Neural networks in economic modelling: An empirical study

W.J.H. Verkooijen

    Research output: ThesisDoctoral Thesis

    392 Downloads (Pure)

    Abstract

    This dissertation addresses the statistical aspects of neural networks and their usability for solving problems in economics and finance. Neural networks are discussed in a framework of modelling which is generally accepted in econometrics. Within this framework a neural network is regarded as a statistical technique that implements a model-free regression strategy. Model-free regression seems particularly useful in situations where economic theory cannot provide sensible model specifications. Neural networks are applied in three case studies: modelling house prices; predicting the production of new mortgage loans; predicting the foreign exchange rates. From these case studies is concluded that neural networks are a valuable addition to the econometrician's toolbox, but that they are no panacea.
    Original languageEnglish
    QualificationDoctor of Philosophy
    Awarding Institution
    • Tilburg University
    Supervisors/Advisors
    • Daniels, Hennie, Promotor
    • Plasmans, J.E.J., Promotor
    Award date9 Feb 1996
    Place of PublicationTilburg
    Publisher
    Print ISBNs9056680102
    Publication statusPublished - 1996

    Fingerprint

    Empirical study
    Neural networks
    Economic modelling
    Modeling
    Finance
    Econometrics
    House prices
    Usability
    Mortgage loan
    Economics
    Model specification
    Economic theory
    Foreign exchange rates
    Problem solving

    Cite this

    Verkooijen, W. J. H. (1996). Neural networks in economic modelling: An empirical study. Tilburg: CentER, Center for Economic Research.
    Verkooijen, W.J.H.. / Neural networks in economic modelling : An empirical study. Tilburg : CentER, Center for Economic Research, 1996. 205 p.
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    author = "W.J.H. Verkooijen",
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    language = "English",
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    Verkooijen, WJH 1996, 'Neural networks in economic modelling: An empirical study', Doctor of Philosophy, Tilburg University, Tilburg.

    Neural networks in economic modelling : An empirical study. / Verkooijen, W.J.H.

    Tilburg : CentER, Center for Economic Research, 1996. 205 p.

    Research output: ThesisDoctoral Thesis

    TY - THES

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    T2 - An empirical study

    AU - Verkooijen, W.J.H.

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    AB - This dissertation addresses the statistical aspects of neural networks and their usability for solving problems in economics and finance. Neural networks are discussed in a framework of modelling which is generally accepted in econometrics. Within this framework a neural network is regarded as a statistical technique that implements a model-free regression strategy. Model-free regression seems particularly useful in situations where economic theory cannot provide sensible model specifications. Neural networks are applied in three case studies: modelling house prices; predicting the production of new mortgage loans; predicting the foreign exchange rates. From these case studies is concluded that neural networks are a valuable addition to the econometrician's toolbox, but that they are no panacea.

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    T3 - CentER Dissertation Series

    PB - CentER, Center for Economic Research

    CY - Tilburg

    ER -

    Verkooijen WJH. Neural networks in economic modelling: An empirical study. Tilburg: CentER, Center for Economic Research, 1996. 205 p. (CentER Dissertation Series).