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Predicting Housing Value: A Comparison of Multiple Regression Analysis and Artificial Neural Networks

Author

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  • Nghiep Nguyen

    (Middle Tennessee State University, Murfreesboro, TN)

  • Al Cripps

    (Middle Tennessee State University, Murfreesboro, TN)

Abstract

This paper compares the predictive performance of artificial neural networks (ANN) and multiple regression analysis (MRA) for single family housing sales. Multiple comparisons are made between the two data models in which the data sample size is varied, the funcional specifications is varied, and the temporal prediction is varied. We conclude that ANN performs better than MRA when a moderate to large data sample size is used. For our application, this "moderate to large data sample size" varied from 13% to 39% of the total data sample (506 to 1506 observations out of 3906 total observations). Our results give a plausible explanation why previous papers have obtained varied results when comparing MRA and ANN predictive performance for housing values.

Suggested Citation

  • Nghiep Nguyen & Al Cripps, 2001. "Predicting Housing Value: A Comparison of Multiple Regression Analysis and Artificial Neural Networks," Journal of Real Estate Research, American Real Estate Society, vol. 22(3), pages 313-336.
    • Handle: RePEc:jre:issued:v:22:n:3:2001:p:313-336
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    References listed on IDEAS

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    JEL classification:

    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services

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