def taxcalc_results(start_year, reform_dict, itax_clp, ptax_clp):
"""
Use taxcalc package on this computer to compute aggregate income tax and
payroll tax revenue difference (between reform and current-law policy)
for ten years beginning with the specified start_year using the specified
reform_dict dictionary and the two specified current-law-policy results
dictionaries.
Return two aggregate tax revenue difference dictionaries indexed by
calendar year.
"""
pol = Policy()
pol.implement_reform(reform_dict)
calc = Calculator(policy=pol,
records=Records(data=PUF_PATH),
verbose=False)
calc.advance_to_year(start_year)
nyears = NUMBER_OF_YEARS
adts = list()
for iyr in range(-1, nyears - 1):
calc.calc_all()
adts.append(create_diagnostic_table(calc))
if iyr < nyears:
calc.increment_year()
adt = pd.concat(adts, axis=1)
# note that adt is Pandas DataFrame object
itax_ref = adt.xs('Ind Income Tax ($b)').to_dict()
ptax_ref = adt.xs('Payroll Taxes ($b)').to_dict()
itax_diff = {}
ptax_diff = {}
for year in itax_ref:
itax_diff[year] = round(itax_ref[year] - itax_clp[year], 1)
ptax_diff[year] = round(ptax_ref[year] - ptax_clp[year], 1)
return (itax_diff, ptax_diff)
def taxcalc_clp_results():
"""
Use taxcalc package on this computer to compute aggregate income tax
and payroll tax revenues for years beginning with MIN_START_YEAR and
ending with MAX_START_YEAR+NUMBER_OF_YEARS-1 for current-law policy.
Return two aggregate revenue dictionaries indexed by calendar year.
"""
calc = Calculator(policy=Policy(),
records=Records(data=PUF_PATH),
verbose=False)
nyears = MAX_START_YEAR + NUMBER_OF_YEARS - MIN_START_YEAR - 1
adts = list()
for iyr in range(-1, nyears - 1):
calc.calc_all()
adts.append(create_diagnostic_table(calc))
if iyr < nyears:
calc.increment_year()
adt = pd.concat(adts, axis=1)
# note that adt is Pandas DataFrame object
return (adt.xs('Ind Income Tax ($b)').to_dict(),
adt.xs('Payroll Taxes ($b)').to_dict())
def test_Calculator_create_diagnostic_table(records_2009):
calc = Calculator(policy=Policy(), records=records_2009)
calc.calc_all()
adt = create_diagnostic_table(calc)
assert isinstance(adt, pd.DataFrame)
def test_Calculator_create_diagnostic_table(cps_subsample):
recs = Records.cps_constructor(data=cps_subsample)
calc = Calculator(policy=Policy(), records=recs)
calc.calc_all()
adt = create_diagnostic_table(calc)
assert isinstance(adt, pd.DataFrame)
def test_Calculator_create_diagnostic_table(records_2009):
calc = Calculator(policy=Policy(), records=records_2009)
calc.calc_all()
adt = create_diagnostic_table(calc)
assert isinstance(adt, pd.DataFrame)