dependents Grant", start=count_year_row)
+    pla_count_row = _find_row(df, "Parents Learning Allowance", start=count_year_row)
+    adg_amount_row = _find_row(df, "Adult Dependents Grant", start=amount_year_row)
+    pla_amount_row = _find_row(df, "Parents Learning Allowance", start=amount_year_row)
+
+    return {
+        "adult_dependants_grant": {
+            "recipients": _series_from_row(
+                df, count_year_row, adg_count_row, multiplier=1_000
+            ),
+            "amount_paid": _series_from_row(
+                df, amount_year_row, adg_amount_row, multiplier=1_000_000
+            ),
+        },
+        "parents_learning_allowance": {
+            "recipients": _series_from_row(
+                df, count_year_row, pla_count_row, multiplier=1_000
+            ),
+            "amount_paid": _series_from_row(
+                df, amount_year_row, pla_amount_row, multiplier=1_000_000
+            ),
+        },
+    }
+
+
 def get_targets() -> list[Target]:
     """Generate SLC calibration targets by fetching live data."""
     slc_data = _fetch_slc_data()
     maintenance_loan_data = _fetch_maintenance_loan_data()
+    targeted_support_data = _fetch_targeted_support_data()
 
     targets = []
 
@@ -299,15 +431,53 @@ def get_targets() -> list[Target]:
                 unit=Unit.COUNT,
                 is_count=True,
                 values=maintenance_loan_data["recipients"],
-                reference_url=_MAINTENANCE_LOAN_URL,
+                reference_url=_STUDENT_SUPPORT_URL,
             ),
             Target(
                 name="slc/maintenance_loan_spend",
                 variable="maintenance_loan",
                 source="slc",
                 unit=Unit.GBP,
                 values=maintenance_loan_data["amount_paid"],
-                reference_url=_MAINTENANCE_LOAN_URL,
+                reference_url=_STUDENT_SUPPORT_URL,
+            ),
+            Target(
+                name="slc/parents_learning_allowance_recipients",
+                variable="parents_learning_allowance",
+                source="slc",
+                unit=Unit.COUNT,
+                is_count=True,
+                values=targeted_support_data["parents_learning_allowance"][
+                    "recipients"
+                ],
+                reference_url=_STUDENT_SUPPORT_URL,
+            ),
+            Target(
+                name="slc/parents_learning_allowance_spend",
+                variable="parents_learning_allowance",
+                source="slc",
+                unit=Unit.GBP,
+                values=targeted_support_data["parents_learning_allowance"][
+                    "amount_paid"
+                ],
+                reference_url=_STUDENT_SUPPORT_URL,
+            ),
+            Target(
+                name="slc/adult_dependants_grant_recipients",
+                variable="adult_dependants_grant",
+                source="slc",
+                unit=Unit.COUNT,
+                is_count=True,
+                values=targeted_support_data["adult_dependants_grant"]["recipients"],
+                reference_url=_STUDENT_SUPPORT_URL,
+            ),
+            Target(
+                name="slc/adult_dependants_grant_spend",
+                variable="adult_dependants_grant",
+                source="slc",
+                unit=Unit.GBP,
+                values=targeted_support_data["adult_dependants_grant"]["amount_paid"],
+                reference_url=_STUDENT_SUPPORT_URL,
             ),
         ]
     )