This document tells you how to begin contributing to Behavioral-Responses by reporting a bug, improving the documentation, or making an enhancement to the Python source code. If you only want to use Behavioral-Responses, you should begin by reading the user documentation that describes how to write Python scripts that use Behavioral-Responses on your own computer.
Behavioral-Responses, which is part of the Policy Simulation Library (PSL) collection of USA tax models, estimates partial-equilibrium behavioral responses to changes in the US federal individual income and payroll tax system as simulated by Tax-Calculator
Results will change as the underlying models improve. A fundamental reason for adopting open source methods in this project is so that people from all backgrounds can contribute to the models that our society uses to assess economic policy; when community-contributed improvements are incorporated, the model will produce different results.
If you want to report a bug, create a new issue here providing details on what you think is wrong with Behavioral-Responses.
If you want to request an enhancement, create a new issue here providing details on what you think should be added to Behavioral-Responses.
If you want to propose code changes, follow the directions in the Tax-Calculator Contributor Guide on how to fork and clone the Behavioral-Responses git repository. Before developing any code changes be sure to read completely the Tax-Calculator Contributor Guide and then read about the Tax-Calculator pull-request workflow. When reading both documents, be sure to mentally substitute Behavioral-Response for Tax-Calculator and behresp for taxcalc.
The Behavioral-Responses release history provides a high-level summary of past pull requests and access to a complete list of merged, closed, and pending pull requests.
Please cite the source of your analysis as "Behavioral-Responses release #.#.#, author's calculations." If you wish to link to Behavioral-Responses, https://PSLmodels.github.io/Behavioral-Responses/ is preferred. Additionally, we strongly recommend that you describe the elasticity assumptions used, and provide a link to the materials required to replicate your analysis or, at least, note that those materials are available upon request.