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Calculates federal tax liabilities from individual data under a range of policy scenarios
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README.md

Tax-Cruncher

Tax-Cruncher calculates federal tax liabilities from individual data under different policy proposals.

Tax-Cruncher accepts inputs similar to NBER's TAXSIM Version 27, converts those inputs to a format usable by Tax-Calculator, an open-source microsimulation model of federal individual income and payroll tax law, and uses Tax-Calculator capabilities to analyze the user-specified inputs under various tax policy proposals.

Tax-Cruncher's web application is hosted on COMP. The code that powers the web application can be found in this repository in the compconfig directory.

How to use Tax-Cruncher

Tax-Cruncher can analyze individual data from one filer or multiple filers under different policy proposals. The procedures for the two uses are different. For examples on how to use Tax-Cruncher and the outputs you can expect to generate, explore the Jupyter Notebooks in the docs directory.

To analyze individual data from one filer:

  • First, define your inputs. You may either edit taxcrunch/adjustment_template.json directly in your local repository or create a separate JSON file that includes just the parameters you would like to adjust.

  • Second, pick the policy proposal you would like to analyze. Browse the Tax-Calculator reforms folder for a preset reform, or specify your own reform in a JSON file in accordance with the instructions in the Tax-Calculator repository. Fill out the reform_options field in your adjustment file with the appropriate preset reform name. Do not specify a preset reform if you specified a file path to a custom reform.

  • Third, initiate the Cruncher class. If you modified taxcrunch/adjustment_template.json directly and chose a preset policy reform file, you can initiate the class with c = Cruncher(). Otherwise, initiate the Cruncher class with: c = Cruncher(inputs='ADJUSTMENT_FILE_NAME', custom_reform='REFORM_FILE_NAME').

  • Fourth, analyze your reform. Try out the following methods:

#basic outputs
c.basic_table()
#marginal tax rates
c.mtr_table()
#detailed outputs with marginal tax rate analysis 
c.calc_table()
#detailed outputs with difference between reform and baseline
c.calc_diff_table()

To analyze individual data from multiple filers:

  • First, define your inputs in a csv file. Instructions on how to make this CSV file can be found here.

  • Second, initiate the Batch class. The Batch class can be found in the multi_cruncher module. Initiate the Batch class with b = Batch('INPUT_DATA_FILE')

  • Third, analyze your data. You can analyze your data under current law or under a policy reform using the create_table() method. If you do not pass an argument to the method, the default policy is current law. To analyze your data under a policy reform, pass a JSON reform file, a reform dictionary, or a preset reform from the Tax-Calculator reforms folder to the create_table() method.

#liabilities under current law
b.create_table()
#liabilities under reform 
b.create_table('REFORM_FILE_NAME')

How to install Tax-Cruncher

Install from source:

git clone https://github.com/PSLmodels/Tax-Cruncher
cd Tax-Cruncher
conda env create
conda activate taxcrunch-env
pip install -e .

How to cite Tax-Cruncher

Please cite the source of your analysis as "Tax-Cruncher release #.#.#, author's calculations." If you would like to link to Tax-Cruncher, please use https://github.com/PSLmodels/Tax-Cruncher.

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