PolicyEngine UK
For microsimulation, use policyengine.py. Society-wide microsimulation — population aggregates and distributional or budgetary impacts — is moving to the managed
policyengine.pybundle, which pins certified, calibration-gated datasets. Direct microsimulation viapolicyengine-uk(Microsimulation()) is deprecated and being migrated topolicyengine.py. This package remains the home of the UK tax-benefit rules and household-level calculations. Microsimulation results are estimates.
PolicyEngine UK is PolicyEngine's microsimulation model of the UK tax-benefit system. It uses the PolicyEngine Core microsimulation framework, which is based on OpenFisca.
The elements are described in different folders. All the modelling happens within the policyengine_uk folder.
- The rates and other system parameters are in the
parametersfolder. - The formulas and inputs are in the
variablesfolder. - This country package comes also with reforms in the
reformsfolder.
The files that are outside from the policyengine_uk folder are used to set up the development environment. Installation instructions are located along with other documentation in the docs folder.
The model supports multiple different input datasets provided by the user, one of which is the Family Resources Survey,1 containing microdata on household incomes across the UK. PolicyEngine UK enhances this dataset by fusing it to other surveys and reweighting it to minimize a comprehensive loss metric that measures the difference from an array of administrative totals.
Fast setup instructions (Linux / macOS)
-
Run
pip install policyengine-uk -
Run
policyengine-ukand go through the prompt to setup microdata.
Contact
The primary maintainer for PolicyEngine UK is Nikhil Woodruff, co-founder and CTO of PolicyEngine (nikhil@policyengine.org).
Citation
You may cite the source of your analysis as "PolicyEngine UK release #.#.#, author's calculations."
-
Department for Work and Pensions, Office for National Statistics, NatCen Social Research. (2021). Family Resources Survey, 2019-2020. [data collection]. UK Data Service. SN: 8802, http://doi.org/10.5255/UKDA-SN-8802-1 ↩
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