Forecasting Regional Employment in Germany by Means of Neural Networks and Genetic Algorithms
Download full text from publisher
Other versions of this item:
- Roberto Patuelli & Simonetta Longhi & Aura Reggiani & Peter Nijkamp, 2008. "Neural networks and genetic algorithms as forecasting tools: a case study on German regions," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 35(4), pages 701-722, July.
References listed on IDEAS
- Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
- John Cooper, 1999. "Artificial neural networks versus multivariate statistics: An application from economics," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 909-921.
- Norman R. Swanson & Halbert White, 1997.
"A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks,"
The Review of Economics and Statistics,
MIT Press, vol. 79(4), pages 540-550, November.
- Norman R. Swanson & Halbert White, 1995. "A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Macroeconomics 9503004, EconWPA.
- Swanson, N.R. & White, H., 1995. "A Models Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Papers 04-95-12, Pennsylvania State - Department of Economics.
- Nag, Ashok K & Mitra, Amit, 2002. "Forecasting Daily Foreign Exchange Rates Using Genetically Optimized Neural Networks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(7), pages 501-511, November.
- James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc.
- Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
- Longhi, Simonetta & Nijkamp, Peter & Reggiani, Aura & Blien, Uwe, 2002. "Forecasting regional labour markets in Germany: an evaluation of the performance of neural network analysis," ERSA conference papers ersa02p117, European Regional Science Association.
- Reggiani, Aura & Nijkamp, Peter & Sabella, Enrico, 2001. "New advances in spatial network modelling: Towards evolutionary algorithms," European Journal of Operational Research, Elsevier, vol. 128(2), pages 385-401, January.
- Baker, Bruce D. & Richards, Craig E., 1999. "A comparison of conventional linear regression methods and neural networks for forecasting educational spending," Economics of Education Review, Elsevier, vol. 18(4), pages 405-415, October.
- Manfred M. Fischer & Yee Leung, 1998. "A genetic-algorithms based evolutionary computational neural network for modelling spatial interaction data," ERSA conference papers ersa98p478, European Regional Science Association.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Roberto Patuelli & Aura Reggiani & Peter Nijkamp & Norbert Schanne, 2011.
"Neural networks for regional employment forecasts: are the parameters relevant?,"
Journal of Geographical Systems,
Springer, vol. 13(1), pages 67-85, March.
- Patuelli, R. & Reggiani, A. & Nijkamp, P. & Schanne, N., 2009. "Neural networks for cross-sectional employment forecasts: a comparison of model specifications for germany," Serie Research Memoranda 0014, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
- Roberto Patuelli & Aura Reggiani & Peter Nijkamp & Norbert Schanne, 2009. "Neural Networks for Regional Employment Forecasts: Are the Parameters Relevant?," Working Paper series 07_09, Rimini Centre for Economic Analysis, revised Feb 2010.
- Roberto Patuelli & Aura Reggiani & Peter Nijkamp & Norbert Schanne, 2009. "Neural Networks for Cross-Sectional Employment Forecasts: A Comparison of Model Specifications for Germany," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 0903, USI Università della Svizzera italiana.
- MatÃas Mayor & Roberto Patuelli, 2012.
"Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions,"
Working Paper series
15_12, Rimini Centre for Economic Analysis, revised Oct 2012.
- M. Mayor-Fernández & R. Patuelli, 2012. "Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions," Working Papers wp835, Dipartimento Scienze Economiche, Universita' di Bologna.
- Robert Lehmann & Klaus Wohlrabe, 2014.
"Regional economic forecasting: state-of-the-art methodology and future challenges,"
Economics and Business Letters,
Oviedo University Press, vol. 3(4), pages 218-231.
- Robert Lehmann & Klaus Wohlrabe, 2014. "Regional Economic Forecasting: State-of-the-Art Methodology and Future Challenge," CESifo Working Paper Series 5145, CESifo Group Munich.
- repec:dgr:vuarem:2009-14 is not listed on IDEAS
More about this item
Keywordsforecasting; neural networks; regional labour markets;
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2005-11-12 (All new papers)
- NEP-FOR-2005-11-12 (Forecasting)
- NEP-GEO-2005-11-12 (Economic Geography)
StatisticsAccess and download statistics
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wpa:wuwpco:0511002. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA). General contact details of provider: http://econwpa.repec.org .
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.