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Merge pull request #1791 from martinholmer/oop-calc-records
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Add more Calculator methods and use them in Tax-Calculator code
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@martinholmer
martinholmer authored Jan 13, 2018
2 parents 9a62b66 + 96116cd commit ea0eeb9
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Showing 18 changed files with 364 additions and 980 deletions.
47 changes: 25 additions & 22 deletions taxcalc/behavior.py
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Original file line number Diff line number Diff line change
Expand Up @@ -114,8 +114,8 @@ def response(calc1, calc2, trace=False):
Implements TaxBrain "Partial Equilibrium Simulation" dynamic analysis.
Modify calc2 records to account for behavioral responses that arise
from the policy reform that involves moving from calc1.policy to
calc2.policy. Neither calc1 nor calc2 need to have had calc_all()
from the policy reform that involves moving from calc1 policy to
calc2 policy. Neither calc1 nor calc2 need to have had calc_all()
executed before calling the Behavior.response(calc1, calc2) method.
Returns new Calculator object --- a deepcopy of calc2 --- that
incorporates behavioral responses to the reform.
Expand Down Expand Up @@ -170,7 +170,7 @@ def trace_output(varname, variable, histbins, pweight, dweight):
assert calc1.array_len == calc2.array_len
assert calc1.current_year == calc2.current_year
# calculate sum of substitution and income effects
if calc2.behavior.BE_sub == 0.0 and calc2.behavior.BE_inc == 0.0:
if calc2.behavior('BE_sub') == 0.0 and calc2.behavior('BE_inc') == 0.0:
zero_sub_and_inc = True
else:
zero_sub_and_inc = False
Expand All @@ -180,20 +180,22 @@ def trace_output(varname, variable, histbins, pweight, dweight):
mtr_of='e00200p',
tax_type='combined')
# calculate magnitude of substitution effect
if calc2.behavior.BE_sub == 0.0:
if calc2.behavior('BE_sub') == 0.0:
sub = np.zeros(calc1.array_len)
else:
# proportional change in marginal net-of-tax rates on earnings
nearone = 0.999999
mtr1 = np.where(wage_mtr1 > nearone, nearone, wage_mtr1)
mtr2 = np.where(wage_mtr2 > nearone, nearone, wage_mtr2)
pch = ((1. - mtr2) / (1. - mtr1)) - 1.
if calc2.behavior.BE_subinc_wrt_earnings:
if calc2.behavior('BE_subinc_wrt_earnings'):
# Note: e00200 is filing unit's wages+salaries
sub = calc2.behavior.BE_sub * pch * calc1.array('e00200')
sub = (calc2.behavior('BE_sub') *
pch * calc1.array('e00200'))
else:
# Note: c04800 is filing unit's taxable income
sub = calc2.behavior.BE_sub * pch * calc1.array('c04800')
sub = (calc2.behavior('BE_sub') *
pch * calc1.array('c04800'))
if trace:
trace_output('pch', pch,
[-9e99, -1.00, -0.50, -0.20, -0.10,
Expand All @@ -208,26 +210,27 @@ def trace_output(varname, variable, histbins, pweight, dweight):
calc1.array('s006'),
np.zeros(calc1.array_len))
# calculate magnitude of income effect
if calc2.behavior.BE_inc == 0.0:
if calc2.behavior('BE_inc') == 0.0:
inc = np.zeros(calc1.array_len)
else:
if calc2.behavior.BE_subinc_wrt_earnings:
if calc2.behavior('BE_subinc_wrt_earnings'):
# proportional change in after-tax income
with np.errstate(invalid='ignore'):
pch = np.where(calc1.array('aftertax_income') > 0.,
(calc2.array('aftertax_income') /
calc1.array('aftertax_income')) - 1.,
0.)
inc = calc2.behavior.BE_inc * pch * calc1.array('e00200')
inc = (calc2.behavior('BE_inc') *
pch * calc1.array('e00200'))
else:
# dollar change in after-tax income
# Note: combined is f.unit's income+payroll tax liability
dch = calc1.array('combined') - calc2.array('combined')
inc = calc2.behavior.BE_inc * dch
inc = calc2.behavior('BE_inc') * dch
# calculate sum of substitution and income effects
si_chg = sub + inc
# calculate long-term capital-gains effect
if calc2.behavior.BE_cg == 0.0:
if calc2.behavior('BE_cg') == 0.0:
ltcg_chg = np.zeros(calc1.array_len)
else:
# calculate marginal tax rates on long-term capital gains
Expand All @@ -236,11 +239,11 @@ def trace_output(varname, variable, histbins, pweight, dweight):
mtr_of='p23250',
tax_type='iitax')
rch = ltcg_mtr2 - ltcg_mtr1
exp_term = np.exp(calc2.behavior.BE_cg * rch)
exp_term = np.exp(calc2.behavior('BE_cg') * rch)
new_ltcg = calc1.array('p23250') * exp_term
ltcg_chg = new_ltcg - calc1.array('p23250')
# calculate charitable giving effect
no_charity_response = (calc2.behavior.BE_charity.tolist() ==
no_charity_response = (calc2.behavior('BE_charity').tolist() ==
[0.0, 0.0, 0.0])
if no_charity_response:
c_charity_chg = np.zeros(calc1.array_len)
Expand Down Expand Up @@ -268,46 +271,46 @@ def trace_output(varname, variable, histbins, pweight, dweight):
c_charity_chg = np.zeros(calc1.array_len)
# AGI < 50000
c_charity_chg = np.where(low_income,
(calc2.behavior.BE_charity[0] *
(calc2.behavior('BE_charity')[0] *
c_charity_price_pch *
calc1.array('e19800')),
c_charity_chg)
# 50000 <= AGI < 1000000
c_charity_chg = np.where(mid_income,
(calc2.behavior.BE_charity[1] *
(calc2.behavior('BE_charity')[1] *
c_charity_price_pch *
calc1.array('e19800')),
c_charity_chg)
# 1000000 < AGI
c_charity_chg = np.where(high_income,
(calc2.behavior.BE_charity[2] *
(calc2.behavior('BE_charity')[2] *
c_charity_price_pch *
calc1.array('e19800')),
c_charity_chg)
# calculate change in non-cash contributions
nc_charity_chg = np.zeros(calc1.array_len)
# AGI < 50000
nc_charity_chg = np.where(low_income,
(calc2.behavior.BE_charity[0] *
(calc2.behavior('BE_charity')[0] *
nc_charity_price_pch *
calc1.array('e20100')),
nc_charity_chg)
# 50000 <= AGI < 1000000
nc_charity_chg = np.where(mid_income,
(calc2.behavior.BE_charity[1] *
(calc2.behavior('BE_charity')[1] *
nc_charity_price_pch *
calc1.array('e20100')),
nc_charity_chg)
# 1000000 < AGI
nc_charity_chg = np.where(high_income,
(calc2.behavior.BE_charity[2] *
(calc2.behavior('BE_charity')[2] *
nc_charity_price_pch *
calc1.array('e20100')),
nc_charity_chg)
# Add behavioral-response changes to income sources
calc2_behv = copy.deepcopy(calc2)
if not zero_sub_and_inc:
if calc2_behv.behavior.BE_subinc_wrt_earnings:
if calc2_behv.behavior('BE_subinc_wrt_earnings'):
calc2_behv = Behavior._update_earnings(si_chg,
calc2_behv)
else:
Expand Down Expand Up @@ -416,7 +419,7 @@ def _update_ordinary_income(taxinc_change, calc):
delta_ided[pos] = delta_income[pos] * ided[pos] / agi_m_ided[pos]
# confirm that the three parts are consistent with delta_income
assert np.allclose(delta_income, delta_winc + delta_oinc - delta_ided)
# add the three parts to different calc.records variables
# add the three parts to different records variables embedded in calc
calc.incarray('e00200', delta_winc)
calc.incarray('e00200p', delta_winc)
calc.incarray('e00300', delta_oinc)
Expand Down
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