Maryland Poverty Line Credit#
Maryland’s Poverty Line Credit provides up to 5% of earned income to eligible Maryland filers with income below the poverty line.
Examples#
Because the Poverty Line Credit is based on the poverty line relative to the Earned Income Tax Credit, which is more generous for families with children and which doesn’t give more for families with more than three children, it primarily reaches low-income childless filers and filers with more than six children.
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)
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],
plc=sim.calc("md_poverty_line_credit")[0].round(),
plc_mtr=-sim.deriv(
"md_poverty_line_credit",
"employment_income",
wrt_target="head",
),
adults=adults,
children=children,
)
)
l = []
for adults in range(1, 3):
for children in range(0, 10):
l.append(make(adults, children))
df = pd.concat(l)
LABELS = dict(
employment_income="Employment income",
plc="MD Poverty Line Credit",
plc_mtr="MD Poverty Line Credit marginal tax rate",
adults="Adults",
children="Children",
)
fig = px.line(
df,
"employment_income",
"plc",
color="children",
animation_frame="adults",
labels=LABELS,
title="Maryland Poverty Line Credit",
)
fig.update_layout(
xaxis_tickformat="$,",
yaxis_tickformat="$,",
yaxis_range=[0, df.plc.max() * 1.05],
)
fig.show()