What Is USW-Tax-Analyzer?
USW-Tax-Analyzer is a microsimulation model for analysis of US wealth taxation policy.
It is based on wealth distribution data developed by Thomas Piketty, Emmanuel Saez, and Gabriel Zucman, which have been made publicly available in an Open Policy Analysis project by the Berkeley Initiative for Transparency in the Social Sciences (BITSS). That project incorporates analysis of Senator Elizabeth Warren's 2019 wealth tax proposal conducted by Emmanuel Saez and Gabriel Zucman.
USW-Tax-Analyzer is easy to use.
There is a command line interface (CLI) that provides complete access
to the capabilities of the model without doing any programming. Users
of the CLI simply prepare a JSON file that describes a tax policy
reform and then enter a command that produces the CSV-formatted output
file in a few seconds. The output files from two model runs can then
be imported into any data analysis tool to tabulate or graph the
differences in output. The CLI conducts static analysis of a tax
reform by default, but has an option for conducting analysis that
includes one or more partial-equilibrium responses to the reform using
user-specified, non-linear elasticities. The CLI also has an option
for analyzing the implications of the growth effects of a reform using
user-specified growth differences that can be developed from a
general-equilibrium model or specified as what-if assumptions. The
CLI is executed using the
uswta command at the terminal prompt.
USW-Tax-Analyzer also has an application programming interface (API)
that allows users to write Python applications that utilize any of the
model's classes and functions to produce customized tax analysis. The
API is accessed using an
statement in a Python application.
USW-Tax-Analyzer is easy to develop.
The USW-Tax-Analyzer is built using the PSG-Tax-Analyzer, which is a software framework for developing tax microsimulation models with minimal coding. Development involves simply specifying parameters in several JSON files and preparing tax-filing-unit input data in CSV-formatted files. The logic of tax calculation is written in code that is very simple and would be easy to write for anyone with experience in any programming language.
Why was USW-Tax-Analyzer created?
The model was built to test the ability to do rapid development with minimal coding of a tax microsimulation model using the PSG-Tax-Analyzer framework. That test was a success: the model was able to replicate the 2019 BITSS results after about a day's work. And the microsimulation approach to analyzing wealth tax reforms was found to provide an easy path to enhancements of the basic capabilities: assuming non-uniform avoidance rates that depend on the marginal tax rate structure of a reform, extrapolating 2019 data to future years with changes in the distribution of wealth, and specifying time-varying policy reforms (including inflation-indexed wealth tax brackets and the reversion of reform provisions in future years).
Ask questions, submit bug reports, or request model enhancements, using the Forum.
Code for the current release can be downloaded in several formats, but wait to download until after you have installed Python and begun installing the model as described in the links just below. A list of changes in each release can be viewed in the change log.
Information for USW-Tax-Analyzer Users
Everyone involved with the USW-Tax-Analyzer model should be familiar with the following information about how to install and use the model:
Information for USW-Tax-Analyzer Developers
Those who only use the model for tax analysis do not need to read the following information. Those who are developing the model should first read the information for users and then read the following information: