[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpex/0511001.html
   My bibliography  Save this paper

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
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/exp/papers/0511/0511001.pdf
    Download Restriction: no
    ---><---

    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. Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-183, May.
    3. Uwe Blien & Alexandros Tassinopoulos, 2001. "Forecasting Regional Employment with the ENTROP Method," Regional Studies, Taylor & Francis Journals, vol. 35(2), pages 113-124.
    4. 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.
    5. 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.
    6. 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.
    7. Aura Reggiani (ed.), 2000. "Spatial Economic Science," Advances in Spatial Science, Springer, number 978-3-642-59787-9.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Roberto Patuelli & Peter Nijkamp & Simonetta Longhi & Aura Reggiani, 2008. "Neural Networks and Genetic Algorithms as Forecasting Tools: A Case Study on German Regions," Environment and Planning B, , vol. 35(4), pages 701-722, August.
    2. Roberto Patuelli & Peter Nijkamp & Simonetta Longhi & Aura Reggiani, 2008. "Neural Networks and Genetic Algorithms as Forecasting Tools: A Case Study on German Regions," Environment and Planning B, , vol. 35(4), pages 701-722, August.
    3. Nijkamp, Peter & Reggiani, Aura & Tsang, Wai Fai, 2004. "Comparative modelling of interregional transport flows: Applications to multimodal European freight transport," European Journal of Operational Research, Elsevier, vol. 155(3), pages 584-602, June.
    4. Patuelli, Roberto & Reggiani, Aura & Nijkamp, Peter & Bade, Franz-Josef, 2010. "The evolution of the commuting network in Germany: Spatial and connectivity patterns," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 2(3), pages 5-37.
    5. Fischer, Manfred M. & Reismann, Martin, 2002. "A Methodology for Neural Spatial Interaction Modeling," MPRA Paper 77794, University Library of Munich, Germany.
    6. 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.
    7. Fischer, Manfred M., 2006. "Neural Networks. A General Framework for Non-Linear Function Approximation," MPRA Paper 77776, University Library of Munich, Germany.
    8. Simonetta Longhi & Peter Nijkamp & Aura Reggianni & Erich Maierhofer, 2005. "Neural Network Modeling as a Tool for Forecasting Regional Employment Patterns," International Regional Science Review, , vol. 28(3), pages 330-346, July.
    9. Manfred M. Fischer, 2009. "Principles of Neural Spatial Interaction Modeling," Advances in Spatial Science, in: Michael Sonis & Geoffrey J. D. Hewings (ed.), Tool Kits in Regional Science, chapter 8, pages 199-214, Springer.
    10. Rao, B. Bhaskara, 2010. "Estimates of the steady state growth rates for selected Asian countries with an extended Solow model," Economic Modelling, Elsevier, vol. 27(1), pages 46-53, January.
    11. Cho, Seo-young & Vadlamannati, Krishna Chaitanya, 2010. "Compliance for big brothers: An empirical analysis on the impact of the anti-trafficking protocol," University of Göttingen Working Papers in Economics 118, University of Goettingen, Department of Economics.
    12. Jeffrey Frankel, 2014. "Mauritius: African Success Story," NBER Chapters, in: African Successes, Volume IV: Sustainable Growth, pages 295-342, National Bureau of Economic Research, Inc.
    13. Roger M. Cooke & Harry Joe & Bo Chang, 2020. "Vine copula regression for observational studies," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(2), pages 141-167, June.
    14. Balima, Hippolyte Weneyam, 2020. "Coups d’état and the cost of debt," Journal of Comparative Economics, Elsevier, vol. 48(3), pages 509-528.
    15. Saaed, A.A.J., 2007. "Inflation and Economic Growth in Kuwait: 1985-2005. Evidence from Co-Integration and Error Correction Model," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 7(1).
    16. Chong, Alberto E., 2006. "Does It Matter How People Speak?," IDB Publications (Working Papers) 1946, Inter-American Development Bank.
    17. Arturo Galindo & Alberto Chong & César Calderón, 2001. "Structure and Development of Financial Institutions and Links with Trust: Cross-Country Evidence," Research Department Publications 4251, Inter-American Development Bank, Research Department.
    18. Vojtěch Roženský, 2012. "Mandatorní výdaje a flexibilita fiskální politiky v ČR [Mandatory Expenditure and the Flexibility of Fiscal Policy in the Czech Republic]," Politická ekonomie, Prague University of Economics and Business, vol. 2012(1), pages 40-57.
    19. Mothuti Gosego & Phiri Andrew, 2018. "Inflation-Growth Nexus in Botswana: Can Lower Inflation Really Spur Growth in the Country?," Global Economy Journal, De Gruyter, vol. 18(4), pages 1-11, December.
    20. B. Bhaskara Rao & Arusha Cooray, 2012. "How useful is growth literature for policies in the developing countries?," Applied Economics, Taylor & Francis Journals, vol. 44(6), pages 671-681, February.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wpa:wuwpex:0511001. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: EconWPA (email available below). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.