[WIP] Adding Corporate Income Tax Distribution

taxcalc/calculate.py

@@ -23,7 +23,7 @@
                                NonrefundableCredits, C1040, IITAX,
                                BenefitSurtax, BenefitLimitation,
                                FairShareTax, LumpSumTax, ExpandIncome,
-                               AfterTaxIncome)
+                               AfterTaxIncome, AggCorpIncTax, DistCorpIncTax)
 from taxcalc.policy import Policy
 from taxcalc.records import Records
 from taxcalc.behavior import Behavior
@@ -149,6 +149,8 @@ def calc_all(self, zero_out_calc_vars=False):
         LumpSumTax(self.policy, self.records)
         ExpandIncome(self.policy, self.records)
         AfterTaxIncome(self.policy, self.records)
+        AggCorpIncTax(self)
+        DistCorpIncTax(self.policy, self.records)
 
     def increment_year(self):
         """

taxcalc/current_law_policy.json

@@ -3438,5 +3438,21 @@
         "col_var": "",
         "col_label": "",
         "value": [0.0]
+    },
+
+    "_CIT_Distribution": {
+        "long_name": "Corporate Income Tax distribution among labor income, normal income and supernormal income",
+        "description": "Set to 0.2, 0.2 and 0.6, according to TPC",
+        "section_1": "",
+        "section_2": "",
+        "irs_ref": "",
+        "notes": "",
+        "row_var": "FLPDYR",
+        "row_label": ["2013"],
+        "start_year": 2013,
+        "cpi_inflated": false,
+        "col_var": "",
+        "col_label": "",
+        "value": [[0.2,0.2,0.6]]
     }
 }

taxcalc/functions.py

@@ -1633,3 +1633,78 @@ def AfterTaxIncome(combined, expanded_income, aftertax_income):
     """
     aftertax_income = expanded_income - combined
     return aftertax_income
+
+def AggCorpIncTax(calc):
+    """
+    AggCorpIncTax function: computes the aggregated amounts of labor income, normal income and supernormal income
+    Prepares the parameters for DistCorpIncTax function
+    """
+    #No e00250
+    length = len(calc.records.s006)
+    #positive p23250 and p22250
+    #positivep23250 = np.where(calc.records.p23250<0, 0, calc.records.p23250)
+    #positivep22250 = np.where(calc.records.p22250<0, 0, calc.records.p22250)
+    #labor = ((calc.records.e00200 + calc.records.e07240 + calc.records.e03150 + calc.records.e01400 + calc.records.e01700 + calc.records.e02400 + calc.records.e02100 + calc.records.e00900 + calc.records.e02000) * calc.records.s006).sum()
+    #normal = 0.4 * ((calc.records.e00650 + positivep23250 + positivep22250 + calc.records.e02100 + calc.records.e00900 + calc.records.e02000) * calc.records.s006).sum() + ((calc.records.e00300 + calc.records.e00400 + calc.records.e00600) * calc.records.s006).sum()
+    #supernormal = 0.6 * ((calc.records.e00650 + positivep23250 + positivep22250) * calc.records.s006).sum()
+    #original p23250 and p22250
+    labor = ((calc.records.e00200 + calc.records.e07240 + calc.records.e03150 + calc.records.e01400 + calc.records.e01700 + calc.records.e02400 + calc.records.e02100 + calc.records.e00900 + calc.records.e02000) * calc.records.s006).sum()
+    normal = 0.4 * ((calc.records.e00650 + calc.records.p23250 + calc.records.p22250 + calc.records.e02100 + calc.records.e00900 + calc.records.e02000) * calc.records.s006).sum() + ((calc.records.e00300 + calc.records.e00400 + calc.records.e00600) * calc.records.s006).sum()
+    supernormal = 0.6 * ((calc.records.e00650 + calc.records.p23250 + calc.records.p22250) * calc.records.s006).sum()    
+    # Create arrays with same aggregated amounts for each tax-payer
+    calc.records.agg_labor = np.ones(length) * labor + 0.0000000001
+    calc.records.agg_normal = np.ones(length) * normal + 0.0000000001
+    calc.records.agg_supernormal = np.ones(length) * supernormal + 0.0000000001
+
+@iterate_jit(nopython=True)
+def DistCorpIncTax(e00200, e07240, e03150, e01400, e01700, e02400, e02100, e00900, e02000, e00650, p23250, p22250, e00300, e00400, e00600, share_corptax_burden, agg_labor, agg_normal, agg_supernormal, CIT_Distribution):
+    """
+    Compute Corporate Income Tax Distribution
+    According to TPC,
+    20% distributed by labor income
+    20% distributed by normal income
+    60% distributed by supernormal income
+
+    Parameters:
+    e00200: salaries and wages
+    e00250: other earned income(DNE)
+    e07240: retirement savings contribution
+    e03150: IRA deduction
+    e01400: taxable IRA distribution
+    e01700: taxable pensions and annuities included in AGI
+    e02400: social security benefits
+    e02100: farm income or loss
+    e00900: business income or loss
+    e02000: schedule E net income or loss
+    e00650: qualified dividends
+    p23250: long-term gains / losses
+    p22250: short-term gains / losses
+    e00300: interest received
+    e00400: tax-exempt interest income
+    e00600: dividends included in AGI
+    CIT_Distribution: [0.2, 0.2, 0.6]
+    """
+    #Do not have this variable in current Puf: e00250
+    #positive p23250 and p22250
+    #if p23250<0:
+    #    positivep23250 = 0
+    #else:
+    #    positivep23250 = p23250
+    #if p22250<0:
+    #    positivep22250 = 0
+    #else:
+    #    positivep22250 = p22250
+    #labor = e00200 + e07240 + e03150 + e01400 + e01700 + e02400 + e02100 + e00900 + e02000
+    #normal = 0.4 * (e00650 + positivep23250 + positivep22250 + e02100 + e00900 + e02000) + (e00300 + e00400 + e00600)    
+    #supernormal = 0.6 * (e00650 + positivep23250 + positivep22250)      
+    #original p23250 and p22250
+    labor = e00200 + e07240 + e03150 + e01400 + e01700 + e02400 + e02100 + e00900 + e02000
+    normal = 0.4 * (e00650 + p23250 + p22250 + e02100 + e00900 + e02000) + (e00300 + e00400 + e00600)
+    supernormal = 0.6 * (e00650 + p23250 + p22250)
+    revenue_collected = 100000000000
+    share_from_labor = CIT_Distribution[0] * revenue_collected * labor / agg_labor
+    share_from_normal = CIT_Distribution[1] * revenue_collected * normal / agg_normal
+    share_from_supernormal = CIT_Distribution[2] * revenue_collected * supernormal / agg_supernormal
+    share_corptax_burden = share_from_labor  + share_from_normal + share_from_supernormal
+    return share_corptax_burden
+

taxcalc/records_variables.json

@@ -891,6 +891,26 @@
       "type": "float",
       "desc": "After tax income is equal to expanded_income minus combined",
       "form": {}
+    },
+    "share_corptax_burden": {
+      "type": "float",
+      "desc": "Amount of corporate income tax distribution",
+      "form": {}
+    },
+    "agg_labor": {
+      "type": "float",
+      "desc": "Amount of corporate income tax distribution",
+      "form": {}
+    },
+    "agg_normal": {
+      "type": "float",
+      "desc": "Amount of corporate income tax distribution",
+      "form": {}
+    },
+    "agg_supernormal": {
+      "type": "float",
+      "desc": "Amount of corporate income tax distribution",
+      "form": {}
     }
   }
 }

taxcalc/tests/test_functions.py

@@ -90,6 +90,7 @@ def test_calc_and_used_vars(tests_path):
     all_cvars.update(set(['num', 'sep', 'exact']))
     # .. add to all_cvars set variables calculated elsewhere
     all_cvars.update(set(['mtr_paytax', 'mtr_inctax']))
+    all_cvars.update(set(['agg_labor', 'agg_normal', 'agg_supernormal']))
     # .. check that each var in Records.CALCULATED_VARS is in the all_cvars set
     found_error1 = False
     if not Records.CALCULATED_VARS <= all_cvars:
@@ -99,7 +100,7 @@ def test_calc_and_used_vars(tests_path):
             msg1 += 'VAR NOT CALCULATED: {}\n'.format(var)
     # Test (2):
     faux_functions = ['EITCamount', 'ComputeBenefit',
-                      'BenefitSurtax', 'BenefitLimitation']
+                      'BenefitSurtax', 'BenefitLimitation', 'AggCorpIncTax']
     found_error2 = False
     msg2 = 'calculated & returned variables are not function arguments\n'
     for fname in fnames:

taxcalc/utils.py

@@ -30,7 +30,7 @@
 STATS_COLUMNS = ['expanded_income', 'c00100', 'aftertax_income', 'standard',
                  'c04470', 'c04600', 'c04800', 'taxbc', 'c62100', 'c09600',
                  'c05800', 'othertaxes', 'refund', 'c07100', 'iitax',
-                 'payrolltax', 'combined', 's006']
+                 'payrolltax', 'combined', 's006', 'share_corptax_burden']
 
 # Items in the TABLE_COLUMNS list below correspond to the items in the
 # TABLE_LABELS list below; this correspondence allows us to use TABLE_LABELS
@@ -49,6 +49,10 @@
                 'Individual Income Tax Liabilities', 'Payroll Tax Liablities',
                 'Combined Payroll and Individual Income Tax Liabilities']
 
+# Items in the CORP_TABLE are used in the table fro the corporate income tax
+
+CORP_TABLE = ['s006', 'expanded_income', 'c00100', 'share_corptax_burden']
+
 # Following list is used in our difference table to label its columns.
 DIFF_TABLE_LABELS = ['Tax Units with Tax Cut', 'Tax Units with Tax Increase',
                      'Count', 'Average Tax Change', 'Total Tax Difference',
@@ -1273,3 +1277,55 @@ def delete_file(filename):
     """
     if os.path.isfile(filename):
         os.remove(filename)
+
+def create_corpinctax_table(calc, groupby, result_type, income_measure='expanded_income'):
+    res = results(calc.records)
+    # weight of returns with positive AGI and
+    # itemized deduction greater than standard deduction
+    res['c04470'] = res['c04470'].where(((res['c00100'] > 0) &
+                                        (res['c04470'] > res['standard'])), 0)
+
+    # weight of returns with positive AGI and itemized deduction
+    res['num_returns_ItemDed'] = res['s006'].where(((res['c00100'] > 0) &
+                                                   (res['c04470'] > 0)), 0)
+
+    # weight of returns with positive AGI and standard deduction
+    res['num_returns_StandardDed'] = res['s006'].where(((res['c00100'] > 0) &
+                                                    (res['standard'] > 0)),0)
+
+    # weight of returns with positive Alternative Minimum Tax (AMT)
+    res['num_returns_AMT'] = res['s006'].where(res['c09600'] > 0, 0)
+
+    # sorts the data
+    if groupby == "weighted_deciles":
+        df = add_weighted_income_bins(res, income_measure=income_measure)
+    elif groupby == "small_income_bins":
+        df = add_income_bins(res, compare_with="soi",
+                             income_measure=income_measure)
+    elif groupby == "large_income_bins":
+        df = add_income_bins(res, compare_with="tpc",
+                             income_measure=income_measure)
+    elif groupby == "webapp_income_bins":
+        df = add_income_bins(res, compare_with="webapp",
+                             income_measure=income_measure)
+    else:
+        err = ("groupby must be either 'weighted_deciles' or 'small_income_bins'"
+               "or 'large_income_bins' or 'webapp_income_bins'")
+        raise ValueError(err)
+
+    # manipulates the data
+    pd.options.display.float_format = '{:8,.0f}'.format
+    if result_type == "weighted_sum":
+        df = weighted(df, STATS_COLUMNS)
+        gp_mean = df.groupby('bins', as_index=False)[CORP_TABLE].sum()
+        gp_mean.drop('bins', axis=1, inplace=True)
+        sum_row = get_sums(df)[CORP_TABLE]
+    elif result_type == "weighted_avg":
+        gp_mean = weighted_avg_allcols(df, CORP_TABLE,
+                                       income_measure=income_measure)
+        sum_row = get_sums(df, not_available=True)[CORP_TABLE]
+    else:
+        err = ("result_type must be either 'weighted_sum' or 'weighted_avg")
+        raise ValueError(err)
+
+    return gp_mean.append(sum_row)