Are tbi behavioral-response results for TCJA reform different from non-tbi results? #1827

MattHJensen · 2018-01-14T23:17:49Z

I am finding these on TaxBrain.

https://www.ospc.org/dynamic/behavior_results/820/

cc @codykallen @martinholmer @hdoupe @siervicul

martinholmer · 2018-01-15T15:00:40Z

@MattHJensen,

Do you get the same "very odd" results using the tc command-line tool?

If so, please post your tc results here and explain what about them is "very odd".

If not, then this issue should be moved to the PolicyBrain repository.

MattHJensen · 2018-01-15T15:31:27Z

I have not replicated the results with the tc command line tool.

I opened this issue here because the TaxBrain PE page is an interface to Tax-Calculator and my intuition is that this is a problem in Tax-Calculator rather than TaxBrain. I could be wrong, but if I'm right, I thought other Tax-Calculator devs would want to know about this quickly.

The results are very odd because they say that the Tax Cuts and Jobs Act raises $6 Trillion of revenue over 10 years. The JCT, for instance, scores the individual side of TCJA as losing $1.1 T over the same period.

GoFroggyRun · 2018-01-22T20:31:40Z

To provide more information regarding this PR, I created a TCJA reform that resembles the current TCJA preset on taxBrain, upon which the result here is generated, and got the following result based on the current TC master as of Jan.22, 2018:

Here is its counterpart on TB:

Based on the results in TC, the total combined liability over 10 years is $34,662.52 B, which yields a loss of $0.55 T over the period.

It seems to me that something went wrong in TB (particularly within the dynamic provision as static results do match between TB and TC) starting 2020.

Here is the reform file used:

{
    "policy": {
        "_II_rt1":
            {"2018": [0.1],
             "2026": [0.1]},
        "_II_rt2":
            {"2018": [0.12],
             "2026": [0.15]},
        "_II_rt3":
            {"2018": [0.22],
             "2026": [0.25]},
        "_II_rt4":
            {"2018": [0.24],
             "2026": [0.28]},
        "_II_rt5":
            {"2018": [0.32],
             "2026": [0.33]},
        "_II_rt6":
            {"2018": [0.35],
             "2026": [0.35]},
        "_II_rt7":
            {"2018": [0.37],
             "2026": [0.396]},
        "_II_brk1":
            {"2018": [[9525, 19050, 9525, 13600, 19050]],
             "2026": [[11242, 22484, 11242, 16094, 22484]]},
        "_II_brk2":
            {"2018": [[38700, 77400, 38700, 51800, 77400]],
             "2026": [[45751, 91502, 45751, 61242, 91502]]},
        "_II_brk3":
            {"2018": [[82500, 165000, 82500, 82500, 165000]],
             "2026": [[110791, 184571,  92286, 158169, 184571]]},
        "_II_brk4":
            {"2018": [[157500, 315000, 157500, 157500, 315000]],
             "2026": [[231045, 281317, 140659, 256181, 281317]]},
        "_II_brk5":
            {"2018": [[200000, 400000, 200000, 200000, 400000]],
             "2026": [[502356, 502356, 251178, 502356, 502356]]},
        "_II_brk6":
            {"2018": [[500000, 600000, 300000, 500000, 500000]],
             "2026": [[504406 ,567457, 283728, 535931, 567457]]},
        "_PT_rt1":
            {"2018": [0.1],
             "2026": [0.1]},
        "_PT_rt2":
            {"2018": [0.12],
             "2026": [0.15]},
        "_PT_rt3":
            {"2018": [0.22],
             "2026": [0.25]},
        "_PT_rt4":
            {"2018": [0.24],
             "2026": [0.28]},
        "_PT_rt5":
            {"2018": [0.32],
             "2026": [0.33]},
        "_PT_rt6":
            {"2018": [0.35],
             "2026": [0.35]},
        "_PT_rt7":
            {"2018": [0.37],
             "2026": [0.396]},
        "_PT_brk1":
            {"2018": [[9525, 19050, 9525, 13600, 19050]],
             "2026": [[11242, 22484, 11242, 16094, 22484]]},
        "_PT_brk2":
            {"2018": [[38700, 77400, 38700, 51800, 77400]],
             "2026": [[45751, 91502, 45751, 61242, 91502]]},
        "_PT_brk3":
            {"2018": [[82500, 165000, 82500, 82500, 165000]],
             "2026": [[110791, 184571, 92286, 158169, 184571]]},
        "_PT_brk4":
            {"2018": [[157500, 315000, 157500, 157500, 315000]],
             "2026": [[231045, 281317, 140659, 256181, 281317]]},
        "_PT_brk5":
            {"2018": [[200000, 400000, 200000, 200000, 400000]],
             "2026": [[502356, 502356, 251178, 502356, 502356]]},
        "_PT_brk6":
            {"2018": [[500000, 600000, 300000, 500000, 500000]],
             "2026": [[504406, 567457, 283728, 535931, 567457]]},
        "_PT_excl_rt":
            {"2018": [0.2],
             "2026": [0.0]},
        "_PT_excl_wagelim_rt":
            {"2018": [0.5],
             "2026": [9e99]},
        "_STD":
            {"2018": [[12000, 24000, 12000, 18000, 24000]],
             "2026": [[7655, 15311, 7655, 11272, 15311]]},
        "_II_em":
            {"2018": [0],
             "2026": [4883]},
        "_CTC_ps":
            {"2018": [[200000, 400000, 200000, 200000, 400000]],
             "2026": [[75000, 110000, 55000, 75000, 75000]]},
        "_CTC_c":
            {"2018": [1400],
             "2022": [1500],
             "2025": [1600],
             "2026": [1000]},
        "_ALD_AlimonyPaid_hc":
            {"2019": [1],
             "2026": [0]},
        "_DependentCredit_Child_c":
            {"2018": [600],
             "2022": [500],
             "2025": [400],
             "2026": [0]},
        "_DependentCredit_Nonchild_c":
            {"2018": [500],
             "2026": [0]},
        "_DependentCredit_before_CTC":
            {"2018": [true]},  
        "_ACTC_Income_thd":
            {"2018": [2500],
             "2026": [3000]},
        "_AMT_em":
            {"2018": [[70300, 109400, 54700, 70300, 109400]],
             "2026": [[65462, 101870, 50935, 65461, 101870]]},
        "_AMT_em_ps":
            {"2018": [[500000, 1000000, 500000, 500000, 1000000]],
             "2026": [[145511, 193974, 96987, 145511, 193974]]},
        "_ALD_DomesticProduction_hc":
            {"2018": [1],
             "2026": [0]},
        "_ID_prt":
            {"2018": [0],
             "2026": [0.03]},
        "_ID_crt":
            {"2018": [1],
             "2026": [0.8]},
        "_ID_Charity_crt_all":
            {"2018": [0.6],
             "2026": [0.5]},
        "_ID_Casualty_hc":
            {"2018": [1],
             "2026": [0]},
        "_ID_AllTaxes_c":
            {"2018": [[10000, 10000, 5000, 10000, 10000]],
             "2026": [[9e99, 9e99, 9e99, 9e99, 9e99]]},
        "_ID_Miscellaneous_hc":
            {"2018": [1],
             "2026": [0]},
        "_ID_Medical_frt":
            {"2017": [0.075],
             "2019": [0.1]},
        "_cpi_offset":
            {"2017": [-0.0025]}  
    }
}

The assumption content:

{2018: {'_BE_sub': [0.25]}}

MattHJensen · 2018-01-22T20:56:11Z

Thanks very much @GoFroggyRun. Sounds like this issue does belong in PolicyBrain then. Could you reopen over there? Closing here.

martinholmer · 2018-01-22T20:56:45Z

@GoFroggyRun, Thanks for providing in issue #1827 TCJA reform behavioral results generated directly by Tax-Calculator. Am I reading your comment correctly when I say your analysis suggests that the odd results @MattHJensen got using TaxBrain might be a TaxBrain problem? To be sure about that, I guess you need to determine that you get the kind of results you reported above calling tbi functions rather than calling Behavior directly, which is what I imagine you did. What script did you run to get your results?

@hdoupe

GoFroggyRun · 2018-01-22T21:14:49Z

@martinholmer thanks for your suggestion. I actually tried to generate results via tbi, it seems that, however, in order to replicate the results on TB, the base line has to be 2017_law.json. And I am not aware of how to do that via tbi.

hdoupe · 2018-01-22T21:22:10Z

@GoFroggyRun tbi is the last hand off from taxcalc to TaxBrain. It would be nice to inspect the results from that before we dive into the TaxBrain side. You can modify this script here to do this.

import taxcalc
import numpy as np
import pandas as pd

kw = {
    'start_year': 2017,
    'use_full_sample': True,
    'user_mods': {
        u'policy': {
            2017: {
                u'_FICA_ss_trt': [0.01],
            }
        },
        u'growdiff_response': {},
        u'behavior': {},
        u'consumption': {},
        u'growdiff_baseline': {}
    },
    'year_n': 0,
    'use_puf_not_cps': True,
    'return_dict': False
}

results_df = taxcalc.tbi.run_nth_year_tax_calc_model(**kw)

assert np.allclose(
    (results_df['dist1_xdec']['iitax_0'] +
     results_df['dist1_xdec']['payrolltax_0']).values,
     results_df['dist1_xdec']['combined_0'].values,
     atol=0.0,
     rtol=0.01
)

assert np.allclose(
    (results_df['dist2_xdec']['iitax_0'] +
     results_df['dist2_xdec']['payrolltax_0']).values,
     results_df['dist2_xdec']['combined_0'].values,
     atol=0.0,
     rtol=0.01
)


kw['return_dict'] = True
results_dict = taxcalc.tbi.run_nth_year_tax_calc_model(**kw)

dist_labels = [str((lab, col)) for lab, col in zip(taxcalc.DIST_TABLE_LABELS, taxcalc.DIST_TABLE_COLUMNS)]
diff_labels = [str((lab, col)) for lab, col in zip(taxcalc.DIFF_TABLE_LABELS, taxcalc.DIFF_TABLE_COLUMNS)]


for table_id, _var, labels in [('dist1_xdec', '0-10_0', dist_labels),
                               ('dist1_xbin', '<$10K_0', dist_labels),
                               ('diff_itax_xdec', '0-10_0', diff_labels),
                               ('diff_ptax_xbin', '<$10K_0', diff_labels)]:
    dict_0_10 = {k: [v] for k, v in zip(labels, results_dict[table_id][_var])}
    dict_df_0_10 = pd.DataFrame(dict_0_10)


    print('\n\ncurrent law dist table by {} for year 0 and var {}'.format(table_id, _var))
    print('\ndataframe version\n')
    print(results_df[table_id].iloc[0])
    print('\ndict version\n')
    print(dict_df_0_10.T)


print('\n\ncurrent law aggregate results')
print('\ndataframe version\n')
print(results_df['aggr_d'])
print('\ndict version\n')
print(results_dict['aggr_d'])

You'll need to get the policy in dictionary form from taxcalc.Calculator.read_json_param_objects() and plug that in to the policy keyword in the kw dictionary above.

Thanks for looking into this. Please let me know if you have any problems/questions.

GoFroggyRun · 2018-01-22T21:30:49Z

@hdoupe I'm a bit confused. Could you clarify how the script you provided allows me to specify alternative baseline for behavioral assumptions?

hdoupe · 2018-01-22T22:00:11Z

@GoFroggyRun is this what you have in mind?

import taxcalc
print('taxcalc vers:', taxcalc.__version__)
import numpy as np
import pandas as pd
#https://github.com/hdoupe/PolicyBrain/blob/17a8043d0e7d4e16d600e27918b56723b4e7574d/webapp/apps/test_assets/test_tcja.py
tcja_json = """
// Title: Tax Cuts and Jobs Act, Reconciliation version
// Reform_File_Author: Cody Kallen
// Reform_Reference: http://docs.house.gov/billsthisweek/20171218/CRPT-115HRPT-466.pdf
// Reform_Baseline: 2017_law.json
// Reform_Description:
// -  New personal income tax schedule (regular/non-AMT/non-pass-through) (1)
// -  New pass-through income tax schedule (2)
// -  New standard deductions (3)
// -  Repeal personal exemption (4)
// -  Modification to child tax credit, nonrefundable dependent credits (5)
// -  Modification of Alternative Minimum Tax exemption (6)
// -  Repeal of certain above the line deductions (7)
// -  Changes to itemized deductions (8)
// -  Switch to chained CPI from CPI-U for tax parameter adjustment (9)
// Reform_Parameter_Map:
// - 1: _II_*
// - 2: _PT_*
// - 3: _STD (can safely ignore WARNINGs about 2026+ values)
// - 4: _II_em
// - 5: _DependentCredit_*, _CTC_c, _CTC_ps, _ACTC_Income_thd
// - 6: _AMT_rt*
// - 7: _ALD_*
// - 8: _ID_* (can safely ignore WARNINGs about values for several parameters)
// - 9: _cpi_offset
// Note: _II_rt*, _PT_rt*, _STD and _II_em are rounded to the nearest integer value.
{
    "policy": {
        "_II_rt1":
            {"2018": [0.1],
             "2026": [0.1]},
        "_II_rt2":
            {"2018": [0.12],
             "2026": [0.15]},
        "_II_rt3":
            {"2018": [0.22],
             "2026": [0.25]},
        "_II_rt4":
            {"2018": [0.24],
             "2026": [0.28]},
        "_II_rt5":
            {"2018": [0.32],
             "2026": [0.33]},
        "_II_rt6":
            {"2018": [0.35],
             "2026": [0.35]},
        "_II_rt7":
            {"2018": [0.37],
             "2026": [0.396]},
        "_II_brk1":
            {"2018": [[9525, 19050, 9525, 13600, 19050]],
             "2026": [[11242, 22484, 11242, 16094, 22484]]},
        "_II_brk2":
            {"2018": [[38700, 77400, 38700, 51800, 77400]],
             "2026": [[45751, 91502, 45751, 61242, 91502]]},
        "_II_brk3":
            {"2018": [[82500, 165000, 82500, 82500, 165000]],
             "2026": [[110791, 184571,  92286, 158169, 184571]]},
        "_II_brk4":
            {"2018": [[157500, 315000, 157500, 157500, 315000]],
             "2026": [[231045, 281317, 140659, 256181, 281317]]},
        "_II_brk5":
            {"2018": [[200000, 400000, 200000, 200000, 400000]],
             "2026": [[502356, 502356, 251178, 502356, 502356]]},
        "_II_brk6":
            {"2018": [[500000, 600000, 300000, 500000, 500000]],
             "2026": [[504406 ,567457, 283728, 535931, 567457]]},
        "_PT_rt1":
            {"2018": [0.1],
             "2026": [0.1]},
        "_PT_rt2":
            {"2018": [0.12],
             "2026": [0.15]},
        "_PT_rt3":
            {"2018": [0.22],
             "2026": [0.25]},
        "_PT_rt4":
            {"2018": [0.24],
             "2026": [0.28]},
        "_PT_rt5":
            {"2018": [0.32],
             "2026": [0.33]},
        "_PT_rt6":
            {"2018": [0.35],
             "2026": [0.35]},
        "_PT_rt7":
            {"2018": [0.37],
             "2026": [0.396]},
        "_PT_brk1":
            {"2018": [[9525, 19050, 9525, 13600, 19050]],
             "2026": [[11242, 22484, 11242, 16094, 22484]]},
        "_PT_brk2":
            {"2018": [[38700, 77400, 38700, 51800, 77400]],
             "2026": [[45751, 91502, 45751, 61242, 91502]]},
        "_PT_brk3":
            {"2018": [[82500, 165000, 82500, 82500, 165000]],
             "2026": [[110791, 184571, 92286, 158169, 184571]]},
        "_PT_brk4":
            {"2018": [[157500, 315000, 157500, 157500, 315000]],
             "2026": [[231045, 281317, 140659, 256181, 281317]]},
        "_PT_brk5":
            {"2018": [[200000, 400000, 200000, 200000, 400000]],
             "2026": [[502356, 502356, 251178, 502356, 502356]]},
        "_PT_brk6":
            {"2018": [[500000, 600000, 300000, 500000, 500000]],
             "2026": [[504406, 567457, 283728, 535931, 567457]]},
        "_PT_exclusion_rt":
            {"2018": [0.2],
             "2026": [0.0]},
        "_PT_exclusion_wage_limit":
            {"2018": [0.5],
             "2026": [9e+99]},
        "_STD":
            {"2018": [[12000, 24000, 12000, 18000, 24000]],
             "2026": [[7655, 15311, 7655, 11272, 15311]]},
        "_II_em":
            {"2018": [0],
             "2026": [4883]},
        "_CTC_ps":
            {"2018": [[200000, 400000, 200000, 200000, 400000]],
             "2026": [[75000, 110000, 55000, 75000, 75000]]},
        "_CTC_c":
            {"2018": [1400],
             "2022": [1500],
             "2025": [1600],
             "2026": [1000]},
        "_DependentCredit_Child_c":
            {"2018": [600],
             "2022": [500],
             "2025": [400],
             "2026": [0]},
        "_DependentCredit_Nonchild_c":
            {"2018": [500],
             "2026": [0]},
        "_DependentCredit_before_CTC":
            {"2018": [true]},
        "_ACTC_Income_thd":
            {"2018": [2500],
             "2026": [3000]},
        "_AMT_em":
            {"2018": [[70300, 109400, 54700, 70300, 109400]],
             "2026": [[65462, 101870, 50935, 65461, 101870]]},
        "_AMT_em_ps":
            {"2018": [[500000, 1000000, 500000, 500000, 1000000]],
             "2026": [[145511, 193974, 96987, 145511, 193974]]},
        "_ALD_DomesticProduction_hc":
            {"2018": [1],
             "2026": [0]},
        "_ALD_Alimony_hc":
            {"2019": [1],
             "2026": [0]},
        "_ID_prt":
            {"2018": [0],
             "2026": [0.03]},
        "_ID_crt":
            {"2018": [1],
             "2026": [0.8]},
        "_ID_Charity_crt_all":
            {"2018": [0.6],
             "2026": [0.5]},
        "_ID_Casualty_hc":
            {"2018": [1],
             "2026": [0]},
        "_ID_AllTaxes_c":
            {"2018": [[10000, 10000, 5000, 10000, 10000]],
             "2026": [[9e99, 9e99, 9e99, 9e99, 9e99]]},
        "_ID_Miscellaneous_hc":
            {"2018": [1],
             "2026": [0]},
        "_ID_Medical_frt":
            {"2017": [0.075],
             "2019": [0.1]},
        "_cpi_offset":
            {"2017": [-0.0025]}
    }
}"""

policy_dict = taxcalc.Calculator.read_json_param_objects(tcja_json, None)

kw = {
    'start_year': 2018,
    'use_full_sample': True,
    'user_mods': {
        u'policy': policy_dict['policy'],
        u'growdiff_response': {},
        u'behavior': {2018: {"_BE_sub": [0.25]}},
        u'consumption': {},
        u'growdiff_baseline': {}
    },
    'year_n': 0,
    'use_puf_not_cps': True,
    'return_dict': False
}

results_dfs = {}
for year in range(0, 10):
    kw["year_n"] = year
    results_dfs[year] = taxcalc.tbi.run_nth_year_tax_calc_model(**kw)

    print('aggr_d results for year: ', year)
    print(results_dfs[year]['aggr_d'])

GoFroggyRun · 2018-01-22T23:48:39Z

@hdoupe thanks for your advice. I was having troubles with defining pre-TCJA baseline, and realized that I don't have to worry about it at all if I were working with TC ver 0.14.2.

For TC release 0.14.2, which is the version that the result here is based on, the tbi interface yield exactly same results as TaxBrain. The difference table generated via tbi looks like the following:

	2018	2019	2020	2021	2022	2023	2024	2025	2026	2027
Individual Diff	-143.2	-73.9	2,069.9	1,795.9	1,669.5	782.3	-148.2	47.2	25.7	29.7
Payroll Diff	9.8	17.0	75.3	68.3	64.1	39.3	11.8	32.8	-0.7	-0.8
Combined Diff	-133.4	-56.9	2,145.1	1,864.2	1,733.7	821.6	-136.4	79.9	25.0	28.9

Given my previous comment, looks like the real issue here lies within tbi, instead of PolicyBrain. In particular, tbi's result doesn't agree with tax-calculator (at least for 0.14.2).

Raw results:

puf-read-time= 2.1
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
seed=4014022474
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
elapsed time for this run: 67.4
('aggr_d results for year: ', 0)
                          0_0
ind_tax      -143,190,327,631
payroll_tax     9,770,324,193
combined_tax -133,420,003,438
puf-read-time= 2.2
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
seed=4014022474
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
elapsed time for this run: 51.4
('aggr_d results for year: ', 1)
                         0_1
ind_tax      -73,879,740,558
payroll_tax   17,019,124,295
combined_tax -56,860,616,263
puf-read-time= 2.1
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
seed=4014022474
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
elapsed time for this run: 50.5
('aggr_d results for year: ', 2)
                           0_2
ind_tax      2,069,919,789,705
payroll_tax     75,225,190,671
combined_tax 2,145,144,980,376
puf-read-time= 1.9
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
seed=4014022474
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
elapsed time for this run: 51.6
('aggr_d results for year: ', 3)
                           0_3
ind_tax      1,795,928,293,107
payroll_tax     68,267,871,627
combined_tax 1,864,196,164,734
puf-read-time= 1.9
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
seed=4014022474
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
elapsed time for this run: 50.7
('aggr_d results for year: ', 4)
                           0_4
ind_tax      1,669,543,103,182
payroll_tax     64,109,567,267
combined_tax 1,733,652,670,449
puf-read-time= 1.9
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
seed=4014022474
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
elapsed time for this run: 49.9
('aggr_d results for year: ', 5)
                         0_5
ind_tax      782,285,868,153
payroll_tax   39,277,596,627
combined_tax 821,563,464,780
puf-read-time= 1.9
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
seed=4014022474
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
elapsed time for this run: 50.8
('aggr_d results for year: ', 6)
                          0_6
ind_tax      -148,244,067,068
payroll_tax    11,794,610,301
combined_tax -136,449,456,767
puf-read-time= 2.1
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
seed=4014022474
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
elapsed time for this run: 50.3
('aggr_d results for year: ', 7)
                        0_7
ind_tax      47,150,744,073
payroll_tax  32,792,569,397
combined_tax 79,943,313,470
puf-read-time= 1.8
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
seed=4014022474
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
elapsed time for this run: 53.2
('aggr_d results for year: ', 8)
                        0_8
ind_tax      25,663,017,542
payroll_tax    -668,074,598
combined_tax 24,994,942,943
puf-read-time= 2.2
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
You loaded data for 2009.
Tax-Calculator startup automatically extrapolated your data to 2013.
seed=4014022474
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Buffer dtype mismatch, expected 'Python object' but got 'long'

Exception ValueError: "Buffer dtype mismatch, expected 'Python object' but got 'long'" in 'pandas._libs.lib.is_bool_array' ignored
elapsed time for this run: 50.8
('aggr_d results for year: ', 9)
                        0_9
ind_tax      29,661,748,014
payroll_tax    -755,190,231
combined_tax 28,906,557,783

Code:

import pandas as pd
import numpy as np 
import sys
import taxcalc

tcja_tb='''
{
    "policy": {
        "_II_rt1":
            {"2018": [0.1],
             "2026": [0.1]},
        "_II_rt2":
            {"2018": [0.12],
             "2026": [0.15]},
        "_II_rt3":
            {"2018": [0.22],
             "2026": [0.25]},
        "_II_rt4":
            {"2018": [0.24],
             "2026": [0.28]},
        "_II_rt5":
            {"2018": [0.32],
             "2026": [0.33]},
        "_II_rt6":
            {"2018": [0.35],
             "2026": [0.35]},
        "_II_rt7":
            {"2018": [0.37],
             "2026": [0.396]},
        "_II_brk1":
            {"2018": [[9525, 19050, 9525, 13600, 19050]],
             "2026": [[11242, 22484, 11242, 16094, 22484]]},
        "_II_brk2":
            {"2018": [[38700, 77400, 38700, 51800, 77400]],
             "2026": [[45751, 91502, 45751, 61242, 91502]]},
        "_II_brk3":
            {"2018": [[82500, 165000, 82500, 82500, 165000]],
             "2026": [[110791, 184571,  92286, 158169, 184571]]},
        "_II_brk4":
            {"2018": [[157500, 315000, 157500, 157500, 315000]],
             "2026": [[231045, 281317, 140659, 256181, 281317]]},
        "_II_brk5":
            {"2018": [[200000, 400000, 200000, 200000, 400000]],
             "2026": [[502356, 502356, 251178, 502356, 502356]]},
        "_II_brk6":
            {"2018": [[500000, 600000, 300000, 500000, 500000]],
             "2026": [[504406 ,567457, 283728, 535931, 567457]]},
        "_PT_rt1":
            {"2018": [0.1],
             "2026": [0.1]},
        "_PT_rt2":
            {"2018": [0.12],
             "2026": [0.15]},
        "_PT_rt3":
            {"2018": [0.22],
             "2026": [0.25]},
        "_PT_rt4":
            {"2018": [0.24],
             "2026": [0.28]},
        "_PT_rt5":
            {"2018": [0.32],
             "2026": [0.33]},
        "_PT_rt6":
            {"2018": [0.35],
             "2026": [0.35]},
        "_PT_rt7":
            {"2018": [0.37],
             "2026": [0.396]},
        "_PT_brk1":
            {"2018": [[9525, 19050, 9525, 13600, 19050]],
             "2026": [[11242, 22484, 11242, 16094, 22484]]},
        "_PT_brk2":
            {"2018": [[38700, 77400, 38700, 51800, 77400]],
             "2026": [[45751, 91502, 45751, 61242, 91502]]},
        "_PT_brk3":
            {"2018": [[82500, 165000, 82500, 82500, 165000]],
             "2026": [[110791, 184571, 92286, 158169, 184571]]},
        "_PT_brk4":
            {"2018": [[157500, 315000, 157500, 157500, 315000]],
             "2026": [[231045, 281317, 140659, 256181, 281317]]},
        "_PT_brk5":
            {"2018": [[200000, 400000, 200000, 200000, 400000]],
             "2026": [[502356, 502356, 251178, 502356, 502356]]},
        "_PT_brk6":
            {"2018": [[500000, 600000, 300000, 500000, 500000]],
             "2026": [[504406, 567457, 283728, 535931, 567457]]},
        "_PT_exclusion_rt":
            {"2018": [0.2],
             "2026": [0.0]},
        "_PT_exclusion_wage_limit":
            {"2018": [0.5],
             "2026": [9e99]},
        "_STD":
            {"2018": [[12000, 24000, 12000, 18000, 24000]],
             "2026": [[7655, 15311, 7655, 11272, 15311]]},
        "_II_em":
            {"2018": [0],
             "2026": [4883]},
        "_CTC_ps":
            {"2018": [[200000, 400000, 200000, 200000, 400000]],
             "2026": [[75000, 110000, 55000, 75000, 75000]]},
        "_CTC_c":
            {"2018": [1400],
             "2022": [1500],
             "2025": [1600],
             "2026": [1000]},
        "_ALD_Alimony_hc":
            {"2019": [1],
             "2026": [0]},
        "_DependentCredit_Child_c":
            {"2018": [600],
             "2022": [500],
             "2025": [400],
             "2026": [0]},
        "_DependentCredit_Nonchild_c":
            {"2018": [500],
             "2026": [0]},
        "_DependentCredit_before_CTC":
            {"2018": [true]},  
        "_ACTC_Income_thd":
            {"2018": [2500],
             "2026": [3000]},
        "_AMT_em":
            {"2018": [[70300, 109400, 54700, 70300, 109400]],
             "2026": [[65462, 101870, 50935, 65461, 101870]]},
        "_AMT_em_ps":
            {"2018": [[500000, 1000000, 500000, 500000, 1000000]],
             "2026": [[145511, 193974, 96987, 145511, 193974]]},
        "_ALD_DomesticProduction_hc":
            {"2018": [1],
             "2026": [0]},
        "_ID_prt":
            {"2018": [0],
             "2026": [0.03]},
        "_ID_crt":
            {"2018": [1],
             "2026": [0.8]},
        "_ID_Charity_crt_all":
            {"2018": [0.6],
             "2026": [0.5]},
        "_ID_Casualty_hc":
            {"2018": [1],
             "2026": [0]},
        "_ID_AllTaxes_c":
            {"2018": [[10000, 10000, 5000, 10000, 10000]],
             "2026": [[9e99, 9e99, 9e99, 9e99, 9e99]]},
        "_ID_Miscellaneous_hc":
            {"2018": [1],
             "2026": [0]},
        "_ID_Medical_frt":
            {"2017": [0.075],
             "2019": [0.1]},
        "_cpi_offset":
            {"2017": [-0.0025]}  
    }
}
'''

policy_dict = taxcalc.Calculator.read_json_param_objects(tcja_tb, None)
kw = {
    'start_year': 2018,
    'use_full_sample': True,
    'user_mods': {
        u'policy': policy_dict['policy'],
        u'growdiff_response': {},
        u'behavior': {2018: {"_BE_sub": [0.25]}},
        u'consumption': {},
        u'growdiff_baseline': {}
    },
    'year_n': 0,
    'use_puf_not_cps': True,
    'return_dict': False
}

print('taxcalc vers:', taxcalc.__version__)
results_dfs = {}
for year in range(0, 10):
    kw["year_n"] = year
    results_dfs[year] = taxcalc.tbi.run_nth_year_tax_calc_model(**kw)
    print('aggr_d results for year: ', year)
    print(results_dfs[year]['aggr_d'])

martinholmer · 2018-01-23T00:14:24Z

@GoFroggyRun, Thanks for your Tax-Calculator bug report.

martinholmer · 2018-01-23T14:04:41Z

@GoFroggyRun said his code included this statement:

print('taxcalc vers:', taxcalc.__version__)

But I don't see the results of this print statement in the output you posted.
Were you using a taxcalc package? If so, what version?

GoFroggyRun · 2018-01-23T15:16:40Z

@martinholmer Right. I only included the output for the loop part.

I'm using a taxcalc package, and its version is 0.14.2, which is the version Policy Brain uses when the result here is found.

martinholmer · 2018-01-24T20:06:24Z

@GoFroggyRun referred in the discussion of pull request #1840 to this issue #1827 using the phrase:

the bug report in #1827

Perhaps it is a bug, I don't really know for certain. If you think there is a bug in Tax-Calculator, we have a standard procedure to deal with bugs. You should prepare a two-part pull request that does this:

Identify bug by creating a new test that fails because of the buggy logic
Correct bug by fixing the buggy logic so that the new test now passes and all old tests continue to pass

We look forward to your pull request.

martinholmer · 2018-02-13T21:41:07Z

The "odd" results reported in the first comment in issue #1827 has been resolve by the merge of pull request #1858.

MattHJensen closed this as completed Jan 22, 2018

MattHJensen reopened this Jan 22, 2018

martinholmer changed the title ~~Very odd TCJA results with small positive substitution elasticity~~ tbi TCJA behavioral response results differ from non-tbi results Jan 23, 2018

martinholmer self-assigned this Jan 23, 2018

martinholmer added the bug label Jan 23, 2018

martinholmer changed the title ~~tbi TCJA behavioral response results differ from non-tbi results~~ tbi behavioral response results for TCJA reform differ from non-tbi results Jan 23, 2018

martinholmer added question and removed bug labels Jan 23, 2018

martinholmer changed the title ~~tbi behavioral response results for TCJA reform differ from non-tbi results~~ Are tbi behavioral-response results for TCJA reform different from non-tbi results? Jan 23, 2018

martinholmer mentioned this issue Jan 23, 2018

Add test that compares tbi and std behavioral-response estimates #1840

Merged

martinholmer removed their assignment Jan 23, 2018

GoFroggyRun mentioned this issue Feb 5, 2018

Add logic to allow dropping units with high MTR while behavioral response calculation #1856

Closed

martinholmer mentioned this issue Feb 6, 2018

Add more Behavior.response trace output #1857

Merged

martinholmer mentioned this issue Feb 6, 2018

Add optional argument to Behavior.response method #1858

Merged

martinholmer closed this as completed Feb 13, 2018

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Are tbi behavioral-response results for TCJA reform different from non-tbi results? #1827

Are tbi behavioral-response results for TCJA reform different from non-tbi results? #1827

MattHJensen commented Jan 14, 2018 •

edited

Loading

martinholmer commented Jan 15, 2018

MattHJensen commented Jan 15, 2018 •

edited

Loading

GoFroggyRun commented Jan 22, 2018 •

edited

Loading

MattHJensen commented Jan 22, 2018

martinholmer commented Jan 22, 2018

GoFroggyRun commented Jan 22, 2018

hdoupe commented Jan 22, 2018

GoFroggyRun commented Jan 22, 2018

hdoupe commented Jan 22, 2018

GoFroggyRun commented Jan 22, 2018 •

edited

Loading

martinholmer commented Jan 23, 2018

martinholmer commented Jan 23, 2018

GoFroggyRun commented Jan 23, 2018

martinholmer commented Jan 24, 2018

martinholmer commented Feb 13, 2018

Are tbi behavioral-response results for TCJA reform different from non-tbi results? #1827

Are tbi behavioral-response results for TCJA reform different from non-tbi results? #1827

Comments

MattHJensen commented Jan 14, 2018 • edited Loading

martinholmer commented Jan 15, 2018

MattHJensen commented Jan 15, 2018 • edited Loading

GoFroggyRun commented Jan 22, 2018 • edited Loading

MattHJensen commented Jan 22, 2018

martinholmer commented Jan 22, 2018

GoFroggyRun commented Jan 22, 2018

hdoupe commented Jan 22, 2018

GoFroggyRun commented Jan 22, 2018

hdoupe commented Jan 22, 2018

GoFroggyRun commented Jan 22, 2018 • edited Loading

martinholmer commented Jan 23, 2018

martinholmer commented Jan 23, 2018

GoFroggyRun commented Jan 23, 2018

martinholmer commented Jan 24, 2018

martinholmer commented Feb 13, 2018

MattHJensen commented Jan 14, 2018 •

edited

Loading

MattHJensen commented Jan 15, 2018 •

edited

Loading

GoFroggyRun commented Jan 22, 2018 •

edited

Loading

GoFroggyRun commented Jan 22, 2018 •

edited

Loading