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A new approach for estimation of long-run relationships in economic analysis using Engle-Granger and artificial intelligence methods

Author

Listed:
  • Arshia Amiri

    (Department of Agricultural Economics - Shiraz University - Shiraz University)

  • Ulf-G Gerdtham

    (Skane University Hospital [Lund])

  • Bruno Ventelou

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

Abstract

In time series analysis, most estimation of relationships and tests are typically based on linear estimators and most classical co-integration methods and causality tests are based on OLS regresses. However the linear functional specification is not necessarily the most appropriate form. This paper breaks the ordinary rules in econometrics and makes use of time series with artificial intelligence methods, testing for existence of nonlinear relationship. We illustrate the testing exercise using two examples based on OECD health data. In our illustration we confirm that improved nonlinear AEG and VEC, significantly, have a better ability to identify long run co-integration and causal relationships than ordinary linear ones. Ordinary methods and improved-nonlinear methods demonstrate similar results if the variables in a model are approximately linear.

Suggested Citation

  • Arshia Amiri & Ulf-G Gerdtham & Bruno Ventelou, 2012. "A new approach for estimation of long-run relationships in economic analysis using Engle-Granger and artificial intelligence methods," Working Papers halshs-00606048, HAL.
    • Handle: RePEc:hal:wpaper:halshs-00606048
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00606048v2
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    References listed on IDEAS

    as
    1. Selma J. Mushkin, 1962. "Health as an Investment," NBER Chapters, in: Investment in Human Beings, pages 129-157, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Amiri, Arshia & Zibaei, Mansour, 2012. "Granger causality between energy use and economic growth in France with using geostatistical models," MPRA Paper 36357, University Library of Munich, Germany.

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