Efficient Sampling and Metamodeling for Computational Economic Models
AbstractExtensive exploration of simulation models comes at a high computational cost, all the more when the model involves a lot of parameters. Economists usually rely on random explorations, such as Monte Carlo simulations, and basic econometric modelling to approximate the properties of computational models. This paper aims at providing guidelines for the use of a much more parsimonious method, based on an efficient sampling of the parameters space – a design of experiments (DOE), associated with a well-suited metamodel – kriging. We analyze two simple economic models using this approach to illustrate the possibilities offered by it. Our appendix gives a sample of the R-project code that can be used to apply this method on other models.
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Bibliographic InfoPaper provided by Groupe de Recherche en Economie Théorique et Appliquée in its series Cahiers du GREThA with number 2012-18.
Date of creation: 2012
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Computational Economics; Exploration of Agent-Based Models; Design of Experiments; Metamodeling;
Find related papers by JEL classification:
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
- C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
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- Murat YILDIZOGLU (GREQAM, CNRS, UMR 6579) & Marc-Alexandre SENEGAS (GREThA, CNRS, UMR 5113) & Isabelle SALLE (GREThA, CNRS, UMR 5113) & Martin ZUMPE (GREThA, CNRS, UMR 5113), 2011.
"Learning the optimal buffer-stock consumption rule of Carroll,"
Cahiers du GREThA
2011-11, Groupe de Recherche en Economie Théorique et Appliquée.
- Murat Yildizoglu & Marc-Alexandre Sénégas & Isabelle Salle & Martin Zumpe, 2011. "Learning the optimal buffer-stock consumption rule of Carroll," Working Papers halshs-00573689, HAL.
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