model 04 — Federal Reserve macroeconomic model · frb-us · US · hosted

Test US monetary and fiscal shocks.

Trace how a funds-rate or fiscal shock affects US output, inflation, and unemployment quarter by quarter using the April 2026 baseline.

with the microsimulation

Its labour-market path tells the microsimulation who bears a shock.

→Connection. Shock-to-incidence bridge: frbus_shock_incidence scales the US microsimulation's employment income with the wage and hours deviations a shock produces. Uniform scaling — an experimental illustration, and labelled as such. score_reform refuses model="frbus": no mapping from statute exists.

→Worked example. The 100bp tightening below moves the 2027 wage bill −0.65%; the microsimulation then shows how much the federal and state tax system absorbs and what SNAP and the EITC give back, decile by decile.

→Validation. Shocked paths match the Fed's own pyfrbus at its version-to-version noise floor, CI-gated, plus a weekly baseline-vs-outturn backtest. The baseline tracking residual is an add-factor identity, not evidence.

→Results. Run frbus_shock from any connected client, or pe-macro frbus-shock locally.

01 — what it is

The US counterpart to the OBR emulator.

The Federal Reserve Board has used this large-scale macroeconometric model for policy analysis and forecasting since 1996, and publishes it whole in the public domain — the equation system as model.xml, the LONGBASE historical and projection database, the documentation, and a reference Python solver, pyfrbus — but no modern, readable, dependency-light implementation.

This is that: a from-scratch build on numpy, scipy and sympy under Python 3.10+, parsing the Board's own model file rather than re-specifying it — 284 endogenous variables and their equations, split into behavioural and identity blocks exactly as the Board's file declares them, solved as one simultaneous system per quarter.

In the suite it is the US counterpart of the OBR emulator: it reproduces the estimated equation system an official institution actually relies on, rather than deriving behaviour from first principles like the overlapping-generations model. One divergence shapes everything below: the OBR emulator has a bridge from statute; this one does not.

02 — what it can answer

US monetary and fiscal shocks, quarter by quarter.

The model's designed job is the US economy's dynamic response to a policy impulse. A 100bp funds-rate tightening in 2026Q1 moves the policy rate +1.000pp on impact, pushes real GDP to a trough of −0.55% in 2027Q4, raises unemployment by a peak +0.26pp, and takes core inflation down 0.034pp at its trough — signs, magnitudes and timing consistent with the Board's own documented simulation properties.

Fiscal impulses land in the published cross-model ranges.

A government-purchases shock worth 1% of GDP gives a year-one multiplier of 0.72 under the inertial Taylor rule, inside the 0.7–1.0 no-accommodation range in Coenen et al. (2012); with the funds rate fixed, the year-two multiplier is 0.90.

A personal tax cut worth 1% of GDP ex ante gives 0.22 rising to 0.32 over years one and two, inside both the 0.2–0.4 cross-model range and CBO's central estimate of about 0.3.

It cannot score a PolicyEngine reform — see the known limits. It cannot do forward guidance or anything needing model-consistent expectations. It cannot score a reform: score_reform refuses model="frbus" rather than return a plausible-but-wrong number, because no mapping exists from a PolicyEngine reform to FRB/US levers. And it says nothing about the UK.

What it can hand the microsimulation is its labour-market path. The frbus_shock_incidence tool takes the wage and hours deviations a shock produces — the 100bp tightening above moves the 2027 wage bill −0.65% — and scales the US microsimulation's employment income with them, so the automatic stabilizers answer who bears it: how much of the earnings loss the federal and state tax system absorbs, and what SNAP and the EITC give back, decile by decile. Uniform scaling, an experimental illustration — real incidence concentrates in job losers, and the caveats say so.