def cli_core(startyear, endyear, data, usecps, reform, behavior, assump,
baseline, outdir, name, make_report, author):
"""
Core logic for the CLI
"""
tb = TaxBrain(start_year=startyear,
end_year=endyear,
microdata=data,
use_cps=usecps,
reform=reform,
behavior=behavior,
assump=assump,
base_policy=baseline,
verbose=True)
tb.run()
# create outputs
dirname = name
if not dirname:
dirname = f"TaxBrain Analysis {datetime.today().date()}"
outputpath = Path(outdir, dirname)
outputpath.mkdir()
# create output tables
aggregate = tb.weighted_totals("combined")
aggregate.to_csv(Path(outputpath, "aggregate_tax_liability.csv"))
for year in range(startyear, endyear + 1):
yeardir = Path(outputpath, str(year))
yeardir.mkdir()
make_tables(tb, year, yeardir)
if make_report:
report(tb, name=name, outdir=outputpath, author=author)
def cli_core(startyear, endyear, data, usecps, reform, behavior, assump,
baseline, outdir, name, make_report, author):
"""
Core logic for the CLI
Parameters
----------
startyear: int
year to start analysis
endyear: int
last year for analysis
data: str or Pandas DataFrame
path to or DataFrame with data for Tax-Calculator
usecps: bool
whether to use the CPS or (if False) the PUF-based file
reform: dict
parameter changes for reform run in Tax-Calculator
behavior: dict
behavioral assumptions for Behavioral-Responses
assump: dict
consumption assumptions
base_policy: dict
parameter changes (relative to current law baseline) for baseline
policy
verbose: bool
indicator for printing of output
Returns
-------
None
reports saved to disk at path specified by outdir
"""
tb = TaxBrain(start_year=startyear,
end_year=endyear,
microdata=data,
use_cps=usecps,
reform=reform,
behavior=behavior,
assump=assump,
base_policy=baseline,
verbose=True)
tb.run()
# create outputs
dirname = name
if not dirname:
dirname = f"TaxBrain Analysis {datetime.today().date()}"
outputpath = Path(outdir, dirname)
outputpath.mkdir(exist_ok=True)
# create output tables
aggregate = tb.weighted_totals("combined")
aggregate.to_csv(Path(outputpath, "aggregate_tax_liability.csv"))
for year in range(startyear, endyear + 1):
yeardir = Path(outputpath, str(year))
yeardir.mkdir(exist_ok=True)
make_tables(tb, year, yeardir)
if make_report:
report(tb, name=name, outdir=outputpath, author=author)
from taxbrain import TaxBrain
reform_url = "https://raw.githubusercontent.com/PSLmodels/Tax-Calculator/master/taxcalc/reforms/Larson2019.json"
# run static analysis
tb_static = TaxBrain(2019, 2028, use_cps=True, reform=reform_url)
tb_static.run()
static_table = tb_static.weighted_totals("c00100")
print("Tax Liability by Year\n")
print("Static Results")
print(static_table)
# run dynamic analysis
tb_dynamic = TaxBrain(2019,
2028,
use_cps=True,
reform=reform_url,
behavior={"sub": 0.25})
tb_dynamic.run()
dynamic_table = tb_dynamic.weighted_totals("c00100")
print("Dynamic Results")
print(dynamic_table)
# produce a differences table
diff = tb_static.differences_table(2019, "weighted_deciles", "combined")
print("\nDifferences Table for 2019")
print(diff)