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Multicriteria Analysis of Neural Network Forecasting Models: An Application to German Regional Labour Markets

Author

Listed:
  • Roberto Patuelli

    (Vrije Universiteit)

  • Simonetta Longhi

    (University of Essex)

  • Aura Reggiani

    (University of Bologna)

  • Peter Nijkamp

    (Vrije Universiteit)

Abstract

This paper develops a flexible multi-dimensional assessment method for the comparison of different statistical-econometric techniques based on learning mechanisms, with a view to analysing and forecasting regional labour markets. The aim of this paper is twofold. A first major objective is to explore the use of a standard choice tool, namely Multicriteria Analysis (MCA), in order to cope with the intrinsic methodological uncertainty on the choice of a suitable statistical- econometric learning technique for regional labour market analysis. MCA is applied here to support choices on the performance of various models – based on classes of Neural Network (NN) techniques – that serve to generate employment forecasts in West Germany at a regional/district level. A second objective of the paper is to analyse the methodological potential of a blend of approaches (NN-MCA) in order to extend the analysis framework to other economic research domains, where formal models are not available, but where a variety of statistical data is present. The paper offers a basis for a more balanced judgement of the performance of rival statistical tests.

Suggested Citation

  • Roberto Patuelli & Simonetta Longhi & Aura Reggiani & Peter Nijkamp, 2005. "Multicriteria Analysis of Neural Network Forecasting Models: An Application to German Regional Labour Markets," Experimental 0511001, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpex:0511001
    Note: Type of Document - pdf; pages: 26. Published in: Studies in Regional Science 33 (3): 205-230
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/exp/papers/0511/0511001.pdf
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    References listed on IDEAS

    as
    1. Edwin Hinloopen & Peter Nijkamp, 1990. "Qualitative multiple criteria choice analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 24(1), pages 37-56, February.
    2. Uwe Blien & Alexandros Tassinopoulos, 2001. "Forecasting Regional Employment with the ENTROP Method," Regional Studies, Taylor & Francis Journals, vol. 35(2), pages 113-124.
    3. Longhi, Simonetta & Nijkamp, Peter & Reggiani, Aura & Blien, Uwe, 2002. "Forecasting regional labour markets in Germany: an evaluation of the performance of neural network analysis," ERSA conference papers ersa02p117, European Regional Science Association.
    4. Reggiani, Aura & Nijkamp, Peter & Sabella, Enrico, 2001. "New advances in spatial network modelling: Towards evolutionary algorithms," European Journal of Operational Research, Elsevier, vol. 128(2), pages 385-401, January.
    5. Manfred M. Fischer & Yee Leung, 1998. "A genetic-algorithms based evolutionary computational neural network for modelling spatial interaction data," ERSA conference papers ersa98p478, European Regional Science Association.
    6. Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-183, May.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    multicriteria analysis; neural networks; regional labour markets;
    All these keywords.

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments

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    This paper has been announced in the following NEP Reports:

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