A Dynamic Baseline Calibration Procedure for CGE models

Abstract Baseline assumptions play a crucial role in conducting consistent quantitative policy assessments for dynamic Computable General Equilibrium (CGE) models. Two essential factors that influence the determination of baselines are data sources projections and applied calibration methods. We propose general, Bayesian approach can be employed to build baseline any recursive-dynamic CGE model. use metamodeling techniques transform problem into tractable optimization while simultaneously reducing computational costs. This transformation allows us derive exogenous model parameters needed match projections. demonstrate how apply using simple supply full code. Additionally, we our method multi-region, multi-sector show calibrated matter as implications derived from simulations differ significantly between them.