UK fiscal reform, quarter by quarter.

The quickest route is the hosted MCP server — no install, no credentials. obr_shock shocks one variable in model units and reads the per-quarter GDP deviation; list_reform_variables lists the shockable levers with units; score_reform with model="obr" scores a PolicyEngine reform end to end through the static-costing bridge.

The pe-macro CLI mirrors the hosted tools one for one: shock a variable, list the levers, or score a reform from the terminal.

pe-macro obr-shock --var CGG --shock 1250
pe-macro variables
pe-macro score --reform '{...}' --model obr

Locally, the package installs straight from GitHub — the equation listing, the March 2026 EFO forecast tables, and the ONS snapshot ship inside it, so there is no data step. A reform is one call: pick an exogenous variable, apply a shock, read the deviation from baseline.

Two solves, so about a minute. python -m obr_macro.reform_analysis runs the five bundled scenarios — a £5bn spending rise, a 5pp corporation-tax cut and rise, £10bn public real investment (~£3bn nominal CGIPS per quarter), and a £10bn austerity cut — with charts landing in outputs/.

pip install git+https://github.com/PolicyEngine/obr-macroeconomic-model

from obr_macro import run_reform

# £5bn/yr government spending shock (£1.25bn per quarter)
results = run_reform(
    name="Fiscal Stimulus",
    var="CGG",        # government consumption (exogenous)
    shock=1250,        # £1.25bn per quarter, in £m
    periods=12,
)
print(results[["period", "delta_gdp_bn", "pct_gdp"]])
# ΔGDP ≈ £1.25bn in the impact quarter, near-flat thereafter —
# under the demand closure the impact multiplier is ~1 by construction

Reforms enter through the 253 exogenous inputs; results come out of the 383 the model solves — the test is simply whether a variable has its own equation. The most useful levers and readouts are in the table alongside.

The full glossary — all 636 codes with descriptions, ONS series and equations — is the model package's variable and equation references.