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. DOI https://doi.org/10.2457/srs.33.3_205
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. DOI https://doi.org/10.2457/srs.33.3_205
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. DOI https://doi.org/10.2457/srs.33.3_205
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.
Item Type: | Article |
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Subjects: | H Social Sciences > H Social Sciences (General) |
Divisions: | Faculty of Social Sciences > Institute for Social and Economic Research |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 16 Dec 2013 11:17 |
Last Modified: | 05 Dec 2024 11:46 |
URI: | http://repository.essex.ac.uk/id/eprint/7901 |
Available files
Filename: 33_205.pdf