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The Optimal Prediction Simultaneous Equations Selection

Author

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  • Alexander Gorobets

    (Sevastopol National Technical University)

Abstract

This paper presents a method for selection of the optimal simultaneous equation system from a set of nested models under the condition of a small sample. The purpose of selection is to identify a model with the best prognostic possibilities. Multivariate AIC, BIC and AICC are used as the selection criteria. The selection properties of this method are investigated by Monte-Carlo simulations. They show that the structural form of system can outperform its reduced form for making predictions.

Suggested Citation

  • Alexander Gorobets, 2005. "The Optimal Prediction Simultaneous Equations Selection," Economics Bulletin, AccessEcon, vol. 3(36), pages 1-8.
    • Handle: RePEc:ebl:ecbull:eb-05c30009
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    References listed on IDEAS

    as
    1. Alexander Gorobets, 2005. "The error of prediction for a simultaneous equation model," Economics Bulletin, AccessEcon, vol. 3(17), pages 1-7.
    2. Brown, Bryan W, 1983. "The Identification Problem in Systems Nonlinear in the Variables," Econometrica, Econometric Society, vol. 51(1), pages 175-196, January.
    3. Bozdogan, Hamparsum & Haughton, Dominique M. A., 1998. "Informational complexity criteria for regression models," Computational Statistics & Data Analysis, Elsevier, vol. 28(1), pages 51-76, July.
    4. repec:ebl:ecbull:v:3:y:2005:i:17:p:1-7 is not listed on IDEAS
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    Cited by:

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    2. Manjón-Antolín, Miguel C., 2010. "Firm size and short-term dynamics in aggregate entry and exit," International Journal of Industrial Organization, Elsevier, vol. 28(5), pages 464-476, September.

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    More about this item

    Keywords

    criteria;

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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