Parameter uncertainty in CGE modeling of the macroeconomic impact of carbon reduction in China

Formal methods are used to characterize the uncertainty in the computable general equilibrium (CGE) model outputs to assess the use of the CGE model of China (integrated energy-economyenvironment dynamic CGE, TEDCGE) for carbon tax policy issues. Monte Carlo experiment was used for the parameter uncertainty propagation and unconditional sensitivity analysis, using the variance of the conditional expectation (VCE) as the importance index to identify critical uncertainties. The results illustrate the statistical characteristics of TEDCGE outputs and sensitivities of the TEOCGE outputs to 50 uncertain elasticities. The results show that the carbon tax level for a predefined emission reduction goal is quite sensitive to both capital-energy substitution elasticity and inter-fuel substitution elasticity in the production function, while the key parameter for the GDP reduction rate was only the inter-fuel substitution elasticity. Among the various sectors, heavy industry and electricity are most vitally affected by a carbon tax.