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Fix CPS taxable pensions, qualified dividends, and taxable/non-taxable interest #165

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Mar 9, 2018
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Fix CPS taxable pensions, qualified dividends, and taxable/non-taxable interest #165

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336eb71
randomly determine taxable pensions
andersonfrailey Mar 3, 2018
b819bdf
new methodology
andersonfrailey Mar 7, 2018
53c2280
slope method
andersonfrailey Mar 7, 2018
91d408b
merge master
andersonfrailey Mar 8, 2018
f16482b
fix interest income logic
andersonfrailey Mar 9, 2018
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Binary file modified cps_data/cps.csv.gz
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51 changes: 41 additions & 10 deletions cps_data/finalprep.py
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Original file line number Diff line number Diff line change
Expand Up @@ -70,17 +70,48 @@ def main():
data['e00200'] = data['e00200p'] + data['e00200s']
data['e00900'] = data['e00900p'] + data['e00900s']
data['e02100'] = data['e02100p'] + data['e02100s']
# Determine amount of qualified dividends using IRS ratio
data['e00650'] = data.e00600 * 0.7556

# Split interest income into taxable and tax exempt using IRS ratio
taxable = 0.6
nontaxable = 1. - taxable
data['e00300'] = data.INTST * taxable
data['e00400'] = data.INTST * nontaxable

# Split pentions and annuities using PUF ratio
data['e01700'] = data['e01500'] * 0.1656
np.random.seed(79)
# Determine amount of qualified dividends
# percent of units where all dividends are qualified
all_qualified_prob = 0.429
# percent of units where no dividends are qualified
no_qualified_prob = 0.093
# percent of units where either all or no dividends are qualified
non_avg_prob = all_qualified_prob + no_qualified_prob
# percent of dividends that are qualified among remaining units
qualified_frac = 0.678
# Determine qualified dividend percentage
probs = np.random.random(len(data['e00600']))
qualified = np.ones(len(data['e00600']))
qualified = np.where((probs > all_qualified_prob) &
(probs <= non_avg_prob), 0.0, qualified)
qualified = np.where(probs > non_avg_prob, qualified_frac, qualified)
data['e00650'] = data.e00600 * qualified

# Split interest income into taxable and tax exempt
slope = 0.068
ratio = 0.46
prob = 1. - slope * (data.INTST * 1e-3)
uniform_rn = np.random.random(len(prob))
data['e00300'] = np.where(uniform_rn < prob,
data.INTST,
data.INTST * ratio)
data['e00400'] = data['INTST'] - data['e00300']

# Split pentions and annuities using random assignment
# probabiliies used for random assignment
probs = np.random.random(len(data['e01500']))
fully_taxable_prob = 0.612
zero_tax_prob = 0.073
non_avg_prob = fully_taxable_prob + zero_tax_prob
avg_taxable_amout = 0.577
# determine tax ability
taxability = np.ones(len(data['e01500']))
taxability = np.where((probs > fully_taxable_prob) &
(probs <= non_avg_prob), 0.0, taxability)
taxability = np.where(probs > non_avg_prob, avg_taxable_amout, taxability)
data['e01700'] = data['e01500'] * taxability

print 'Applying deduction limits'
data = deduction_limits(data)
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