Merge pull request #45 from martinholmer/revert-pr-37

Postpone resolution of issue 36

Author: martinholmer

behresp/behavior.py

@@ -85,12 +85,6 @@ def response(calc_1, calc_2, behavior, dump=False):
       implications", Journal of Public Economics 84:1-32 (2002) [see
       equation 2 on page 10].
 
-    Note: the substitution effect here is calculated from a taxable income
-      base that excludes long-term capital gains, since long-term capital
-      gains behavior may be modeled separately using the capital-gains
-      elasticity. You should consider this when applying estimates of the
-      elasticity of taxable income from the literature.
-
     Note: the nature of the capital-gains elasticity used here is similar
       to that used in Joint Committee on Taxation, "New Evidence on the
       Tax Elasticity of Capital Gains: A Joint Working Paper of the Staff
@@ -200,10 +194,8 @@ def _mtr12(calc__1, calc__2, mtr_of='e00200p', tax_type='combined'):
             mtr1 = np.where(wage_mtr1 > mtr_cap, mtr_cap, wage_mtr1)
             mtr2 = np.where(wage_mtr2 > mtr_cap, mtr_cap, wage_mtr2)
             pch = ((1. - mtr2) / (1. - mtr1)) - 1.
-            # Note: c04800 is filing unit's taxable income and
-            #       p23250 is filing units' long-term capital gains
-            taxinc_less_ltcg = calc1.array('c04800') - calc1.array('p23250')
-            sub = (pvalue['BE_sub'] * pch * taxinc_less_ltcg)
+            # Note: c04800 is filing unit's taxable income
+            sub = pvalue['BE_sub'] * pch * calc1.array('c04800')
         # calculate magnitude of income effect
         if pvalue['BE_inc'] == 0.0:
             inc = np.zeros(calc1.array_len)

behresp/tests/test_behavior.py

@@ -8,6 +8,7 @@
 from io import StringIO
 import numpy as np
 import pandas as pd
+import pytest
 import taxcalc as tc
 from behresp import PARAM_INFO, response, quantity_response
 
@@ -133,24 +134,68 @@ def test_alternative_behavior_parameters(cps_subsample):
     del df2
 
 
-def test_sub_effect_independence():
+def test_quantity_response():
+    """
+    Test quantity_response function.
+    """
+    quantity = np.array([1.0] * 10)
+    res = quantity_response(quantity,
+                            price_elasticity=0,
+                            aftertax_price1=None,
+                            aftertax_price2=None,
+                            income_elasticity=0,
+                            aftertax_income1=None,
+                            aftertax_income2=None)
+    assert np.allclose(res, np.zeros(quantity.shape))
+    one = np.ones(quantity.shape)
+    res = quantity_response(quantity,
+                            price_elasticity=-0.2,
+                            aftertax_price1=one,
+                            aftertax_price2=one,
+                            income_elasticity=0.1,
+                            aftertax_income1=one,
+                            aftertax_income2=(one + one))
+    assert not np.allclose(res, np.zeros(quantity.shape))
+
+
+@pytest.mark.skip
+@pytest.mark.parametrize("stcg",
+                         [-3600,
+                          -2400,
+                          -1200,
+                          0,
+                          1200,
+                          2400,
+                          3600,
+                          4800])
+def test_sub_effect_independence(stcg):
     """
     Ensure that LTCG amount does not affect magnitude of substitution effect.
     """
+    # pylint: disable=too-many-locals
     # specify reform that raises top-bracket marginal tax rate
     refyear = 2020
     reform = {refyear: {'_II_rt7': [0.70]}}
     # specify a substitution effect behavioral response
     beh_json = """{
     "BE_sub": {"2013": 0.25}
     }"""
-    # specify input consisting of two filing units with high earnings, but
-    # with one having large long-term capital gains and the other having
-    # no long-term capital gains
-    input_csv = (u'RECID,MARS,e00200,e00200p,p23250\n'
-                 u'1,1,1000000,1000000,500000\n'
-                 u'2,1,1000000,1000000,0\n')
-    recs = tc.Records(data=pd.read_csv(StringIO(input_csv)),
+    # specify several high-earning filing units
+    num_recs = 9
+    input_csv = (u'RECID,MARS,e00200,e00200p,p22250,p23250\n'
+                 u'1,2,1000000,1000000,stcg,    0\n'
+                 u'2,2,1000000,1000000,stcg, 4800\n'
+                 u'3,2,1000000,1000000,stcg, 3600\n'
+                 u'4,2,1000000,1000000,stcg, 2400\n'
+                 u'5,2,1000000,1000000,stcg, 1200\n'
+                 u'6,2,1000000,1000000,stcg,    0\n'
+                 u'7,2,1000000,1000000,stcg,-1200\n'
+                 u'8,2,1000000,1000000,stcg,-2400\n'
+                 u'9,2,1000000,1000000,stcg,-3600\n')
+    inputcsv = input_csv.replace('stcg', str(stcg))
+    input_dataframe = pd.read_csv(StringIO(inputcsv))
+    assert len(input_dataframe.index) == num_recs
+    recs = tc.Records(data=input_dataframe,
                       start_year=refyear,
                       gfactors=None, weights=None)
     beh_dict = tc.Calculator.read_json_assumptions(beh_json)
@@ -164,39 +209,24 @@ def test_sub_effect_independence():
     df1, df2 = response(calc1, calc2, beh_dict)
     del calc1
     del calc2
-    # compute change in taxable income for each of the two filing units
-    chg_funit1 = df2['c04800'][0] - df1['c04800'][0]  # funit with RECID=1
-    chg_funit2 = df2['c04800'][1] - df1['c04800'][1]  # funit with RECID=2
+    # compute change in taxable income for each of the filing units
+    chg_funit = dict()
+    for rid in range(1, num_recs + 1):
+        idx = rid - 1
+        chg_funit[rid] = df2['c04800'][idx] - df1['c04800'][idx]
     del df1
     del df2
     # confirm reform reduces taxable income when assuming substitution effect
-    assert chg_funit1 < 0
-    assert chg_funit2 < 0
-    # confirm change in taxable income is same for the two filing units
-    assert np.allclose(chg_funit1, chg_funit2)
-    del chg_funit1
-    del chg_funit2
-
-
-def test_quantity_response():
-    """
-    Test quantity_response function.
-    """
-    quantity = np.array([1.0] * 10)
-    res = quantity_response(quantity,
-                            price_elasticity=0,
-                            aftertax_price1=None,
-                            aftertax_price2=None,
-                            income_elasticity=0,
-                            aftertax_income1=None,
-                            aftertax_income2=None)
-    assert np.allclose(res, np.zeros(quantity.shape))
-    one = np.ones(quantity.shape)
-    res = quantity_response(quantity,
-                            price_elasticity=-0.2,
-                            aftertax_price1=one,
-                            aftertax_price2=one,
-                            income_elasticity=0.1,
-                            aftertax_income1=one,
-                            aftertax_income2=(one + one))
-    assert not np.allclose(res, np.zeros(quantity.shape))
+    emsg = ''
+    for rid in range(1, num_recs + 1):
+        if not chg_funit[rid] < 0:
+            txt = '\nFAIL: stcg={} : chg[{}]={:.2f} is not negative'
+            emsg += txt.format(stcg, rid, chg_funit[rid])
+    # confirm change in taxable income is same for all filing units
+    for rid in range(2, num_recs + 1):
+        if not np.allclose(chg_funit[rid], chg_funit[1]):
+            txt = '\nFAIL: stcg={} : chg[{}]={:.2f} != chg[1]={:.2f}'
+            emsg += txt.format(stcg, rid, chg_funit[rid], chg_funit[1])
+    del chg_funit
+    if emsg:
+        raise ValueError(emsg)