Neural Networks for Regional Employment Forecasts: Are the Parameters Relevant?

Roberto Patuelli (), Aura Reggiani (), Peter Nijkamp and Norbert Schanne ()

Working Paper series from Rimini Centre for Economic Analysis

Abstract: In this paper, we present a review of various computational experiments concerning neural network (NN) models developed for regional employment forecasting. NNs are nowadays widely used in several fields because of their flexible specification structure. A series of NN experiments is presented in the paper, using two data sets on German NUTS-3 districts. Individual forecasts are computed by our models for each district, in order to answer the following question: How relevant are NN parameters in comparison to NN structure? Comprehensive testing of these parameters is limited in the literature. Building on different specifications of NN models – in terms of explanatory variables and NN structures – we propose a systematic choice of NN learning parameters and internal functions by means of a sensitivity analysis. Our results show that different combinations of NN parameters provide significantly varying statistical performance and forecasting power. Finally, we note that the sets of parameters chosen for a given model specification cannot be light-heartedly applied to different or more complex models.

Keywords: neural networks; sensitivity analysis; employment forecasts; local labour markets (search for similar items in EconPapers)
JEL-codes: C45 E27 R23 (search for similar items in EconPapers)
Date: 2009-01, Revised 2010-02
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Published in the Journal of Geographical Systems, 13(1):67–85, 2011

Downloads: (external link)
http://www.rcea.org/RePEc/pdf/wp07_09.pdf

Related works:
Journal Article: Neural networks for regional employment forecasts: are the parameters relevant? (2011)
Working Paper: Neural Networks for Cross-Sectional Employment Forecasts: A Comparison of Model Specifications for Germany (2009)
Working Paper: Neural networks for cross-sectional employment forecasts: a comparison of model specifications for germany (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:rim:rimwps:07_09

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