This notebook contains an example for how to use the taxbrain python package
from taxbrain import TaxBrain, differences_plot, distribution_plot
reform_url = "https://raw.githubusercontent.com/PSLmodels/Tax-Calculator/master/taxcalc/reforms/Larson2019.json"
start_year = 2021
end_year = 2030
Static Reform#
After importing the TaxBrain class from the taxbrain package, we initiate an instance of the class by specifying the start and end year of the anlaysis, which microdata to use, and a policy reform. Additional arguments can be used to specify econoimc assumptions and individual behavioral elasticites.
Once the class has been initiated, the run() method will handle executing each model
tb_static = TaxBrain(start_year, end_year, use_cps=True, reform=reform_url)
tb_static.run()
Once the calculators have been run, you can produce a number of tables, including a weighted total of a given variable each year under both current law and the user reform.
print("Combined Tax Liability Over the Budget Window")
tb_static.weighted_totals("combined")
Combined Tax Liability Over the Budget Window
| 2021 | 2022 | 2023 | 2024 | 2025 | 2026 | 2027 | 2028 | 2029 | 2030 | |
|---|---|---|---|---|---|---|---|---|---|---|
| Base | 2.271315e+12 | 3.067829e+12 | 3.246660e+12 | 3.395741e+12 | 3.575933e+12 | 3.979720e+12 | 4.161644e+12 | 4.344157e+12 | 4.543405e+12 | 4.749710e+12 |
| Reform | 2.328361e+12 | 3.146043e+12 | 3.342355e+12 | 3.509862e+12 | 3.710031e+12 | 4.126731e+12 | 4.329945e+12 | 4.534786e+12 | 4.744460e+12 | 4.961584e+12 |
| Difference | 5.704648e+10 | 7.821354e+10 | 9.569515e+10 | 1.141207e+11 | 1.340978e+11 | 1.470101e+11 | 1.683017e+11 | 1.906294e+11 | 2.010547e+11 | 2.118738e+11 |
If you are interested in a detailed look on the reform’s effect, you can produce a differences table for a given year.
print("Differences Table")
tb_static.differences_table(start_year, "weighted_deciles", "combined")
Differences Table
| count | tax_cut | perc_cut | tax_inc | perc_inc | mean | tot_change | share_of_change | ubi | benefit_cost_total | benefit_value_total | pc_aftertaxinc | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0-10n | 0.102049 | 0.000000 | 0.000000 | 0.035165 | 34.458500 | 8.218450 | 0.000839 | 0.001470 | 0.0 | 0.0 | 0.0 | 0.006305 |
| 0-10z | 8.390627 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 |
| 0-10p | 12.214010 | 0.000000 | 0.000000 | 5.510201 | 45.113777 | 3.693061 | 0.045107 | 0.079071 | 0.0 | 0.0 | 0.0 | -0.030271 |
| 10-20 | 20.708304 | 0.000000 | 0.000000 | 15.031974 | 72.589110 | 17.199754 | 0.356178 | 0.624364 | 0.0 | 0.0 | 0.0 | -0.049706 |
| 20-30 | 20.706921 | 0.019010 | 0.091803 | 13.230015 | 63.891753 | 27.007745 | 0.559247 | 0.980336 | 0.0 | 0.0 | 0.0 | -0.047443 |
| 30-40 | 20.707534 | 0.259493 | 1.253135 | 11.850040 | 57.225744 | 29.340902 | 0.607578 | 1.065057 | 0.0 | 0.0 | 0.0 | -0.036806 |
| 40-50 | 20.706181 | 1.026022 | 4.955149 | 12.904516 | 62.322051 | 27.858098 | 0.576835 | 1.011166 | 0.0 | 0.0 | 0.0 | -0.014259 |
| 50-60 | 20.708634 | 2.988466 | 14.431013 | 12.852511 | 62.063539 | -36.682205 | -0.759638 | -1.331613 | 0.0 | 0.0 | 0.0 | 0.110990 |
| 60-70 | 20.707540 | 3.812725 | 18.412256 | 12.691828 | 61.290851 | -155.371271 | -3.217357 | -5.639887 | 0.0 | 0.0 | 0.0 | 0.261920 |
| 70-80 | 20.705701 | 4.045475 | 19.537975 | 13.337835 | 64.416242 | -199.030473 | -4.121066 | -7.224049 | 0.0 | 0.0 | 0.0 | 0.271875 |
| 80-90 | 20.709850 | 4.421863 | 21.351497 | 14.297523 | 69.037307 | -428.662224 | -8.877530 | -15.561926 | 0.0 | 0.0 | 0.0 | 0.417652 |
| 90-100 | 20.708024 | 1.431391 | 6.912254 | 17.352383 | 83.795459 | 3470.938895 | 71.876285 | 125.996010 | 0.0 | 0.0 | 0.0 | -1.292600 |
| ALL | 207.075375 | 18.004445 | 8.694633 | 129.093991 | 62.341546 | 275.486531 | 57.046477 | 100.000000 | 0.0 | 0.0 | 0.0 | -0.321131 |
| 90-95 | 10.354203 | 1.292340 | 12.481311 | 8.241434 | 79.595059 | -299.507547 | -3.101162 | -5.436202 | 0.0 | 0.0 | 0.0 | 0.257404 |
| 95-99 | 8.282277 | 0.139051 | 1.678898 | 7.283324 | 87.938673 | 318.526119 | 2.638122 | 4.624513 | 0.0 | 0.0 | 0.0 | -0.070457 |
| Top 1% | 2.071544 | 0.000000 | 0.000000 | 1.827625 | 88.225265 | 34920.482300 | 72.339325 | 126.807699 | 0.0 | 0.0 | 0.0 | -4.338197 |
TaxBrain comes with two (and counting) built in plots as well
differences_plot(tb_static, 'combined', figsize=(10, 8));
distribution_plot(tb_static, 2021, figsize=(10, 8));
You can run a partial-equlibrium dynamic simulation by initiating the TaxBrian instance exactly as you would for the static reform, but with your behavioral assumptions specified
tb_dynamic = TaxBrain(start_year, end_year, use_cps=True, reform=reform_url,
behavior={"sub": 0.25})
tb_dynamic.run()
Once that finishes running, we can produce the same weighted total table as we did with the static run.
print("Partial Equilibrium - Combined Tax Liability")
tb_dynamic.weighted_totals("combined")
Partial Equilibrium - Combined Tax Liability
| 2021 | 2022 | 2023 | 2024 | 2025 | 2026 | 2027 | 2028 | 2029 | 2030 | |
|---|---|---|---|---|---|---|---|---|---|---|
| Base | 2.271315e+12 | 3.067829e+12 | 3.246660e+12 | 3.395741e+12 | 3.575933e+12 | 3.979720e+12 | 4.161644e+12 | 4.344157e+12 | 4.543405e+12 | 4.749710e+12 |
| Reform | 2.309368e+12 | 3.119490e+12 | 3.312328e+12 | 3.476846e+12 | 3.673556e+12 | 4.082938e+12 | 4.282362e+12 | 4.483176e+12 | 4.690509e+12 | 4.904597e+12 |
| Difference | 3.805276e+10 | 5.166050e+10 | 6.566857e+10 | 8.110481e+10 | 9.762328e+10 | 1.032177e+11 | 1.207188e+11 | 1.390191e+11 | 1.471038e+11 | 1.548868e+11 |
Or we can produce a distribution table to see details on the effects of the reform.
print("Distribution Table")
tb_dynamic.distribution_table(start_year, "weighted_deciles", "expanded_income", "reform")
Distribution Table
| count | c00100 | count_StandardDed | standard | count_ItemDed | c04470 | c04600 | c04800 | taxbc | c62100 | ... | othertaxes | refund | iitax | payrolltax | combined | ubi | benefit_cost_total | benefit_value_total | expanded_income | aftertax_income | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0-10n | 0.102049 | -7.647952 | 0.102049 | 1.812331 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.000000 | -7.647952 | ... | 0.000000 | 0.354646 | -0.354646 | 0.064998 | -0.289648 | 0.0 | 0.799655 | 0.799655 | -6.940854 | -6.651206 |
| 0-10z | 8.391348 | -0.092134 | 8.391348 | 112.606869 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.000000 | -0.092134 | ... | 0.000000 | 17.779859 | -17.779859 | 0.000000 | -17.779859 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 17.779859 |
| 0-10p | 12.213289 | 28.286906 | 12.209152 | 166.998865 | 0.004137 | 0.020264 | 0.0 | 0.115147 | 0.004012 | 28.266967 | ... | 0.000000 | 28.404318 | -28.400306 | 3.495389 | -24.904918 | 0.0 | 19.592770 | 19.592770 | 50.389804 | 75.294721 |
| 10-20 | 20.707972 | 207.041116 | 20.173943 | 279.070002 | 0.534030 | 8.393380 | 0.0 | 26.229378 | 2.425275 | 199.422615 | ... | 0.000000 | 68.924806 | -66.500012 | 27.626000 | -38.874012 | 0.0 | 107.290602 | 107.290602 | 323.220266 | 362.094278 |
| 20-30 | 20.707838 | 316.392003 | 19.633355 | 286.707946 | 1.074483 | 19.058592 | 0.0 | 116.797081 | 11.644893 | 299.603803 | ... | 0.000000 | 67.788343 | -56.136439 | 43.579523 | -12.556916 | 0.0 | 258.441980 | 258.441980 | 590.820467 | 603.377382 |
| 30-40 | 20.707454 | 392.668937 | 19.509537 | 297.097008 | 1.197917 | 22.261841 | 0.0 | 185.726018 | 19.395839 | 373.666568 | ... | 0.000000 | 67.102597 | -47.693680 | 53.608167 | 5.914487 | 0.0 | 369.304538 | 369.304538 | 787.731338 | 781.816851 |
| 40-50 | 20.707364 | 550.410665 | 18.991769 | 306.176932 | 1.715595 | 34.181501 | 0.0 | 287.897992 | 30.615532 | 522.215435 | ... | 0.000000 | 78.289892 | -47.665191 | 72.867999 | 25.202808 | 0.0 | 404.586150 | 404.586150 | 994.564480 | 969.361672 |
| 50-60 | 20.707681 | 735.693914 | 18.281940 | 324.354035 | 2.425742 | 50.438493 | 0.0 | 426.774194 | 47.229773 | 695.612196 | ... | 0.000000 | 93.111897 | -45.875872 | 95.841593 | 49.965721 | 0.0 | 466.904520 | 466.904520 | 1258.106329 | 1208.140608 |
| 60-70 | 20.707211 | 959.452172 | 17.711308 | 354.258061 | 2.995903 | 64.792324 | 0.0 | 607.430407 | 72.421326 | 910.121076 | ... | 0.000000 | 112.382158 | -39.951339 | 122.148704 | 82.197364 | 0.0 | 578.443039 | 578.443039 | 1603.057532 | 1520.860167 |
| 70-80 | 20.706335 | 1365.627637 | 16.535255 | 367.973421 | 4.171081 | 102.216426 | 0.0 | 943.339939 | 119.245670 | 1290.183814 | ... | 0.000000 | 121.725681 | -2.458567 | 172.509446 | 170.050879 | 0.0 | 634.006174 | 634.006174 | 2085.251135 | 1915.200256 |
| 80-90 | 20.709137 | 2093.718554 | 14.366293 | 343.536073 | 6.342845 | 184.679463 | 0.0 | 1580.388004 | 218.923144 | 1959.318861 | ... | 0.004426 | 125.342365 | 93.607594 | 257.209862 | 350.817456 | 0.0 | 640.746399 | 640.746399 | 2872.462554 | 2521.645098 |
| 90-100 | 20.707694 | 6246.184432 | 9.266562 | 228.685942 | 11.441133 | 391.287689 | 0.0 | 5608.682792 | 1197.871725 | 5960.908106 | ... | 13.806216 | 47.684944 | 1165.754937 | 553.869339 | 1719.624276 | 0.0 | 512.857359 | 512.857359 | 6987.357401 | 5267.733125 |
| ALL | 207.075375 | 12887.736249 | 175.172511 | 3069.277483 | 31.902865 | 877.329973 | 0.0 | 9783.380950 | 1719.777187 | 12231.579354 | ... | 13.810642 | 828.891508 | 906.546618 | 1402.821021 | 2309.367639 | 0.0 | 3992.973188 | 3992.973188 | 17546.020451 | 15236.652812 |
| 90-95 | 10.353358 | 1667.261937 | 5.582845 | 137.918986 | 4.770512 | 150.459298 | 0.0 | 1374.944792 | 220.510290 | 1559.942410 | ... | 0.030695 | 34.012381 | 186.549573 | 189.181036 | 375.730610 | 0.0 | 284.750604 | 284.750604 | 2039.166713 | 1663.436103 |
| 95-99 | 8.283571 | 2341.019686 | 3.206924 | 79.394642 | 5.076647 | 172.735614 | 0.0 | 2075.405871 | 397.093634 | 2215.715352 | ... | 1.300536 | 13.627020 | 385.144055 | 212.266850 | 597.410905 | 0.0 | 192.019886 | 192.019886 | 2627.392016 | 2029.981111 |
| Top 1% | 2.070766 | 2237.902809 | 0.476792 | 11.372314 | 1.593974 | 68.092777 | 0.0 | 2158.332128 | 580.267801 | 2185.250344 | ... | 12.474984 | 0.045543 | 594.061308 | 152.421452 | 746.482761 | 0.0 | 36.086868 | 36.086868 | 2320.798672 | 1574.315911 |
16 rows × 24 columns
Dynamic Reform with Corporate Income Tax Incidence#
Now we simulate a dynamic revenue estimate while accounting for the incidence of a corporate income tax change.
# Corporate revenue estimate
corp_rev = [5_000_000_000] * (end_year - start_year + 1)
incidence_assumptions = {
"Incidence": { # long-run incidence of corporate tax
"Labor share": 0.5,
"Shareholder share": 0.4,
"All capital share": 0.1,
},
"Long run years": 10, # number of years to reach long-run incidence
}
tb_dynamic = TaxBrain(start_year, end_year, use_cps=True, reform=reform_url,
behavior={"sub": 0.25},
corp_revenue=corp_rev,
corp_incidence_assumptions=incidence_assumptions)
tb_dynamic.run()
print("Partial Equilibrium - Combined Tax Liability")
tb_dynamic.weighted_totals("combined")
Partial Equilibrium - Combined Tax Liability
| 2021 | 2022 | 2023 | 2024 | 2025 | 2026 | 2027 | 2028 | 2029 | 2030 | |
|---|---|---|---|---|---|---|---|---|---|---|
| Base | 2.271315e+12 | 3.067829e+12 | 3.246660e+12 | 3.395741e+12 | 3.575933e+12 | 3.979720e+12 | 4.161644e+12 | 4.344157e+12 | 4.543405e+12 | 4.749710e+12 |
| Reform | 2.311004e+12 | 3.121100e+12 | 3.313873e+12 | 3.478419e+12 | 3.675133e+12 | 4.084667e+12 | 4.284068e+12 | 4.484878e+12 | 4.692227e+12 | 4.906319e+12 |
| Difference | 3.968873e+10 | 5.327112e+10 | 6.721343e+10 | 8.267846e+10 | 9.920007e+10 | 1.049468e+11 | 1.224242e+11 | 1.407211e+11 | 1.488219e+11 | 1.566086e+11 |