Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/234256 
Authors: 
Year of Publication: 
2021
Series/Report no.: 
Working Papers of Agricultural Policy No. WP2021-02
Publisher: 
Kiel University, Department of Agricultural Economics, Chair of Agricultural Policy, Kiel
Abstract: 
Computational simulation models are widely used in the field of agricultural economics for a variety of tasks, particularly for evidence-based policy analysis. Despite the substantial and continuing growth of computing power and speed, the growing complexity together with the implicit nature of the simulation models, on the one hand, still lead to high computational costs in applying the models along with great difficulties in the parameter specification where data availability and parametrization constraints for empirical calibration problems are notably challenging. On the other hand, they also limit the use of simulation models in many other aspects such as integration into other research frameworks like policy optimization coupled with uncertainty analysis. In this paper, we attempt to systematically and comprehensively introduce the metamodeling technique and investigate several metamodel types in terms of accuracy, computational time, variable importance, and potential practical applications.
Subjects: 
Computational simulation models
metamodeling
policy analysis
DoE
JEL: 
D58
C68
O13
Q11
I3
O21
G11
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Working Paper

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