GTAP Resources: Resource Display
| GTAP Resource #6517 |
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"CGE model calibration using multi-objective evolutionary algorithms" by Nechifor, Victor, Mohammed Basheer and Emanuele Ferrari Abstract The research aims to expand the possibilities for country-level model calibration with the interest of speeding up and facilitating parameter choice when data to inform these values is not available while certain model responses are desirable. For this aim, we use a single-country CGE model set up in a dynamic recursive model and embed it in a multi-objective evolutionary algorithm (MOEA) framework. The framework is thus employed to search the space of possible parameter values, notably in the case of elasticities, to minimise the error between the model target- and actual responses. For illustrative purposes, the case study of aligning a country-level model to a global multi-regional model is considered. |
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- Baseline development - Calibration and parameter estimation |
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Public Access  Paper (359.3 KB) Replicated: 0 time(s) Presentation (1.8 MB) Replicated: 0 time(s)Restricted Access No documents have been attached. Special Instructions No instructions have been specified. |
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Last Modified: 9/15/2023 1:05:45 PM
