The model leaves military retired pay out of 54 benefit income lists, including WIC, HUD, Head Start and TANF #10890

from policyengine_us import Simulation

YEAR = 2026
JANUARY = f"{YEAR}-01"
STATES = (
    "AL AK AZ AR CA CO CT DE DC FL GA HI ID IL IN IA KS KY LA ME MD MA MI MN MS MO "
    "MT NE NV NH NJ NM NY NC ND OH OK OR PA RI SC SD TN TX UT VT VA WA WV WI WY"
).split()
SOURCES = ["military_retirement_pay", "taxable_private_pension_income"]


def simulate(households):
    """Each household is (state, {person: inputs}, SPM unit inputs)."""
    s = {
        key: {}
        for key in [
            "people",
            "families",
            "tax_units",
            "spm_units",
            "marital_units",
            "households",
        ]
    }
    for i, (state, people, spm_inputs) in enumerate(households):
        names = [f"{name}_{i}" for name in people]
        for pid, inputs in zip(names, people.values()):
            s["people"][pid] = {k: {YEAR: v} for k, v in inputs.items()}
        adults = [pid for pid in names if s["people"][pid]["age"][YEAR] >= 18]
        s["families"][f"family_{i}"] = {"members": names}
        s["tax_units"][f"tax_unit_{i}"] = {"members": names}
        s["spm_units"][f"spm_unit_{i}"] = {
            "members": names,
            **{k: {YEAR: v} for k, v in spm_inputs.items()},
        }
        s["marital_units"][f"marital_unit_{i}"] = {"members": adults}
        for pid in names:
            if pid not in adults:
                s["marital_units"][f"marital_unit_{pid}"] = {"members": [pid]}
        s["households"][f"household_{i}"] = {
            "members": names,
            "state_code": {YEAR: state},
        }
    return Simulation(situation=s)


# One household per income source: index 0 holds military retired pay and
# index 1 holds the same amount as a private pension.
print("WIC: Idaho parent aged 42 with $60,000 of retired pay, child aged 2")
sim = simulate(
    [("ID", {"parent": {"age": 42, src: 60_000}, "child": {"age": 2}}, {}) for src in SOURCES]
)
income = sim.calculate("wic_countable_income", YEAR)
tanf = sim.calculate("tanf", YEAR)
limit = sim.calculate("wic_income_limit", JANUARY)
meets = sim.calculate("meets_wic_income_test", JANUARY)
categorical = sim.calculate("meets_wic_categorical_eligibility", JANUARY)
wic_january = sim.calculate("wic", JANUARY)
wic_year = sim.calculate("wic", YEAR)
for j, src in enumerate(SOURCES):
    child = 2 * j + 1
    print(
        f"  {src}: countable income {income[j]:,.0f} (of which TANF {tanf[j]:,.0f}), "
        f"limit {limit[j]:,.0f}, "
        f"meets income test {bool(meets[j])}, child categorically eligible "
        f"{bool(categorical[child])}, child WIC {wic_january[child]:,.2f} in January "
        f"and {wic_year[child]:,.2f} in {YEAR}"
    )

print("HUD: Ohio tenant aged 50 with $30,000 of retired pay and $12,000 of rent, in assisted housing")
sim = simulate(
    [
        (
            "OH",
            {"tenant": {"age": 50, src: 30_000, "pre_subsidy_rent": 12_000}},
            {"receives_housing_assistance": True},
        )
        for src in SOURCES
    ]
)
for variable in ["hud_annual_income", "hud_adjusted_income", "hud_ttp"]:
    values = sim.calculate(variable, YEAR)
    print(f"  {variable}: " + ", ".join(f"{src} {v:,.2f}" for src, v in zip(SOURCES, values)))

print("Head Start: Ohio parent aged 30 with $60,000 of retired pay, child aged 4")
sim = simulate(
    [("OH", {"parent": {"age": 30, src: 60_000}, "child": {"age": 4}}, {}) for src in SOURCES]
)
gross = sim.calculate("head_start_gross_income", YEAR)
fpg = sim.calculate("spm_unit_fpg", YEAR)
income_eligible = sim.calculate("is_head_start_income_eligible", YEAR)
eligible = sim.calculate("is_head_start_eligible", YEAR)
for j, src in enumerate(SOURCES):
    child = 2 * j + 1
    print(
        f"  {src}: gross income {gross[j]:,.0f}, poverty guideline {fpg[j]:,.0f}, "
        f"child income eligible {bool(income_eligible[child])}, child eligible {bool(eligible[child])}"
    )

print("North Dakota TANF: parent aged 40 with $24,000 of retired pay, child aged 8")
sim = simulate(
    [("ND", {"parent": {"age": 40, src: 24_000}, "child": {"age": 8}}, {}) for src in SOURCES]
)
unearned = sim.calculate("nd_tanf_gross_unearned_income", JANUARY)
tanf = sim.calculate("nd_tanf", JANUARY)
for j, src in enumerate(SOURCES):
    print(
        f"  {src}: parent's gross unearned income in January {unearned[2 * j]:,.2f}, "
        f"TANF in January {tanf[j]:,.2f}"
    )

print("CSFP: couple aged 67 and 65 with $30,000 of Social Security and $45,000 of retired pay")
for src in SOURCES:
    sim = simulate(
        [
            (
                state,
                {
                    "head": {"age": 67, "social_security_retirement": 30_000, src: 45_000},
                    "spouse": {"age": 65},
                },
                {},
            )
            for state in STATES
        ]
    )
    csfp = sim.calculate("commodity_supplemental_food_program", YEAR)
    ratio = sim.calculate("school_meal_fpg_ratio", YEAR)
    countable = sim.calculate("school_meal_countable_income", YEAR)
    oh = STATES.index("OH")
    both = [state for k, state in enumerate(STATES) if csfp[2 * k] > 0 and csfp[2 * k + 1] > 0]
    print(
        f"  {src}: Ohio countable income {countable[oh]:,.0f}, income-to-poverty ratio "
        f"{ratio[oh]:.3f}, CSFP {csfp[2 * oh]:,.0f} and {csfp[2 * oh + 1]:,.0f}; "
        f"both spouses get CSFP in {len(both)} of {len(STATES)} states; "
        f"neither or one in {sorted(set(STATES) - set(both))}"
    )