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Which model answers your question?

Start with the question and country, then check the comparison. The suite covers both the UK and US; each model's country scope is stated explicitly. Compare method and run surface here, then use the Papers and Validation tabs for the supporting evidence.

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Five model classes, side by side.

The five models compared across question class, method, country, vintage, verification and run surface
OBR macroeconometric
obr-macro
Bank of England structural VAR
boe-svar
Federal Reserve model
frb-us
Overlapping generations
psl-og
PolicyEngine microsimulation
pe-microsim
Question classSelected near-term UK fiscal and macro scenariosWhat drove the UK economy at the latest model-data vintage; short-run forecasts and revision narrativesUS macro dynamics: monetary and fiscal shocks, quarter by quarterLong-run incentives: labour supply, saving, the capital stock over decadesWhat a specific family pays and receives; distributional effects
MethodStructural macroeconometric emulator — Gauss–Seidel over 372 equations per quarterBayesian structural VAR — posterior sampling with zero + sign restrictions naming the shocksLarge-scale macroeconometric model — 284 equations solved under VAR expectationsDynamic general equilibrium (OLG) — steady-state root-find and transition-path iterationStatic tax-benefit microsimulation — direct rule evaluation, no behavioural response
CountryUKUKUSUK (OG-UK)UK & US
Data vintageOBR Economic and Fiscal Outlook, March 2026ONS, BoE and FRED series — coefficients estimated through 2025Q1; conditioned through the 2026Q1 data edgeThe Fed's model.xml and LONGBASE database, April 2026ONS, OBR and BoE national accounts as calibration targets; OG-UK 0.3.2 (from GitHub)UK & US statute; enhanced FRS 2023–24 microdata for UK population runs
Evidence class (numbers →)Validated for selected scenarios; published anchor is not out-of-sample validationValidated replication for selected outputsValidated software replication; substantive comparisons are approximateResearch prototype; calibrated counterfactual with no ground truthDeterministic rule calculation; population estimates add survey uncertainty
Reform scoringYes — shocks to exogenous model variables; static-costing bridge from PolicyEngine reformsNo — the baseline/conditioning member: it reads the economy reforms are scored againstNo — shock experiments only (funds-rate or fiscal shocks under VAR expectations); score_reform refuses model="frbus", as no PolicyEngine reform bridge existsYes — a PolicyEngine policy translated into estimated tax functionsYes — a PolicyEngine parameter + a new value, applied directly to households
Cannot establishArbitrary reform incidence or borrowing through the current adapterThe causal effect of a specific statutory reformPolicyEngine reform effects, anticipated-policy paths, or MCE scenariosA short-run forecast or independently validated reform effectGDP, inflation, interest rates, or macro feedback
Run surfaceHosted (CLI, MCP, Python API)Hosted (CLI, MCP, Python API)Hosted (CLI, MCP, Python API) — raw shocks onlyLocal onlyHosted
Typical runtimeSeconds to minutes per scenarioMinutes per full estimation + identification runSeconds to minutes per simulation~17+ min per steady-state solve (two per score); hours for transition pathsSub-second per household; minutes for population runs
Comparison rule. These models use different horizons, baselines, mechanisms, and output definitions. Related results should be interpreted together, not added, averaged, or ranked. The CLI and JSON result schema retain units, time basis, provenance, and an explicit comparability label for this reason.

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