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Application of Dynamic Models and an Support Vector Machine to Inflation Modelling

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  • Dušan Marček
  • Milan Marček

Abstract

In Support Vector Machines (SVM's), a non-linear model is estimated based on solving a Quadratic Programming (QP) problem. Based on work [1] we investigate the quantifying of econometric structural model parameters of inflation in Slovak economics. Dynamic and SYM's modelling approaches are used for automated specification of a functional form of the model. Based on dynamic modelling, we provide the fit of inflation models over the period 1993-2003 in the Slovak Republic, and use them as a tool to compare their forecasting abilities with those obtained using SYM's method. Some methodological contributions are made to dynamic and SYM's modelling approaches in economics and to their use in data mining systems. The study discusses, analytically and numerically demonstrates the quality and interpretability of the obtained results. The SYM's methodology is extended to predict the time series models.

Suggested Citation

  • Dušan Marček & Milan Marček, 2006. "Application of Dynamic Models and an Support Vector Machine to Inflation Modelling," Bulletin of the Czech Econometric Society, The Czech Econometric Society, vol. 13(23).
  • Handle: RePEc:czx:journl:v:13:y:2006:i:23:id:147
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    File URL: http://ces.utia.cas.cz/bulletin/index.php/bulletin/article/view/147
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    Keywords

    Support vector machines; data mining; learning machines; time senes analysis and forecasting; dynamic modelling;

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C29 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Other

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