policyengine-us
US federal and state tax-benefit microsimulation model.
Decision gist · record as of 2026-08-14
Yes, if you need to model US household-level tax and benefit outcomes and are comfortable with AGPL v3 licensing. The package is actively maintained, has low install friction, and is the canonical source for US tax-benefit rules. However, note that direct microsimulation is deprecated in favor of the policyengine.py bundle for population-wide analysis. Verify that your Python version (3.11–3.14) and pandas 3+ are available before installing.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11–3.14 and pandas 3 or later.
- Direct microsimulation via Microsimulation() is deprecated; the description recommends using the policyengine.py bundle for population-wide modeling instead.
- Low install friction with a pure-Python wheel.
License · maintenance · safety
(agpl) — Licensed under AGPL v3, which requires that any modifications or derivative works be shared under the same license and that source code be made available to users. This is a strong copyleft obligation suitable for open research but may constrain commercial or proprietary use.
last release 2026-08-14 (0 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 167,425 downloads/mo, #10,470 on PyPI
Alternatives
Verify before relying
pip install policyengine-us
from policyengine_us import Microsimulation
sim = Microsimulation()
# Household-level tax and benefit calculations follow- Exact calibration quality and validation metrics for microsimulation estimates beyond the reference to calibration-diagnostics.vercel.app.
- Performance characteristics (runtime, memory) for typical household-scale and population-scale simulations.
- Whether the package's tax-benefit rules are current with the latest federal and state legislation as of the fact sheet date.
What it is and what it does
PolicyEngine US is a microsimulation engine that encodes the rules of the US federal and state tax and benefit system, allowing you to compute tax liabilities, benefit eligibility, and household-level financial outcomes under different policy scenarios. It is built on policyengine-core and integrates with pandas, microdf-python, spm-calculator, and tables to handle data processing and tabular storage.
The package is actively maintained and positioned as the authoritative source for US tax-benefit rules and household calculations. However, the description explicitly notes that direct microsimulation via the Microsimulation() class is deprecated; the maintainers recommend using the policyengine.py bundle for population-wide modeling, which pins certified and calibration-gated datasets. Microsimulation results are estimates and should be validated against the calibration diagnostics.
Use it for
- Compute household tax liability and benefit eligibility under current or proposed tax-benefit rules.
- Analyze distributional or budgetary impacts of policy changes on specific household types.
- Validate policy proposals by running microsimulation scenarios against calibrated US demographic and income data.
- Integrate US tax-benefit calculations into a larger policy analysis or research workflow.
- Inspect and audit the encoded rules of the federal and state tax-benefit system.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to model US household-level tax and benefit outcomes and are comfortable with AGPL v3 licensing.
The package is actively maintained, has low install friction, and is the canonical source for US tax-benefit rules. However, note that direct microsimulation is deprecated in favor of the policyengine.py bundle for population-wide analysis. Verify that your Python version (3.11–3.14) and pandas 3+ are available before installing.
Install
policyengine-us on PyPI
Before you install
Low install friction with a pure-Python wheel. Actively maintained with a release on 2026-08-14. Requires Python 3.11–3.14 and pandas 3 or later; verify your environment matches before installing.
Requires Python 3.11–3.14 and pandas 3 or later. Direct microsimulation via Microsimulation() is deprecated; the description recommends using the policyengine.py bundle for population-wide modeling instead.
License in practice
Licensed under AGPL v3, which requires that any modifications or derivative works be shared under the same license and that source code be made available to users. This is a strong copyleft obligation suitable for open research but may constrain commercial or proprietary use.
Quickstart
pip install policyengine-us
from policyengine_us import Microsimulation
sim = Microsimulation()
# Household-level tax and benefit calculations followVerify before relying
- Exact calibration quality and validation metrics for microsimulation estimates beyond the reference to calibration-diagnostics.vercel.app.
- Performance characteristics (runtime, memory) for typical household-scale and population-scale simulations.
- Whether the package's tax-benefit rules are current with the latest federal and state legislation as of the fact sheet date.
Package facts
| License | Not declared agpl |
| Python support | Supports the current Python release <3.15,>=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 6 packagesmicrodf-pythonpandaspolicyengine-corespm-calculatortablestqdm |
| Maintenance | Actively maintained 0 days since the last release |
| First released | |
| Downloads | 167,425 / month, #10,470 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableLicense :: OSI Approved :: GNU Affero General Public License v3Operating System :: POSIXProgramming Language :: PythonProgramming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: Information Analysis |
Evidence: policyengine_us-1.808.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “tax benefit microsimulation”
- policyengine-usPolicyEngine US models the US federal and state tax and benefit…
- policyengine-corePolicyEngine Core provides a microsimulation engine and policy reform…
- taxjarPython client library for the TaxJar Sales Tax API, providing methods…
Give your agent the search over MCP, or paste the wish link into any chat.
More Information Analysis packages
A drop-in replacement for Python's standard `re` module that adds advanced regex features like nested sets, fuzzy matching, lookaround in conditionals, and full Unicode case-folding while maintaining backward compatibility.
pyarrow provides Python bindings to Apache Arrow's C++ libraries for efficient columnar data processing, serialization, and interoperability with pandas, NumPy, and other Python ecosystem tools.
NetworkX provides data structures and algorithms for creating, analyzing, and manipulating graphs and networks, supporting everything from simple undirected graphs to complex directed and weighted networks.
Connects Python applications to Snowflake data warehouses using the DB API 2.0 specification, enabling SQL queries, data transfers, and warehouse operations.
ContourPy calculates contours of 2D quadrilateral grids using C++11 algorithms wrapped in Python, offering serial and multithreaded implementations without requiring Matplotlib as a dependency.
Snowpark Python provides APIs to query and process data directly in Snowflake without moving data to your local system, with support for both native Snowpark and pandas-compatible interfaces.
Install it if you use Snowflake and want to process data without moving it to your application layer.
See also policyengine-core · dataengine · bddl · openbb-federal-reserve · openbb-fred · spm-calculator · cpi · geonamescache · vat-utils · toolguard