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MRICE-E model is a new integrated assessment model (IAM) applied on evaluating climate change and the loss of economic welfare. Its economic module for China adopts a dynamic, nonlinear and multi-sectional CGE model. In this paper, we are concerned with the effects of perturbations in input-output coefficients in the CGE model. In the analytical framework, some concepts such as the Lyapunov exponent and the condition number from dynamic system and numerical linear algebra are employed to measure the errors brought by perturbations of the I-O coefficients. We finally derive the upper bound estimation of errors growth through time. To reduce the effects of the possible perturbations, some suggestions about categorization of the industrial sectors are given in the end.
}, issn = {2617-8710}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/ijnam/439.html} }MRICE-E model is a new integrated assessment model (IAM) applied on evaluating climate change and the loss of economic welfare. Its economic module for China adopts a dynamic, nonlinear and multi-sectional CGE model. In this paper, we are concerned with the effects of perturbations in input-output coefficients in the CGE model. In the analytical framework, some concepts such as the Lyapunov exponent and the condition number from dynamic system and numerical linear algebra are employed to measure the errors brought by perturbations of the I-O coefficients. We finally derive the upper bound estimation of errors growth through time. To reduce the effects of the possible perturbations, some suggestions about categorization of the industrial sectors are given in the end.