PolicySandbox is not a black box. What runs today is a calibrated semi-structural causal engine with distributed lags, solved in deviation-from-baseline space, with Monte Carlo over coefficient uncertainty and a household microsimulation on top. The wider toolkit below is listed with an honest status against each entry, because the fastest way to lose an economist is to claim a DSGE you do not have.
Dynamic stochastic general equilibrium: micro-founded households and firms optimising under rational expectations. Policy shocks propagate with full internal consistency.
MARTIN-class models: econometrically estimated equations with theory-imposed long-run structure. The workhorse of official Australian policy analysis.
Hundreds of estimated behavioural equations with rich sectoral detail for budget-grade costings and forecasts.
Computable general equilibrium: multi-sector, multi-region resource reallocation. The standard for tax, trade and energy-transition policy.
Intergenerational structure for superannuation, pensions, housing and demographic policy questions.
Identified vector autoregressions estimating how the economy historically responds to policy shocks.
Jorda-style impulse responses: the modern default for tracing a shock's path over time.
Long-run equilibrium relationships with short-run error-correction dynamics.
Dynamic factor models, MIDAS and bridge equations reading the real-time state of the economy from high-frequency data.
Tax-and-transfer engines run over unit-record household data: who wins, who loses, dollars per week.
Monetary policy with realistic wealth and income distributions: mortgage holders, renters and savers respond differently.
Bottom-up simulation of adaptive interacting agents with no equilibrium assumption; suited to housing dynamics and contagion.
APRA / FSAP-style adverse scenario propagation through balance sheets and default channels.
Baseline plus alternative paths with probability bands: uncertainty, communicated honestly.
Thousands of stochastic runs over shock distributions: outcome distributions, not point estimates.
Leontief tables tracing sectoral and employment flow-through of spending shocks.
Bilateral trade-flow structure for tariff and trade-policy scenarios.
Gradient boosting, neural components and causal ML disciplined by structural models.
Difference-in-differences, regression discontinuity, synthetic control and event studies: what a policy actually did, feeding back into calibration.
4 of 19 run in the engine today; 4 are what its coefficients are calibrated against; 11 are roadmap. What exists now is documented in full - 90 registered models over 132 variables and 342 relationships, each with an elasticity, a lag, a confidence class and its limitations written down.
Enterprise engagements include full model documentation: specification, sources, elasticities and validation. Bring your economists - the hard questions are the useful ones.