In 2014, the Policy Simulation Library [1] added a model called Tax-Simulator [2], which is a Python reimplementation of TAXSIM [3][4]. It is available as open-source [5], and designed to let researchers both change existing policy variables and implement new tax reforms in Python.
> Each year Americans spend over two billion hours and $30 billion preparing individual tax returns, and these filing costs are regressive. To lower and redistribute the filing burden, some commentators have proposed having the IRS pre-populate tax returns for individuals. We evaluate this hypothetical policy using a large, nationally representative sample of returns filed for the tax year 2019. Our baseline results indicate that between 62 and 73 million returns (41 to 48 percent of all returns) could be accurately pre-populated using only current-year information returns and the prior-year return. Accuracy rates decline with income and are higher for taxpayers who have fewer dependents or are unmarried. We also examine 2019 non-filers, finding that pre- populated returns tentatively indicate $9.0 billion in refunds due to 12 million (22 percent) of them.