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

PATUELLI, Roberto and LONGHI, Simonetta and REGGIANI, Aura and NIJKAMP, Peter (2002) 'Multicriteria Analysis of Neural Network Forecasting Models: An Application to German Regional Labour Markets.' Studies in Regional Science, 33 (3). pp. 205-229. ISSN 0287-6256


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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.

Item Type: Article
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Faculty of Social Sciences > Institute for Social and Economic Research
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 16 Dec 2013 11:17
Last Modified: 06 Jan 2022 14:38

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