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A Rank-Order Test on the Statistical Performance of Neural Network Models for Regional Labour Market Forecasts

Patuelli, Roberto and Longhi, Simonetta and Reggiani, Aura and Nijkamp, Peter and Blien, Uwe (2007) 'A Rank-Order Test on the Statistical Performance of Neural Network Models for Regional Labour Market Forecasts.' Review of Regional Studies, 37 (1). pp. 64-145. ISSN 0048-749X

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Abstract

Using a panel of 439 German regions, we evaluate and compare the performance of various Neural Network (NN) models as forecasting tools for regional employment growth. Because of relevant differences in data availability between the former East and West Germany, the NN models are computed separately for the two parts of the country. The comparisons of the models and their ex post forecasts are carried out by means of a non-parametric test: viz. the Friedman statistic. The Friedman statistic tests the consistency of model results obtained in terms of their rank order. Since there is no normal distribution assumption, this methodology is an interesting substitute for a standard analysis of variance.

Item Type: Article
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Faculty of Social Sciences > Institute for Social and Economic Research
Depositing User: Jim Jamieson
Date Deposited: 19 Sep 2013 16:03
Last Modified: 19 Sep 2013 16:03
URI: http://repository.essex.ac.uk/id/eprint/7796

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