Predicting Housing Value: A Comparison of Multiple Regression Analysis and Artificial Neural Networks
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.
Volume (Year): 22 (2001)
Issue (Month): 3 ()
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- A. Quang Do & G. Grudnitski, 1993. "A Neural Network Analysis of the Effect of Age on Housing Values," Journal of Real Estate Research, American Real Estate Society, vol. 8(2), pages 253-264.
- Halvorsen, Robert & Pollakowski, Henry O., 1981. "Choice of functional form for hedonic price equations," Journal of Urban Economics, Elsevier, vol. 10(1), pages 37-49, July.
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"Determinants of Real Estate Values,"
28, California Institute of Technology, Division of the Humanities and Social Sciences.
- Goodman, Allen C., 1978. "Hedonic prices, price indices and housing markets," Journal of Urban Economics, Elsevier, vol. 5(4), pages 471-484, October.
- Linneman, Peter, 1980. "Some empirical results on the nature of the hedonic price function for the urban housing market," Journal of Urban Economics, Elsevier, vol. 8(1), pages 47-68, July.
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