def test_implement_reform():
specs = Specifications()
new_specs = {'profit_rate': 0.4, 'm': 0.5}
specs.update_specifications(new_specs)
assert specs.profit_rate == 0.4
assert specs.m == 0.5
assert len(specs.errors) == 0
def test_implement_reform():
specs = Specifications()
new_specs = {'profit_rate': 0.4, 'm': 0.5, 'start_year': 2019}
specs.update_specifications(new_specs)
assert specs.profit_rate == 0.4
assert specs.m == 0.5
assert specs.start_year == 2019
assert len(specs.parameter_errors) == 0
assert len(specs.parameter_warnings) == 0
def test_implement_bad_reform1():
specs = Specifications()
# profit rate has an upper bound at 1.0
new_specs = {'profit_rate': 1.2}
specs.update_specifications(new_specs, raise_errors=False)
assert len(specs.parameter_errors) > 0
assert specs.parameter_errors == 'ERROR: profit_rate value 1.2 > max value 1.0\n'
assert len(specs.parameter_warnings) == 0
def test_implement_bad_reform2():
specs = Specifications()
# Pick a category for depreciation that is out of bounds
new_specs = {'profit_rate': 0.5, 'DeprecSystem_3yr': 'not_a_deprec_system'}
specs.update_specifications(new_specs, raise_errors=False)
assert len(specs.parameter_errors) > 0
assert specs.parameter_errors == "ERROR: DeprecSystem_3yr value ['not_a_deprec_system'] not in possible values ['GDS', 'ADS', 'Economic']\n"
assert len(specs.parameter_warnings) == 0
def test_implement_bad_reform1():
specs = Specifications()
# profit rate has an upper bound at 1.0
new_specs = {'profit_rate': 1.2}
specs.update_specifications(new_specs, raise_errors=False)
assert len(specs.errors) > 0
print(specs.errors)
exp = {'profit_rate': ['profit_rate 1.2 must be less than 1.0.']}
assert specs.errors == exp
def test_bubble_widget():
'''
Test asset bubble plot method.
'''
assets = Assets()
p = Specifications()
calc = Calculator(p, assets)
p2 = Specifications(year=2026)
p2.update_specifications({'CIT_rate': 0.25})
calc2 = Calculator(p2, assets)
fig = calc.bubble_widget(calc2)
assert fig
def test_implement_bad_reform1():
specs = Specifications()
# profit rate has an upper bound at 1.0
new_specs = {
'profit_rate': 1.2
}
specs.update_specifications(new_specs, raise_errors=False)
assert len(specs.parameter_errors) > 0
assert specs.parameter_errors == 'ERROR: profit_rate value 1.2 > max value 1.0\n'
assert len(specs.parameter_warnings) == 0
def test_implement_bad_reform2():
specs = Specifications()
# Pick a category for depreciation that is out of bounds
new_specs = {
'profit_rate': 0.5,
'DeprecSystem_3yr': 'not_a_deprec_system'
}
specs.update_specifications(new_specs, raise_errors=False)
assert len(specs.parameter_errors) > 0
assert specs.parameter_errors == "ERROR: DeprecSystem_3yr value ['not_a_deprec_system'] not in possible values ['GDS', 'ADS', 'Economic']\n"
assert len(specs.parameter_warnings) == 0
def test_range_plot():
'''
Test range_plot method.
'''
assets = Assets()
p = Specifications()
calc = Calculator(p, assets)
p2 = Specifications(year=2026)
p2.update_specifications({'CIT_rate': 0.25})
calc2 = Calculator(p2, assets)
fig = calc.range_plot(calc2)
assert fig
fig = calc.range_plot(calc2, output_variable='rho')
assert fig
def test_implement_bad_reform2():
specs = Specifications()
# Pick a category for depreciation that is out of bounds
new_specs = {'profit_rate': 0.5, 'DeprecSystem_3yr': 'not_a_deprec_system'}
specs.update_specifications(new_specs, raise_errors=False)
assert len(specs.errors) > 0
exp = {
'DeprecSystem_3yr': [
'DeprecSystem_3yr "not_a_deprec_system" must be in list of choices GDS, ADS, Economic.'
]
}
assert specs.errors == exp
def test_implement_reform():
specs = Specifications()
new_specs = {
'profit_rate': 0.4,
'm': 0.5,
'start_year': 2019
}
specs.update_specifications(new_specs)
assert specs.profit_rate == 0.4
assert specs.m == 0.5
assert specs.start_year == 2019
assert len(specs.parameter_errors) == 0
assert len(specs.parameter_warnings) == 0
def test_asset_bubble():
'''
Test asset bubble plot method.
'''
assets = Assets()
p = Specifications()
calc = Calculator(p, assets)
p2 = Specifications(year=2026)
p2.update_specifications({'CIT_rate': 0.25})
calc2 = Calculator(p2, assets)
fig = calc.asset_bubble(calc2)
assert fig
fig = calc.asset_bubble(calc2, output_variable='rho_mix')
assert fig
def test_grouped_bar():
'''
Test grouped_bar method.
'''
assets = Assets()
p = Specifications()
calc = Calculator(p, assets)
p2 = Specifications(year=2026)
p2.update_specifications({'CIT_rate': 0.25})
calc2 = Calculator(p2, assets)
fig = calc.grouped_bar(calc2)
assert fig
fig = calc.grouped_bar(calc2, output_variable='rho', group_by_asset=False)
assert fig
def test_summary_table():
'''
Test difference_table method.
'''
yr = 2018
assets = Assets()
p = Specifications(year=yr)
calc1 = Calculator(p, assets)
assert calc1.current_year == yr
reform = {'CIT_rate': 0.38}
p.update_specifications(reform)
calc2 = Calculator(p, assets)
assert calc2.current_year == yr
summary_df = calc1.summary_table(calc2)
assert isinstance(summary_df, pd.DataFrame)
assets = Assets()
# Baseline
baseline_parameters = Specifications(year=2019, call_tc=False, iit_reform={})
calc1 = Calculator(baseline_parameters, assets)
# Reform
reform_parameters = Specifications(year=2019, call_tc=False, iit_reform={})
business_tax_adjustments = {
'CIT_rate': 0.35,
'BonusDeprec_3yr': 0.50,
'BonusDeprec_5yr': 0.50,
'BonusDeprec_7yr': 0.50,
'BonusDeprec_10yr': 0.50,
'BonusDeprec_15yr': 0.50,
'BonusDeprec_20yr': 0.50
}
reform_parameters.update_specifications(business_tax_adjustments)
calc2 = Calculator(reform_parameters, assets)
# Do calculations by asset
base_assets_df = calc1.calc_by_asset()
reform_assets_df = calc2.calc_by_asset()
# Do Calculations by Industry
base_industry_df = calc1.calc_by_industry()
reform_industry_df = calc2.calc_by_industry()
# Generate dataframes with differences
diff_assets_df = ccc.utils.diff_two_tables(reform_assets_df, base_assets_df)
diff_industry_df = ccc.utils.diff_two_tables(reform_industry_df,
base_industry_df)
# Save dataframes to disk as csv files
ref = taxcalc.Calculator.read_json_param_objects(reform_url, None)
iit_reform = ref['policy']
# Initialize Asset and Calculator Objects
assets = Assets()
# Baseline
baseline_parameters = Specifications(year=2018, call_tc=True, iit_reform={})
calc1 = Calculator(baseline_parameters, assets)
# Reform
reform_parameters = Specifications(year=2018, call_tc=True,
iit_reform=iit_reform)
business_tax_adjustments = {
'CIT_rate': 0.35, 'BonusDeprec_3yr': 0.50, 'BonusDeprec_5yr': 0.50,
'BonusDeprec_7yr': 0.50, 'BonusDeprec_10yr': 0.50,
'BonusDeprec_15yr': 0.50, 'BonusDeprec_20yr': 0.50}
reform_parameters.update_specifications(business_tax_adjustments)
calc2 = Calculator(reform_parameters, assets)
# Do calculations by asset
base_assets_df = calc1.calc_by_asset()
reform_assets_df = calc2.calc_by_asset()
# Do Calculations by Industry
base_industry_df = calc1.calc_by_industry()
reform_industry_df = calc2.calc_by_industry()
# Generate dataframes with differences
diff_assets_df = ccc.utils.diff_two_tables(
reform_assets_df, base_assets_df)
diff_industry_df = ccc.utils.diff_two_tables(
reform_industry_df, base_industry_df)
from ccc.run_ccc import run_ccc_with_baseline_delta
from taxcalc import *
from ccc.parameters import Specifications
test_run = False # flag for test run (for Travis CI)
start_year = 2018
# Note that TCJA is current law baseline in TC 0.16+
# Thus to compare TCJA to 2017 law, we'll use 2017 law as the reform
reform_url = ('https://raw.githubusercontent.com/'
'PSLmodels/Tax-Calculator/master/taxcalc/'
'reforms/2017_law.json')
ref = Calculator.read_json_param_objects(reform_url, None)
iit_reform = ref['policy']
# Initialize Cost-of-Capital-Calculator parameters
baseline_parameters = Specifications(year=2018, call_tc=True,
iit_reform={})
reform_parameters = Specifications(year=2018, call_tc=True,
iit_reform=iit_reform)
reform_params = {'CIT_rate': 0.35, 'BonusDeprec_3yr': 0.50,
'BonusDeprec_5yr': 0.50, 'BonusDeprec_7yr': 0.50,
'BonusDeprec_10yr': 0.50, 'BonusDeprec_15yr': 0.50,
'BonusDeprec_20yr': 0.50}
reform_parameters.update_specifications(reform_params)
# Run Cost-of-Capital-Calculator
run_ccc_with_baseline_delta(baseline_parameters, reform_parameters,
data='cps')