A Comparison of Conventional Linear Regression Methods and Neural Networks for Forecasting Educational Spending.

Baker, Bruce D.; Richards, Craig E.

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Peer reviewed

ERIC Number: EJ594812

Record Type: Journal

Publication Date: 1999

Pages: N/A

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ISSN: ISSN-0272-7757

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A Comparison of Conventional Linear Regression Methods and Neural Networks for Forecasting Educational Spending.

Baker, Bruce D.; Richards, Craig E.

Economics of Education Review, v18 n4 p405-15 Oct 1999

Applies neural network methods for forecasting 1991-95 per-pupil expenditures in U.S. public elementary and secondary schools. Forecasting models included the National Center for Education Statistics' multivariate regression model and three neural architectures. Regarding prediction accuracy, neural network results were comparable or superior to the NCES model. (20 references) (MLH)

Descriptors: Algorithms, Econometrics, Elementary Secondary Education, Expenditure per Student, Mathematical Models, Multivariate Analysis, Prediction, Regression (Statistics)

Publication Type: Journal Articles; Numerical/Quantitative Data; Reports - Research

Education Level: N/A

Audience: N/A

Language: English

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