Longhi, Simonetta and Nijkamp, Peter and Reggianni, Aura and Maierhofer, Erich (2005) 'Neural Network Modeling as a Tool for Forecasting Regional Employment Patterns.' International Regional Science Review, 28 (3). pp. 330-346. ISSN 0160-0176
Full text not available from this repository.Abstract
<jats:p> This article analyzes artificial neural networks (ANNs) as a method to compute employment forecasts at a regional level. The empirical application is based on employment data collected for 327West German regionsover a periodof fourteenyears. First, the authors compare ANNs to models commonly used in panel data analysis. Second, they verify, in the case of panel data, whether the common practice of combining forecasts of the computed models is able to produce more reliable forecasts. The technique currently employed by the German authorities to compute such regional employment forecasts is comparable to a simple naïve no-change model. For this reason, ANNs are also compared to this undemanding technique. </jats:p>
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: | Elements |
Depositing User: | Elements |
Date Deposited: | 05 Dec 2013 16:23 |
Last Modified: | 06 Jan 2022 14:38 |
URI: | http://repository.essex.ac.uk/id/eprint/7854 |
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