000K utf8 1100 $c2018 1500 eng 2050 urn:nbn:de:gbv:8-publ-22648 3000 Jin, Ding 3010 Hedtrich, Johannes 3010 Henning, Christian 4000 Applying Meta-modeling for extended CGE-modeling:Sampling techniques and potential application [Jin, Ding] 4209 Apart from the computational time and expenses of the CGE model, the discussion of elasticity parameter estimation and various closure rules as well as the difficulty of combining the results with other analysis approaches always poses obstacles ahead of us, therefore we are motivated to apply the Bayesian model selection method and the meta-modeling technique in order to tackle these problems from a new perspective in the framework of the Senegal-CGE model and even compare the CGE models. The meta-modeling technique can be deemed as an intermediate step towards the application of Bayesian model selection method because the CGE models cannot be directly integrated into the method. The meta-modeling technique, whose three essential components are the simulation models, the meta-models and the design of experimetns, aims at generating valid and simplified approximation models of the simulation models and gives us the opportunity of combining the CGE models with the Bayesian model selection method. The purpose of this paper is to demonstrate the meta-modeling technique, test the performace of the meta-models generated by it and analyze whether various combinations of elasticity parameters affect the outputs of the CGE models which are quantified by the marginal effects. Our findings show that the produced meta-models possess a decent prediction capacity but we have not detected significant variability of the marginal effects within each unique sector. 4950 https://nbn-resolving.org/urn:nbn:de:gbv:8-publ-22648$xR$3Volltext$534 4961 https://macau.uni-kiel.de/receive/publ_mods_00002264 5051 630 5550 Bayesian model selection 5550 CGE modeling 5550 Closure Rules 5550 DOE 5550 Elasticities 5550 Meta-modeling 5550 Meta-models