def test_create_parameters_from_file(policyfile):
with open(policyfile.name) as pfile:
policy = json.load(pfile)
ppo = Policy(parameter_dict=policy)
irates = Policy.default_inflation_rates()
inf_rates = [irates[ppo.start_year + i] for i in range(0, ppo.num_years)]
assert_allclose(ppo._almdep,
Policy.expand_array(np.array([7150, 7250, 7400]),
inflate=True,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01, rtol=0.0)
assert_allclose(ppo._almsep,
Policy.expand_array(np.array([40400, 41050]),
inflate=True,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01, rtol=0.0)
assert_allclose(ppo._rt5,
Policy.expand_array(np.array([0.33]),
inflate=False,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01, rtol=0.0)
assert_allclose(ppo._rt7,
Policy.expand_array(np.array([0.396]),
inflate=False,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01, rtol=0.0)
def test_create_parameters_from_file(policyfile):
with open(policyfile.name) as pfile:
policy = json.load(pfile)
ppo = Policy(parameter_dict=policy)
irates = Policy.default_inflation_rates()
inf_rates = [irates[ppo.start_year + i] for i in range(0, ppo.num_years)]
assert_allclose(ppo._almdep,
Policy.expand_array(np.array([7150, 7250, 7400]),
inflate=True,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01,
rtol=0.0)
assert_allclose(ppo._almsep,
Policy.expand_array(np.array([40400, 41050]),
inflate=True,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01,
rtol=0.0)
assert_allclose(ppo._rt5,
Policy.expand_array(np.array([0.33]),
inflate=False,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01,
rtol=0.0)
assert_allclose(ppo._rt7,
Policy.expand_array(np.array([0.396]),
inflate=False,
inflation_rates=inf_rates,
num_years=ppo.num_years),
atol=0.01,
rtol=0.0)
def test_make_Calculator_user_mods_with_cpi_flags(policyfile, puf_1991):
with open(policyfile.name) as pfile:
policy = json.load(pfile)
ppo = Policy(parameter_dict=policy,
start_year=1991,
num_years=len(IRATES),
inflation_rates=IRATES,
wage_growth_rates=WRATES)
rec = Records(data=puf_1991, start_year=1991)
calc = Calculator(policy=ppo, records=rec)
user_mods = {
1991: {
"_almdep": [7150, 7250, 7400],
"_almdep_cpi": True,
"_almsep": [40400, 41050],
"_almsep_cpi": False,
"_rt5": [0.33],
"_rt7": [0.396]
}
}
calc.policy.implement_reform(user_mods)
# compare actual and expected values
inf_rates = [IRATES[1991 + i] for i in range(0, Policy.DEFAULT_NUM_YEARS)]
exp_almdep = Policy.expand_array(np.array([7150, 7250, 7400]),
inflate=True,
inflation_rates=inf_rates,
num_years=Policy.DEFAULT_NUM_YEARS)
act_almdep = getattr(calc.policy, '_almdep')
assert np.allclose(act_almdep, exp_almdep)
exp_almsep_values = [40400] + [41050] * (Policy.DEFAULT_NUM_YEARS - 1)
exp_almsep = np.array(exp_almsep_values)
act_almsep = getattr(calc.policy, '_almsep')
assert np.allclose(act_almsep, exp_almsep)
def test_make_Calculator_user_mods_with_cpi_flags(policyfile, puf_1991):
with open(policyfile.name) as pfile:
policy = json.load(pfile)
ppo = Policy(parameter_dict=policy, start_year=1991,
num_years=len(IRATES), inflation_rates=IRATES,
wage_growth_rates=WRATES)
rec = Records(data=puf_1991, start_year=1991)
calc = Calculator(policy=ppo, records=rec)
user_mods = {1991: {"_almdep": [7150, 7250, 7400],
"_almdep_cpi": True,
"_almsep": [40400, 41050],
"_almsep_cpi": False,
"_rt5": [0.33],
"_rt7": [0.396]}}
calc.policy.implement_reform(user_mods)
# compare actual and expected values
inf_rates = [IRATES[1991 + i] for i in range(0, Policy.DEFAULT_NUM_YEARS)]
exp_almdep = Policy.expand_array(np.array([7150, 7250, 7400]),
inflate=True,
inflation_rates=inf_rates,
num_years=Policy.DEFAULT_NUM_YEARS)
act_almdep = getattr(calc.policy, '_almdep')
assert np.allclose(act_almdep, exp_almdep)
exp_almsep_values = [40400] + [41050] * (Policy.DEFAULT_NUM_YEARS - 1)
exp_almsep = np.array(exp_almsep_values)
act_almsep = getattr(calc.policy, '_almsep')
assert np.allclose(act_almsep, exp_almsep)
def test_expand_2D_accept_None_additional_row():
_II_brk2 = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, None, None, None, None, None],
[43000, None, None, None, None, None]]
exp1 = 74900 * 1.02
exp2 = 37450 * 1.02
exp3 = 50200 * 1.02
exp4 = 74900 * 1.02
exp5 = 37450 * 1.02
exp6 = exp1 * 1.03
exp7 = exp2 * 1.03
exp8 = exp3 * 1.03
exp9 = exp4 * 1.03
exp10 = exp5 * 1.03
exp = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, exp1, exp2, exp3, exp4, exp5],
[43000, exp6, exp7, exp8, exp9, exp10]]
exp = np.array(exp).astype('i4', casting='unsafe')
inflation_rates = [0.015, 0.02, 0.02, 0.03]
res = Policy.expand_array(_II_brk2, inflate=True,
inflation_rates=inflation_rates, num_years=5)
npt.assert_array_equal(res, exp)
def test_make_Calculator_user_mods_with_cpi_flags(policyfile):
with open(policyfile.name) as pfile:
policy = json.load(pfile)
ppo = Policy(parameter_dict=policy, start_year=1991,
num_years=len(IRATES), inflation_rates=IRATES,
wage_growth_rates=WRATES)
calc = Calculator(policy=ppo, records=TAX_DTA_PATH, start_year=1991,
inflation_rates=IRATES)
user_mods = {1991: {"_almdep": [7150, 7250, 7400],
"_almdep_cpi": True,
"_almsep": [40400, 41050],
"_almsep_cpi": False,
"_rt5": [0.33],
"_rt7": [0.396]}}
calc.policy.implement_reform(user_mods)
inf_rates = [IRATES[1991 + i] for i in range(0, 12)]
exp_almdep = Policy.expand_array(np.array([7150, 7250, 7400]),
inflate=True,
inflation_rates=inf_rates, num_years=12)
act_almdep = getattr(calc.policy, '_almdep')
assert_array_equal(act_almdep, exp_almdep)
exp_almsep_values = [40400] + [41050] * 11
exp_almsep = np.array(exp_almsep_values)
act_almsep = getattr(calc.policy, '_almsep')
assert_array_equal(act_almsep, exp_almsep)
def test_expand_2D_accept_None():
_II_brk2 = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, None, None, None, None, None]]
exp1 = 74900 * 1.02
exp2 = 37450 * 1.02
exp3 = 50200 * 1.02
exp4 = 74900 * 1.02
exp5 = 37450 * 1.02
exp = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, exp1, exp2, exp3, exp4, exp5]]
exp = np.array(exp).astype('i4', casting='unsafe')
res = Policy.expand_array(_II_brk2,
inflate=True,
inflation_rates=[0.02] * 5,
num_years=4)
npt.assert_array_equal(res, exp)
syr = 2013
pol = Policy(start_year=syr)
irates = pol.inflation_rates()
reform = {2016: {u'_II_brk2': _II_brk2}}
pol.implement_reform(reform)
pol.set_year(2019)
# The 2019 policy should be the combination of the user-defined
# value and CPI-inflated values from 2018
exp_2019 = [41000.] + [(1.0 + irates[2018 - syr]) * i
for i in _II_brk2[2][1:]]
exp_2019 = np.array(exp_2019)
npt.assert_array_equal(pol.II_brk2, exp_2019)
def test_expand_2D_accept_None():
_II_brk2 = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, None, None, None, None, None]]
exp1 = 74900 * 1.02
exp2 = 37450 * 1.02
exp3 = 50200 * 1.02
exp4 = 74900 * 1.02
exp5 = 37450 * 1.02
exp = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, exp1, exp2, exp3, exp4, exp5]]
exp = np.array(exp).astype('i4', casting='unsafe')
res = Policy.expand_array(_II_brk2, inflate=True,
inflation_rates=[0.02] * 5,
num_years=4)
npt.assert_array_equal(res, exp)
user_mods = {2016: {u'_II_brk2': _II_brk2}}
pol = Policy(start_year=2013)
pol.implement_reform(user_mods)
pol.set_year(2019)
irates = Policy.default_inflation_rates()
# The 2019 policy should be the combination of the user-defined
# value and CPI-inflated values from 2018
exp_2019 = [41000.] + [(1 + irates[2018]) * i for i in _II_brk2[2][1:]]
exp_2019 = np.array(exp_2019)
npt.assert_array_equal(pol.II_brk2, exp_2019)
def test_expand_1D_accept_None():
x = [4.0, 5.0, None]
irates = [0.02, 0.02, 0.03, 0.035]
exp = []
cur = 5.0 * 1.02
exp = [4.0, 5.0, cur]
cur *= 1.03
exp.append(cur)
cur *= 1.035
exp.append(cur)
exp = np.array(exp)
res = Policy.expand_array(x, inflate=True, inflation_rates=irates, num_years=5)
npt.assert_allclose(exp.astype("f4", casting="unsafe"), res)
def test_expand_1D_accept_None():
x = [4., 5., None]
irates = [0.02, 0.02, 0.03, 0.035]
exp = []
cur = 5.0 * 1.02
exp = [4., 5., cur]
cur *= 1.03
exp.append(cur)
cur *= 1.035
exp.append(cur)
exp = np.array(exp)
res = Policy.expand_array(x, inflate=True, inflation_rates=irates,
num_years=5)
assert np.allclose(exp.astype('f4', casting='unsafe'), res)
def test_expand_2D_accept_None():
_II_brk2 = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, None, None, None, None, None]]
exp1 = 74900 * 1.02
exp2 = 37450 * 1.02
exp3 = 50200 * 1.02
exp4 = 74900 * 1.02
exp5 = 37450 * 1.02
exp = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, exp1, exp2, exp3, exp4, exp5]]
exp = np.array(exp).astype('i4', casting='unsafe')
res = Policy.expand_array(_II_brk2, inflate=True,
inflation_rates=[0.02] * 5,
num_years=4)
npt.assert_array_equal(res, exp)
def test_expand_2D_accept_None_additional_row():
_II_brk2 = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, None, None, None, None, None],
[43000, None, None, None, None, None]]
exp1 = 74900 * 1.02
exp2 = 37450 * 1.02
exp3 = 50200 * 1.02
exp4 = 74900 * 1.02
exp5 = 37450 * 1.02
exp6 = exp1 * 1.03
exp7 = exp2 * 1.03
exp8 = exp3 * 1.03
exp9 = exp4 * 1.03
exp10 = exp5 * 1.03
exp = [[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, exp1, exp2, exp3, exp4, exp5],
[43000, exp6, exp7, exp8, exp9, exp10]]
inflation_rates = [0.015, 0.02, 0.02, 0.03]
res = Policy.expand_array(_II_brk2,
inflate=True,
inflation_rates=inflation_rates,
num_years=5)
npt.assert_array_equal(res, exp)
user_mods = {2016: {u'_II_brk2': _II_brk2}}
syr = 2013
pol = Policy(start_year=syr)
irates = pol.inflation_rates()
pol.implement_reform(user_mods)
pol.set_year(2020)
irates = pol.inflation_rates()
# The 2020 policy should be the combination of the user-defined
# value and CPI-inflated values from 2018
exp_2020 = [43000.] + [(1 + irates[2019 - syr]) *
(1 + irates[2018 - syr]) * i
for i in _II_brk2[2][1:]]
exp_2020 = np.array(exp_2020)
npt.assert_allclose(pol.II_brk2, exp_2020)
def test_expand_2D_accept_None_additional_row():
_II_brk2 = [
[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, None, None, None, None, None],
[43000, None, None, None, None, None],
]
exp1 = 74900 * 1.02
exp2 = 37450 * 1.02
exp3 = 50200 * 1.02
exp4 = 74900 * 1.02
exp5 = 37450 * 1.02
exp6 = exp1 * 1.03
exp7 = exp2 * 1.03
exp8 = exp3 * 1.03
exp9 = exp4 * 1.03
exp10 = exp5 * 1.03
exp = [
[36000, 72250, 36500, 48600, 72500, 36250],
[38000, 74000, 36900, 49400, 73800, 36900],
[40000, 74900, 37450, 50200, 74900, 37450],
[41000, exp1, exp2, exp3, exp4, exp5],
[43000, exp6, exp7, exp8, exp9, exp10],
]
inflation_rates = [0.015, 0.02, 0.02, 0.03]
res = Policy.expand_array(_II_brk2, inflate=True, inflation_rates=inflation_rates, num_years=5)
npt.assert_array_equal(res, exp)
user_mods = {2016: {u"_II_brk2": _II_brk2}}
pol = Policy(start_year=2013)
pol.implement_reform(user_mods)
pol.set_year(2020)
irates = Policy.default_inflation_rates()
# The 2020 policy should be the combination of the user-defined
# value and CPI-inflated values from 2018
exp_2020 = [43000.0] + [(1 + irates[2019]) * (1 + irates[2018]) * i for i in _II_brk2[2][1:]]
exp_2020 = np.array(exp_2020)
npt.assert_allclose(pol.II_brk2, exp_2020)
def test_multi_year_reform():
"""
Test multi-year reform involving 1D and 2D parameters.
"""
# specify dimensions of policy Policy object
syr = 2013
nyrs = 10
# specify assumed inflation rates
irates = {
2013: 0.02,
2014: 0.02,
2015: 0.02,
2016: 0.03,
2017: 0.03,
2018: 0.04,
2019: 0.04,
2020: 0.04,
2021: 0.04,
2022: 0.04
}
ifactor = {}
for i in range(0, nyrs):
ifactor[syr + i] = 1.0 + irates[syr + i]
iratelist = [irates[syr + i] for i in range(0, nyrs)]
# specify assumed inflation rates
wrates = {
2013: 0.0276,
2014: 0.0419,
2015: 0.0465,
2016: 0.0498,
2017: 0.0507,
2018: 0.0481,
2019: 0.0451,
2020: 0.0441,
2021: 0.0437,
2022: 0.0435
}
wfactor = {}
for i in range(0, nyrs):
wfactor[syr + i] = 1.0 + wrates[syr + i]
wratelist = [wrates[syr + i] for i in range(0, nyrs)]
# instantiate policy Policy object
ppo = Policy(start_year=syr,
num_years=nyrs,
inflation_rates=irates,
wage_growth_rates=wrates)
# confirm that parameters have current-law values
assert_allclose(getattr(ppo, '_AMT_thd_MarriedS'),
Policy.expand_array(np.array([40400, 41050]),
inflate=True,
inflation_rates=iratelist,
num_years=nyrs),
atol=0.01,
rtol=0.0)
assert_allclose(getattr(ppo, '_EITC_c'),
Policy.expand_array(np.array([[487, 3250, 5372, 6044],
[496, 3305, 5460, 6143],
[503, 3359, 5548, 6242],
[506, 3373, 5572, 6269]]),
inflate=True,
inflation_rates=iratelist,
num_years=nyrs),
atol=0.01,
rtol=0.0)
assert_allclose(getattr(ppo, '_II_em'),
Policy.expand_array(np.array([3900, 3950, 4000, 4050]),
inflate=True,
inflation_rates=iratelist,
num_years=nyrs),
atol=0.01,
rtol=0.0)
assert_allclose(getattr(ppo, '_CTC_c'),
Policy.expand_array(np.array([1000]),
inflate=False,
inflation_rates=iratelist,
num_years=nyrs),
atol=0.01,
rtol=0.0)
# this parameter uses a different inflating rate
assert_allclose(getattr(ppo, '_SS_Earnings_c'),
Policy.expand_array(np.array(
[113700, 117000, 118500, 118500]),
inflate=True,
inflation_rates=wratelist,
num_years=nyrs),
atol=0.01,
rtol=0.0)
# specify multi-year reform using a dictionary of year_provisions dicts
reform = {
2015: {
'_AMT_thd_MarriedS': [60000],
'_CTC_c': [2000]
},
2016: {
'_EITC_c': [[900, 5000, 8000, 9000]],
'_II_em': [7000],
'_SS_Earnings_c': [300000]
},
2017: {
'_AMT_thd_MarriedS': [80000],
'_SS_Earnings_c': [500000],
'_SS_Earnings_c_cpi': False
},
2019: {
'_EITC_c': [[1200, 7000, 10000, 12000]],
'_II_em': [9000],
'_SS_Earnings_c': [700000],
'_SS_Earnings_c_cpi': True
}
}
# implement multi-year reform
ppo.implement_reform(reform)
assert ppo.current_year == syr
# move policy Policy object forward in time so current_year is syr+2
# Note: this would be typical usage because the first budget year
# is greater than Policy start_year.
ppo.set_year(ppo.start_year + 2)
assert ppo.current_year == syr + 2
# confirm that actual parameters have expected post-reform values
check_amt_thd_marrieds(ppo, reform, ifactor)
check_eitc_c(ppo, reform, ifactor)
check_ii_em(ppo, reform, ifactor)
check_ss_earnings_c(ppo, reform, wfactor)
check_ctc_c(ppo, reform)
def test_multi_year_reform():
"""
Test multi-year reform involving 1D and 2D parameters.
"""
# specify dimensions of policy Policy object
syr = 2013
nyrs = 10
# specify assumed inflation rates
irates = {2013: 0.02, 2014: 0.02, 2015: 0.02, 2016: 0.03, 2017: 0.03,
2018: 0.04, 2019: 0.04, 2020: 0.04, 2021: 0.04, 2022: 0.04}
ifactor = {}
for i in range(0, nyrs):
ifactor[syr + i] = 1.0 + irates[syr + i]
iratelist = [irates[syr + i] for i in range(0, nyrs)]
# specify assumed inflation rates
wrates = {2013: 0.0276, 2014: 0.0419, 2015: 0.0465, 2016: 0.0498,
2017: 0.0507, 2018: 0.0481, 2019: 0.0451, 2020: 0.0441,
2021: 0.0437, 2022: 0.0435}
wfactor = {}
for i in range(0, nyrs):
wfactor[syr + i] = 1.0 + wrates[syr + i]
wratelist = [wrates[syr + i] for i in range(0, nyrs)]
# instantiate policy Policy object
ppo = Policy(start_year=syr, num_years=nyrs, inflation_rates=irates,
wage_growth_rates=wrates)
# confirm that parameters have current-law values
assert_allclose(getattr(ppo, '_AMT_thd_MarriedS'),
Policy.expand_array(np.array([40400, 41050]),
inflate=True,
inflation_rates=iratelist,
num_years=nyrs),
atol=0.01, rtol=0.0)
assert_allclose(getattr(ppo, '_EITC_c'),
Policy.expand_array(np.array([[487, 3250, 5372, 6044],
[496, 3305, 5460, 6143],
[503, 3359, 5548, 6242],
[506, 3373, 5572, 6269]]),
inflate=True,
inflation_rates=iratelist,
num_years=nyrs),
atol=0.01, rtol=0.0)
assert_allclose(getattr(ppo, '_II_em'),
Policy.expand_array(np.array([3900, 3950, 4000, 4050]),
inflate=True,
inflation_rates=iratelist,
num_years=nyrs),
atol=0.01, rtol=0.0)
assert_allclose(getattr(ppo, '_CTC_c'),
Policy.expand_array(np.array([1000]),
inflate=False,
inflation_rates=iratelist,
num_years=nyrs),
atol=0.01, rtol=0.0)
# this parameter uses a different inflating rate
assert_allclose(getattr(ppo, '_SS_Earnings_c'),
Policy.expand_array(np.array([113700, 117000,
118500, 118500]),
inflate=True,
inflation_rates=wratelist,
num_years=nyrs),
atol=0.01, rtol=0.0)
# specify multi-year reform using a dictionary of year_provisions dicts
reform = {
2015: {
'_AMT_thd_MarriedS': [60000],
'_CTC_c': [2000]
},
2016: {
'_EITC_c': [[900, 5000, 8000, 9000]],
'_II_em': [7000],
'_SS_Earnings_c': [300000]
},
2017: {
'_AMT_thd_MarriedS': [80000],
'_SS_Earnings_c': [500000], '_SS_Earnings_c_cpi': False
},
2019: {
'_EITC_c': [[1200, 7000, 10000, 12000]],
'_II_em': [9000],
'_SS_Earnings_c': [700000], '_SS_Earnings_c_cpi': True
}
}
# implement multi-year reform
ppo.implement_reform(reform)
assert ppo.current_year == syr
# move policy Policy object forward in time so current_year is syr+2
# Note: this would be typical usage because the first budget year
# is greater than Policy start_year.
ppo.set_year(ppo.start_year + 2)
assert ppo.current_year == syr + 2
# confirm that actual parameters have expected post-reform values
check_amt_thd_marrieds(ppo, reform, ifactor)
check_eitc_c(ppo, reform, ifactor)
check_ii_em(ppo, reform, ifactor)
check_ss_earnings_c(ppo, reform, wfactor)
check_ctc_c(ppo, reform)
