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Efficient Sampling and Metamodeling for Computational Economic Models

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  • Murat YILDIZOGLU
  • Isabelle SALLE

Abstract

Extensive 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.

Suggested Citation

  • Murat YILDIZOGLU & Isabelle SALLE, 2012. "Efficient Sampling and Metamodeling for Computational Economic Models," Cahiers du GREThA (2007-2019) 2012-18, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
  • Handle: RePEc:grt:wpegrt:2012-18
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    File URL: http://cahiersdugretha.u-bordeaux.fr/2012/2012-18.pdf
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    References listed on IDEAS

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    1. Yıldızoğlu, Murat & Sénégas, Marc-Alexandre & Salle, Isabelle & Zumpe, Martin, 2014. "Learning The Optimal Buffer-Stock Consumption Rule Of Carroll," Macroeconomic Dynamics, Cambridge University Press, vol. 18(4), pages 727-752, June.
    2. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
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    6. Edward Herbst & Frank Schorfheide, 2014. "Sequential Monte Carlo Sampling For Dsge Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1073-1098, November.
    7. Oeffner, Marc, 2008. "Agent–Based Keynesian Macroeconomics - An Evolutionary Model Embedded in an Agent–Based Computer Simulation," MPRA Paper 18199, University Library of Munich, Germany, revised Oct 2009.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Computational Economics; Exploration of Agent-Based Models; Design of Experiments; Metamodeling;
    All these keywords.

    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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