About taxdata Repository

This repository prepares data used in the Tax-Calculator repository.

The data files produced here, all of which have CSV format, provide two different sets of data files for Tax-Calculator:

• A set based on a recent IRS-SOI Public Use File (PUF)

• A set based on recent Census Current Population Survey (CPS) data

Because the PUF data are restricted in their use, the IRS-SOI-supplied PUF file and the puf.csv data file produced here are not part of the taxdata repository or the Tax-Calculator repository.

Each of these two sets of data files contains several types of files:

0. a sample data file containing variables for each tax filing unit;

1. a factors file containing annual variable extrapolation factors;

2. a weights file containing annual weights for each filing unit;

3. a ratios file containing annual adjustment ratios for some variables (currently only the PUF data set includes a ratios file);

4. a benefits file containing extrapolated benefits for each filing unit (currently only the CPS data set includes a benefits file).

Note that the factors file is the same in both sets of data files because the variable extrapolation factors are independent of the sample data being used. But the weights, ratios, and benefits files do depend on the data file, so they are different in the two sets of data files.

Installation

Currently, the only way to install taxdata currently is to clone the git repo locally.

git clone https://github.com/PSLmodels/taxdata.git

Next navigate to the directory and install the taxdata-dev conda environment

cd taxdata
conda env create -f environment.yml

After installing the conda environment, install pre-commit so that all the pre-commit hooks are run using:

pre-commit install

To run the scripts that produce puf.csv and cps.csv.gz, activate the taxdata-dev conda environment and follow the workflow laid out below.

Julia must also be installed to solve for the PUF and CPS weights. You can download Julia from their website or by using homebrew.

Data-Preparation Documentation and Workflow

The best documentation of the data-preparation workflow is the taxdata Makefile. The Makefile shows the input files and the Python script that generates each made file. The files made in early stages of the workflow serve as input files in later stages, which means there is a cascading effect of changes in the scripts and/or input files. The Makefile automates this complex workflow in an economical way because it executes scripts to make new versions of made files only when necessary. Start exploring the Makefile by running the make help command. If you want more background on the make utility and makefiles, search for Internet links with the keywords makefile and automate.

Note that the stage2 linear program that generates the weights file for the PUF is very long-running, taking five or more hours depending on your computer's CPU speed. We are considering options for speeding up this stage2 work, but for the time being you can execute make puf-files and make cps-files in separate terminal windows to have the two stage2 linear programs run in parallel. (If you try this parallel execution approach, be sure to wait for the make puf-files job to begin stage2 work before executing the make cps-files command in the other terminal window. This is necessary because the CPS stage1 work depends on output from PUF stage1.) If you are generating the taxdata made files in an overnight run, then simply execute the make all command.

You can copy the made files to your local Tax-Calculator directory tree using the csvcopy.sh bash script. Use the dryrun option to see which files would be copied (because they are newer than the corresponding files in the Tax-Calculator directory tree) without actually doing the file copies. At the terminal command-prompt in the top-level taxdata directory, execute ./csvcopy.sh to get help.

Example

To create cps.csv.gz, run

conda activate taxdata-dev
make cps-files

Contributing to taxdata Repository

Before creating a GitHub pull request, on your development branch in the top-level directory of the taxdata repository, run make cstest to make sure your proposed code is consistent with the repository's coding style and then run make pytest to ensure that all the tests pass.

Disclaimer

taxdata is under continuous development. As such, results will change as the underlying data and logic improves.

Contributors

A full list of contributors on GitHub can be found here. John O'Hare of Quantria Strategies has also made significant contributions to the development of taxdata.