Merge pull request #1579 from martinholmer/fix-gdp-logic

Fix macro-elasticity logic so that GDP change in year t depends on tax change in year t-1

RELEASES.md

@@ -35,6 +35,9 @@ Release 0.12.0 on 2017-??-??
 - Relax _STD and _STD_Dep minimum value warning logic
   [[#1578](https://github.com/open-source-economics/Tax-Calculator/pull/1578)
   by Martin Holmer]
+- Fix macro-elasticity model logic so that GDP change in year t depends on tax rate changes in year t-1
+  [[#1579](https://github.com/open-source-economics/Tax-Calculator/pull/1579)
+  by Martin Holmer]
 
 Release 0.11.0 on 2017-09-21
 ----------------------------

taxcalc/calculate.py

@@ -187,6 +187,13 @@ def current_year(self):
         """
         return self.policy.current_year
 
+    @property
+    def data_year(self):
+        """
+        Calculator class initial (i.e., first) records data year property.
+        """
+        return self.records.data_year
+
     MTR_VALID_VARIABLES = ['e00200p', 'e00200s',
                            'e00900p', 'e00300',
                            'e00400', 'e00600',

taxcalc/macro_elasticity.py

@@ -5,54 +5,76 @@
 # pep8 --ignore=E402 macro_elasticity.py
 # pylint --disable=locally-disabled macro_elasticity.py
 
+from taxcalc.policy import Policy
 
-def proportional_change_gdp(calc1, calc2, elasticity):
+
+def proportional_change_in_gdp(year, calc1, calc2, elasticity):
     '''
     This function harnesses econometric estimates of the historic relationship
-    between tax policy and the macroeconomy to predict the effect of tax
-    reforms on growth.
+    between tax policy and the macro economy to predict the effect of tax
+    reforms on economic growth.
 
     In particular, this model relies on estimates of how GDP responds to
     changes in the average after tax rate on wage income across all taxpayers
     (one minus the average marginal tax rate, or 1-AMTR). These estimates are
     derived from calculations of income-weighted marginal tax rates under the
-    baseline and reform.
+    baseline and reform.  The reform-induced change in GDP in year t is
+    assumed to be equal to the assumed elasticity times the absolute (not
+    proportional) change in one minus the average marginal tax rate in
+    year t-1.  In other words, the current-year change in GDP is assumed to
+    be related to the prior-year change in the average marginal tax rate.
 
     Empirical evidence on this elasticity can be found in Robert Barro
     and Charles Redlick, "Macroeconomic Effects from Government Purchases
-    and Taxes" (2011 Quarterly Journal of Economics).  In particular,
-    Barro and Redlick find that a 1 percentage point decrease in the AMTR
-    leads to a 0.54 percent increase in GDP.  Evaluated at the sample mean,
-    this translates to an elasticity of GDP with respect to the average
-    after-tax marginal rate of about 0.36.
+    and Taxes" (2011 Quarterly Journal of Economics).  A pre-publication
+    version of this paper is available at the following URL:
+    <siteresources.worldbank.org/INTMACRO/Resources/BarroBRedlickBpaper.pdf>.
+    In particular, Barro and Redlick find that a 1 percentage point decrease
+    in the AMTR leads to a 0.54 percent increase in GDP.  Evaluated at the
+    sample mean, this translates to an elasticity of GDP with respect to the
+    average after-tax marginal rate of about 0.36.
 
     A more recent paper by Karel Mertens and Jose L. Montiel Olea,
     entitled "Marginal Tax Rates and Income: New Time Series Evidence",
     NBER working paper 19171 (June 2013 with September 2017 revisions)
-    <http://www.nber.org/papers/w19171.pdf>,
-    contains additional empirical evidence suggesting the elasticity is
-    no less than the 0.36 Barro-Redlick estimate and perhaps somewhat
-    higher (see section 4.6).
+    <www.nber.org/papers/w19171.pdf>, contains additional empirical
+    evidence suggesting the elasticity is no less than the 0.36 Barro-
+    Redlick estimate and perhaps somewhat higher (see section 4.6).
+    Their summary of the Barro and Redlick findings (on page 5) are
+    as follows: "Barro and Redlick (2011) however find that a one
+    percentage point cut in the AMTR raises per capita GDP by around
+    0.5% in the following year. This estimate is statistically
+    significant and amounts to a short run GDP elasticity to the
+    net-of-tax rate of 0.36".
 
     Parameters
     ----------
-    calc1 : Calculator object for the pre-reform baseline
-    calc2 : Calculator object for the policy reform
+    year : calendar year of the reform-induced proportion change in GDP
+    calc1 : Calculator object for the pre-reform baseline for prior year
+    calc2 : Calculator object for the policy reform for prior year
     elasticity: Float estimate of elasticity of GDP wrt 1-AMTR
 
     Returns
     -------
-    Float estimate of proportional GDP impact of the reform.
+    Float estimate of proportional change in GDP induced by the reform
+    Note that proportional means a relative change but it is not expressed
+    in percentage terms
     '''
+    assert elasticity >= 0.0
+    assert calc1.current_year == calc2.current_year
+    assert calc1.data_year == calc2.data_year
+    if year <= max(Policy.JSON_START_YEAR, calc1.data_year):
+        return 0.0  # because Calculator cannot simulate taxes in year-1
+    if calc1.current_year != (year - 1):
+        msg = 'calc.current_year={} must be one less than year={}'
+        raise ValueError(msg.format(calc1.current_year, year))
     _, _, mtr_combined1 = calc1.mtr()
     _, _, mtr_combined2 = calc2.mtr()
-    avg_one_mtr1 = (1.0 - (mtr_combined1 * calc1.records.c00100 *
-                           calc1.records.s006).sum() /
-                    (calc1.records.c00100 * calc1.records.s006).sum())
-    avg_one_mtr2 = (1.0 - (mtr_combined2 * calc2.records.c00100 *
-                           calc2.records.s006).sum() /
-                    (calc2.records.c00100 * calc2.records.s006).sum())
-    diff_avg_one_mtr = avg_one_mtr2 - avg_one_mtr1
-    proportional_diff_mtr = diff_avg_one_mtr / avg_one_mtr1
-    gdp_effect_of_reform = proportional_diff_mtr * elasticity
-    return gdp_effect_of_reform
+    avg_mtr1 = ((mtr_combined1 * calc1.records.c00100 *
+                 calc1.records.s006).sum() /
+                (calc1.records.c00100 * calc1.records.s006).sum())
+    avg_mtr2 = ((mtr_combined2 * calc2.records.c00100 *
+                 calc2.records.s006).sum() /
+                (calc2.records.c00100 * calc2.records.s006).sum())
+    proportional_chg_in_rate = ((1.0 - avg_mtr2) / (1.0 - avg_mtr1)) - 1.0
+    return elasticity * proportional_chg_in_rate

taxcalc/records.py

@@ -14,10 +14,6 @@
 from taxcalc.utils import read_egg_csv, read_egg_json
 
 
-PUFCSV_YEAR = 2009
-CPSCSV_YEAR = 2014
-
-
 class Records(object):
     """
     Constructor for the tax-filing-unit Records class.
@@ -100,6 +96,9 @@ class instance: Records
     # suppress pylint warnings about too many class instance attributes:
     # pylint: disable=too-many-instance-attributes
 
+    PUFCSV_YEAR = 2009
+    CPSCSV_YEAR = 2014
+
     CUR_PATH = os.path.abspath(os.path.dirname(__file__))
     PUF_WEIGHTS_FILENAME = 'puf_weights.csv'
     PUF_RATIOS_FILENAME = 'puf_ratios.csv'
@@ -191,7 +190,7 @@ def cps_constructor(data=None,
                        gfactors=gfactors,
                        weights=Records.CPS_WEIGHTS_FILENAME,
                        adjust_ratios=Records.CPS_RATIOS_FILENAME,
-                       start_year=CPSCSV_YEAR)
+                       start_year=Records.CPSCSV_YEAR)
 
     @property
     def data_year(self):

taxcalc/tbi/tbi.py

@@ -1,4 +1,6 @@
 """
+The public API of the TaxBrain Interface (tbi).
+
 The tbi functions are used by TaxBrain to call Tax-Calculator in order
 to do distributed processing of TaxBrain runs and in order to maintain
 the privacy of the IRS-SOI PUF data being used by TaxBrain.  Maintaining
@@ -16,12 +18,14 @@
 import time
 import numpy as np
 import pandas as pd
-from taxcalc.tbi.tbi_utils import (calculate,
+from taxcalc.tbi.tbi_utils import (check_years_return_first_year,
+                                   calculate,
                                    random_seed,
                                    summary,
                                    AGGR_ROW_NAMES)
 from taxcalc import (results, DIST_TABLE_LABELS,
-                     proportional_change_gdp, Growdiff, Growfactors, Policy)
+                     proportional_change_in_gdp,
+                     Growdiff, Growfactors, Policy)
 
 
 # specify constants
@@ -99,6 +103,7 @@ def run_nth_year_tax_calc_model(year_n, start_year,
     start_time = time.time()
 
     # create calc1 and calc2 calculated for year_n and mask
+    check_years_return_first_year(year_n, start_year, use_puf_not_cps)
     (calc1, calc2, mask) = calculate(year_n, start_year,
                                      use_puf_not_cps, use_full_sample,
                                      user_mods,
@@ -178,17 +183,22 @@ def run_nth_year_gdp_elast_model(year_n, start_year,
     Setting use_full_sample=False implies use sub-sample of input file;
       otherwsie, use the complete sample.
     """
-    # pylint: disable=too-many-arguments
-
-    # create calc1 and calc2 calculated for year_n
-    (calc1, calc2, _) = calculate(year_n, start_year,
-                                  use_puf_not_cps,
-                                  use_full_sample,
-                                  user_mods,
-                                  behavior_allowed=False)
+    # pylint: disable=too-many-arguments,too-many-locals
 
-    # compute GDP effect given specified gdp_elasticity
-    gdp_effect = proportional_change_gdp(calc1, calc2, gdp_elasticity)
+    # calculate gdp_effect
+    fyear = check_years_return_first_year(year_n, start_year, use_puf_not_cps)
+    if (start_year + year_n) > fyear:
+        # create calc1 and calc2 calculated for year_n - 1
+        (calc1, calc2, _) = calculate((year_n - 1), start_year,
+                                      use_puf_not_cps,
+                                      use_full_sample,
+                                      user_mods,
+                                      behavior_allowed=False)
+        # compute GDP effect given specified gdp_elasticity
+        gdp_effect = proportional_change_in_gdp((start_year + year_n),
+                                                calc1, calc2, gdp_elasticity)
+    else:
+        gdp_effect = 0.0
 
     # return gdp_effect results
     if return_dict:

taxcalc/tbi/tbi_utils.py

@@ -20,20 +20,28 @@
                            WEBAPP_INCOME_BINS, read_egg_csv)
 
 
-def check_years(start_year, year_n):
+def check_years_return_first_year(year_n, start_year, use_puf_not_cps):
     """
-    Ensure start_year and year_n values are consistent with Policy constants.
+    Ensure year_n and start_year values are valid given input data used.
+    Return value of first year, which is maximum of first records data year
+    and first policy parameter year.
     """
-    if start_year < Policy.JSON_START_YEAR:
-        msg = 'start_year={} < Policy.JSON_START_YEAR={}'
-        raise ValueError(msg.format(start_year, Policy.JSON_START_YEAR))
     if year_n < 0:
         msg = 'year_n={} < 0'
         raise ValueError(msg.format(year_n))
+    if use_puf_not_cps:
+        first_data_year = Records.PUFCSV_YEAR
+    else:
+        first_data_year = Records.CPSCSV_YEAR
+    first_year = max(Policy.JSON_START_YEAR, first_data_year)
+    if start_year < first_year:
+        msg = 'start_year={} < first_year={}'
+        raise ValueError(msg.format(start_year, first_year))
     if (start_year + year_n) > Policy.LAST_BUDGET_YEAR:
         msg = '(start_year={} + year_n={}) > Policy.LAST_BUDGET_YEAR={}'
         raise ValueError(msg.format(start_year, year_n,
                                     Policy.LAST_BUDGET_YEAR))
+    return first_year
 
 
 def check_user_mods(user_mods):
@@ -70,7 +78,6 @@ def calculate(year_n, start_year,
     # pylint: disable=too-many-arguments,too-many-locals
     # pylint: disable=too-many-branches,too-many-statements
 
-    check_years(start_year, year_n)
     check_user_mods(user_mods)
 
     # specify Consumption instance

taxcalc/tests/test_macro_elasticity.py

@@ -1,17 +1,43 @@
-from taxcalc import Policy, Records, Calculator, proportional_change_gdp
+"""
+Tests of proportional_change_in_gdp function.
+"""
+# CODING-STYLE CHECKS:
+# pep8 --ignore=E402 test_macro_elasticity.py
+# pylint --disable=locally-disabled test_macro_elasticity.py
 
+import pytest
+from taxcalc import (Policy, Records,  # pylint: disable=import-error
+                     Calculator, proportional_change_in_gdp)
 
-def test_proportional_change_gdp(cps_subsample):
+
+def test_proportional_change_in_gdp(cps_subsample):
+    """
+    Test correct and incorrect calls to proportional_change_in_gdp function.
+    """
     rec1 = Records.cps_constructor(data=cps_subsample)
     calc1 = Calculator(policy=Policy(), records=rec1)
     rec2 = Records.cps_constructor(data=cps_subsample)
     pol2 = Policy()
-    reform = {2013: {'_II_em': [0.0]}}  # reform increases taxes and MTRs
+    reform = {2015: {'_II_em': [0.0]}}  # reform increases taxes and MTRs
     pol2.implement_reform(reform)
     calc2 = Calculator(policy=pol2, records=rec2)
-    calc1.advance_to_year(2014)
-    calc2.advance_to_year(2014)
-    gdp_pchg = 100.0 * proportional_change_gdp(calc1, calc2, elasticity=0.36)
-    exp_pchg = -0.6  # higher MTRs imply negative expected GDP percent change
+    assert calc1.current_year == 2014  # because using CPS data
+    gdpc = proportional_change_in_gdp(2014, calc1, calc2, elasticity=0.36)
+    assert gdpc == 0.0  # no effect for first data year
+    gdpc = proportional_change_in_gdp(2015, calc1, calc2, elasticity=0.36)
+    assert gdpc == 0.0  # no effect in first year of reform
+    calc1.increment_year()
+    calc2.increment_year()
+    assert calc1.current_year == 2015
+    gdp_pchg = 100.0 * proportional_change_in_gdp(2016, calc1, calc2,
+                                                  elasticity=0.36)
+    exp_pchg = -0.54  # higher MTRs imply negative expected GDP percent change
     abs_diff_pchg = abs(gdp_pchg - exp_pchg)
-    assert abs_diff_pchg < 0.05
+    if abs_diff_pchg > 0.01:
+        msg = 'year,gdp_pchg,exp_pchg= {} {:.3f} {:.3f}'.format(2016,
+                                                                gdp_pchg,
+                                                                exp_pchg)
+        assert msg == 'ERROR: gdp_pchg not close to exp_pchg'
+    # skip calcN.increment_year to 2016, so calcN.current_year is still 2015
+    with pytest.raises(ValueError):
+        proportional_change_in_gdp(2017, calc1, calc2, elasticity=0.36)

taxcalc/tests/test_records.py

@@ -5,7 +5,7 @@
 import pandas as pd
 import pytest
 from io import StringIO
-from taxcalc import Growfactors, Policy, Records, Calculator, CPSCSV_YEAR
+from taxcalc import Growfactors, Policy, Records, Calculator
 
 
 def test_incorrect_Records_instantiation(cps_subsample):
@@ -42,7 +42,7 @@ def test_correct_Records_instantiation(cps_subsample):
                    gfactors=Growfactors(),
                    weights=wghts_df,
                    adjust_ratios=ratio_df,
-                   start_year=CPSCSV_YEAR)
+                   start_year=Records.CPSCSV_YEAR)
     assert rec2
     assert np.all(rec2.MARS != 0)
     assert rec2.current_year == rec2.data_year

taxcalc/tests/test_tbi.py

@@ -36,7 +36,7 @@
                           (2017, 10)])
 def test_check_years_errors(start_year, year_n):
     with pytest.raises(ValueError):
-        check_years(start_year, year_n)
+        check_years_return_first_year(year_n, start_year, use_puf_not_cps=True)
 
 
 def test_check_user_mods_errors():