Temporary Assistance for Needy Families (TANF)#

TANF is a state-level benefit program run by the Department of Health and Human Services, part of which funds cash assistance.

From benefits.gov:

The Temporary Assistance for Needy Families (TANF) program provides grant funds to states and territories to provide families with financial assistance and related support services. State-administered programs may include childcare assistance, job preparation, and work assistance.

General formula#

To calculate TANF entitlement, we use the general computation tree below (may vary depending on state and county):

tanf: TANF entitlement
- tanf_amount_if_eligible: amount if eligible
  - Definition: tanf_max_amount - tanf_countable_income
  - tanf_max_amount: maximum amount
    - Parameters: the maximum amount defined by different state TANF programs may vary due to these factors:
      - Household size: How many people live in the household.
      - “Region”: Some states may define a “region”-level distinction for maximum amounts; for example, California (CalWORKS) defines two regions based on what county the household resides in.
      - Individual household properties such as caregiver or disability status.
      - Example: California (CalWORKS) has different maximum amounts based on these factors, which they define as “exempt/non-exempt”.
      - State-specific policies.
  - tanf_countable_income: Amount deducted from TANF maximum amount based on income.
    - tanf_gross_earned_income: earned income.
      - Parameter: list of earned income sources summed.
    - tanf_gross_unearned_income: unearned income. (ADD DEF HERE)
      - Parameter: list of unearned income sources summed.
    - deductions: deductions from assessed income.
      - earnings_deduction: deduction amount based on earnings.
        
        Parameter: percentage of earnings deducted from gross earned income.
        
        Parameter: flat amount deducted from the household’s gross earned income.
        
        Parameter: flat amount deducted from each earner’s gross earned income.
- is_tanf_eligible: whether eligible for TANF
  - is_tanf_enrolled: whether a family is already enrolled in TANF.
  - is_tanf_demographically_eligible: demographic definition of TANF eligibility, which is mostly constant across the US.
    - Definition: If there are children (ages 0-17) present in the household, pregnant people, or there are people aged 18 years old that are currently enrolled in a school, the family is demographically eligible for TANF.
  - is_tanf_economically_eligible: Whether the family has sufficiently low income to qualify for eligibility.
    - is_tanf_enrolled: whether a family is already enrolled in TANF.
    - is_tanf_continuous_eligible:
      - tanf_eligibility_income: income measure used to assess eligibility for TANF.
        
        Parameters: income definition varies depending on state policies:
        
        Parameter: deductions from income per earner
        
        Parameter: deductions from income per household
      - tanf_max_amount (defined above)
    - is_tanf_initial_eligible:
      - This variable is very similar to is_continuous_eligible, except for the initial employment deductions that are applied to determininig initial eligibility.
      - tanf_eligibility_income: income measure used to assess eligibility for TANF.
        
        Parameters: income definition varies depending on state policies:
        
        Parameter: deductions from income per earner
        
        Parameter: deductions from income per household
      - tanf_max_amount (defined above)

from policyengine_us import IndividualSim
import pandas as pd
import plotly.express as px

sim_emp = IndividualSim(year=2022)
sim_emp.add_person(name="adult", age=30, employment_income=250 * 12)
sim_emp.add_person(name="child", age=10)
sim_emp.add_spm_unit(name="spm_unit", members=["adult", "child"])
sim_emp.add_household(
    name="household", members=["adult", "child"], state_code="IL"
)

print("TANF: ", sim_emp.calc("tanf") / 12)

TANF:  [372.5]

Their benefit falls steadily with earnings, until they earn $430 per month, at which point they no longer qualify (assuming they are already enrolled).

LABELS = dict(
    employment_income="Monthly employment income",
    dividend_income="Monthly dividend income",
    monthly_income="Monthly income",
    income_source="Income source",
    monthly_tanf="Monthly TANF allotment",
    mtr="Marginal tax rate from TANF?",
    allotment="TANF allotment",
    state_code="State",
)


def make_df(state_code, enrolled, vary_var):
    sim = IndividualSim(year=2022)
    sim.add_person(name="adult", age=30)
    sim.add_person(name="child", age=10)
    sim.add_spm_unit(
        name="spm_unit", members=["adult", "child"], is_tanf_enrolled=enrolled
    )
    sim.add_household(
        name="household", members=["adult", "child"], state_code=state_code
    )

    sim.vary(vary_var, max=1500 * 12, step=120)

    return pd.DataFrame(
        dict(
            monthly_income=sim.calc(vary_var)[0] / 12,
            enrolled="Enrolled" if enrolled else "Not Enrolled",
            state_code=state_code,
            monthly_tanf=sim.calc("tanf")[0] / 12,
            vary_var=vary_var,
            # mtr=-sim.deriv("tanf", "employment_income"),
        )
    )


fig = px.line(
    make_df("IL", True, "employment_income"),
    "monthly_income",
    "monthly_tanf",
    labels=LABELS,
    title="TANF allotment for a two-person household in Illinois",
)

fig.update_layout(xaxis_tickformat="$,", yaxis_tickformat="$,")
fig.show()