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

机译:中国碳减排宏观经济影响的CGE建模中的参数不确定性

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摘要

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.
机译:形式化方法用于表征可计算一般均衡(CGE)模型输出中的不确定性,以评估中国的CGE模型(能源经济环境动态CGE,TEDCGE)在碳税政策问题上的使用。蒙特卡罗实验用于参数不确定性的传播和无条件敏感性分析,使用条件期望值(VCE)的方差作为识别关键不确定性的重要指标。结果说明了TEDCGE输出的统计特性以及TEOCGE输出对50种不确定弹性的敏感性。结果表明,既定的减排目标的碳税水平对生产函数中的资本能源替代弹性和燃料间替代弹性都非常敏感,而GDP降低率的关键参数只是燃料间替代弹性。在各个部门中,重工业和电力受到碳税的影响最大。

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