policyengine 3.1.10

A package to conduct policy analysis using PolicyEngine tax-benefit models.

PolicyEngine.py

A Python package for tax-benefit microsimulation analysis. Run policy simulations, analyse distributional impacts, and visualise results across the UK and US.

Quick start

from policyengine.core import Simulation
from policyengine.tax_benefit_models.uk import PolicyEngineUKDataset, uk_latest
from policyengine.outputs.aggregate import Aggregate, AggregateType

# Load representative microdata
dataset = PolicyEngineUKDataset(
    name="FRS 2023-24",
    filepath="./data/frs_2023_24_year_2026.h5",
    year=2026,
)

# Run simulation
simulation = Simulation(
    dataset=dataset,
    tax_benefit_model_version=uk_latest,
)
simulation.run()

# Calculate total universal credit spending
agg = Aggregate(
    simulation=simulation,
    variable="universal_credit",
    aggregate_type=AggregateType.SUM,
    entity="benunit",
)
agg.run()
print(f"Total UC spending: £{agg.result / 1e9:.1f}bn")

Documentation

Core concepts:

• Core concepts: Architecture, datasets, simulations, outputs
• UK tax-benefit model: Entities, parameters, examples
• US tax-benefit model: Entities, parameters, examples

Examples:

• examples/income_distribution_us.py: Analyse benefit distribution by decile
• examples/employment_income_variation_uk.py: Model employment income phase-outs
• examples/policy_change_uk.py: Analyse policy reform impacts

Installation

pip install policyengine

Features

• Multi-country support: UK and US tax-benefit systems
• Representative microdata: Load FRS, CPS, or create custom scenarios
• Policy reforms: Parametric reforms with date-bound parameter values
• Distributional analysis: Aggregate statistics by income decile, demographics
• Entity mapping: Automatic mapping between person, household, tax unit levels
• Visualisation: PolicyEngine-branded charts with Plotly

Key concepts

Datasets

Datasets contain microdata at entity level (person, household, tax unit). Load representative data or create custom scenarios:

from policyengine.tax_benefit_models.uk import PolicyEngineUKDataset

dataset = PolicyEngineUKDataset(
    name="Representative data",
    filepath="./data/frs_2023_24_year_2026.h5",
    year=2026,
)
dataset.load()

Simulations

Simulations apply tax-benefit models to datasets:

from policyengine.core import Simulation
from policyengine.tax_benefit_models.uk import uk_latest

simulation = Simulation(
    dataset=dataset,
    tax_benefit_model_version=uk_latest,
)
simulation.run()

# Access calculated variables
output = simulation.output_dataset.data
print(output.household[["household_net_income", "household_benefits"]])

Outputs

Extract insights with aggregate statistics:

from policyengine.outputs.aggregate import Aggregate, AggregateType

# Mean income in top decile
agg = Aggregate(
    simulation=simulation,
    variable="household_net_income",
    aggregate_type=AggregateType.MEAN,
    filter_variable="household_net_income",
    quantile=10,
    quantile_eq=10,
)
agg.run()
print(f"Top decile mean income: £{agg.result:,.0f}")

Policy reforms

Apply parametric reforms:

from policyengine.core import Policy, Parameter, ParameterValue
import datetime

parameter = Parameter(
    name="gov.hmrc.income_tax.allowances.personal_allowance.amount",
    tax_benefit_model_version=uk_latest,
    data_type=float,
)

policy = Policy(
    name="Increase personal allowance",
    parameter_values=[
        ParameterValue(
            parameter=parameter,
            start_date=datetime.date(2026, 1, 1),
            end_date=datetime.date(2026, 12, 31),
            value=15000,
        )
    ],
)

# Run reform simulation
reform_sim = Simulation(
    dataset=dataset,
    tax_benefit_model_version=uk_latest,
    policy=policy,
)
reform_sim.run()

Country models

UK

Three entity levels:

• Person: Individual with income and demographics
• Benunit: Benefit unit (single person or couple with children)
• Household: Residence unit

Key benefits: Universal Credit, Child Benefit, Pension Credit Key taxes: Income tax, National Insurance

US

Six entity levels:

• Person: Individual
• Tax unit: Federal tax filing unit
• SPM unit: Supplemental Poverty Measure unit
• Family: Census family definition
• Marital unit: Married couple or single person
• Household: Residence unit

Key benefits: SNAP, TANF, EITC, CTC, SSI, Social Security Key taxes: Federal income tax, payroll tax

Contributing

See CONTRIBUTING.md for development setup and guidelines.

License

AGPL-3.0