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A comparison of conventional linear regression methods and neural networks for forecasting educational spending

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  • Baker, Bruce D.
  • Richards, Craig E.

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  • 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.
    • Handle: RePEc:eee:ecoedu:v:18:y:1999:i:4:p:405-415
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    References listed on IDEAS

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    1. Tim Liao, 1992. "A modified GMDH approach for social science research: exploring patterns of relationships in the data," Quality & Quantity: International Journal of Methodology, Springer, vol. 26(1), pages 19-38, February.
    2. Elaine M. Worzala & Margarita Lenk & Ana Silva, 1995. "An Exploration of Neural Networks and Its Application to Real Estate Valuation," Journal of Real Estate Research, American Real Estate Society, vol. 10(2), pages 185-202.
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    Cited by:

    1. Roberto Patuelli & Peter Nijkamp & Simonetta Longhi & Aura Reggiani, 2008. "Neural Networks and Genetic Algorithms as Forecasting Tools: A Case Study on German Regions," Environment and Planning B, , vol. 35(4), pages 701-722, August.
    2. Callum Scott, 2006. "Measuring Contagion in the South-East Asian Economic Crisis: An Exploration Using Artificial Neural Networks," Accounting Research Journal, Emerald Group Publishing, vol. 19(2), pages 139-152, September.
    3. Tang, Hui-Wen Vivian & Yin, Mu-Shang, 2012. "Forecasting performance of grey prediction for education expenditure and school enrollment," Economics of Education Review, Elsevier, vol. 31(4), pages 452-462.
    4. Christian A. Johnson, 2005. "Modelos de alerta temprana para pronosticar crisis bancarias: desde la extracción de señales a las redes neuronales," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 20(1), pages 95-121, June.
    5. Christian A. Johnson & Rodrigo Vergara, 2005. "The implementation of monetary policy in an emerging economy: the case of Chile," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 20(1), pages 45-62, June.
    6. Oancea, Bogdan & Dragoescu, Raluca & Ciucu, Stefan, 2013. "Predicting students’ results in higher education using a neural network," MPRA Paper 72041, University Library of Munich, Germany.
    7. Roberto Patuelli & Aura Reggiani & Peter Nijkamp & Uwe Blien, 2006. "New Neural Network Methods for Forecasting Regional Employment: an Analysis of German Labour Markets," Spatial Economic Analysis, Taylor & Francis Journals, vol. 1(1), pages 7-30.
    8. Roberto Patuelli & Peter Nijkamp & Simonetta Longhi & Aura Reggiani, 2008. "Neural Networks and Genetic Algorithms as Forecasting Tools: A Case Study on German Regions," Environment and Planning B, , vol. 35(4), pages 701-722, August.
    9. Angelini, Eliana & di Tollo, Giacomo & Roli, Andrea, 2008. "A neural network approach for credit risk evaluation," The Quarterly Review of Economics and Finance, Elsevier, vol. 48(4), pages 733-755, November.
    10. Al Shami, Ahmad & Lotfi, Ahmad & Coleman, Simeon & Dostál, Petr, 2015. "Unified knowledge based economy hybrid forecasting," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 107-123.

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