Source code for ccc.get_taxcalc_rates

# imports
import numpy as np
from taxcalc import Policy, Records, Calculator

[docs] def get_calculator( baseline, calculator_start_year, baseline_policy=None, reform=None, data="cps", gfactors=None, weights=None, records_start_year=RECORDS_START_YEAR, ): """ This function creates the tax calculator object for the microsim Args: baseline (bool): `True` if baseline tax policy calculator_start_year (integer): first year of budget window baseline_policy (dictionary): IIT baseline parameters reform (dictionary): IIT reform parameters data (string or Pandas DataFrame): path to file or DataFrame for Tax-Calculator Records object (optional) weights (DataFrame): weights DataFrame for Tax-Calculator Records object (optional) records_start_year (integer): the start year for the data and weights dfs Returns: calc1 (Tax Calculator Calculator object): TC Calculator object with a current_year equal to calculator_start_year """ # create a calculator policy1 = Policy() if data is not None and "cps" in data: records1 = Records.cps_constructor() # impute short and long term capital gains if using CPS data # in 2012 SOI data 6.587% of CG as short-term gains records1.p22250 = 0.06587 * records1.e01100 records1.p23250 = (1 - 0.06587) * records1.e01100 # set total capital gains to zero records1.e01100 = np.zeros(records1.e01100.shape[0]) elif data is not None: # pragma: no cover records1 = Records( data=data, gfactors=gfactors, weights=weights, start_year=records_start_year, ) # pragma: no cover else: records1 = Records() # pragma: no cover if baseline: if ( baseline_policy ): # if something other than current law policy baseline update_policy(policy1, baseline_policy) if not baseline: if baseline_policy: # update baseline policy to layer reform on top update_policy(policy1, baseline_policy) update_policy(policy1, reform) # the default set up increments year to 2013 calc1 = Calculator(records=records1, policy=policy1) print("Calculator initial year = ", calc1.current_year) # this increment_year function extrapolates all PUF variables to # the next year so this step takes the calculator to the start_year if calculator_start_year > TC_LAST_YEAR: raise RuntimeError("Start year is beyond data extrapolation.") while calc1.current_year < calculator_start_year: calc1.increment_year() return calc1
[docs] def get_rates( baseline=False, start_year=DEFAULT_START_YEAR, baseline_policy=None, reform={}, data="cps", ): """ This function computes weighted average marginal tax rates using micro data from the tax calculator Args: baseline (bool): `True` if baseline tax policy, `False` if reform start_year (integer): first year of budget window reform (dict): reform parameters Returns: individual_rates (dict): individual income (IIT+payroll) marginal tax rates """ calc1 = get_calculator( baseline=baseline, calculator_start_year=start_year, baseline_policy=baseline_policy, reform=reform, data=data, ) # running all the functions and calculates taxes calc1.calc_all() # Loop over years in window of calculations end_year = start_year array_size = end_year - start_year + 1 rates_dict = { "tau_div": "e00650", "tau_int": "e00300", "tau_scg": "p22250", "tau_lcg": "p23250", } individual_rates = { "tau_pt": np.zeros(array_size), "tau_div": np.zeros(array_size), "tau_int": np.zeros(array_size), "tau_scg": np.zeros(array_size), "tau_lcg": np.zeros(array_size), "tau_td": np.zeros(array_size), "tau_h": np.zeros(array_size), } for year in range(start_year, end_year + 1): print("Calculator year = ", calc1.current_year) calc1.advance_to_year(year) print("year: ", str(calc1.current_year)) # Compute mtrs # Sch C [mtr_fica_schC, mtr_iit_schC, mtr_combined_schC] ="e00900p") # Sch E - includes partnership and s corp income [mtr_fica_schE, mtr_iit_schE, mtr_combined_schE] ="e02000") # Partnership and s corp income [mtr_fica_PT, mtr_iit_PT, mtr_combined_PT] ="e26270") # pension distributions # does PUF have e01500? Do we want IRA distributions here? # Weird - I see e01500 in PUF, but error when try to call it [mtr_fica_pension, mtr_iit_pension, mtr_combined_pension] = "e01700" ) # mortgage interest and property tax deductions # do we also want mtg ins premiums here? # mtg interest [mtr_fica_mtg, mtr_iit_mtg, mtr_combined_mtg] ="e19200") # prop tax [mtr_fica_prop, mtr_iit_prop, mtr_combined_prop] ="e18500") pos_ti = calc1.array("c04800") > 0 individual_rates["tau_pt"][year - start_year] = ( ( (mtr_iit_schC * np.abs(calc1.array("e00900p"))) + ( mtr_iit_schE * np.abs(calc1.array("e02000") - calc1.array("e26270")) ) + (mtr_iit_PT * np.abs(calc1.array("e26270"))) ) * pos_ti * calc1.array("s006") ).sum() / ( ( np.abs(calc1.array("e00900p")) + np.abs(calc1.array("e02000") - calc1.array("e26270")) + np.abs(calc1.array("e26270")) ) * pos_ti * calc1.array("s006") ).sum() individual_rates["tau_td"][year - start_year] = ( mtr_iit_pension * calc1.array("e01500") * pos_ti * calc1.array("s006") ).sum() / (calc1.array("e01500") * pos_ti * calc1.array("s006")).sum() individual_rates["tau_h"][year - start_year] = -1 * ( ( (mtr_iit_mtg * calc1.array("e19200")) + (mtr_iit_prop * calc1.array("e18500")) * pos_ti * calc1.array("s006") ).sum() / ( (calc1.array("e19200")) + (calc1.array("e18500")) * pos_ti * calc1.array("s006") ).sum() ) # Loop over MTRs that have only one income source for k, v in rates_dict.items(): [mtr_fica, mtr_iit, mtr_combined] = individual_rates[k][year - start_year] = ( mtr_iit * calc1.array(v) * pos_ti * calc1.array("s006") ).sum() / (calc1.array(v) * pos_ti * calc1.array("s006")).sum() print(individual_rates) return individual_rates
def update_policy(policy_obj, reform, **kwargs): """ Convenience method that updates the Policy object with the reform dict using the appropriate method, given the reform format. """ if is_paramtools_format(reform): policy_obj.adjust(reform, **kwargs) else: policy_obj.implement_reform(reform, **kwargs) def is_paramtools_format(reform): """ Check first item in reform to determine if it is using the ParamTools adjustment or the Tax-Calculator reform format. If first item is a dict, then it is likely be a Tax-Calculator reform: { param: {2020: 1000} } Otherwise, it is likely to be a ParamTools format. Returns: format (bool): True if reform is likely to be in PT format. """ for _, data in reform.items(): if isinstance(data, dict): return False # taxcalc reform else: # Not doing a specific check to see if the value is a list # since it could be a list or just a scalar value. return True