# Child and Dependent Care Credit#

The Child and Dependent Care Tax Credit (CDCC) provides a share of care expenses depending on income.

## Examples#

Consider a single parent with $8,000 child care expenses per child (the CDCC’s maximum in 2021, up to two children). Since the CDCC is capped at the lower of head and spouse’s earnings, this example is limited to single parents. In 2020, the CDCC phased out only at one level; in 2021 only, it phased out twice, and in 2022 and beyond, it returns to 2020 law. from openfisca_us import IndividualSim import pandas as pd import plotly.express as px def make_cdcc(children, year): sim = IndividualSim(year=year) sim.add_person(name="head", is_tax_unit_head=True) members = ["head"] for i in range(children): child = "child{}".format(i) sim.add_person(name=child, age=5) members += [child] sim.add_tax_unit( name="tax_unit", members=members, tax_unit_childcare_expenses=8_000 * children, ) sim.add_spm_unit(name="spm_unit", members=members) sim.add_household(name="household", members=members, state_code="MD") sim.vary("employment_income", max=500_000) return pd.DataFrame( dict( employment_income=sim.calc("employment_income"), cdcc=sim.calc("cdcc").round(), cdcc_mtr=-sim.deriv( "cdcc", "employment_income", wrt_target="head", ), children=children, year=year, ) ) # Make a table of CDCC amounts for different numbers of adults and children. l = [] for year in [2020, 2021, 2022]: for children in range(1, 3): l.append(make_cdcc(children, year)) df = pd.concat(l) LABELS = dict( employment_income="Employment income", cdcc="CDCC", cdcc_mtr="CDCC Marginal Tax Rate", children="Children", year="Year", ) fig = px.line( df, "employment_income", "cdcc", color="children", animation_frame="year", labels=LABELS, title="Child and Dependent Care Credit", ) fig.update_layout( xaxis_tickformat="$,",
yaxis_tickformat="\$,",
yaxis_range=[0, df.cdcc.max() * 1.05],
)
fig.show()