Multicriteria Analysis of Neural Network Forecasting Models: An Application to German Regional Labour Markets
AbstractThis 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.
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Bibliographic InfoPaper provided by EconWPA in its series Experimental with number 0511001.
Length: 26 pages
Date of creation: 08 Nov 2005
Date of revision:
Note: Type of Document - pdf; pages: 26. Published in: Studies in Regional Science 33 (3): 205-230
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multicriteria analysis; neural networks; regional labour markets;
Find related papers by JEL classification:
- C9 - Mathematical and Quantitative Methods - - Design of Experiments
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-11-12 (All new papers)
- NEP-ECM-2005-11-12 (Econometrics)
- NEP-FOR-2005-11-12 (Forecasting)
- NEP-GEO-2005-11-12 (Economic Geography)
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- 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.
- Sala-i-Martin, Xavier, 1997.
"I Just Ran Two Million Regressions,"
American Economic Review,
American Economic Association, vol. 87(2), pages 178-83, May.
- 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.
- Edwin Hinloopen & Peter Nijkamp, 1990. "Qualitative multiple criteria choice analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 24(1), pages 37-56, February.
- Uwe Blien & Alexandros Tassinopoulos, 2001.
"Forecasting Regional Employment with the ENTROP Method,"
Taylor & Francis Journals, vol. 35(2), pages 113-124.
- Blien, Uwe & Tassinopoulos, Alexandros, 1999. "Forecasting Regional Employment with the ENTROP Method," ERSA conference papers ersa99pa344, European Regional Science Association.
- 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.
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