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)
Examples

A single parent of one in Illinois with earnings of $250 per month will receive $372.50 per month in TANF benefits.

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()

This household’s TANF benefit would vary depending on their state and whether they are already enrolled.

emp_df_combined = pd.concat(
    [
        make_df("IL", True, "employment_income"),
        make_df("IL", False, "employment_income"),
        make_df("CA", True, "employment_income"),
        make_df("CA", False, "employment_income"),
    ]
)

fig = px.line(
    emp_df_combined,
    "monthly_income",
    "monthly_tanf",
    color="enrolled",
    labels=LABELS,
    animation_frame="state_code",
    title="TANF allotment for a two-person household",
)

fig.update_layout(
    xaxis_tickformat="$,",
    yaxis_tickformat="$,",
    yaxis_range=[0, emp_df_combined.monthly_tanf.max() * 1.1],
    legend_title=None,
)
fig.show()

If the household’s income is from Social Security instead of employment income, their TANF benefit phases out differently, and prior enrollment doesn’t affect the benefit.

ss_df_combined = pd.concat(
    [
        make_df("IL", True, "social_security_disability"),
        make_df("IL", False, "social_security_disability"),
        make_df("CA", True, "social_security_disability"),
        make_df("CA", False, "social_security_disability"),
    ]
)

fig_ss = px.line(
    ss_df_combined,
    "monthly_income",
    "monthly_tanf",
    color="enrolled",
    labels=LABELS,
    animation_frame="state_code",
    title="TANF allotment for a two-person household as Social Security income varies",
)

fig_ss.update_layout(
    xaxis_tickformat="$,",
    yaxis_tickformat="$,",
    yaxis_range=[0, ss_df_combined.monthly_tanf.max() * 1.1],
    legend_title=None,
)
fig_ss.show()

Temporary Assistance for Needy Families (TANF)¶

General formula¶

Examples