Neural networks for regional employment forecasts: are the parameters relevant?

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

Journal of Geographical Systems, 2011, vol. 13, issue 1, pages 67-85

Keywords: Neural networks; Sensitivity analysis; Employment forecasts; Local labour markets; C45; E27; R23 (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10.1007/s10109-010-0133-5 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Neural Networks for Regional Employment Forecasts: Are the Parameters Relevant? (2010)
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)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:kap:jgeosy:v:13:y:2011:i:1:p:67-85

Access Statistics for this article

Journal of Geographical Systems is edited by Manfred M. Fischer and Antonio P·ez

More articles in Journal of Geographical Systems from Springer
Series data maintained by Guenther Eichhorn ().