Read monthly SSI support in Maryland and California benefits

changelog.d/ssi-monthly-ism-state-readers.fixed.md

@@ -0,0 +1 @@
+Count each month's SSI in-kind support and maintenance in Maryland PAA income and in California's supplement for a couple with one SSI and one CAPI spouse. Read each month's SSI couple status and income deemed from an ineligible spouse in Maryland PAA income.

policyengine_us/tests/core/test_ssi_monthly_state_readers.py

@@ -0,0 +1,265 @@
+"""Check Maryland PAA and California SSP against changes to one month's ISM."""
+
+import numpy as np
+import pytest
+from hypothesis import given, settings
+from hypothesis import strategies as st
+
+from policyengine_core.periods import period as make_period
+from policyengine_us import Simulation
+from policyengine_us.system import system
+from policyengine_us.variables.gov.ssa.ssi.eligibility.income._apply_ssi_exclusions import (
+    _apply_ssi_exclusions,
+)
+
+
+YEAR = "2024"
+MONTHS = tuple(f"{YEAR}-{month:02d}" for month in range(1, 13))
+VARIABLES = (
+    "md_paa_countable_income",
+    "md_paa_imputed_federal_ssi",
+    "md_paa",
+    "ca_state_supplement_person",
+)
+
+
+def _situation(profiles, annual_earned, annual_unearned):
+    situation = {
+        group: {}
+        for group in (
+            "people",
+            "households",
+            "tax_units",
+            "marital_units",
+            "families",
+            "spm_units",
+        )
+    }
+    rows = {}
+    for name, profile in profiles.items():
+        for state, citizenship in (
+            ("MD", "CITIZEN"),
+            ("MD", "LEGAL_PERMANENT_RESIDENT"),
+            ("CA", "CITIZEN"),
+        ):
+            unit = f"{name}_{state}_{citizenship}"
+            person = f"{unit}_head"
+            members = [person]
+            rows[name, state, citizenship] = len(situation["people"])
+            values = {
+                "age": {YEAR: 70},
+                "is_tax_unit_head": {YEAR: True},
+                "immigration_status": {YEAR: citizenship},
+                "is_ssi_qualified_noncitizen": {YEAR: False},
+                "ssi_earned_income": {YEAR: annual_earned},
+                "ssi_unearned_income": {YEAR: annual_unearned},
+                "ssi_in_kind_support_and_maintenance": dict(zip(MONTHS, profile)),
+            }
+            if state == "MD":
+                values.update(
+                    md_paa_eligible={YEAR: True},
+                    md_paa_total_cost_of_care={YEAR: 18_000},
+                )
+            else:
+                # Hold federal SSI and the couple's income fixed to isolate
+                # the supplement's own-income reader for a CAPI spouse.
+                values.update(
+                    ssi={YEAR: 7_200},
+                    ssi_countable_income={YEAR: 0},
+                )
+            situation["people"][person] = values
+            if state == "CA":
+                spouse = f"{unit}_spouse"
+                members.append(spouse)
+                situation["people"][spouse] = {
+                    "age": {YEAR: 68},
+                    "is_tax_unit_spouse": {YEAR: True},
+                    "immigration_status": {YEAR: "LEGAL_PERMANENT_RESIDENT"},
+                    "ssi_qualifying_quarters_earnings": {YEAR: 39},
+                    "ssi_countable_income": {YEAR: 0},
+                }
+            for group in (
+                "households",
+                "tax_units",
+                "marital_units",
+                "families",
+                "spm_units",
+            ):
+                situation[group][unit] = {"members": members}
+            situation["households"][unit].update(
+                state_code={YEAR: state},
+                living_arrangements_allow_for_food_preparation={YEAR: True},
+            )
+    return situation, rows
+
+
+def _monthly(simulation, variable):
+    return np.stack([simulation.calculate(variable, month) for month in MONTHS])
+
+
+@settings(max_examples=8, deadline=None, database=None, derandomize=True)
+@given(
+    ism=st.integers(20, 200),
+    extra=st.integers(1, 100),
+    annual_earned=st.integers(0, 1_200),
+    annual_unearned=st.integers(0, 2_400),
+)
+def test_state_readers_keep_a_december_ism_change_in_december(
+    ism, extra, annual_earned, annual_unearned
+):
+    situation, rows = _situation(
+        {"constant": [ism] * 12, "changed": [ism] * 11 + [ism + extra]},
+        annual_earned,
+        annual_unearned,
+    )
+    simulation = Simulation(tax_benefit_system=system, situation=situation)
+    results = {name: _monthly(simulation, name) for name in VARIABLES}
+
+    for name, values in results.items():
+        assert np.all(values >= 0)
+        np.testing.assert_allclose(
+            simulation.calculate(name, YEAR), values.sum(axis=0), atol=0.01
+        )
+        for state, citizenship in (
+            ("MD", "CITIZEN"),
+            ("MD", "LEGAL_PERMANENT_RESIDENT"),
+            ("CA", "CITIZEN"),
+        ):
+            constant = rows["constant", state, citizenship]
+            changed = rows["changed", state, citizenship]
+            np.testing.assert_allclose(
+                values[:11, constant], values[:11, changed], atol=0.01
+            )
+
+    for citizenship in ("CITIZEN", "LEGAL_PERMANENT_RESIDENT"):
+        constant = rows["constant", "MD", citizenship]
+        changed = rows["changed", "MD", citizenship]
+        countable = results["md_paa_countable_income"][-1]
+        # ISM already uses the whole $20 exclusion, so each extra dollar
+        # increases this month's countable income by one dollar.
+        assert countable[changed] - countable[constant] == pytest.approx(
+            extra, abs=0.01
+        )
+        imputed = results["md_paa_imputed_federal_ssi"][-1]
+        payment = results["md_paa"][-1]
+        if citizenship == "CITIZEN":
+            assert imputed[constant] - imputed[changed] == pytest.approx(
+                extra, abs=0.01
+            )
+            # Federal SSI offsets the income change while both amounts
+            # remain below the federal benefit rate.
+            assert payment[changed] == pytest.approx(payment[constant], abs=0.01)
+        else:
+            assert imputed[constant] == imputed[changed] == 0
+            assert payment[constant] - payment[changed] == pytest.approx(
+                extra, abs=0.01
+            )
+
+    constant = rows["constant", "CA", "CITIZEN"]
+    changed = rows["changed", "CA", "CITIZEN"]
+    payment = results["ca_state_supplement_person"][-1]
+    assert payment[constant] - payment[changed] == pytest.approx(extra, abs=0.011)
+
+
+@settings(max_examples=6, deadline=None, database=None, derandomize=True)
+@given(
+    ism=st.integers(0, 400),
+    annual_earned=st.integers(0, 24_000),
+    annual_unearned=st.integers(0, 12_000),
+)
+def test_constant_ism_keeps_the_annual_exclusion_result(
+    ism, annual_earned, annual_unearned
+):
+    situation, rows = _situation(
+        {"constant": [ism] * 12}, annual_earned, annual_unearned
+    )
+    simulation = Simulation(tax_benefit_system=system, situation=situation)
+    # Constant monthly income must retain the existing annual computation.
+    annual_countable = _apply_ssi_exclusions(
+        np.array([annual_earned]),
+        np.array([annual_unearned + 12 * ism]),
+        simulation.tax_benefit_system.parameters,
+        make_period(YEAR),
+    )[0]
+    countable = annual_countable / 12
+    for citizenship in ("CITIZEN", "LEGAL_PERMANENT_RESIDENT"):
+        index = rows["constant", "MD", citizenship]
+        np.testing.assert_allclose(
+            _monthly(simulation, "md_paa_countable_income")[:, index],
+            countable,
+            atol=0.01,
+        )
+
+    index = rows["constant", "CA", "CITIZEN"]
+    payment = _monthly(simulation, "ca_state_supplement_person")[:, index]
+    # POMS SI 01415.056 B.2.a gives the 2024 aged standard of $1,182.94.
+    # Federal administration rounds a positive balance and pays at least $1.
+    # https://secure.ssa.gov/apps10/poms.nsf/lnx/0501415056
+    balance = max(1_182.94 - 600 - countable, 0)
+    if balance == 0:
+        np.testing.assert_allclose(payment, 0, atol=0.01)
+    else:
+        assert np.all(payment >= min(balance, 1))
+        np.testing.assert_allclose(payment, max(balance, 1), atol=0.011)
+
+
+def _maryland_reference_countable(monthly_earned, monthly_unearned):
+    # Maryland DHS deducts $20 from unearned income, then $65 and one-half
+    # of the remaining earned income. When unearned income falls short of
+    # $20, DHS applies the unused part to earnings (PAA Manual 900). Under
+    # COMAR 07.03.07.08(A), DHS takes these disregards "in any month".
+    # https://dhs.maryland.gov/documents/FIA/Manuals/Public%20Assistance%20to%20Adults%20%28PAA%29%20Manual/PAA%20900%20Calculation%20of%20Benefits%20rev%2011.22.docx
+    # https://regs.maryland.gov/us/md/exec/comar/07.03.07.08
+    general = min(20, monthly_unearned)
+    return monthly_unearned - general + max(monthly_earned - 65 - (20 - general), 0) / 2
+
+
+@settings(max_examples=5, deadline=None, database=None, derandomize=True)
+@given(
+    ism=st.integers(0, 19),
+    extra=st.integers(1, 19),
+    annual_earned=st.integers(0, 2_400),
+)
+def test_state_readers_keep_a_small_ism_exclusion_in_its_month(
+    ism, extra, annual_earned
+):
+    # With ISM under $20 and no other unearned income, the unused part of
+    # the $20 exclusion reduces that month's earnings and no other month's.
+    profiles = {"constant": [ism] * 12, "changed": [ism] * 11 + [ism + extra]}
+    situation, rows = _situation(profiles, annual_earned, 0)
+    simulation = Simulation(tax_benefit_system=system, situation=situation)
+    countable = _monthly(simulation, "md_paa_countable_income")
+    supplement = _monthly(simulation, "ca_state_supplement_person")
+
+    for name, profile in profiles.items():
+        expected = [
+            _maryland_reference_countable(annual_earned / 12, monthly_ism)
+            for monthly_ism in profile
+        ]
+        for citizenship in ("CITIZEN", "LEGAL_PERMANENT_RESIDENT"):
+            np.testing.assert_allclose(
+                countable[:, rows[name, "MD", citizenship]], expected, atol=0.01
+            )
+
+    constant = rows["constant", "CA", "CITIZEN"]
+    changed = rows["changed", "CA", "CITIZEN"]
+    np.testing.assert_allclose(
+        supplement[:11, constant], supplement[:11, changed], atol=0.01
+    )
+    # SSA applies the same exclusions to this person's own income in each
+    # month (20 CFR 416.1112(c)). In December, as in every other month, it
+    # pays the 2024 aged standard of $1,182.94, less $600 of SSI and that
+    # month's countable income, rounded up to the cent. For example, $10 of
+    # ISM and $200 of earnings leave 0 + (200 - 65 - 10) / 2 = $62.50
+    # countable and a $520.44 payment; a December ISM of $25 leaves
+    # (25 - 20) + (200 - 65) / 2 = $72.50 and a $510.44 payment.
+    for name, profile in profiles.items():
+        expected = [
+            1_182.94
+            - 600
+            - _maryland_reference_countable(annual_earned / 12, monthly_ism)
+            for monthly_ism in profile
+        ]
+        np.testing.assert_allclose(
+            supplement[:, rows[name, "CA", "CITIZEN"]], expected, atol=0.011
+        )

policyengine_us/tests/policy/baseline/gov/states/ca/cdss/state_supplement/ca_state_supplement.yaml

@@ -833,3 +833,115 @@
     # 1,233.94 - 0 - (800.0833 - 20) = 453.8567, which rounds up to 453.86
     # (POMS SI 02001.010 A.2).
     ca_state_supplement_person: [453.86, 0]
+
+- name: California counts January's SSI in-kind support for the SSI member of a split SSI and CAPI couple.
+  period: 2024-01
+  absolute_error_margin: 0.01
+  input:
+    people:
+      citizen:
+        age:
+          2024: 72
+        immigration_status:
+          2024: CITIZEN
+        ssi_receives_food_from_others:
+          2024: true
+      noncitizen:
+        age:
+          2024: 68
+        immigration_status:
+          2024: LEGAL_PERMANENT_RESIDENT
+        ssi_qualifying_quarters_earnings:
+          2024: 39
+    marital_units:
+      couple:
+        members: [citizen, noncitizen]
+    households:
+      household:
+        members: [citizen, noncitizen]
+        state_code:
+          2024: CA
+        living_arrangements_allow_for_food_preparation:
+          2024: true
+  output:
+    ca_capi_eligible_person: [false, true]
+    # Couple PMV = 1,415 / 3 + 20 = 491.666667 for the recipient.
+    ssi_in_kind_support_and_maintenance: [491.666667, 0]
+    # SSI = 1,415 / 2 - (491.666667 - 20) / 2 = 471.666667.
+    ssi: [471.666667, 0]
+    # Own income = 491.666667 - 20 = 471.666667.
+    # SSP = ceil_cent(1,182.94 - 471.666667 - 471.666667) = 239.61.
+    ca_state_supplement_person: [239.61, 0]
+
+- name: California counts November's SSI in-kind support in the split couple's November supplement.
+  period: 2024-11
+  absolute_error_margin: 0.01
+  input:
+    people:
+      citizen:
+        age:
+          2024: 72
+        immigration_status:
+          2024: CITIZEN
+        ssi_receives_food_from_others:
+          2024: true
+      noncitizen:
+        age:
+          2024: 68
+        immigration_status:
+          2024: LEGAL_PERMANENT_RESIDENT
+        ssi_qualifying_quarters_earnings:
+          2024: 39
+    marital_units:
+      couple:
+        members: [citizen, noncitizen]
+    households:
+      household:
+        members: [citizen, noncitizen]
+        state_code:
+          2024: CA
+        living_arrangements_allow_for_food_preparation:
+          2024: true
+  output:
+    ca_capi_eligible_person: [false, true]
+    # November uses September food; the January arithmetic still applies.
+    ssi_in_kind_support_and_maintenance: [491.666667, 0]
+    ssi: [471.666667, 0]
+    ca_state_supplement_person: [239.61, 0]
+
+- name: California counts no SSI in-kind support in the split couple's December 2024 supplement.
+  period: 2024-12
+  absolute_error_margin: 0.01
+  input:
+    people:
+      citizen:
+        age:
+          2024: 72
+        immigration_status:
+          2024: CITIZEN
+        ssi_receives_food_from_others:
+          2024: true
+      noncitizen:
+        age:
+          2024: 68
+        immigration_status:
+          2024: LEGAL_PERMANENT_RESIDENT
+        ssi_qualifying_quarters_earnings:
+          2024: 39
+    marital_units:
+      couple:
+        members: [citizen, noncitizen]
+    households:
+      household:
+        members: [citizen, noncitizen]
+        state_code:
+          2024: CA
+        living_arrangements_allow_for_food_preparation:
+          2024: true
+  output:
+    ca_capi_eligible_person: [false, true]
+    # October food no longer counts; SSI = 1,415 / 2 = 707.50.
+    ssi_in_kind_support_and_maintenance: [0, 0]
+    ssi: [707.50, 0]
+    # SSP = 1,182.94 - 707.50 - 0 = 475.44.
+    ca_state_supplement_person: [475.44, 0]