Maryland Child Tax Credit#
Maryland’s Child Tax Credit provides up to \(500 for each child with a qualified disability in a family with less than \)6,000 in federal adjusted gross income.
Examples#
Consider a set of Maryland households whose income is solely from earnings.
from policyengine_us import IndividualSim
import pandas as pd
import plotly.express as px
def make(adults, children):
sim = IndividualSim(year=2022)
sim.add_person(name="head", age=25, is_tax_unit_head=True)
members = ["head"]
if adults > 1:
sim.add_person(name="spouse", is_tax_unit_head=False)
members += ["spouse"]
for i in range(children):
child = "child{}".format(i)
sim.add_person(name=child, age=5, is_disabled=True)
members += [child]
sim.add_tax_unit(
name="tax_unit",
members=members,
)
sim.add_spm_unit(name="spm_unit", members=members)
sim.add_household(name="household", members=members, state_code="MD")
sim.vary("employment_income", max=100_000, step=100)
return pd.DataFrame(
dict(
employment_income=sim.calc("employment_income")[0],
ctc=sim.calc("md_ctc")[0].round(),
ctc_mtr=-sim.deriv(
"md_ctc",
"employment_income",
wrt_target="head",
),
adults=adults,
children=children,
)
)
l = []
for adults in range(1, 3):
for children in range(0, 5):
l.append(make(adults, children))
df = pd.concat(l)
LABELS = dict(
employment_income="Employment income",
ctc="MD Child Tax Credit",
ctc_mtr="MD Child Tax Credit marginal tax rate",
adults="Adults",
children="Children",
)
fig = px.line(
df,
"employment_income",
"ctc",
color="children",
animation_frame="adults",
labels=LABELS,
title="Maryland Child Tax Credit",
)
fig.update_layout(
xaxis_tickformat="$,",
yaxis_tickformat="$,",
yaxis_range=[0, df.ctc.max() * 1.05],
)
fig.show()
The Maryland Child Tax Credit is a flat amount for each eligible child. There is no phase out of the credit, and the amount of the credit falls to zero for households with income above $6,000.
Budgetary impact#
PolicyEngine US does not yet impute the number of children with disabilities in a household, so the budgetary impact is not yet known.
from policyengine_us import Microsimulation
sim = Microsimulation(dataset_year=2020)
sim.calc("md_ctc", period=2022).sum() / 1e6
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/tmp/ipykernel_3239/2916062418.py in <cell line: 0>()
1 from policyengine_us import Microsimulation
2
----> 3 sim = Microsimulation(dataset_year=2020)
4
5 sim.calc("md_ctc", period=2022).sum() / 1e6
~/work/policyengine-us/policyengine-us/policyengine_us/system.py in __init__(self, *args, **kwargs)
136
137 def __init__(self, *args, **kwargs):
--> 138 super().__init__(*args, **kwargs)
139
140 reform = create_structural_reforms_from_parameters(
TypeError: Simulation.__init__() got an unexpected keyword argument 'dataset_year'